WorldWideScience

Sample records for satellite-derived geopotential models

  1. The use of absolute gravity data for the validation of Global Geopotential Models and for improving quasigeoid heights determined from satellite-only Global Geopotential Models

    Science.gov (United States)

    Godah, Walyeldeen; Krynski, Jan; Szelachowska, Malgorzata

    2018-05-01

    The objective of this paper is to demonstrate the usefulness of absolute gravity data for the validation of Global Geopotential Models (GGMs). It is also aimed at improving quasigeoid heights determined from satellite-only GGMs using absolute gravity data. The area of Poland, as a unique one, covered with a homogeneously distributed set of absolute gravity data, has been selected as a study area. The gravity anomalies obtained from GGMs were validated using the corresponding ones determined from absolute gravity data. The spectral enhancement method was implemented to overcome the spectral inconsistency in data being validated. The quasigeoid heights obtained from the satellite-only GGM as well as from the satellite-only GGM in combination with absolute gravity data were evaluated with high accuracy GNSS/levelling data. Estimated accuracy of gravity anomalies obtained from GGMs investigated is of 1.7 mGal. Considering omitted gravity signal, e.g. from degree and order 101 to 2190, satellite-only GGMs can be validated at the accuracy level of 1 mGal using absolute gravity data. An improvement up to 59% in the accuracy of quasigeoid heights obtained from the satellite-only GGM can be observed when combining the satellite-only GGM with absolute gravity data.

  2. Geopotential Stress

    DEFF Research Database (Denmark)

    Schiffer, Christian; Nielsen, S.B.

    Density heterogeneity in the Earth’s lithosphere causes lateral pressure variations. Horizontal gradients of the vertically integrated lithostatic pressure, the Geopotential Energy (GPE), are a source of stresses (Geopotential Stress) that contribute to the Earth’s Stress Field. In theory the GPE...... is linearly related to the lithospheric part of the Geoid. The Geopotential Stress can be calculated if either the density structure and as a consequence the GPE or the lithospheric contribution to the Geoid is known. The lithospheric Geoid is usually obtained by short pass filtering of satellite Geoid...... are not entirely suitable for the stress calculations but can be compiled and adjusted. We present an approach in which a global lithospheric density model based on CRUST2.0 is obtained by simultaneously fitting topography and surface heat flow in the presence of isostatic compensation and long-wavelength lateral...

  3. Intercomparison of Satellite Derived Gravity Time Series with Inferred Gravity Time Series from TOPEX/POSEIDON Sea Surface Heights and Climatological Model Output

    Science.gov (United States)

    Cox, C.; Au, A.; Klosko, S.; Chao, B.; Smith, David E. (Technical Monitor)

    2001-01-01

    The upcoming GRACE mission promises to open a window on details of the global mass budget that will have remarkable clarity, but it will not directly answer the question of what the state of the Earth's mass budget is over the critical last quarter of the 20th century. To address that problem we must draw upon existing technologies such as SLR, DORIS, and GPS, and climate modeling runs in order to improve our understanding. Analysis of long-period geopotential changes based on SLR and DORIS tracking has shown that addition of post 1996 satellite tracking data has a significant impact on the recovered zonal rates and long-period tides. Interannual effects such as those causing the post 1996 anomalies must be better characterized before refined estimates of the decadal period changes in the geopotential can be derived from the historical database of satellite tracking. A possible cause of this anomaly is variations in ocean mass distribution, perhaps associated with the recent large El Nino/La Nina. In this study, a low-degree spherical harmonic gravity time series derived from satellite tracking is compared with a TOPEX/POSEIDON-derived sea surface height time series. Corrections for atmospheric mass effects, continental hydrology, snowfall accumulation, and ocean steric model predictions will be considered.

  4. Modelling of the Global Geopotential Energy & Stress Field

    DEFF Research Database (Denmark)

    Schiffer, Christian; Nielsen, S.B.

    Lateral density and topography variations yield in and important contribution to the lithospheric stress field. The leading quantity is the Geopotential Energy, the integrated lithostatic pressure in a rock column. The horizontal gradient of this quantity is related to horizontal stresses through...... the Equations of equilibrium of stresses. The Geopotential Energy furthermore can be linearly related to the Geoid under assumption of local isostasy. Satellite Geoid measurements contain, however, also non-isostatic deeper mantle responses of long wavelength. Unfortunately, high-pass filtering of the Geoid...... flow in the presence of local isostasy and a steady state geotherm. Subsequently we use a FEM code to solve the Equations of equilibrium of stresses for a three dimensional elastic shell. The modelled results are shown and compared with the global stress field and other publications....

  5. Spheroidal Integral Equations for Geodetic Inversion of Geopotential Gradients

    Science.gov (United States)

    Novák, Pavel; Šprlák, Michal

    2018-03-01

    The static Earth's gravitational field has traditionally been described in geodesy and geophysics by the gravitational potential (geopotential for short), a scalar function of 3-D position. Although not directly observable, geopotential functionals such as its first- and second-order gradients are routinely measured by ground, airborne and/or satellite sensors. In geodesy, these observables are often used for recovery of the static geopotential at some simple reference surface approximating the actual Earth's surface. A generalized mathematical model is represented by a surface integral equation which originates in solving Dirichlet's boundary-value problem of the potential theory defined for the harmonic geopotential, spheroidal boundary and globally distributed gradient data. The mathematical model can be used for combining various geopotential gradients without necessity of their re-sampling or prior continuation in space. The model extends the apparatus of integral equations which results from solving boundary-value problems of the potential theory to all geopotential gradients observed by current ground, airborne and satellite sensors. Differences between spherical and spheroidal formulations of integral kernel functions of Green's kind are investigated. Estimated differences reach relative values at the level of 3% which demonstrates the significance of spheroidal approximation for flattened bodies such as the Earth. The observation model can be used for combined inversion of currently available geopotential gradients while exploring their spectral and stochastic characteristics. The model would be even more relevant to gravitational field modelling of other bodies in space with more pronounced spheroidal geometry than that of the Earth.

  6. Stabilized determination of geopotential coefficients by the mixed hom-BLUP approach

    Science.gov (United States)

    Middel, B.; Schaffrin, B.

    1989-01-01

    For the determination of geopotential coefficients, data can be used from rather different sources, e.g., satellite tracking, gravimetry, or altimetry. As each data type is particularly sensitive to certain wavelengths of the spherical harmonic coefficients it is of essential importance how they are treated in a combination solution. For example the longer wavelengths are well described by the coefficients of a model derived by satellite tracking, while other observation types such as gravity anomalies, delta g, and geoid heights, N, from altimetry contain only poor information for these long wavelengths. Therefore, the lower coefficients of the satellite model should be treated as being superior in the combination. In the combination a new method is presented which turns out to be highly suitable for this purpose due to its great flexibility combined with robustness.

  7. An Evaluation of Recent Gravity Models wrt. Altimeter Satellite Missions

    Science.gov (United States)

    Lemoine, Frank G.; Zelensky, N. P.; Luthcke, S. B.; Beckley, B. D.; Chinn, D. S.; Rowlands, D. D.

    2003-01-01

    With the launch of CHAMP and GRACE, we have entered a new phase in the history of satellite geodesy. For the first time, geopotential models are now available based almost exclusively on satellite-satellite tracking either with GPS in the case of the CHAMP-based geopotential models, or co-orbital intersatellite ultra-precise ranging in the case of GRACE. Different groups have analyzed these data, and produced a series of geopotential models (e.g., EIGENlS, EIGEN2, GGM0lS, GGMOlC) that incorporate the new data. We will compare the performance of these "newer" geopotential models with the standard models now used for computations, (e.g., JGM-3, BGM-96, PGS7727, and GRIMS-C1) for TOPEX, JASON, Geosat-Follow-On (GFO), and Envisat using standard metrics such as SLR RMS of fit, altimeter crossovers, and orbit overlaps. Where covariances are available we can evaluate the predicted geographically correlated orbit error. These predicted results can be compared with the Earth-fixed differences between dynamic and reduced-dynamic orbits to test the predictive accuracy of the covariances, as well as to calibrate the error of the solutions.

  8. Evaluation of JGM 2 geopotential errors from geosat, TOPEX/poseidon and ERS-1 crossover altimetry

    Science.gov (United States)

    Wagner, C. A.; Klokocník, J.; Tai, C. K.

    1995-08-01

    World-ocean distribution of the crossover altimetry data from Geosat, TOPEX/Poseidon (T/P) and the ERS 1 missions have provided strong independent evidence that NASA's/CSR's JGM 2 geopotential model (70 x 70 in spherical harmonics) yields accurate radial ephemerides for these satellites. In testing the sea height crossover differences found from altimetry and JGM 2 orbits for these satellites, we have used the sea height differences themselves (of ascending minus descending passes averaged at each location over many exact repeat cycles) and the Lumped Latitude Coefficients (LLC) derived from them. For Geosat we find the geopotential-induced LLC errors (exclusive of non-gravitational and initial state discrepancies) mostly below 6 cm, for TOPEX the corresponding errors are usually below 2 cm, and for ERS 1 (35-day cycle) they are generally belo2 5 cm. In addition, we have found that these observations agree well overall with predictions of accuracy derived from the JGM 2 variance-covariance matrix; the corresponding projected LLC errors for Geosat, T/P, and ERS 1 are usually between 1 and 4 cm, 1 - 2 cm, and 1 - 4 cm, respectively (they depend on the filtering of long-periodic perturbations and on the order of the LLC). This agreement is especially impressive for ERS 1 since no data of any kind from this mission was used in forming JGM 2. The observed crossover differences for Geosat, T/P and ERS 1 are 8, 3, and 11 cm (rms), respectively. These observations also agree well with prediction of accuracy derived from the JGM 2 variance-covariance matrix; the corresponding projected crossover errors for Geosat and T/P are 8 cm and 2.3 cm, respectively. The precision of our mean difference observations is about 3 cm for Geosat (approx. 24,000 observations), 1.5 cm for T/P (approx. 6,000 observations) and 5 cm for ERS 1 (approx. 44,000 observations). Thus, these ``global'' independent data should provide a valuable new source for improving geopotential models. Our results

  9. Modeling and estimation of a low degree geopotential model from terrestrial gravity data

    Science.gov (United States)

    Pavlis, Nikolaos K.

    1988-01-01

    The development of appropriate modeling and adjustment procedures for the estimation of harmonic coefficients of the geopotential, from surface gravity data was studied, in order to provide an optimum way of utilizing the terrestrial gravity information in combination solutions currently developed at NASA/Goddard Space Flight Center, for use in the TOPEX/POSEIDON mission. The mathematical modeling was based on the fundamental boundary condition of the linearized Molodensky boundary value problem. Atmospheric and ellipsoidal corrections were applied to the surface anomalies. Terrestrial gravity solutions were found to be in good agreement with the satellite ones over areas which are well surveyed (gravimetrically), such as North America or Australia. However, systematic differences between the terrestrial only models and GEMT1, over extended regions in Africa, the Soviet Union, and China were found. In Africa, gravity anomaly differences on the order of 20 mgals and undulation differences on the order of 15 meters, over regions extending 2000 km in diameter, occur. Comparisons of the GEMT1 implied undulations with 32 well distributed Doppler derived undulations gave an RMS difference of 2.6 m, while corresponding comparison with undulations implied by the terrestrial solution gave RMS difference on the order of 15 m, which implies that the terrestrial data in that region are substantially in error.

  10. Geopotential coefficient determination and the gravimetric boundary value problem: A new approach

    Science.gov (United States)

    Sjoeberg, Lars E.

    1989-01-01

    New integral formulas to determine geopotential coefficients from terrestrial gravity and satellite altimetry data are given. The formulas are based on the integration of data over the non-spherical surface of the Earth. The effect of the topography to low degrees and orders of coefficients is estimated numerically. Formulas for the solution of the gravimetric boundary value problem are derived.

  11. On global and regional spectral evaluation of global geopotential models

    International Nuclear Information System (INIS)

    Ustun, A; Abbak, R A

    2010-01-01

    Spectral evaluation of global geopotential models (GGMs) is necessary to recognize the behaviour of gravity signal and its error recorded in spherical harmonic coefficients and associated standard deviations. Results put forward in this wise explain the whole contribution of gravity data in different kinds that represent various sections of the gravity spectrum. This method is more informative than accuracy assessment methods, which use external data such as GPS-levelling. Comparative spectral evaluation for more than one model can be performed both in global and local sense using many spectral tools. The number of GGMs has grown with the increasing number of data collected by the dedicated satellite gravity missions, CHAMP, GRACE and GOCE. This fact makes it necessary to measure the differences between models and to monitor the improvements in the gravity field recovery. In this paper, some of the satellite-only and combined models are examined in different scales, globally and regionally, in order to observe the advances in the modelling of GGMs and their strengths at various expansion degrees for geodetic and geophysical applications. The validation of the published errors of model coefficients is a part of this evaluation. All spectral tools explicitly reveal the superiority of the GRACE-based models when compared against the models that comprise the conventional satellite tracking data. The disagreement between models is large in local/regional areas if data sets are different, as seen from the example of the Turkish territory

  12. Evaluation of the geopotential value W0LVD of China

    Directory of Open Access Journals (Sweden)

    Lin He

    2017-11-01

    Full Text Available Estimation of the zero-height geopotential value W0LVD for the CVD (China Vertical Datum plays a fundamental role in the connection of traditional height reference systems into a global height system. Estimation the W0LVD of China is based on the computation of the mean geopotential offset between the value W0 = 62636856.0 m2s−2, selected as reference in this study, and the unknown geopotential value W0LVD. This estimation is based on the combination of ellipsoidal heights, levelled heights (referring to the CVD, and some physical parameters, such as geopotential values, gravity values, and geoid undulations. The geoid undulations derived from the GGM (Global Geopotential Models. This combination is performed through three approaches: The first one is based on the theory of Molodensky, and the second one compares levelled heights and geopotential values derived from the GGMs, while the third one analyses the differences between GPS/Levelling and GGMs geoid undulations. The approaches are evaluated at 65 benchmarks (BMs covered around Qingdao where the tide gauge is used to observe the local mean sea level of China. The results from three approaches are very similar. Furthermore, the W0LVD determined for the China local vertical datum was 62636852.9462 m2s−2, indicates a bias of about 3.0538 m2/s−2 compared to the conventional value of 62636856.0 m2s−2.

  13. Marine Geoid Undulation Assessment Over South China Sea Using Global Geopotential Models and Airborne Gravity Data

    Science.gov (United States)

    Yazid, N. M.; Din, A. H. M.; Omar, K. M.; Som, Z. A. M.; Omar, A. H.; Yahaya, N. A. Z.; Tugi, A.

    2016-09-01

    Global geopotential models (GGMs) are vital in computing global geoid undulations heights. Based on the ellipsoidal height by Global Navigation Satellite System (GNSS) observations, the accurate orthometric height can be calculated by adding precise and accurate geoid undulations model information. However, GGMs also provide data from the satellite gravity missions such as GRACE, GOCE and CHAMP. Thus, this will assist to enhance the global geoid undulations data. A statistical assessment has been made between geoid undulations derived from 4 GGMs and the airborne gravity data provided by Department of Survey and Mapping Malaysia (DSMM). The goal of this study is the selection of the best possible GGM that best matches statistically with the geoid undulations of airborne gravity data under the Marine Geodetic Infrastructures in Malaysian Waters (MAGIC) Project over marine areas in Sabah. The correlation coefficients and the RMS value for the geoid undulations of GGM and airborne gravity data were computed. The correlation coefficients between EGM 2008 and airborne gravity data is 1 while RMS value is 0.1499.In this study, the RMS value of EGM 2008 is the lowest among the others. Regarding to the statistical analysis, it clearly represents that EGM 2008 is the best fit for marine geoid undulations throughout South China Sea.

  14. Local Analysis Approach for Short Wavelength Geopotential Variations

    Science.gov (United States)

    Bender, P. L.

    2009-12-01

    The value of global spherical harmonic analyses for determining 15 day to 30 day changes in the Earth's gravity field has been demonstrated extensively using data from the GRACE mission and previous missions. However, additional useful information appears to be obtainable from local analyses of the data. A number of such analyses have been carried out by various groups. In the energy approximation, the changes in the height of the satellite altitude geopotential can be determined from the post-fit changes in the satellite separation during individual one-revolution arcs of data from a GRACE-type pair of satellites in a given orbit. For a particular region, it is assumed that short wavelength spatial variations for the arcs crossing that region during a time T of interest would be used to determine corrections to the spherical harmonic results. The main issue in considering higher measurement accuracy in future missions is how much improvement in spatial resolution can be achieved. For this, the shortest wavelengths that can be determined are the most important. And, while the longer wavelength variations are affected by mass distribution changes over much of the globe, the shorter wavelength ones hopefully will be determined mainly by more local changes in the mass distribution. Future missions are expected to have much higher accuracy for measuring changes in the satellite separation than GRACE. However, how large an improvement in the derived results in hydrology will be achieved is still very much a matter of study, particularly because of the effects of uncertainty in the time variations in the atmospheric and oceanic mass distributions. To be specific, it will be assumed that improving the spatial resolution in continental regions away from the coastlines is the objective, and that the satellite altitude is in the range of roughly 290 to 360 km made possible for long missions by drag-free operation. The advantages of putting together the short wavelength

  15. Time series of low-degree geopotential coefficients from SLR data: estimation of Earth's figure axis and LOD variations

    Science.gov (United States)

    Luceri, V.; Sciarretta, C.; Bianco, G.

    2012-12-01

    The redistribution of the mass within the earth system induces changes in the Earth's gravity field. In particular, the second-degree geopotential coefficients reflect the behaviour of the Earth's inertia tensor of order 2, describing the main mass variations of our planet impacting the EOPs. Thanks to the long record of accurate and continuous laser ranging observations to Lageos and other geodetic satellites, SLR is the only current space technique capable to monitor the long time variability of the Earth's gravity field with adequate accuracy. Time series of low-degree geopotential coefficients are estimated with our analysis of SLR data (spanning more than 25 years) from several geodetic satellites in order to detect trends and periodic variations related to tidal effects and atmospheric/oceanic mass variations. This study is focused on the variations of the second-degree Stokes coefficients related to the Earth's principal figure axis and oblateness: C21, S21 and C20. On the other hand, surface mass load variations induce excitations in the EOPs that are proportional to the same second-degree coefficients. The time series of direct estimates of low degree geopotential and those derived from the EOP excitation functions are compared and presented together with their time and frequency analysis.

  16. Global Geopotential Energy & Stress Field

    DEFF Research Database (Denmark)

    Schiffer, Christian; Nielsen, S.B.

    of the oceanic lithosphere. An entire modelling of the shallow Geopotential Energy is hereby approached, not taking into account possible deeper signals but all lithospheric signals for the subsequent stress calculation. Therefore a global lithospheric density model is necessary to calculate the corresponding...... response to Geopotential Energy and the Geoid. A linearized inverse method fits a lithospheric reference model to reproduce measured data sets, such as topography and surface heat flow, while assuming isostasy and solving the steady state heat equation. A FEM code solves the equations of equilibrium...

  17. MLS/Aura L2 Geopotential Height V003

    Data.gov (United States)

    National Aeronautics and Space Administration — ML2GPH is the EOS Aura Microwave Limb Sounder (MLS) standard product for geopotential height derived from radiances measured by the 118 and 240 GHz radiometers. The...

  18. MLS/Aura L2 Geopotential Height V002

    Data.gov (United States)

    National Aeronautics and Space Administration — ML2GPH is the EOS Aura Microwave Limb Sounder (MLS) standard product for geopotential height derived from radiances measured by the 118 and 240 GHz radiometers. The...

  19. Validation of gravity data from the geopotential field model for subsurface investigation of the Cameroon Volcanic Line (Western Africa)

    Science.gov (United States)

    Marcel, Jean; Abate Essi, Jean Marcel; Nouck, Philippe Njandjock; Sanda, Oumarou; Manguelle-Dicoum, Eliézer

    2018-03-01

    Belonging to the Cameroon Volcanic Line (CVL), the western part of Cameroon is an active volcanic zone with volcanic eruptions and deadly gas emissions. The volcanic flows generally cover areas and bury structural features like faults. Terrestrial gravity surveys can hardly cover entirely this mountainous area due to difficult accessibility. The present work aims to evaluate gravity data derived from the geopotential field model, EGM2008 to investigate the subsurface of the CVL. The methodology involves upward continuation, horizontal gradient, maxima of horizontal gradient-upward continuation combination and Euler deconvolution techniques. The lineaments map inferred from this geopotential field model confirms several known lineaments and reveals new ones covered by lava flows. The known lineaments are interpreted as faults or geological contacts such as the Foumban fault and the Pan-African Belt-Congo craton contact. The lineaments highlighted coupled with the numerous maar lakes identified in this volcanic sector attest of the vulnerability of the CVL where special attention should be given for geohazard prevention.

  20. A study of the chilean vertical network through global geopotential models and the cnes cls 2011 global mean sea surface

    Directory of Open Access Journals (Sweden)

    Henry Montecino Castro

    Full Text Available Most aspects related to the horizontal component of the Geocentric Reference System for the Americas (SIRGAS have been solved. However, in the case of the vertical component there are still aspects of definition, national realizations and continental unification still not accomplished. Chile is no exception; due to its particular geographic characteristics, a number of tide gauges (TG had to be installed in the coast from which the leveling lines that compose the Chilean Vertical Network (CHVN were established. This study explored the offsets of the CHVN by two different approaches; one geodetic and one oceanographic. In the first approach, the offsets were obtained in relation to the following Global Geopotential Models (GGM: the satellite-only model (unbiased GO_CONS_gcf_2_tim_r3 derived from GOCE satellite mission; EGM2008 (combined-biased; and GOEGM08, combining information from the GO_CONS_gcf_2_tim_r3 in long wavelengths (n max~200 with the mean/short wavelengths of EGM2008 (n>200. In the oceanographic method, we used the CNES CLS 2011 Global Mean Sea surface and EIGEN_GRACE_5C GGM to obtain the values of MDT at the different TG. We also evaluated the CHVN in relation to different GGMs. The results showed consistency between the values obtained by the two methods at the TG of Valparaíso and Puerto Chacabuco. In terms of the evaluation of the GGM, GOEGM08 produced the best results.

  1. Long-term stability of geoidal geopotential from Topex/Poseidon satellite altimetry 1993-1999

    Czech Academy of Sciences Publication Activity Database

    Burša, Milan; Kenyon, S.; Kouba, J.; Müller, A.; Raděj, K.; Vatrt, V.; Vojtíšková, M.; Vítek, V.

    2001-01-01

    Roč. 84, - (2001), s. 163-176 ISSN 0167-9295 Institutional research plan: CEZ:AV0Z1003909 Keywords : geoidal geopotential * Topex/Poseidon altimetry Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.457, year: 2001

  2. The AUSGeoid98 geoid model of Australia: data treatment, computations and comparisons with GPS-levelling data

    DEFF Research Database (Denmark)

    Featherstone, W.E.; Kirby, J.F.; Kearsley, A.H.W.

    2001-01-01

    The AUSGeoid98 gravimetric geoid model of Australia has been computed using data from the EGM96 global geopotential model, the 1996 release of the Australian gravity database, a nationwide digital elevation model, and satellite altimeter-derived marine gravity anomalies. The geoid heights are on ...

  3. Along-track geopotential difference and deflection of the vertical from grace range rate : Use of GEOGRACE

    NARCIS (Netherlands)

    Tangdamrongsub, N.; Hwang, Cheinway

    2016-01-01

    We present a theory and numerical algorithm to directly determine the time-varying along-track geopotential difference and deflection of the vertical at the Gravity Recovery and Climate Experiment (GRACE) satellite altitude. The determination was implemented using the GEOGRACE computer program

  4. Testing global geopotential models through comparison of a local quasi-geoid model with GPS/leveling data

    Czech Academy of Sciences Publication Activity Database

    Novák, P.; Kostelecký, J.; Klokočník, Jaroslav

    2009-01-01

    Roč. 53, č. 1 (2009), s. 39-60 ISSN 0039-3169 R&D Projects: GA AV ČR IAA3003407; GA MŠk(CZ) LC506 Institutional research plan: CEZ:AV0Z10030501 Keywords : global geopotential model s * CHAMP * GRACE Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.000, year: 2009

  5. Influence of satellite-derived photolysis rates and NOx emissions on Texas ozone modeling

    Science.gov (United States)

    Tang, W.; Cohan, D. S.; Pour-Biazar, A.; Lamsal, L. N.; White, A. T.; Xiao, X.; Zhou, W.; Henderson, B. H.; Lash, B. F.

    2015-02-01

    Uncertain photolysis rates and emission inventory impair the accuracy of state-level ozone (O3) regulatory modeling. Past studies have separately used satellite-observed clouds to correct the model-predicted photolysis rates, or satellite-constrained top-down NOx emissions to identify and reduce uncertainties in bottom-up NOx emissions. However, the joint application of multiple satellite-derived model inputs to improve O3 state implementation plan (SIP) modeling has rarely been explored. In this study, Geostationary Operational Environmental Satellite (GOES) observations of clouds are applied to derive the photolysis rates, replacing those used in Texas SIP modeling. This changes modeled O3 concentrations by up to 80 ppb and improves O3 simulations by reducing modeled normalized mean bias (NMB) and normalized mean error (NME) by up to 0.1. A sector-based discrete Kalman filter (DKF) inversion approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx)-decoupled direct method (DDM) model to adjust Texas NOx emissions using a high-resolution Ozone Monitoring Instrument (OMI) NO2 product. The discrepancy between OMI and CAMx NO2 vertical column densities (VCDs) is further reduced by increasing modeled NOx lifetime and adding an artificial amount of NO2 in the upper troposphere. The region-based DKF inversion suggests increasing NOx emissions by 10-50% in most regions, deteriorating the model performance in predicting ground NO2 and O3, while the sector-based DKF inversion tends to scale down area and nonroad NOx emissions by 50%, leading to a 2-5 ppb decrease in ground 8 h O3 predictions. Model performance in simulating ground NO2 and O3 are improved using sector-based inversion-constrained NOx emissions, with 0.25 and 0.04 reductions in NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both GOES-derived photolysis rates and OMI-constrained NOx emissions together reduces modeled NMB and NME by 0.05, increases the model

  6. A comparative study of spherical and flat-Earth geopotential modeling at satellite elevations

    Science.gov (United States)

    Parrott, M. H.; Hinze, W. J.; Braile, L. W.; Vonfrese, R. R. B.

    1985-01-01

    Flat-Earth modeling is a desirable alternative to the complex spherical-Earth modeling process. These methods were compared using 2 1/2 dimensional flat-earth and spherical modeling to compute gravity and scalar magnetic anomalies along profiles perpendicular to the strike of variably dimensioned rectangular prisms at altitudes of 150, 300, and 450 km. Comparison was achieved with percent error computations (spherical-flat/spherical) at critical anomaly points. At the peak gravity anomaly value, errors are less than + or - 5% for all prisms. At 1/2 and 1/10 of the peak, errors are generally less than 10% and 40% respectively, increasing to these values with longer and wider prisms at higher altitudes. For magnetics, the errors at critical anomaly points are less than -10% for all prisms, attaining these magnitudes with longer and wider prisms at higher altitudes. In general, in both gravity and magnetic modeling, errors increase greatly for prisms wider than 500 km, although gravity modeling is more sensitive than magnetic modeling to spherical-Earth effects. Preliminary modeling of both satellite gravity and magnetic anomalies using flat-Earth assumptions is justified considering the errors caused by uncertainties in isolating anomalies.

  7. Recursive analytical solution describing artificial satellite motion perturbed by an arbitrary number of zonal terms

    Science.gov (United States)

    Mueller, A. C.

    1977-01-01

    An analytical first order solution has been developed which describes the motion of an artificial satellite perturbed by an arbitrary number of zonal harmonics of the geopotential. A set of recursive relations for the solution, which was deduced from recursive relations of the geopotential, was derived. The method of solution is based on Von-Zeipel's technique applied to a canonical set of two-body elements in the extended phase space which incorporates the true anomaly as a canonical element. The elements are of Poincare type, that is, they are regular for vanishing eccentricities and inclinations. Numerical results show that this solution is accurate to within a few meters after 500 revolutions.

  8. The Impact of Temporal Geopotential Variations on GPS

    Science.gov (United States)

    Melachroinos, Stavros; Lemoine, Frank G.; Zelensky, Nikita P.; Beckley, Brian D.; Chinn, Douglas S.; Nicholas, Joseph B.; McCarthy, John J.; Pennington, Teresa; Luthcke, Scott B.

    2012-01-01

    Lemoine et al. (2006) and Lemoine et al. (2010) showed that applying more detailed models of time-variable gravity (TVG) improved the quality of the altimeter satellite orbits (e.g. TOPEX/Poseidon, Jason-1, Jason-2). This modeling include application of atmospheric gravity derived from 6-hrly pressure fields obtained from the ECMWF and annual gravity variations to degree & order 20x20 in spherical harmonics derived from GRACE data. This approach allowed the development of a consistent geophysical model for application to altimeter satellite orbit determination from 1993 to 2011. In addition, we have also evaluated the impact of TVG modeling on the POD of Jason-1 and Jason-2 by application of a weekly degree & order four gravity coefficient time series developed using data from ten SLR & DORIS-tracked satellites from 1993 to 2011 (Lemoine et al., 2011).

  9. CHAOS-2-a geomagnetic field model derived from one decade of continuous satellite data

    DEFF Research Database (Denmark)

    Olsen, Nils; Mandea, M.; Sabaka, T.J.

    2009-01-01

    We have derived a model of the near-Earth's magnetic field using more than 10 yr of high-precision geomagnetic measurements from the three satellites Orsted, CHAMP and SAC-C. This model is an update of the two previous models, CHAOS (Olsen et al. 2006) and xCHAOS (Olsen & Mandea 2008). Data...... by minimizing the second time derivative of the squared magnetic field intensity at the core-mantle boundary. The CHAOS-2 model describes rapid time changes, as monitored by the ground magnetic observatories, much better than its predecessors....

  10. On High-Frequency Topography-Implied Gravity Signals for a Height System Unification Using GOCE-Based Global Geopotential Models

    Science.gov (United States)

    Grombein, Thomas; Seitz, Kurt; Heck, Bernhard

    2017-03-01

    National height reference systems have conventionally been linked to the local mean sea level, observed at individual tide gauges. Due to variations in the sea surface topography, the reference levels of these systems are inconsistent, causing height datum offsets of up to ±1-2 m. For the unification of height systems, a satellite-based method is presented that utilizes global geopotential models (GGMs) derived from ESA's satellite mission Gravity field and steady-state Ocean Circulation Explorer (GOCE). In this context, height datum offsets are estimated within a least squares adjustment by comparing the GGM information with measured GNSS/leveling data. While the GNSS/leveling data comprises the full spectral information, GOCE GGMs are restricted to long wavelengths according to the maximum degree of their spherical harmonic representation. To provide accurate height datum offsets, it is indispensable to account for the remaining signal above this maximum degree, known as the omission error of the GGM. Therefore, a combination of the GOCE information with the high-resolution Earth Gravitational Model 2008 (EGM2008) is performed. The main contribution of this paper is to analyze the benefit, when high-frequency topography-implied gravity signals are additionally used to reduce the remaining omission error of EGM2008. In terms of a spectral extension, a new method is proposed that does not rely on an assumed spectral consistency of topographic heights and implied gravity as is the case for the residual terrain modeling (RTM) technique. In the first step of this new approach, gravity forward modeling based on tesseroid mass bodies is performed according to the Rock-Water-Ice (RWI) approach. In a second step, the resulting full spectral RWI-based topographic potential values are reduced by the effect of the topographic gravity field model RWI_TOPO_2015, thus, removing the long to medium wavelengths. By using the latest GOCE GGMs, the impact of topography

  11. The Geopotential Research Mission - Mapping the near earth gravity and magnetic fields

    Science.gov (United States)

    Taylor, P. T.; Keating, T.; Smith, D. E.; Langel, R. A.; Schnetzler, C. C.; Kahn, W. D.

    1983-01-01

    The Geopotential Research Mission (GRM), NASA's low-level satellite system designed to measure the gravity and magnetic fields of the earth, and its objectives are described. The GRM will consist of two, Shuttle launched, satellite systems (300 km apart) that will operate simultaneously at a 160 km circular-polar orbit for six months. Current mission goals include mapping the global geoid to 10 cm, measuring gravity-field anomalies to 2 mgal with a spatial resolution of 100 km, detecting crustal magnetic anomalies of 100 km wavelength with 1 nT accuracy, measuring the vectors components to + or - 5 arc sec and 5 nT, and computing the main dipole or core field to 5 nT with a 2 nT/year secular variation detection. Resource analysis and exploration geology are additional applications considered.

  12. An attempt to link the Brazilian Height System to a World Height System

    Directory of Open Access Journals (Sweden)

    V. G. Ferreira

    Full Text Available This paper deals with the geopotential approach to investigate the present Brazilian Height System (BHS. Geopotential numbers are derived from Global Positioning System (GPS satellite surveying and disturbing potential on selected benchmarks. A model for the disturbing potential can be obtained by an existing set of spherical harmonic coefficients such as the Earth Gravity Model 2008 (EGM08. The approach provides absolute evaluation of local normal geopotential numbers (aka spheropotential numbers related to a so-called World Height System (WHS. To test the validity of the proposed methodology, a numerical experiment was carried out related to a test region in Southern Brazil. The accuracy of the derived geopotential numbers was tested versus local normal geopotential numbers based on 262 GPS/leveling points. The root mean square error (RMSE value for metric offset of BHS derived from geopotential numbers and the disturbing potential modeling in the test area was estimated to be near 0.224 meters in the absolute view. Therefore, since these spheropotential numbers are referred to a local datum, these results of comparisons may be an indicator of the mean bias of local network due to the effect of local Sea Surface Topography (SSTop and possible offset between the unknown reference for the BHS and the quasigeoid model in the region.

  13. Validation of Satellite Derived Cloud Properties Over the Southeastern Pacific

    Science.gov (United States)

    Ayers, J.; Minnis, P.; Zuidema, P.; Sun-Mack, S.; Palikonda, R.; Nguyen, L.; Fairall, C.

    2005-12-01

    Satellite measurements of cloud properties and the radiation budget are essential for understanding meso- and large-scale processes that determine the variability in climate over the southeastern Pacific. Of particular interest in this region is the prevalent stratocumulus cloud deck. The stratocumulus albedos are directly related to cloud microphysical properties that need to be accurately characterized in Global Climate Models (GCMs) to properly estimate the Earth's radiation budget. Meteorological observations in this region are sparse causing large uncertainties in initialized model fields. Remote sensing from satellites can provide a wealth of information about the clouds in this region, but it is vital to validate the remotely sensed parameters and to understand their relationship to other parameters that are not directly observed by the satellites. The variety of measurements from the R/V Roger Revelle during the 2003 STRATUS cruise and from the R/V Ron Brown during EPIC 2001 and the 2004 STRATUS cruises are suitable for validating and improving the interpretation of the satellite derived cloud properties. In this study, satellite-derived cloud properties including coverage, height, optical depth, and liquid water path are compared with in situ measurements taken during the EPIC and STRATUS cruises. The remotely sensed values are derived from Geostationary Operational Environmental Satellite (GOES) imager data, Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites, and from the Visible and Infrared Scanner (VIRS) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The products from this study will include regional monthly cloud climatologies derived from the GOES data for the 2003 and 2004 cruises as well as micro and macro physical cloud property retrievals centered over the ship tracks from MODIS and VIRS.

  14. Application of neural network technique to determine a corrector surface for global geopotential model using GPS/levelling measurements in Egypt

    Science.gov (United States)

    Elshambaky, Hossam Talaat

    2018-01-01

    Owing to the appearance of many global geopotential models, it is necessary to determine the most appropriate model for use in Egyptian territory. In this study, we aim to investigate three global models, namely EGM2008, EIGEN-6c4, and GECO. We use five mathematical transformation techniques, i.e., polynomial expression, exponential regression, least-squares collocation, multilayer feed forward neural network, and radial basis neural networks to make the conversion from regional geometrical geoid to global geoid models and vice versa. From a statistical comparison study based on quality indexes between previous transformation techniques, we confirm that the multilayer feed forward neural network with two neurons is the most accurate of the examined transformation technique, and based on the mean tide condition, EGM2008 represents the most suitable global geopotential model for use in Egyptian territory to date. The final product gained from this study was the corrector surface that was used to facilitate the transformation process between regional geometrical geoid model and the global geoid model.

  15. The Effects of Climate Variability on Phytoplankton Composition in the Equatorial Pacific Ocean using a Model and a Satellite-Derived Approach

    Science.gov (United States)

    Rousseaux, C. S.; Gregg, W. W.

    2012-01-01

    Compared the interannual variation in diatoms, cyanobacteria, coccolithophores and chlorophytes from the NASA Ocean Biogeochemical Model with those derived from satellite data (Hirata et al. 2011) between 1998 and 2006 in the Equatorial Pacific. Using NOBM, La Ni a events were characterized by an increase in diatoms (correlation with MEI, r=-0.81, Pphytoplankton community in response to climate variability. However, satellite-derived phytoplankton groups were all negatively correlated with climate variability (r ranged from -0.39 for diatoms to -0.64 for coccolithophores, Pphytoplankton groups except diatoms than NOBM. However, the different responses of phytoplankton to intense interannual events in the Equatorial Pacific raises questions about the representation of phytoplankton dynamics in models and algorithms: is a phytoplankton community shift as in the model or an across-the-board change in abundances of all phytoplankton as in the satellite-derived approach.

  16. Tests and comparisons of gravity models.

    Science.gov (United States)

    Marsh, J. G.; Douglas, B. C.

    1971-01-01

    Optical observations of the GEOS satellites were used to obtain orbital solutions with different sets of geopotential coefficients. The solutions were compared before and after modification to high order terms (necessary because of resonance) and were then analyzed by comparing subsequent observations with predicted trajectories. The most important source of error in orbit determination and prediction for the GEOS satellites is the effect of resonance found in most published sets of geopotential coefficients. Modifications to the sets yield greatly improved orbits in most cases. The results of these comparisons suggest that with the best optical tracking systems and gravity models, satellite position error due to gravity model uncertainty can reach 50-100 m during a heavily observed 5-6 day orbital arc. If resonant coefficients are estimated, the uncertainty is reduced considerably.

  17. Global detailed gravimetric geoid. [based on gravity model derived from satellite tracking and surface gravity data

    Science.gov (United States)

    Vincent, S.; Marsh, J. G.

    1973-01-01

    A global detailed gravimetric geoid has been computed by combining the Goddard Space Flight Center GEM-4 gravity model derived from satellite and surface gravity data and surface 1 deg-by-1 deg mean free air gravity anomaly data. The accuracy of the geoid is + or - 2 meters on continents, 5 to 7 meters in areas where surface gravity data are sparse, and 10 to 15 meters in areas where no surface gravity data are available. Comparisons have been made with the astrogeodetic data provided by Rice (United States), Bomford (Europe), and Mather (Australia). Comparisons have also been carried out with geoid heights derived from satellite solutions for geocentric station coordinates in North America, the Caribbean, Europe, and Australia.

  18. Error estimates for near-Real-Time Satellite Soil Moisture as Derived from the Land Parameter Retrieval Model

    NARCIS (Netherlands)

    Parinussa, R.M.; Meesters, A.G.C.A.; Liu, Y.Y.; Dorigo, W.; Wagner, W.; de Jeu, R.A.M.

    2011-01-01

    A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from

  19. Geographical representation of radial orbit perturbations due to ocean tides: Implications for satellite altimetry

    Science.gov (United States)

    Bettadpur, Srinivas V.; Eanes, Richard J.

    1994-01-01

    In analogy to the geographical representation of the zeroth-order radial orbit perturbations due to the static geopotential, similar relationships have been derived for radial orbit perturbations due to the ocean tides. At each location these perturbations are seen to be coherent with the tide height variations. The study of this singularity is of obvious importance to the estimation of ocean tides from satellite altimeter data. We derive analytical expressions for the sensitivity of altimeter derived ocean tide models to the ocean tide force model induced errors in the orbits of the altimeter satellite. In particular, we focus on characterizing and quantifying the nonresonant tidal orbit perturbations, which cannot be adjusted into the empirical accelerations or radial perturbation adjustments commonly used during orbit determination and in altimeter data processing. As an illustration of the utility of this technique, we study the differences between a TOPEX/POSEIDON-derived ocean tide model and the Cartwright and Ray 1991 Geosat model. This analysis shows that nearly 60% of the variance of this difference for M(sub 2) can be explained by the Geosat radial orbit eror due to the omission of coefficients from the GEM-T2 background ocean tide model. For O(sub 1), K(sub 1), S(sub 2), and K(sub 2) the orbital effects account for approximately 10 to 40% of the variances of these differences. The utility of this technique to assessment of the ocean tide induced errors in the TOPEX/POSEIDON-derived tide models is also discussed.

  20. Assessment of satellite and model derived long term solar radiation for spatial crop models: A case study using DSSAT in Andhra Pradesh

    Directory of Open Access Journals (Sweden)

    Anima Biswal

    2014-09-01

    Full Text Available Crop Simulation models are mathematical representations of the soil plant-atmosphere system that calculate crop growth and yield, as well as the soil and plant water and nutrient balances, as a function of environmental conditions and crop management practices on daily time scale. Crop simulation models require meteorological data as inputs, but data availability and quality are often problematic particularly in spatialising the model for a regional studies. Among these weather variables, daily total solar radiation and air temperature (Tmax and Tmin have the greatest influence on crop phenology and yield potential. The scarcity of good quality solar radiation data can be a major limitation to the use of crop models. Satellite-sensed weather data have been proposed as an alternative when weather station data are not available. These satellite and modeled based products are global and, in general, contiguous in time and also been shown to be accurate enough to provide reliable solar and meteorological resource data over large regions where surface measurements are sparse or nonexistent. In the present study, an attempt was made to evaluate the satellite and model derived daily solar radiation for simulating groundnut crop growth in the rainfed distrcits of Andhra Pradesh. From our preliminary investigation, we propose that satellite derived daily solar radiation data could be used along with ground observed temperature and rainfall data for regional crop simulation studies where the information on ground observed solar radiation is missing or not available.

  1. On the assimilation of satellite derived soil moisture in numerical weather prediction models

    Science.gov (United States)

    Drusch, M.

    2006-12-01

    Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

  2. Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data

    NARCIS (Netherlands)

    de Hoogh, Kees; Gulliver, John; Donkelaar, Aaron van; Martin, Randall V; Marshall, Julian D; Bechle, Matthew J; Cesaroni, Giulia; Pradas, Marta Cirach; Dedele, Audrius; Eeftens, Marloes|info:eu-repo/dai/nl/315028300; Forsberg, Bertil; Galassi, Claudia; Heinrich, Joachim; Hoffmann, Barbara; Jacquemin, Bénédicte; Katsouyanni, Klea; Korek, Michal; Künzli, Nino; Lindley, Sarah J; Lepeule, Johanna; Meleux, Frederik; de Nazelle, Audrey; Nieuwenhuijsen, Mark; Nystad, Wenche; Raaschou-Nielsen, Ole; Peters, Annette; Peuch, Vincent-Henri; Rouil, Laurence; Udvardy, Orsolya; Slama, Rémy; Stempfelet, Morgane; Stephanou, Euripides G; Tsai, Ming Y; Yli-Tuomi, Tarja; Weinmayr, Gudrun; Brunekreef, Bert|info:eu-repo/dai/nl/067548180; Vienneau, Danielle; Hoek, Gerard|info:eu-repo/dai/nl/069553475

    2016-01-01

    Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models,

  3. Small Modifications of Curvilinear Coordinates and Successive Approximations Applied in Geopotential Determination

    Science.gov (United States)

    Holota, P.; Nesvadba, O.

    2016-12-01

    The mathematical apparatus currently applied for geopotential determination is undoubtedly quite developed. This concerns numerical methods as well as methods based on classical analysis, equally as classical and weak solution concepts. Nevertheless, the nature of the real surface of the Earth has its specific features and is still rather complex. The aim of this paper is to consider these limits and to seek a balance between the performance of an apparatus developed for the surface of the Earth smoothed (or simplified) up to a certain degree and an iteration procedure used to bridge the difference between the real and smoothed topography. The approach is applied for the solution of the linear gravimetric boundary value problem in geopotential determination. Similarly as in other branches of engineering and mathematical physics a transformation of coordinates is used that offers a possibility to solve an alternative between the boundary complexity and the complexity of the coefficients of the partial differential equation governing the solution. As examples the use of modified spherical and also modified ellipsoidal coordinates for the transformation of the solution domain is discussed. However, the complexity of the boundary is then reflected in the structure of Laplace's operator. This effect is taken into account by means of successive approximations. The structure of the respective iteration steps is derived and analyzed. On the level of individual iteration steps the attention is paid to the representation of the solution in terms of function bases or in terms of Green's functions. The convergence of the procedure and the efficiency of its use for geopotential determination is discussed.

  4. A model of Earth’s magnetic field derived from 2 years of Swarm satellite constellation data

    DEFF Research Database (Denmark)

    Olsen, Nils; Finlay, Chris; Kotsiaros, Stavros

    2016-01-01

    More than 2 years of magnetic field data taken by the three-satellite constellation mission Swarm are used to derive a model of Earth’s magnetic field and its time variation. This model is called SIFMplus. In addition to the magnetic field observations provided by each of the three Swarm satellites...... the North–South gradient. The SIFMplus model provides a description of the static lithospheric field that is very similar to models determined from CHAMP data, up to at least spherical harmonic degree n=75. Also the core field part of SIFMplus, with a quadratic time dependence for n≤6 and a linear time...... with the model of the core, lithospheric and large-scale magnetospheric fields, a magnetic potential that depends on quasi-dipole latitude and magnetic local time....

  5. An assessment of gravity model improvements using TOPEX/Poseidon TDRSS observations

    Science.gov (United States)

    Putney, B. H.; Teles, J.; Eddy, W. F.; Klosko, S. M.

    1992-01-01

    The contribution of TOPEX/Poseidon (T/P) TDRSS data to geopotential model recovery is assessed. Simulated TDRSS one-way and Bilateration Ranging Transponder System (BRTS) observations have been generated and orbitally reduced to form normal equations for geopotential parameters. These normals have been combined with those of the latest prelaunch T/P gravity model solution using data from over 30 satellites. A study of the resulting solution error covariance shows that TDRSS can make important contributions to geopotential recovery, especially for improving T/P specific effects like those arising from orbital resonance. It is argued that future effort is desirable both to establish TDRSS orbit determination limits in a reference frame compatible with that used for the precise laser/DORIS orbits, and the reduction of these TDRSS data for geopotential recovery.

  6. Evaluation of satellite derived spectral diffuse attenuation coefficients

    Digital Repository Service at National Institute of Oceanography (India)

    Suresh, T.; Talaulikar, M.; Desa, E.; Mascarenhas, A.A.M.Q.; Matondkar, S.G.P.

    , 443, 490, 510, 555 and 670 nm derived from the ocean color satellite sensor, SeaWiFS with the in-situ measured values from the Arabian Sea is compared. The satellite derived values are found to be comparable to the measured values in the lower...

  7. Uncertainties and applications of satellite-derived coastal water quality products

    Science.gov (United States)

    Zheng, Guangming; DiGiacomo, Paul M.

    2017-12-01

    Recent and forthcoming launches of a plethora of ocean color radiometry sensors, coupled with increasingly adopted free and open data policies are expected to boost usage of satellite ocean color data and drive the demand to use these data in a quantitative and routine manner. Here we review factors that introduce uncertainties to various satellite-derived water quality products and recommend approaches to minimize the uncertainty of a specific product. We show that the regression relationships between remote-sensing reflectance and water turbidity (in terms of nephelometric units) established for different regions tend to converge and therefore it is plausible to develop a global satellite water turbidity product derived using a single algorithm. In contrast, solutions to derive suspended particulate matter concentration are much less generalizable; in one case it might be more accurate to estimate this parameter based on satellite-derived particulate backscattering coefficient, whereas in another the nonagal particulate absorption coefficient might be a better proxy. Regarding satellite-derived chlorophyll concentration, known to be subject to large uncertainties in coastal waters, studies summarized here clearly indicate that the accuracy of classical reflectance band-ratio algorithms depends largely on the contribution of phytoplankton to total light absorption coefficient as well as the degree of correlation between phytoplankton and the dominant nonalgal contributions. Our review also indicates that currently available satellite-derived water quality products are restricted to optically significant materials, whereas many users are interested in toxins, nutrients, pollutants, and pathogens. Presently, proxies or indicators for these constituents are inconsistently (and often incorrectly) developed and applied. Progress in this general direction will remain slow unless, (i) optical oceanographers and environmental scientists start collaborating more closely

  8. Statistical modeling of phenological phases in Poland based on coupling satellite derived products and gridded meteorological data

    Science.gov (United States)

    Czernecki, Bartosz; Jabłońska, Katarzyna; Nowosad, Jakub

    2016-04-01

    The aim of the study was to create and evaluate different statistical models for reconstructing and predicting selected phenological phases. This issue is of particular importance in Poland where national-wide phenological monitoring was abandoned in the middle of 1990s and the reactivated network was established in 2006. Authors decided to evaluate possibilities of using a wide-range of statistical modeling techniques to create synthetic archive dataset. Additionally, a robust tool for predicting the most distinguishable phenophases using only free of charge data as predictors was created. Study period covers the years 2007-2014 and contains only quality-controlled dataset of 10 species and 14 phenophases. Phenological data used in this study originates from the manual observations network run by the Institute of Meteorology and Water Management - National Research Institute (IMGW-PIB). Three kind of data sources were used as predictors: (i) satellite derived products, (ii) preprocessed gridded meteorological data, and (iii) spatial properties (longitude, latitude, altitude) of the monitoring site. Moderate-Resolution Imaging Spectroradiometer (MODIS) level-3 vegetation products were used for detecting onset dates of particular phenophases. Following indices were used: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (fPAR). Additionally, Interactive Multisensor Snow and Ice Mapping System (IMS) products were chosen to detect occurrence of snow cover. Due to highly noisy data, authors decided to take into account pixel reliability information. Besides satellite derived products (NDVI, EVI, FPAR, LAI, Snow cover), a wide group of observational data and agrometeorological indices derived from the European Climate Assessment & Dataset (ECA&D) were used as a potential predictors: cumulative growing degree days (GDD), cumulative growing precipitation days (GPD

  9. Integrating Global Satellite-Derived Data Products as a Pre-Analysis for Hydrological Modelling Studies: A Case Study for the Red River Basin

    Directory of Open Access Journals (Sweden)

    Gijs Simons

    2016-03-01

    Full Text Available With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P and land use/land cover (LULC is currently being expanded with the application of actual evapotranspiration (ETact algorithms on the global scale. We demonstrate how global remotely sensed P and ETact datasets can be merged to examine hydrological processes such as storage changes and streamflow prior to applying a numerical simulation model. The study area is the Red River Basin in China in Vietnam, a generally challenging basin for remotely sensed information due to frequent cloud cover. Over this region, several satellite-based P and ETact products are compared, and performance is evaluated using rain gauge records and longer-term averaged streamflow. A method is presented for fusing multiple satellite-derived ETact estimates to generate an ensemble product that may be less susceptible, on a global basis, to errors in individual modeling approaches. Subsequently, monthly satellite-derived rainfall and ETact are combined to assess the water balance for individual subcatchments and types of land use, defined using a global land use classification improved based on auxiliary satellite data. It was found that a combination of TRMM rainfall and the ensemble ETact product is consistent with streamflow records in both space and time. It is concluded that monthly storage changes, multi-annual streamflow and water yield per LULC type in the Red River Basin can be successfully assessed based on currently available global satellite-derived products.

  10. Theoretical algorithms for satellite-derived sea surface temperatures

    Science.gov (United States)

    Barton, I. J.; Zavody, A. M.; O'Brien, D. M.; Cutten, D. R.; Saunders, R. W.; Llewellyn-Jones, D. T.

    1989-03-01

    Reliable climate forecasting using numerical models of the ocean-atmosphere system requires accurate data sets of sea surface temperature (SST) and surface wind stress. Global sets of these data will be supplied by the instruments to fly on the ERS 1 satellite in 1990. One of these instruments, the Along-Track Scanning Radiometer (ATSR), has been specifically designed to provide SST in cloud-free areas with an accuracy of 0.3 K. The expected capabilities of the ATSR can be assessed using transmission models of infrared radiative transfer through the atmosphere. The performances of several different models are compared by estimating the infrared brightness temperatures measured by the NOAA 9 AVHRR for three standard atmospheres. Of these, a computationally quick spectral band model is used to derive typical AVHRR and ATSR SST algorithms in the form of linear equations. These algorithms show that a low-noise 3.7-μm channel is required to give the best satellite-derived SST and that the design accuracy of the ATSR is likely to be achievable. The inclusion of extra water vapor information in the analysis did not improve the accuracy of multiwavelength SST algorithms, but some improvement was noted with the multiangle technique. Further modeling is required with atmospheric data that include both aerosol variations and abnormal vertical profiles of water vapor and temperature.

  11. Global Geopotential Modelling from Satellite-to-Satellite Tracking,

    Science.gov (United States)

    1981-10-01

    individual component of b , corresponding in position to in c , can be written -m b’=(a ) D T - _ I p (ti)(w nm hrm obs ) - i anm ) 2(obs) (2.85) nm is... 4C 0* =ONO~ ~ ’on; 0 N N MiC0𔃺.~Ci2 -0 to % ~0 M44* 2NCOcz0 T O N -r10-t-m 0 - S- e a (A CL: t A 101= 00010 tag- N Mn -53 3.3 Results According to

  12. Scientific analysis of satellite ranging data

    Science.gov (United States)

    Smith, David E.

    1994-01-01

    A network of satellite laser ranging (SLR) tracking systems with continuously improving accuracies is challenging the modelling capabilities of analysts worldwide. Various data analysis techniques have yielded many advances in the development of orbit, instrument and Earth models. The direct measurement of the distance to the satellite provided by the laser ranges has given us a simple metric which links the results obtained by diverse approaches. Different groups have used SLR data, often in combination with observations from other space geodetic techniques, to improve models of the static geopotential, the solid Earth, ocean tides, and atmospheric drag models for low Earth satellites. Radiation pressure models and other non-conservative forces for satellite orbits above the atmosphere have been developed to exploit the full accuracy of the latest SLR instruments. SLR is the baseline tracking system for the altimeter missions TOPEX/Poseidon, and ERS-1 and will play an important role in providing the reference frame for locating the geocentric position of the ocean surface, in providing an unchanging range standard for altimeter calibration, and for improving the geoid models to separate gravitational from ocean circulation signals seen in the sea surface. However, even with the many improvements in the models used to support the orbital analysis of laser observations, there remain systematic effects which limit the full exploitation of SLR accuracy today.

  13. Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite

    Directory of Open Access Journals (Sweden)

    N. Ghilain

    2012-08-01

    Full Text Available Monitoring evapotranspiration over land is highly dependent on the surface state and vegetation dynamics. Data from spaceborn platforms are desirable to complement estimations from land surface models. The success of daily evapotranspiration monitoring at continental scale relies on the availability, quality and continuity of such data. The biophysical variables derived from SEVIRI on board the geostationary satellite Meteosat Second Generation (MSG and distributed by the Satellite Application Facility on Land surface Analysis (LSA-SAF are particularly interesting for such applications, as they aimed at providing continuous and consistent daily time series in near-real time over Africa, Europe and South America. In this paper, we compare them to monthly vegetation parameters from a database commonly used in numerical weather predictions (ECOCLIMAP-I, showing the benefits of the new daily products in detecting the spatial and temporal (seasonal and inter-annual variability of the vegetation, especially relevant over Africa. We propose a method to handle Leaf Area Index (LAI and Fractional Vegetation Cover (FVC products for evapotranspiration monitoring with a land surface model at 3–5 km spatial resolution. The method is conceived to be applicable for near-real time processes at continental scale and relies on the use of a land cover map. We assess the impact of using LSA-SAF biophysical variables compared to ECOCLIMAP-I on evapotranspiration estimated by the land surface model H-TESSEL. Comparison with in-situ observations in Europe and Africa shows an improved estimation of the evapotranspiration, especially in semi-arid climates. Finally, the impact on the land surface modelled evapotranspiration is compared over a north–south transect with a large gradient of vegetation and climate in Western Africa using LSA-SAF radiation forcing derived from remote sensing. Differences are highlighted. An evaluation against remote sensing derived land

  14. Estimation efficiency of usage satellite derived and modelled biophysical products for yield forecasting

    Science.gov (United States)

    Kolotii, Andrii; Kussul, Nataliia; Skakun, Sergii; Shelestov, Andrii; Ostapenko, Vadim; Oliinyk, Tamara

    2015-04-01

    Efficient and timely crop monitoring and yield forecasting are important tasks for ensuring of stability and sustainable economic development [1]. As winter crops pay prominent role in agriculture of Ukraine - the main focus of this study is concentrated on winter wheat. In our previous research [2, 3] it was shown that usage of biophysical parameters of crops such as FAPAR (derived from Geoland-2 portal as for SPOT Vegetation data) is far more efficient for crop yield forecasting to NDVI derived from MODIS data - for available data. In our current work efficiency of usage such biophysical parameters as LAI, FAPAR, FCOVER (derived from SPOT Vegetation and PROBA-V data at resolution of 1 km and simulated within WOFOST model) and NDVI product (derived from MODIS) for winter wheat monitoring and yield forecasting is estimated. As the part of crop monitoring workflow (vegetation anomaly detection, vegetation indexes and products analysis) and yield forecasting SPIRITS tool developed by JRC is used. Statistics extraction is done for landcover maps created in SRI within FP-7 SIGMA project. Efficiency of usage satellite based and modelled with WOFOST model biophysical products is estimated. [1] N. Kussul, S. Skakun, A. Shelestov, O. Kussul, "Sensor Web approach to Flood Monitoring and Risk Assessment", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 815-818. [2] F. Kogan, N. Kussul, T. Adamenko, S. Skakun, O. Kravchenko, O. Kryvobok, A. Shelestov, A. Kolotii, O. Kussul, and A. Lavrenyuk, "Winter wheat yield forecasting in Ukraine based on Earth observation, meteorological data and biophysical models," International Journal of Applied Earth Observation and Geoinformation, vol. 23, pp. 192-203, 2013. [3] Kussul O., Kussul N., Skakun S., Kravchenko O., Shelestov A., Kolotii A, "Assessment of relative efficiency of using MODIS data to winter wheat yield forecasting in Ukraine", in: IGARSS 2013, 21-26 July 2013, Melbourne, Australia, pp. 3235 - 3238.

  15. Satellite derived bathymetry: mapping the Irish coastline

    Science.gov (United States)

    Monteys, X.; Cahalane, C.; Harris, P.; Hanafin, J.

    2017-12-01

    Ireland has a varied coastline in excess of 3000 km in length largely characterized by extended shallow environments. The coastal shallow water zone can be a challenging and costly environment in which to acquire bathymetry and other oceanographic data using traditional survey methods or airborne LiDAR techniques as demonstrated in the Irish INFOMAR program. Thus, large coastal areas in Ireland, and much of the coastal zone worldwide remain unmapped using modern techniques and is poorly understood. Earth Observations (EO) missions are currently being used to derive timely, cost effective, and quality controlled information for mapping and monitoring coastal environments. Different wavelengths of the solar light penetrate the water column to different depths and are routinely sensed by EO satellites. A large selection of multispectral imagery (MS) from many platforms were examined, as well as from small aircrafts and drones. A number of bays representing very different coastal environments were explored in turn. The project's workflow is created by building a catalogue of satellite and field bathymetric data to assess the suitability of imagery captured at a range of spatial, spectral and temporal resolutions. Turbidity indices are derived from the multispectral information. Finally, a number of spatial regression models using water-leaving radiance parameters and field calibration data are examined. Our assessment reveals that spatial regression algorithms have the potential to significantly improve the accuracy of the predictions up to 10m WD and offer a better handle on the error and uncertainty budget. The four spatial models investigated show better adjustments than the basic non-spatial model. Accuracy of the predictions is better than 10% WD at 95% confidence. Future work will focus on improving the accuracy of the predictions incorporating an analytical model in conjunction with improved empirical methods. The recently launched ESA Sentinel 2 will become the

  16. A new model of Earth's radial conductivity structure derived from over 10 yr of satellite and observatory magnetic data

    DEFF Research Database (Denmark)

    Püthe, Christoph; Kuvshinov, Alexey; Khan, Amir

    2015-01-01

    We present a newmodel of the radial (1-D) conductivity structure of Earth's mantle. This model is derived frommore than 10 yr of magnetic measurements from the satellites ørsted, CHAMP, SAC-C and the Swarm trio as well as the global network of geomagnetic observatories. After removal of core...

  17. The Use of Resonant Orbits in Satellite Geodesy: A Review

    Czech Academy of Sciences Publication Activity Database

    Klokočník, Jaroslav; Gooding, R. H.; Wagner, C. A.; Kostelecký, J.; Bezděk, Aleš

    2013-01-01

    Roč. 34, č. 1 (2013), s. 43-72 ISSN 0169-3298 Grant - others:ESA(XE) ESA- PECS project No. 98056 Institutional support: RVO:67985815 Keywords : satellite geodesy * Earth's gravitational field * geopotential Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 5.112, year: 2013

  18. New Methods for Air Quality Model Evaluation with Satellite Data

    Science.gov (United States)

    Holloway, T.; Harkey, M.

    2015-12-01

    Despite major advances in the ability of satellites to detect gases and aerosols in the atmosphere, there remains significant, untapped potential to apply space-based data to air quality regulatory applications. Here, we showcase research findings geared toward increasing the relevance of satellite data to support operational air quality management, focused on model evaluation. Particular emphasis is given to nitrogen dioxide (NO2) and formaldehyde (HCHO) from the Ozone Monitoring Instrument aboard the NASA Aura satellite, and evaluation of simulations from the EPA Community Multiscale Air Quality (CMAQ) model. This work is part of the NASA Air Quality Applied Sciences Team (AQAST), and is motivated by ongoing dialog with state and federal air quality management agencies. We present the response of satellite-derived NO2 to meteorological conditions, satellite-derived HCHO:NO2 ratios as an indicator of ozone production regime, and the ability of models to capture these sensitivities over the continental U.S. In the case of NO2-weather sensitivities, we find boundary layer height, wind speed, temperature, and relative humidity to be the most important variables in determining near-surface NO2 variability. CMAQ agreed with relationships observed in satellite data, as well as in ground-based data, over most regions. However, we find that the southwest U.S. is a problem area for CMAQ, where modeled NO2 responses to insolation, boundary layer height, and other variables are at odds with the observations. Our analyses utilize a software developed by our team, the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS): a free, open-source program designed to make satellite-derived air quality data more usable. WHIPS interpolates level 2 satellite retrievals onto a user-defined fixed grid, in effect creating custom-gridded level 3 satellite product. Currently, WHIPS can process the following data products: OMI NO2 (NASA retrieval); OMI NO2 (KNMI retrieval); OMI

  19. Evaluation of Land Surface Models in Reproducing Satellite-Derived LAI over the High-Latitude Northern Hemisphere. Part I: Uncoupled DGVMs

    Directory of Open Access Journals (Sweden)

    Ning Zeng

    2013-10-01

    Full Text Available Leaf Area Index (LAI represents the total surface area of leaves above a unit area of ground and is a key variable in any vegetation model, as well as in climate models. New high resolution LAI satellite data is now available covering a period of several decades. This provides a unique opportunity to validate LAI estimates from multiple vegetation models. The objective of this paper is to compare new, satellite-derived LAI measurements with modeled output for the Northern Hemisphere. We compare monthly LAI output from eight land surface models from the TRENDY compendium with satellite data from an Artificial Neural Network (ANN from the latest version (third generation of GIMMS AVHRR NDVI data over the period 1986–2005. Our results show that all the models overestimate the mean LAI, particularly over the boreal forest. We also find that seven out of the eight models overestimate the length of the active vegetation-growing season, mostly due to a late dormancy as a result of a late summer phenology. Finally, we find that the models report a much larger positive trend in LAI over this period than the satellite observations suggest, which translates into a higher trend in the growing season length. These results highlight the need to incorporate a larger number of more accurate plant functional types in all models and, in particular, to improve the phenology of deciduous trees.

  20. Modelling spatio-temporal variability of Mytilus edulis (L.) growth by forcing a dynamic energy budget model with satellite-derived environmental data

    Science.gov (United States)

    Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline

    2011-11-01

    In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.

  1. Arctic sea ice albedo - A comparison of two satellite-derived data sets

    Science.gov (United States)

    Schweiger, Axel J.; Serreze, Mark C.; Key, Jeffrey R.

    1993-01-01

    Spatial patterns of mean monthly surface albedo for May, June, and July, derived from DMSP Operational Line Scan (OLS) satellite imagery are compared with surface albedos derived from the International Satellite Cloud Climatology Program (ISCCP) monthly data set. Spatial patterns obtained by the two techniques are in general agreement, especially for June and July. Nevertheless, systematic differences in albedo of 0.05 - 0.10 are noted which are most likely related to uncertainties in the simple parameterizations used in the DMSP analyses, problems in the ISCCP cloud-clearing algorithm and other modeling simplifications. However, with respect to the eventual goal of developing a reliable automated retrieval algorithm for compiling a long-term albedo data base, these initial comparisons are very encouraging.

  2. Exploring Machine Learning to Correct Satellite-Derived Sea Surface Temperatures

    Directory of Open Access Journals (Sweden)

    Stéphane Saux Picart

    2018-02-01

    Full Text Available Machine learning techniques are attractive tools to establish statistical models with a high degree of non linearity. They require a large amount of data to be trained and are therefore particularly suited to analysing remote sensing data. This work is an attempt at using advanced statistical methods of machine learning to predict the bias between Sea Surface Temperature (SST derived from infrared remote sensing and ground “truth” from drifting buoy measurements. A large dataset of collocation between satellite SST and in situ SST is explored. Four regression models are used: Simple multi-linear regression, Least Square Shrinkage and Selection Operator (LASSO, Generalised Additive Model (GAM and random forest. In the case of geostationary satellites for which a large number of collocations is available, results show that the random forest model is the best model to predict the systematic errors and it is computationally fast, making it a good candidate for operational processing. It is able to explain nearly 31% of the total variance of the bias (in comparison to about 24% for the multi-linear regression model.

  3. Evaluation of Latent Heat Flux Fields from Satellites and Models during SEMAPHORE.

    Science.gov (United States)

    Bourras, Denis; Liu, W. Timothy; Eymard, Laurence; Tang, Wenqing

    2003-02-01

    Latent heat fluxes were derived from satellite observations in the region of Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale (SEMAPHORE), which was conducted near the Azores islands in the North Atlantic Ocean in autumn of 1993. The satellite fluxes were compared with output fields of two atmospheric circulation models and in situ measurements. The rms error of the instantaneous satellite fluxes is between 35 and 40 W m-2 and the bias is 60-85 W m-2. The large bias is mainly attributed to a bias in satellite-derived atmospheric humidity and is related to the particular shape of the vertical humidity profiles during SEMAPHORE. The bias in humidity implies that the range of estimated fluxes is smaller than the range of ship fluxes, by 34%-38%. The rms errors for fluxes from models are 30-35 W m-2, and the biases are smaller than the biases in satellite fluxes (14-18 W m-2). Two case studies suggest that the satellites detect horizontal gradients of wind speed and specific humidity if the magnitude of the gradients exceeds a detection threshold, which is 1.27 g kg-1 (100 km)-1 for specific humidity and between 0.35 and 0.82 m s-1 (30 km)-1 for wind speed. In contrast, the accuracy of the spatial gradients of bulk variables from models always varies as a function of the location and number of assimilated observations. A comparison between monthly fluxes from satellites and models reveals that satellite-derived flux anomaly fields are consistent with reanalyzed fields, whereas operational model products lack part of the mesoscale structures present in the satellite fields.

  4. Analytical solution of perturbed relative motion: an application of satellite formations to geodesy

    Science.gov (United States)

    Wnuk, Edwin

    In the upcoming years, several space missions will be operated using a number of spacecraft flying in formation. Clusters of spacecraft with a carefully designed orbits and optimal formation geometry enable a wide variety of applications ranging from remote sensing to astronomy, geodesy and basic physics. Many of the applications require precise relative navigation and autonomous orbit control of satellites moving in a formation. For many missions a centimeter level of orbit control accuracy is required. The GRACE mission, since its launch in 2002, has been improving the Earth's gravity field model to a very high level of accuracy. This mission is a formation flying one consisting of two satellites moving in coplanar orbits and provides range and range-rate measurements between the satellites in the along-track direction. Future geodetic missions probably will employ alternative architectures using additional satellites and/or performing out-of-plane motion, e.g cartwheel orbits. The paper presents an analytical model of a satellite formation motion that enables propagation of the relative spacecraft motion. The model is based on the analytical theory of satellite relative motion that was presented in the previous our papers (Wnuk and Golebiewska, 2005, 2006). This theory takes into account the influence of the following gravitational perturbation effects: 1) zonal and tesseral harmonic geopotential coefficients up to arbitrary degree and order, 2) Lunar gravity, 3) Sun gravity. Formulas for differential perturbations were derived with any restriction concerning a plane of satellite orbits. They can be applied in both: in plane and out of plane cases. Using this propagator we calculated relative orbits and future relative satellite positions for different types of formations: in plane, out of plane, cartwheel and others. We analyzed the influence of particular parts of perturbation effects and estimated the accuracy of predicted relative spacecrafts positions

  5. Geometric model of pseudo-distance measurement in satellite location systems

    Science.gov (United States)

    Panchuk, K. L.; Lyashkov, A. A.; Lyubchinov, E. V.

    2018-04-01

    The existing mathematical model of pseudo-distance measurement in satellite location systems does not provide a precise solution of the problem, but rather an approximate one. The existence of such inaccuracy, as well as bias in measurement of distance from satellite to receiver, results in inaccuracy level of several meters. Thereupon, relevance of refinement of the current mathematical model becomes obvious. The solution of the system of quadratic equations used in the current mathematical model is based on linearization. The objective of the paper is refinement of current mathematical model and derivation of analytical solution of the system of equations on its basis. In order to attain the objective, geometric analysis is performed; geometric interpretation of the equations is given. As a result, an equivalent system of equations, which allows analytical solution, is derived. An example of analytical solution implementation is presented. Application of analytical solution algorithm to the problem of pseudo-distance measurement in satellite location systems allows to improve the accuracy such measurements.

  6. Evaluation of the Precision of Satellite-Derived Sea Surface Temperature Fields

    Science.gov (United States)

    Wu, F.; Cornillon, P. C.; Guan, L.

    2016-02-01

    A great deal of attention has been focused on the temporal accuracy of satellite-derived sea surface temperature (SST) fields with little attention being given to their spatial precision. Specifically, the primary measure of the quality of SST fields has been the bias and variance of selected values minus co-located (in space and time) in situ values. Contributing values, determined by the location of the in situ values and the necessity that the satellite-derived values be cloud free, are generally widely separated in space and time hence provide little information related to the pixel-to-pixel uncertainty in the retrievals. But the main contribution to the uncertainty in satellite-derived SST retrievals relates to atmospheric contamination and because the spatial scales of atmospheric features are, in general, large compared with the pixel separation of modern infra-red sensors, the pixel-to-pixel uncertainty is often smaller than the accuracy determined from in situ match-ups. This makes selection of satellite-derived datasets for the study of submesoscale processes, for which the spatial structure of the upper ocean is significant, problematic. In this presentation we present a methodology to characterize the spatial precision of satellite-derived SST fields. The method is based on an examination of the high wavenumber tail of the 2-D spectrum of SST fields in the Sargasso Sea, a low energy region of the ocean close to the track of the MV Oleander, a container ship making weekly roundtrips between New York and Bermuda, with engine intake temperatures sampled every 75 m along track. Important spectral characteristics are the point at which the satellite-derived spectra separate from the Oleander spectra and the spectral slope following separation. In this presentation a number of high resolution 375 m to 10 km SST datasets are evaluated based on this approach.

  7. A diagnostic approach to obtaining planetary boundary layer winds using satellite-derived thermal data

    Science.gov (United States)

    Belt, Carol L.; Fuelberg, Henry E.

    1984-01-01

    The feasibility of using satellite derived thermal data to generate realistic synoptic scale winds within the planetary boundary layer (PBL) is examined. Diagnostic modified Ekman wind equations from the Air Force Global Weather Central (AFGWC) Boundary Layer Model are used to compute winds at seven levels within the PBL transition layer (50 m to 1600 m AGL). Satellite derived winds based on 62 predawn TIROS-N soundings are compared to similarly derived wind fields based on 39 AVE-SESAME II rawinsonde (RAOB) soundings taken 2 h later. Actual wind fields are also used as a basis for comparison. Qualitative and statistical comparisons show that the Ekman winds from both sources are in very close agreement, with an average vector correlation coefficient of 0.815. Best results are obtained at 300 m AGL. Satellite winds tend to be slightly weaker than their RAOB counterparts and exhibit a greater degree of cross-isobaric flow. The modified Ekman winds show a significant improvement over geostrophic values at levels nearest the surface.

  8. Sorghum yield and associated satellite-derived meteorological ...

    African Journals Online (AJOL)

    Sorghum yield and associated satellite-derived meteorological parameters in semi-arid Botswana. ... African Crop Science Journal ... Sorghum (Sorghum bicolor) yield for five seasons (2005/6 to 2009/10) from the Botswana Department of Crop ... Key Words: Coefficient of determination, NDVI, Pearson correlation ...

  9. Density heterogeneity of the upper mantle beneath Siberia from satellite gravity and a new regional crustal model

    DEFF Research Database (Denmark)

    Herceg, Matija; Thybo, Hans; Artemieva, Irina

    2013-01-01

    We present a new regional model for the density structure of the upper mantle below Siberia. The residual mantle gravity anomalies are based on gravity data derived from the GOCE gravity gradients and geopotential models, with crustal correction to the gravity field being calculated from a new...... on regional and global crustal models. We analyze how uncertainties and errors in the crustal model propagate from crustal densities to mantle residual gravity anomalies and the density model of the upper mantle. The new regional density model for the Siberian craton and the West Siberian Basin complements...... regional crustal model. This newly compiled database on the crustal seismic structure, complemented by additional constraints from petrological analysis of near-surface rocks and lower crustal xenoliths, allows for a high-resolution correction of the crustal effects as compared to previous studies based...

  10. Tectonic Interpretation of CHAMP Geopotential Data over the Northern Adriatic Sea.

    Science.gov (United States)

    Taylor, P. T.; Kim, H. R.; Mayer-Gürr, T.

    2006-05-01

    Recent aeromagnetic anomaly compilations (Chiappini et al., 2000 and Tontini et al., 2004) show a large positive (>700 nT) northwest-southeast trending magnetic anomaly off the Dalmatian coast. Unfortunately these aeromagnetic data cover only a part of this anomaly. We wanted to investigate if this large magnetic anomaly could be detected at satellite altitude and what is the extent and source of this feature. Therefore, magnetic and gravity anomaly maps were made from the CHAMP geopotential data, measured at the current low altitude of 345-350 km over the northern Adriatic Sea. We made the magnetic anomaly map over this relatively small region using 36 descending and 85 ascending orbits screened to be at the lowest altitude and the most magnetically quietest data. We removed the main field component (i.e., IGRF-10 up to degree and order 13) and then demeaned individual tracks and subtracted a second order polynomial to remove regional and/or un-modeled external field features. The resulting map from these well-correlated anomalies revealed a positive magnetic anomaly (>2 nT). Reduction-to-the pole brought these CHAMP anomaly features into coincidence with the aeromagnetic data. Previously Cantini et al. (1999) compared the surface magnetic data with MAGSAT by continuing upward the former and downwards the latter to 100 km and found a good correlation for wavelengths of 300-500 km. We also investigated the CHAMP gravity data. They were reduced using the kinematic short-arc integration method (Ilk et al., 2005 and Mayer Gürr et al., 2005). However, no corresponding short-wavelength gravity anomaly was observed in our study area. This tectonically complex region is under horizontal stress and the source of the large magnetic anomaly can be modelled by an associated ophiolite melange.

  11. Modelling ocean-colour-derived chlorophyll a

    Directory of Open Access Journals (Sweden)

    S. Dutkiewicz

    2018-01-01

    Full Text Available This article provides a proof of concept for using a biogeochemical/ecosystem/optical model with a radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour chlorophyll a (Chl a product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real-world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl a (called derived Chl a in this paper. We compare the derived Chl a to the actual model Chl a field. In the model we find that the mean absolute bias due to the algorithm is 22 % between derived and actual Chl a. The real-world algorithm is found using concurrent in situ measurement of Chl a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. Not surprisingly, we find that region-specific algorithms provide a significant improvement, at least in the annual mean. However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl a and the actual Chl a. These mismatches stem from temporal decoupling between Chl a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter. The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation

  12. The linkage between geopotential height and monthly precipitation in Iran

    Science.gov (United States)

    Shirvani, Amin; Fadaei, Amir Sabetan; Landman, Willem A.

    2018-04-01

    This paper investigates the linkage between large-scale atmospheric circulation and monthly precipitation during November to April over Iran. Canonical correlation analysis (CCA) is used to set up the statistical linkage between the 850 hPa geopotential height large-scale circulation and monthly precipitation over Iran for the period 1968-2010. The monthly precipitation dataset for 50 synoptic stations distributed in different climate regions of Iran is considered as the response variable in the CCA. The monthly geopotential height reanalysis dataset over an area between 10° N and 60° N and from 20° E to 80° E is utilized as the explanatory variable in the CCA. Principal component analysis (PCA) as a pre-filter is used for data reduction for both explanatory and response variables before applying CCA. The optimal number of principal components and canonical variables to be retained in the CCA equations is determined using the highest average cross-validated Kendall's tau value. The 850 hPa geopotential height pattern over the Red Sea, Saudi Arabia, and Persian Gulf is found to be the major pattern related to Iranian monthly precipitation. The Pearson correlation between the area averaged of the observed and predicted precipitation over the study area for Jan, Feb, March, April, November, and December months are statistically significant at the 5% significance level and are 0.78, 0.80, 0.82, 0.74, 0.79, and 0.61, respectively. The relative operating characteristic (ROC) indicates that the highest scores for the above- and below-normal precipitation categories are, respectively, for February and April and the lowest scores found for December.

  13. Long-Term Prediction of Satellite Orbit Using Analytical Method

    Directory of Open Access Journals (Sweden)

    Jae-Cheol Yoon

    1997-12-01

    Full Text Available A long-term prediction algorithm of geostationary orbit was developed using the analytical method. The perturbation force models include geopotential upto fifth order and degree and luni-solar gravitation, and solar radiation pressure. All of the perturbation effects were analyzed by secular variations, short-period variations, and long-period variations for equinoctial elements such as the semi-major axis, eccentricity vector, inclination vector, and mean longitude of the satellite. Result of the analytical orbit propagator was compared with that of the cowell orbit propagator for the KOREASAT. The comparison indicated that the analytical solution could predict the semi-major axis with an accuarcy of better than ~35meters over a period of 3 month.

  14. Satellite-Derived Bathymetry: Accuracy Assessment on Depths Derivation Algorithm for Shallow Water Area

    Science.gov (United States)

    Said, N. M.; Mahmud, M. R.; Hasan, R. C.

    2017-10-01

    Over the years, the acquisition technique of bathymetric data has evolved from a shipborne platform to airborne and presently, utilising space-borne acquisition. The extensive development of remote sensing technology has brought in the new revolution to the hydrographic surveying. Satellite-Derived Bathymetry (SDB), a space-borne acquisition technique which derives bathymetric data from high-resolution multispectral satellite imagery for various purposes recently considered as a new promising technology in the hydrographic surveying industry. Inspiring by this latest developments, a comprehensive study was initiated by National Hydrographic Centre (NHC) and Universiti Teknologi Malaysia (UTM) to analyse SDB as a means for shallow water area acquisition. By adopting additional adjustment in calibration stage, a marginal improvement discovered on the outcomes from both Stumpf and Lyzenga algorithms where the RMSE values for the derived (predicted) depths were 1.432 meters and 1.728 meters respectively. This paper would deliberate in detail the findings from the study especially on the accuracy level and practicality of SDB over the tropical environmental setting in Malaysia.

  15. Application of the Coastal and Marine Ecological Classification Standard using Satellite-derived and Modeled Data Products for Pelagic Habitats in the Northern Gulf of Mexico

    Science.gov (United States)

    Satellite-derived data for sea surface temperature, salinity, chlorophyll; euphotic depth; and modeled bottom to surface temperature differences (Delta t) were evaluated to assess the utility of these products as proxies for in situ measurements. The data were used to classify su...

  16. Short note: the experimental geopotential model XGM2016

    Science.gov (United States)

    Pail, R.; Fecher, T.; Barnes, D.; Factor, J. F.; Holmes, S. A.; Gruber, T.; Zingerle, P.

    2018-04-01

    As a precursor study for the upcoming combined Earth Gravitational Model 2020 (EGM2020), the Experimental Gravity Field Model XGM2016, parameterized as a spherical harmonic series up to degree and order 719, is computed. XGM2016 shares the same combination methodology as its predecessor model GOCO05c (Fecher et al. in Surv Geophys 38(3): 571-590, 2017. doi: 10.1007/s10712-016-9406-y). The main difference between these models is that XGM2016 is supported by an improved terrestrial data set of 15^' × 15^' gravity anomaly area-means provided by the United States National Geospatial-Intelligence Agency (NGA), resulting in significant upgrades compared to existing combined gravity field models, especially in continental areas such as South America, Africa, parts of Asia, and Antarctica. A combination strategy of relative regional weighting provides for improved performance in near-coastal ocean regions, including regions where the altimetric data are mostly unchanged from previous models. Comparing cumulative height anomalies, from both EGM2008 and XGM2016 at degree/order 719, yields differences of 26 cm in Africa and 40 cm in South America. These differences result from including additional information of satellite data, as well as from the improved ground data in these regions. XGM2016 also yields a smoother Mean Dynamic Topography with significantly reduced artifacts, which indicates an improved modeling of the ocean areas.

  17. Comparison of precision orbit derived density estimates for CHAMP and GRACE satellites

    Science.gov (United States)

    Fattig, Eric Dale

    Current atmospheric density models cannot adequately represent the density variations observed by satellites in Low Earth Orbit (LEO). Using an optimal orbit determination process, precision orbit ephemerides (POE) are used as measurement data to generate corrections to density values obtained from existing atmospheric models. Densities obtained using these corrections are then compared to density data derived from the onboard accelerometers of satellites, specifically the CHAMP and GRACE satellites. This comparison takes two forms, cross correlation analysis and root mean square analysis. The densities obtained from the POE method are nearly always superior to the empirical models, both in matching the trends observed by the accelerometer (cross correlation), and the magnitudes of the accelerometer derived density (root mean square). In addition, this method consistently produces better results than those achieved by the High Accuracy Satellite Drag Model (HASDM). For satellites orbiting Earth that pass through Earth's upper atmosphere, drag is the primary source of uncertainty in orbit determination and prediction. Variations in density, which are often not modeled or are inaccurately modeled, cause difficulty in properly calculating the drag acting on a satellite. These density variations are the result of many factors; however, the Sun is the main driver in upper atmospheric density changes. The Sun influences the densities in Earth's atmosphere through solar heating of the atmosphere, as well as through geomagnetic heating resulting from the solar wind. Data are examined for fourteen hour time spans between November 2004 and July 2009 for both the CHAMP and GRACE satellites. This data spans all available levels of solar and geomagnetic activity, which does not include data in the elevated and high solar activity bins due to the nature of the solar cycle. Density solutions are generated from corrections to five different baseline atmospheric models, as well as

  18. Maritime NOx Emissions Over Chinese Seas Derived From Satellite Observations

    Science.gov (United States)

    Ding, J.; van der A, R. J.; Mijling, B.; Jalkanen, J.-P.; Johansson, L.; Levelt, P. F.

    2018-02-01

    By applying an inversion algorithm to NOx satellite observations from Ozone Monitoring Instrument, monthly NOx emissions for a 10 year period (2007 to 2016) over Chinese seas are presented for the first time. No effective regulations on NOx emissions have been implemented for ships in China, which is reflected in the trend analysis of maritime emissions. The maritime emissions display a continuous increase rate of about 20% per year until 2012 and slow down to 3% after that. The seasonal cycle of shipping emissions has regional variations, but all regions show lower emissions during winter. Simulations by an atmospheric chemistry transport model show a notable influence of maritime emissions on air pollution over coastal areas, especially in summer. The satellite-derived spatial distribution and the magnitude of maritime emissions over Chinese seas are in good agreement with bottom-up studies based on the Automatic Identification System of ships.

  19. Quantifying scaling effects on satellite-derived forest area estimates for the conterminous USA

    Science.gov (United States)

    Daolan Zheng; L.S. Heath; M.J. Ducey; J.E. Smith

    2009-01-01

    We quantified the scaling effects on forest area estimates for the conterminous USA using regression analysis and the National Land Cover Dataset 30m satellite-derived maps in 2001 and 1992. The original data were aggregated to: (1) broad cover types (forest vs. non-forest); and (2) coarser resolutions (1km and 10 km). Standard errors of the model estimates were 2.3%...

  20. Studying the Representation Accuracy of the Earth's Gravity Field in the Polar Regions Based on the Global Geopotential Models

    Science.gov (United States)

    Koneshov, V. N.; Nepoklonov, V. B.

    2018-05-01

    The development of studies on estimating the accuracy of the Earth's modern global gravity models in terms of the spherical harmonics of the geopotential in the problematic regions of the world is discussed. The comparative analysis of the results of reconstructing quasi-geoid heights and gravity anomalies from the different models is carried out for two polar regions selected within a radius of 1000 km from the North and South poles. The analysis covers nine recently developed models, including six high-resolution models and three lower order models, including the Russian GAOP2012 model. It is shown that the modern models determine the quasi-geoid heights and gravity anomalies in the polar regions with errors of 5 to 10 to a few dozen cm and from 3 to 5 to a few dozen mGal, respectively, depending on the resolution. The accuracy of the models in the Arctic is several times higher than in the Antarctic. This is associated with the peculiarities of gravity anomalies in every particular region and with the fact that the polar part of the Antarctic has been comparatively less explored by the gravity methods than the polar Arctic.

  1. Assessment of satellite derived diffuse attenuation coefficients ...

    Science.gov (United States)

    Optical data collected in coastal waters off South Florida and in the Caribbean Sea between January 2009 and December 2010 were used to evaluate products derived with three bio-optical inversion algorithms applied to MOIDS/Aqua, MODIS/Terra, and SeaWiFS satellite observations. The products included the diffuse attenuation coefficient at 490 nm (Kd_490) and for the visible range (Kd_PAR), and euphotic depth (Zeu, corresponding to 1% of the surface incident photosynthetically available radiation or PAR). Above-water hyperspectral reflectance data collected over optically shallow waters of the Florida Keys between June 1997 and August 2011 were used to help understand algorithm performance over optically shallow waters. The in situ data covered a variety of water types in South Florida and the Caribbean Sea, ranging from deep clear waters, turbid coastal waters, and optically shallow waters (Kd_490 range of ~0.03 – 1.29m-1). An algorithm based on Inherent Optical Properties (IOPs) showed the best performance (RMSD turbidity or shallow bottom contamination. Similar results were obtained when only in situ data were used to evaluate algorithm performance. The excellent agreement between satellite-derived remote sensing reflectance (Rrs) and in situ Rrs suggested that

  2. A Comparative Study on Satellite- and Model-Based Crop Phenology in West Africa

    Directory of Open Access Journals (Sweden)

    Elodie Vintrou

    2014-02-01

    Full Text Available Crop phenology is essential for evaluating crop production in the food insecure regions of West Africa. The aim of the paper is to study whether satellite observation of plant phenology are consistent with ground knowledge of crop cycles as expressed in agro-simulations. We used phenological variables from a MODIS Land Cover Dynamics (MCD12Q2 product and examined whether they reproduced the spatio-temporal variability of crop phenological stages in Southern Mali. Furthermore, a validated cereal crop growth model for this region, SARRA-H (System for Regional Analysis of Agro-Climatic Risks, provided precise agronomic information. Remotely-sensed green-up, maturity, senescence and dormancy MODIS dates were extracted for areas previously identified as crops and were compared with simulated leaf area indices (LAI temporal profiles generated using the SARRA-H crop model, which considered the main cropping practices. We studied both spatial (eight sites throughout South Mali during 2007 and temporal (two sites from 2002 to 2008 differences between simulated crop cycles and determined how the differences were indicated in satellite-derived phenometrics. The spatial comparison of the phenological indicator observations and simulations showed mainly that (i the satellite-derived start-of-season (SOS was detected approximately 30 days before the model-derived SOS; and (ii the satellite-derived end-of-season (EOS was typically detected 40 days after the model-derived EOS. Studying the inter-annual difference, we verified that the mean bias was globally consistent for different climatic conditions. Therefore, the land cover dynamics derived from the MODIS time series can reproduce the spatial and temporal variability of different start-of-season and end-of-season crop species. In particular, we recommend simultaneously using start-of-season phenometrics with crop models for yield forecasting to complement commonly used climate data and provide a better

  3. A lithospheric magnetic field model derived from the Swarm satellite magnetic field measurements

    Science.gov (United States)

    Hulot, G.; Thebault, E.; Vigneron, P.

    2015-12-01

    The Swarm constellation of satellites was launched in November 2013 and has since then delivered high quality scalar and vector magnetic field measurements. A consortium of several research institutions was selected by the European Space Agency (ESA) to provide a number of scientific products which will be made available to the scientific community. Within this framework, specific tools were tailor-made to better extract the magnetic signal emanating from Earth's the lithospheric. These tools rely on the scalar gradient measured by the lower pair of Swarm satellites and rely on a regional modeling scheme that is more sensitive to small spatial scales and weak signals than the standard spherical harmonic modeling. In this presentation, we report on various activities related to data analysis and processing. We assess the efficiency of this dedicated chain for modeling the lithospheric magnetic field using more than one year of measurements, and finally discuss refinements that are continuously implemented in order to further improve the robustness and the spatial resolution of the lithospheric field model.

  4. A hydro-optical model for deriving water quality variables from satellite images (HydroSat): A case study of the Nile River demonstrating the future Sentinel-2 capabilities

    NARCIS (Netherlands)

    Salama, M.; Radwan, M.; van der Velde, R.

    2012-01-01

    This paper describes a hydro-optical model for deriving water quality variables from satellite images, hereafter HydroSat. HydroSat corrects images for atmospheric interferences and simultaneously retrieves water quality variables. An application of HydroSat to Landsat Enhanced Thematic Mapper (ETM)

  5. Migratory herbivorous waterfowl track satellite-derived green wave index.

    Directory of Open Access Journals (Sweden)

    Mitra Shariatinajafabadi

    Full Text Available Many migrating herbivores rely on plant biomass to fuel their life cycles and have adapted to following changes in plant quality through time. The green wave hypothesis predicts that herbivorous waterfowl will follow the wave of food availability and quality during their spring migration. However, testing this hypothesis is hampered by the large geographical range these birds cover. The satellite-derived normalized difference vegetation index (NDVI time series is an ideal proxy indicator for the development of plant biomass and quality across a broad spatial area. A derived index, the green wave index (GWI, has been successfully used to link altitudinal and latitudinal migration of mammals to spatio-temporal variations in food quality and quantity. To date, this index has not been used to test the green wave hypothesis for individual avian herbivores. Here, we use the satellite-derived GWI to examine the green wave hypothesis with respect to GPS-tracked individual barnacle geese from three flyway populations (Russian n = 12, Svalbard n = 8, and Greenland n = 7. Data were collected over three years (2008-2010. Our results showed that the Russian and Svalbard barnacle geese followed the middle stage of the green wave (GWI 40-60%, while the Greenland geese followed an earlier stage (GWI 20-40%. Despite these differences among geese populations, the phase of vegetation greenness encountered by the GPS-tracked geese was close to the 50% GWI (i.e. the assumed date of peak nitrogen concentration, thereby implying that barnacle geese track high quality food during their spring migration. To our knowledge, this is the first time that the migration of individual avian herbivores has been successfully studied with respect to vegetation phenology using the satellite-derived GWI. Our results offer further support for the green wave hypothesis applying to long-distance migrants on a larger scale.

  6. Comparing multiple model-derived aerosol optical properties to spatially collocated ground-based and satellite measurements

    Science.gov (United States)

    Ocko, Ilissa B.; Ginoux, Paul A.

    2017-04-01

    Anthropogenic aerosols are a key factor governing Earth's climate and play a central role in human-caused climate change. However, because of aerosols' complex physical, optical, and dynamical properties, aerosols are one of the most uncertain aspects of climate modeling. Fortunately, aerosol measurement networks over the past few decades have led to the establishment of long-term observations for numerous locations worldwide. Further, the availability of datasets from several different measurement techniques (such as ground-based and satellite instruments) can help scientists increasingly improve modeling efforts. This study explores the value of evaluating several model-simulated aerosol properties with data from spatially collocated instruments. We compare aerosol optical depth (AOD; total, scattering, and absorption), single-scattering albedo (SSA), Ångström exponent (α), and extinction vertical profiles in two prominent global climate models (Geophysical Fluid Dynamics Laboratory, GFDL, CM2.1 and CM3) to seasonal observations from collocated instruments (AErosol RObotic NETwork, AERONET, and Cloud-Aerosol Lidar with Orthogonal Polarization, CALIOP) at seven polluted and biomass burning regions worldwide. We find that a multi-parameter evaluation provides key insights on model biases, data from collocated instruments can reveal underlying aerosol-governing physics, column properties wash out important vertical distinctions, and improved models does not mean all aspects are improved. We conclude that it is important to make use of all available data (parameters and instruments) when evaluating aerosol properties derived by models.

  7. The Orbital Dynamics of Synchronous Satellites: Irregular Motions in the 2 : 1 Resonance

    Directory of Open Access Journals (Sweden)

    Jarbas Cordeiro Sampaio

    2012-01-01

    Full Text Available The orbital dynamics of synchronous satellites is studied. The 2 : 1 resonance is considered; in other words, the satellite completes two revolutions while the Earth completes one. In the development of the geopotential, the zonal harmonics J20 and J40 and the tesseral harmonics J22 and J42 are considered. The order of the dynamical system is reduced through successive Mathieu transformations, and the final system is solved by numerical integration. The Lyapunov exponents are used as tool to analyze the chaotic orbits.

  8. Thermospheric density and satellite drag modeling

    Science.gov (United States)

    Mehta, Piyush Mukesh

    The United States depends heavily on its space infrastructure for a vast number of commercial and military applications. Space Situational Awareness (SSA) and Threat Assessment require maintaining accurate knowledge of the orbits of resident space objects (RSOs) and the associated uncertainties. Atmospheric drag is the largest source of uncertainty for low-perigee RSOs. The uncertainty stems from inaccurate modeling of neutral atmospheric mass density and inaccurate modeling of the interaction between the atmosphere and the RSO. In order to reduce the uncertainty in drag modeling, both atmospheric density and drag coefficient (CD) models need to be improved. Early atmospheric density models were developed from orbital drag data or observations of a few early compact satellites. To simplify calculations, densities derived from orbit data used a fixed CD value of 2.2 measured in a laboratory using clean surfaces. Measurements from pressure gauges obtained in the early 1990s have confirmed the adsorption of atomic oxygen on satellite surfaces. The varying levels of adsorbed oxygen along with the constantly changing atmospheric conditions cause large variations in CD with altitude and along the orbit of the satellite. Therefore, the use of a fixed CD in early development has resulted in large biases in atmospheric density models. A technique for generating corrections to empirical density models using precision orbit ephemerides (POE) as measurements in an optimal orbit determination process was recently developed. The process generates simultaneous corrections to the atmospheric density and ballistic coefficient (BC) by modeling the corrections as statistical exponentially decaying Gauss-Markov processes. The technique has been successfully implemented in generating density corrections using the CHAMP and GRACE satellites. This work examines the effectiveness, specifically the transfer of density models errors into BC estimates, of the technique using the CHAMP and

  9. Analysis of satellite-derived solar irradiance over the Netherlands

    Science.gov (United States)

    Dirksen, Marieke; Fokke Meirink, Jan; Sluiter, Raymond

    2017-04-01

    Measurements from geostationary satellites allow the retrieval of surface solar irradiance homogeneously over large areas, thereby providing essential information for the solar energy sector. In this paper, the SICCS solar irradiance data record derived from 12 years of Meteosat Second Generation satellite measurements is analysed with a focus on the Netherlands, where the spatial resolution is about 6 by 3 km2. Extensive validation of the SICCS data with pyranometer observations is performed, indicating a bias of approximately 3 W/m2 and RMSE of 11 W/m2 for daily data. Long term averages and seasonal variations of solar irradiance show regional patterns related to the surface type (e.g., coastal waters, forests, cities). The inter-annual variability over the time frame of the data record is quantified. Methods to merge satellite and surface observations into an optimized data record are explored.

  10. Assessment of Satellite Ocean Colour Radiometry and Derived Geophysical Products. Chapter 6.1

    Science.gov (United States)

    Melin, Frederic; Franz, Bryan A.

    2014-01-01

    Standardization of methods to assess and assign quality metrics to satellite ocean color radiometry and derived geophysical products has become paramount with the inclusion of the marine reflectance and chlorophyll-a concentration (Chla) as essential climate variables (ECV; [1]) and the recognition that optical remote sensing of the oceans can only contribute to climate research if and when a continuous succession of satellite missions can be shown to collectively provide a consistent, long-term record with known uncertainties. In 20 years, the community has made significant advancements toward that objective, but providing a complete uncertainty budget for all products and for all conditions remains a daunting task. In the retrieval of marine water-leaving radiance from observed top-of-atmosphere radiance, the sources of uncertainties include those associated with propagation of sensor noise and radiometric calibration and characterization errors, as well as a multitude of uncertainties associated with the modeling and removal of effects from the atmosphere and sea surface. This chapter describes some common approaches used to assess quality and consistency of ocean color satellite products and reviews the current status of uncertainty quantification in the field. Its focus is on the primary ocean color product, the spectrum of marine reflectance Rrs, but uncertainties in some derived products such as the Chla or inherent optical properties (IOPs) will also be considered.

  11. Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

    Science.gov (United States)

    Fang, Li

    The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied

  12. Burn severity mapping using simulation modeling and satellite imagery

    Science.gov (United States)

    Eva C. Karau; Robert E. Keane

    2010-01-01

    Although burn severity maps derived from satellite imagery provide a landscape view of fire impacts, fire effects simulation models can provide spatial fire severity estimates and add a biotic context in which to interpret severity. In this project, we evaluated two methods of mapping burn severity in the context of rapid post-fire assessment for four wildfires in...

  13. Aerosol indirect effects -- general circulation model intercomparison and evaluation with satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Quaas, Johannes; Ming, Yi; Menon, Surabi; Takemura, Toshihiko; Wang, Minghuai; Penner, Joyce E.; Gettelman, Andrew; Lohmann, Ulrike; Bellouin, Nicolas; Boucher, Olivier; Sayer, Andrew M.; Thomas, Gareth E.; McComiskey, Allison; Feingold, Graham; Hoose, Corinna; Kristjansson, Jon Egill; Liu, Xiaohong; Balkanski, Yves; Donner, Leo J.; Ginoux, Paul A.; Stier, Philip; Feichter, Johann; Sednev, Igor; Bauer, Susanne E.; Koch, Dorothy; Grainger, Roy G.; Kirkevag, Alf; Iversen, Trond; Seland, Oyvind; Easter, Richard; Ghan, Steven J.; Rasch, Philip J.; Morrison, Hugh; Lamarque, Jean-Francois; Iacono, Michael J.; Kinne, Stefan; Schulz, Michael

    2009-04-10

    Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (Ta) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between Ta and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and Ta as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld - Ta relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between Ta and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - Ta relationship show a strong positive correlation between Ta and fcld The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of Ta, and parameterisation assumptions such as a lower bound on Nd

  14. Examining the utility of satellite-based wind sheltering estimates for lake hydrodynamic modeling

    Science.gov (United States)

    Van Den Hoek, Jamon; Read, Jordan S.; Winslow, Luke A.; Montesano, Paul; Markfort, Corey D.

    2015-01-01

    Satellite-based measurements of vegetation canopy structure have been in common use for the last decade but have never been used to estimate canopy's impact on wind sheltering of individual lakes. Wind sheltering is caused by slower winds in the wake of topography and shoreline obstacles (e.g. forest canopy) and influences heat loss and the flux of wind-driven mixing energy into lakes, which control lake temperatures and indirectly structure lake ecosystem processes, including carbon cycling and thermal habitat partitioning. Lakeshore wind sheltering has often been parameterized by lake surface area but such empirical relationships are only based on forested lakeshores and overlook the contributions of local land cover and terrain to wind sheltering. This study is the first to examine the utility of satellite imagery-derived broad-scale estimates of wind sheltering across a diversity of land covers. Using 30 m spatial resolution ASTER GDEM2 elevation data, the mean sheltering height, hs, being the combination of local topographic rise and canopy height above the lake surface, is calculated within 100 m-wide buffers surrounding 76,000 lakes in the U.S. state of Wisconsin. Uncertainty of GDEM2-derived hs was compared to SRTM-, high-resolution G-LiHT lidar-, and ICESat-derived estimates of hs, respective influences of land cover type and buffer width on hsare examined; and the effect of including satellite-based hs on the accuracy of a statewide lake hydrodynamic model was discussed. Though GDEM2 hs uncertainty was comparable to or better than other satellite-based measures of hs, its higher spatial resolution and broader spatial coverage allowed more lakes to be included in modeling efforts. GDEM2 was shown to offer superior utility for estimating hs compared to other satellite-derived data, but was limited by its consistent underestimation of hs, inability to detect within-buffer hs variability, and differing accuracy across land cover types. Nonetheless

  15. Interim Service ISDN Satellite (ISIS) network model for advanced satellite designs and experiments

    Science.gov (United States)

    Pepin, Gerard R.; Hager, E. Paul

    1991-01-01

    The Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) Network Model for Advanced Satellite Designs and Experiments describes a model suitable for discrete event simulations. A top-down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ISDN modeling abstractions are added to permit the determination and performance for the NASA Satellite Communications Research (SCAR) Program.

  16. Moisture convergence using satellite-derived wind fields - A severe local storm case study

    Science.gov (United States)

    Negri, A. J.; Vonder Haar, T. H.

    1980-01-01

    Five-minute interval 1-km resolution SMS visible channel data were used to derive low-level wind fields by tracking small cumulus clouds on NASA's Atmospheric and Oceanographic Information Processing System. The satellite-derived wind fields were combined with surface mixing ratios to derive horizontal moisture convergence in the prestorm environment of April 24, 1975. Storms began developing in an area extending from southwest Oklahoma to eastern Tennessee 2 h subsequent to the time of the derived fields. The maximum moisture convergence was computed to be 0.0022 g/kg per sec and areas of low-level convergence of moisture were in general indicative of regions of severe storm genesis. The resultant moisture convergence fields derived from two wind sets 20 min apart were spatially consistent and reflected the mesoscale forcing of ensuing storm development. Results are discussed with regard to possible limitations in quantifying the relationship between low-level flow and between low-level flow and satellite-derived cumulus motion in an antecedent storm environment.

  17. Simulation of stationary and transient geopotential-height eddies in January and July with a spectral general circulation model

    International Nuclear Information System (INIS)

    Malone, R.C.; Pitcher, E.J.; Blackmon, M.L.; Puri, K.; Bourke, W.

    1984-01-01

    We examine the characteristics of stationary and transient eddies in the geopotential-height field as simulated by a spectral general circulation model. The model possessess a realistic, but smootheed, topography. Two simulations with perpetual January and July forcing by climatological sea surface temperatures, sea ice, and insolation were extended to 1200 days, of which the final 600 days were used for the results in this study. We find that the stationary waves are well simulated in both seasons in the Northern Hemisphere, where strong forcing by orography and land-sea thermal contrast exists. However, in the Southern Hemisphere, where no continents are present in midlatitudes, the stationary waves have smaller amplitude than that observed in both seasons. In both hemispheres, the transient eddies are well simulated in the winter season but are too weak in the summer season. The model fails to generate a sufficiently intense summertime midlatitude jet in either hemisphere, and this results in a low level of transient activity. The variance in the tropical troposphere is very well simulated. We examine the geographical distribution and vertical structure of the transient eddies. Fourier analysis in zonal wavenumber and temporal filtering are used to display the wavelength and frequency characteristics of the eddies

  18. Using eddy geopotential height to measure the western North Pacific subtropical high in a warming climate

    Science.gov (United States)

    He, Chao; Lin, Ailan; Gu, Dejun; Li, Chunhui; Zheng, Bin; Wu, Bo; Zhou, Tianjun

    2018-01-01

    The western North Pacific subtropical high (WNPSH) is crucial to the East Asian summer climate, and geopotential height ( H) is widely used to measure the WPNSH. However, a rapidly rising trend of H in the future is projected by the models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Diagnoses based on the hypsometric equation suggest that more than 80% of the rise in H are attributable to zonal uniform warming. Because circulation is determined by the gradient of H rather than its absolute magnitude, the spatially uniform rising trend of H gives rise to difficulties when measuring the WNPSH with H. These difficulties include an invalid western boundary of WNPSH in the future and spurious information regarding long-term trends and interannual variability of WNPSH. Using CMIP5 model simulations and reanalysis data, the applicability of a metric based on eddy geopotential height ( H e ) to the warming climate is investigated. The results show that the H e metric outperforms the H metric under warming climate conditions. First, the mean state rainfall- H e relationship is more robust than the rainfall- H relationship. Second, the area, intensity, and western boundary indices of WNPSH can be effectively defined by the H e = 0-m contour in future warming climate scenarios without spurious trends. Third, the interannual variability of East Asian summer rainfall is more closely related to the H e -based WNPSH indices. We recommend that the H e metric be adopted as an operational metric on the WNPSH under the current warming climate.

  19. On possible a-priori "imprinting" of General Relativity itself on the performed Lense-Thirring tests with LAGEOS satellites

    Science.gov (United States)

    Iorio, Lorenzo

    2010-02-01

    The impact of possible a-priori "imprinting" effects of general relativity itself on recent attempts to measure the general relativistic Lense-Thirring effect with the LAGEOS satellites orbiting the Earth and the terrestrial geopotential models from the dedicated mission GRACE is investigated. It is analytically shown that general relativity, not explicitly solved for in the GRACE-based models, may "imprint" their even zonal harmonic coefficients of low degrees J_l at a non-negligible level, given the present-day accuracy in recovering them. This translates into a bias of the LAGEOS-based relativistic tests as large as the Lense-Thirring effect itself. Further analyses should include general relativity itself in the GRACE data processing by explicitly solving for it.

  20. Improvement in the radial accuracy of altimeter-satellite orbits due to the geopotential

    Czech Academy of Sciences Publication Activity Database

    Klokočník, Jaroslav; Kostelecký, J.; Wagner, C. A.

    2008-01-01

    Roč. 91, 1-4 (2008), s. 106-120 ISSN 0012-8252 R&D Projects: GA AV ČR IAA3003407; GA MŠk(CZ) LC506 Institutional research plan: CEZ:AV0Z10030501 Keywords : orbits of Earth artificial satellites * gravity field of the Earth * radial orbit error Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 6.558, year: 2008

  1. A satellite-based global landslide model

    Directory of Open Access Journals (Sweden)

    A. Farahmand

    2013-05-01

    Full Text Available Landslides are devastating phenomena that cause huge damage around the world. This paper presents a quasi-global landslide model derived using satellite precipitation data, land-use land cover maps, and 250 m topography information. This suggested landslide model is based on the Support Vector Machines (SVM, a machine learning algorithm. The National Aeronautics and Space Administration (NASA Goddard Space Flight Center (GSFC landslide inventory data is used as observations and reference data. In all, 70% of the data are used for model development and training, whereas 30% are used for validation and verification. The results of 100 random subsamples of available landslide observations revealed that the suggested landslide model can predict historical landslides reliably. The average error of 100 iterations of landslide prediction is estimated to be approximately 7%, while approximately 2% false landslide events are observed.

  2. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

  3. Bio-Optical Data Assimilation With Observational Error Covariance Derived From an Ensemble of Satellite Images

    Science.gov (United States)

    Shulman, Igor; Gould, Richard W.; Frolov, Sergey; McCarthy, Sean; Penta, Brad; Anderson, Stephanie; Sakalaukus, Peter

    2018-03-01

    An ensemble-based approach to specify observational error covariance in the data assimilation of satellite bio-optical properties is proposed. The observational error covariance is derived from statistical properties of the generated ensemble of satellite MODIS-Aqua chlorophyll (Chl) images. The proposed observational error covariance is used in the Optimal Interpolation scheme for the assimilation of MODIS-Aqua Chl observations. The forecast error covariance is specified in the subspace of the multivariate (bio-optical, physical) empirical orthogonal functions (EOFs) estimated from a month-long model run. The assimilation of surface MODIS-Aqua Chl improved surface and subsurface model Chl predictions. Comparisons with surface and subsurface water samples demonstrate that data assimilation run with the proposed observational error covariance has higher RMSE than the data assimilation run with "optimistic" assumption about observational errors (10% of the ensemble mean), but has smaller or comparable RMSE than data assimilation run with an assumption that observational errors equal to 35% of the ensemble mean (the target error for satellite data product for chlorophyll). Also, with the assimilation of the MODIS-Aqua Chl data, the RMSE between observed and model-predicted fractions of diatoms to the total phytoplankton is reduced by a factor of two in comparison to the nonassimilative run.

  4. Optimal Filtering in Mass Transport Modeling From Satellite Gravimetry Data

    Science.gov (United States)

    Ditmar, P.; Hashemi Farahani, H.; Klees, R.

    2011-12-01

    Monitoring natural mass transport in the Earth's system, which has marked a new era in Earth observation, is largely based on the data collected by the GRACE satellite mission. Unfortunately, this mission is not free from certain limitations, two of which are especially critical. Firstly, its sensitivity is strongly anisotropic: it senses the north-south component of the mass re-distribution gradient much better than the east-west component. Secondly, it suffers from a trade-off between temporal and spatial resolution: a high (e.g., daily) temporal resolution is only possible if the spatial resolution is sacrificed. To make things even worse, the GRACE satellites enter occasionally a phase when their orbit is characterized by a short repeat period, which makes it impossible to reach a high spatial resolution at all. A way to mitigate limitations of GRACE measurements is to design optimal data processing procedures, so that all available information is fully exploited when modeling mass transport. This implies, in particular, that an unconstrained model directly derived from satellite gravimetry data needs to be optimally filtered. In principle, this can be realized with a Wiener filter, which is built on the basis of covariance matrices of noise and signal. In practice, however, a compilation of both matrices (and, therefore, of the filter itself) is not a trivial task. To build the covariance matrix of noise in a mass transport model, it is necessary to start from a realistic model of noise in the level-1B data. Furthermore, a routine satellite gravimetry data processing includes, in particular, the subtraction of nuisance signals (for instance, associated with atmosphere and ocean), for which appropriate background models are used. Such models are not error-free, which has to be taken into account when the noise covariance matrix is constructed. In addition, both signal and noise covariance matrices depend on the type of mass transport processes under

  5. Producing a satellite-derived map and modelling Spartina alterniflora expansion for Willapa Bay in Washington State

    Science.gov (United States)

    Berlin, Cynthia Jane

    1998-12-01

    This research addresses the identification of the areal extent of the intertidal wetlands of Willapa Bay, Washington, and the evaluation of the potential for exotic Spartina alterniflora (smooth cordgrass) expansion in the bay using a spatial geographic approach. It is hoped that the results will address not only the management needs of the study area but provide a research design that may be applied to studies of other coastal wetlands. Four satellite images, three Landsat Multi-Spectral (MSS) and one Thematic Mapper (TM), are used to derive a map showing areas of water, low, middle and high intertidal, and upland. Two multi-date remote sensing mapping techniques are assessed: a supervised classification using density-slicing and an unsupervised classification using an ISODATA algorithm. Statistical comparisons are made between the resultant derived maps and the U.S.G.S. topographic maps for the Willapa Bay area. The potential for Spartina expansion in the bay is assessed using a sigmoidal (logistic) growth model and a spatial modelling procedure for four possible growth scenarios: without management controls (Business-as-Usual), with moderate management controls (e.g. harvesting to eliminate seed setting), under a hypothetical increase in the growth rate that may reflect favorable environmental changes, and under a hypothetical decrease in the growth rate that may reflect aggressive management controls. Comparisons for the statistics of the two mapping techniques suggest that although the unsupervised classification method performed satisfactorily, the supervised classification (density-slicing) method provided more satisfactory results. Results from the modelling of potential Spartina expansion suggest that Spartina expansion will proceed rapidly for the Business-as-Usual and hypothetical increase in the growth rate scenario, and at a slower rate for the elimination of seed setting and hypothetical decrease in the growth rate scenarios, until all potential

  6. Application of a chlorophyll index derived from satellite data to ...

    African Journals Online (AJOL)

    Application of a chlorophyll index derived from satellite data to investigate the variability of phytoplankton in the Benguela ecosystem. H Demarcq, R Barlow, L Hutchings. Abstract. No Abstract. African Journal of Marine Science Vol.29(2) 2007: pp. 271-282. Full Text: EMAIL FULL TEXT EMAIL FULL TEXT · DOWNLOAD ...

  7. Satellite image analysis and a hybrid ESSS/ANN model to forecast solar irradiance in the tropics

    International Nuclear Information System (INIS)

    Dong, Zibo; Yang, Dazhi; Reindl, Thomas; Walsh, Wilfred M.

    2014-01-01

    Highlights: • Satellite image analysis is performed and cloud cover index is classified using self-organizing maps (SOM). • The ESSS model is used to forecast cloud cover index. • Solar irradiance is estimated using multi-layer perceptron (MLP). • The proposed model shows better accuracy than other investigated models. - Abstract: We forecast hourly solar irradiance time series using satellite image analysis and a hybrid exponential smoothing state space (ESSS) model together with artificial neural networks (ANN). Since cloud cover is the major factor affecting solar irradiance, cloud detection and classification are crucial to forecast solar irradiance. Geostationary satellite images provide cloud information, allowing a cloud cover index to be derived and analysed using self-organizing maps (SOM). Owing to the stochastic nature of cloud generation in tropical regions, the ESSS model is used to forecast cloud cover index. Among different models applied in ANN, we favour the multi-layer perceptron (MLP) to derive solar irradiance based on the cloud cover index. This hybrid model has been used to forecast hourly solar irradiance in Singapore and the technique is found to outperform traditional forecasting models

  8. Using scale heights derived from bottomside ionograms for modelling the IRI topside profile

    Directory of Open Access Journals (Sweden)

    B. W. Reinisch

    2004-01-01

    Full Text Available Groundbased ionograms measure the Chapman scale height HT at the F2-layer peak that is used to construct the topside profile. After a brief review of the topside model extrapolation technique, comparisons are presented between the modeled profiles with incoherent scatter radar and satellite measurements for the mid latitude and equatorial ionosphere. The total electron content TEC, derived from measurements on satellite beacon signals, is compared with the height-integrated profiles ITEC from the ionograms. Good agreement is found with the ISR profiles and with results using the low altitude TOPEX satellite. The TEC values derived from GPS signal analysis are systematically larger than ITEC. It is suggested to use HT , routinely measured by a large number of Digisondes around the globe, for the construction of the IRI topside electron density profile.

  9. Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling

    Directory of Open Access Journals (Sweden)

    Mauro Rossi

    2017-12-01

    Full Text Available Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gauge measurements. The rain gauge data from the Italian network (collected in the system database “Verifica Rischio Frana”, VRF are compared with the National Aeronautics and Space Administration (NASA Tropical Rainfall Measuring Mission (TRMM products. For the purpose, we couple point gauge and satellite rainfall estimates at individual grid cells, evaluating the correlation between gauge and satellite data in different morpho-climatological conditions. We then analyze the statistical distributions of both rainfall data types and the rainfall events derived from them. Results show that satellite data underestimates ground data, with the largest differences in mountainous areas. Power-law models, are more appropriate to correlate gauge and satellite data. The gauge and satellite-based products exhibit different statistical distributions and the rainfall events derived from them differ. In conclusion, satellite rainfall cannot be directly compared with ground data, requiring local investigation to account for specific morpho-climatological settings. Results suggest that satellite data can be used for forecasting landslides, only performing a local scaling between satellite and ground data.

  10. Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

    Science.gov (United States)

    Bell, Thomas L.; Kundu, Prasun K.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

  11. Full Service ISDN Satellite (FSIS) network model for advanced ISDN satellite design and experiments

    Science.gov (United States)

    Pepin, Gerard R.

    1992-01-01

    The Full Service Integrated Services Digital Network (FSIS) network model for advanced satellite designs describes a model suitable for discrete event simulations. A top down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ACTS and the Interim Service ISDN Satellite (ISIS) perform ISDN protocol analyses and switching decisions in the terrestrial domain, whereas FSIS makes all its analyses and decisions on-board the ISDN satellite.

  12. High accuracy satellite drag model (HASDM)

    Science.gov (United States)

    Storz, Mark F.; Bowman, Bruce R.; Branson, Major James I.; Casali, Stephen J.; Tobiska, W. Kent

    The dominant error source in force models used to predict low-perigee satellite trajectories is atmospheric drag. Errors in operational thermospheric density models cause significant errors in predicted satellite positions, since these models do not account for dynamic changes in atmospheric drag for orbit predictions. The Air Force Space Battlelab's High Accuracy Satellite Drag Model (HASDM) estimates and predicts (out three days) a dynamically varying global density field. HASDM includes the Dynamic Calibration Atmosphere (DCA) algorithm that solves for the phases and amplitudes of the diurnal and semidiurnal variations of thermospheric density near real-time from the observed drag effects on a set of Low Earth Orbit (LEO) calibration satellites. The density correction is expressed as a function of latitude, local solar time and altitude. In HASDM, a time series prediction filter relates the extreme ultraviolet (EUV) energy index E10.7 and the geomagnetic storm index ap, to the DCA density correction parameters. The E10.7 index is generated by the SOLAR2000 model, the first full spectrum model of solar irradiance. The estimated and predicted density fields will be used operationally to significantly improve the accuracy of predicted trajectories for all low-perigee satellites.

  13. Comparing land surface phenology derived from satellite and GPS network microwave remote sensing.

    Science.gov (United States)

    Jones, Matthew O; Kimball, John S; Small, Eric E; Larson, Kristine M

    2014-08-01

    The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO2) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints. Direct field measures of canopy water content and biomass changes desired for LSP validation are generally lacking due to the prohibitive costs of maintaining regional monitoring networks. Alternatively, a normalized microwave reflectance index (NMRI) derived from GPS base station measurements is sensitive to daily vegetation water content changes and may provide for effective microwave LSP validation. We compared multiyear (2007-2011) NMRI and satellite VOD records at over 300 GPS sites in North America, and their derived SOS metrics for a subset of 24 homogenous land cover sites to investigate VOD and NMRI correspondence, and potential NMRI utility for LSP validation. Significant correlations (P<0.05) were found at 276 of 305 sites (90.5 %), with generally favorable correspondence in the resulting SOS metrics (r (2)=0.73, P<0.001, RMSE=36.8 days). This study is the first attempt to compare satellite microwave LSP metrics to a GPS network derived reflectance index and highlights both the utility and limitations of the NMRI data for LSP validation, including spatial scale discrepancies between local NMRI measurements and relatively coarse satellite VOD retrievals.

  14. Potentials of satellite derived SIF products to constrain GPP simulated by the new ORCHIDEE-FluOR terrestrial model at the global scale

    Science.gov (United States)

    Bacour, C.; Maignan, F.; Porcar-Castell, A.; MacBean, N.; Goulas, Y.; Flexas, J.; Guanter, L.; Joiner, J.; Peylin, P.

    2016-12-01

    A new era for improving our knowledge of the terrestrial carbon cycle at the global scale has begun with recent studies on the relationships between remotely sensed Sun Induce Fluorescence (SIF) and plant photosynthetic activity (GPP), and the availability of such satellite-derived products now "routinely" produced from GOSAT, GOME-2, or OCO-2 observations. Assimilating SIF data into terrestrial ecosystem models (TEMs) represents a novel opportunity to reduce the uncertainty of their prediction with respect to carbon-climate feedbacks, in particular the uncertainties resulting from inaccurate parameter values. A prerequisite is a correct representation in TEMs of the several drivers of plant fluorescence from the leaf to the canopy scale, and in particular the competing processes of photochemistry and non photochemical quenching (NPQ).In this study, we present the first results of a global scale assimilation of GOME-2 SIF products within a new version of the ORCHIDEE land surface model including a physical module of plant fluorescence. At the leaf level, the regulation of fluorescence yield is simulated both by the photosynthesis module of ORCHIDEE to calculate the photochemical yield and by a parametric model to estimate NPQ. The latter has been calibrated on leaf fluorescence measurements performed for boreal coniferous and Mediterranean vegetation species. A parametric representation of the SCOPE radiative transfer model is used to model the plant fluorescence fluxes for PSI and PSII and the scaling up to the canopy level. The ORCHIDEE-FluOR model is firstly evaluated with respect to in situ measurements of plant fluorescence flux and photochemical yield for scots pine and wheat. The potentials of SIF data to constrain the modelled GPP are evaluated by assimilating one year of GOME-2-SIF products within ORCHIDEE-FluOR. We investigate in particular the changes in the spatial patterns of GPP following the optimization of the photosynthesis and phenology parameters

  15. Clustering of France Monthly Precipitation, Temperature and Discharge Based on their Multiresolution Links with 500mb Geopotential Height from 1968 to 2008

    Science.gov (United States)

    Massei, N.; Fossa, M.; Dieppois, B.; Vidal, J. P.; Fournier, M.; Laignel, B.

    2017-12-01

    In the context of climate change and ever growing use of water resources, identifying how the climate and watershed signature in discharge variability changes with the geographic location is of prime importance. This study aims at establishing how 1968-2008 multiresolution links between 3 local hydrometerological variables (precipitation, temperature and discharge) and 500 mb geopotential height are structured over France. First, a methodology that allows to encode the 3D geopotential height data into its 1D conformal modulus time series is introduced. Then, for each local variable, their covariations with the geopotential height are computed with cross wavelet analysis. Finally, a clustering analysis of each variable cross spectra is done using bootstrap clustering.We compare the clustering results for each local variable in order to untangle the watershed from the climate drivers in France's rivers discharge. Additionally, we identify the areas in the geopotential height field that are responsible for the spatial structure of each local variable.Main results from this study show that for precipitation and discharge, clear spatial zones emerge. Each cluster is characterized either by different different amplitudes and/or time scales of covariations with geopotential height. Precipitation and discharge clustering differ with the later being simpler which indicates a strong low frequency modulation by the watersheds all over France. Temperature on the other hand shows less clearer spatial zones. For precipitation and discharge, we show that the main action path starts at the northern tropical zone then moves up the to central North Atlantic zone which seems to indicates an interaction between the convective cells variability and the reinforcement of the westerlies jets as one of the main control of the precipitation and discharge over France. Temperature shows a main zone of action directly over France hinting at local temperature/pressure interactions.

  16. Modeling UV-B Effects on Primary Production Throughout the Southern Ocean Using Multi-Sensor Satellite Data

    Science.gov (United States)

    Lubin, Dan

    2001-01-01

    This study has used a combination of ocean color, backscattered ultraviolet, and passive microwave satellite data to investigate the impact of the springtime Antarctic ozone depletion on the base of the Antarctic marine food web - primary production by phytoplankton. Spectral ultraviolet (UV) radiation fields derived from the satellite data are propagated into the water column where they force physiologically-based numerical models of phytoplankton growth. This large-scale study has been divided into two components: (1) the use of Total Ozone Mapping Spectrometer (TOMS) and Special Sensor Microwave Imager (SSM/I) data in conjunction with radiative transfer theory to derive the surface spectral UV irradiance throughout the Southern Ocean; and (2) the merging of these UV irradiances with the climatology of chlorophyll derived from SeaWiFS data to specify the input data for the physiological models.

  17. An improved model for the Earth's gravity field

    Science.gov (United States)

    Tapley, B. D.; Shum, C. K.; Yuan, D. N.; Ries, J. C.; Schutz, B. E.

    1989-01-01

    An improved model for the Earth's gravity field, TEG-1, was determined using data sets from fourteen satellites, spanning the inclination ranges from 15 to 115 deg, and global surface gravity anomaly data. The satellite measurements include laser ranging data, Doppler range-rate data, and satellite-to-ocean radar altimeter data measurements, which include the direct height measurement and the differenced measurements at ground track crossings (crossover measurements). Also determined was another gravity field model, TEG-1S, which included all the data sets in TEG-1 with the exception of direct altimeter data. The effort has included an intense scrutiny of the gravity field solution methodology. The estimated parameters included geopotential coefficients complete to degree and order 50 with selected higher order coefficients, ocean and solid Earth tide parameters, Doppler tracking station coordinates and the quasi-stationary sea surface topography. Extensive error analysis and calibration of the formal covariance matrix indicate that the gravity field model is a significant improvement over previous models and can be used for general applications in geodesy.

  18. Improving spatio-temporal model estimation of satellite-derived PM2.5 concentrations: Implications for public health

    Science.gov (United States)

    Barik, M. G.; Al-Hamdan, M. Z.; Crosson, W. L.; Yang, C. A.; Coffield, S. R.

    2017-12-01

    Satellite-derived environmental data, available in a range of spatio-temporal scales, are contributing to the growing use of health impact assessments of air pollution in the public health sector. Models developed using correlation of Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD) with ground measurements of fine particulate matter less than 2.5 microns (PM2.5) are widely applied to measure PM2.5 spatial and temporal variability. In the public health sector, associations of PM2.5 with respiratory and cardiovascular diseases are often investigated to quantify air quality impacts on these health concerns. In order to improve predictability of PM2.5 estimation using correlation models, we have included meteorological variables, higher-resolution AOD products and instantaneous PM2.5 observations into statistical estimation models. Our results showed that incorporation of high-resolution (1-km) Multi-Angle Implementation of Atmospheric Correction (MAIAC)-generated MODIS AOD, meteorological variables and instantaneous PM2.5 observations improved model performance in various parts of California (CA), USA, where single variable AOD-based models showed relatively weak performance. In this study, we further asked whether these improved models actually would be more successful for exploring associations of public health outcomes with estimated PM2.5. To answer this question, we geospatially investigated model-estimated PM2.5's relationship with respiratory and cardiovascular diseases such as asthma, high blood pressure, coronary heart disease, heart attack and stroke in CA using health data from the Centers for Disease Control and Prevention (CDC)'s Wide-ranging Online Data for Epidemiologic Research (WONDER) and the Behavioral Risk Factor Surveillance System (BRFSS). PM2.5 estimation from these improved models have the potential to improve our understanding of associations between public health concerns and air quality.

  19. Rapid core field variations during the satellite era: Investigations using stochastic process based field models

    DEFF Research Database (Denmark)

    Finlay, Chris; Olsen, Nils; Gillet, Nicolas

    We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to tradition...... physical hypotheses can be tested by asking questions of the entire ensemble of core field models, rather than by interpreting any single model.......We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to traditional...... regularization methods based on minimizing the square of second or third time derivative. We invert satellite and observatory data directly by adopting the external field and crustal field modelling framework of the CHAOS model, but apply the stochastic process method of Gillet et al. (2013) to the core field...

  20. Towards the Selection of an Optimal Global Geopotential Model for the Computation of the Long-Wavelength Contribution: A Case Study of Ghana

    Directory of Open Access Journals (Sweden)

    Caleb Iddissah Yakubu

    2017-11-01

    Full Text Available The selection of a global geopotential model (GGM for modeling the long-wavelength for geoid computation is imperative not only because of the plethora of GGMs available but more importantly because it influences the accuracy of a geoid model. In this study, we propose using the Gaussian averaging function for selecting an optimal GGM and degree and order (d/o for the remove-compute-restore technique as a replacement for the direct comparison of terrestrial gravity anomalies and GGM anomalies, because ground data and GGM have different frequencies. Overall, EGM2008 performed better than all the tested GGMs and at an optimal d/o of 222. We verified the results by computing geoid models using Heck and Grüninger’s modification and validated them against GPS/trigonometric data. The results of the validation were consistent with those of the averaging process with EGM2008 giving the smallest standard deviation of 0.457 m at d/o 222, resulting in an 8% improvement over the previous geoid model. In addition, this geoid model, the Ghanaian Gravimetric Geoid 2017 (GGG 2017 may be used to replace second-order class II leveling, with an expected error of 6.8 mm/km for baselines ranging from 20 to 225 km.

  1. Aerosol indirect effects ? general circulation model intercomparison and evaluation with satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Quaas, Johannes; Ming, Yi; Menon, Surabi; Takemura, Toshihiko; Wang, Minghuai; Penner, Joyce E.; Gettelman, Andrew; Lohmann, Ulrike; Bellouin, Nicolas; Boucher, Olivier; Sayer, Andrew M.; Thomas, Gareth E.; McComiskey, Allison; Feingold, Graham; Hoose, Corinna; Kristansson, Jon Egill; Liu, Xiaohong; Balkanski, Yves; Donner, Leo J.; Ginoux, Paul A.; Stier, Philip; Grandey, Benjamin; Feichter, Johann; Sednev, Igor; Bauer, Susanne E.; Koch, Dorothy; Grainger, Roy G.; Kirkevag, Alf; Iversen, Trond; Seland, Oyvind; Easter, Richard; Ghan, Steven J.; Rasch, Philip J.; Morrison, Hugh; Lamarque, Jean-Francois; Iacono, Michael J.; Kinne, Stefan; Schulz, Michael

    2010-03-12

    Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth ({tau}{sub a}) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (N{sub d}) compares relatively well to the satellite data at least over the ocean. The relationship between {tau}{sub a} and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (f{sub cld}) and {tau}{sub a} as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong f{sub cld} - {tau}{sub a} relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between {tau}{sub a} and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - {tau}{sub a} relationship show a strong positive correlation between {tau}{sub a} and f{sub cld} The short-wave total aerosol radiative forcing as simulated by the GCMs is

  2. Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

    Science.gov (United States)

    Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

    2016-01-01

    Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

  3. CyAN satellite-derived Cyanobacteria products in support of Public Health Protection

    Science.gov (United States)

    The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management decision-making and for targeted deployment of existing government and non-government water quality monitoring resources. The Cyanobacteria Assessment Network (CyAN) is a...

  4. Verifying Air Force Weather Passive Satellite Derived Cloud Analysis Products

    Science.gov (United States)

    Nobis, T. E.

    2017-12-01

    Air Force Weather (AFW) has developed an hourly World-Wide Merged Cloud Analysis (WWMCA) using imager data from 16 geostationary and polar-orbiting satellites. The analysis product contains information on cloud fraction, height, type and various optical properties including optical depth and integrated water path. All of these products are derived using a suite of algorithms which rely exclusively on passively sensed data from short, mid and long wave imager data. The system integrates satellites with a wide-range of capabilities, from the relatively simple two-channel OLS imager to the 16 channel ABI/AHI to create a seamless global analysis in real time. Over the last couple of years, AFW has started utilizing independent verification data from active sensed cloud measurements to better understand the performance limitations of the WWMCA. Sources utilized include space based lidars (CALIPSO, CATS) and radar (CloudSat) as well as ground based lidars from the Department of Energy ARM sites and several European cloud radars. This work will present findings from our efforts to compare active and passive sensed cloud information including comparison techniques/limitations as well as performance of the passive derived cloud information against the active.

  5. Assessment of Gravity Field and Steady State Ocean Circulation Explorer (GOCE) geoid model using GPS levelling over Sabah and Sarawak

    Science.gov (United States)

    Othman, A. H.; Omar, K. M.; Din, A. H. M.; Som, Z. A. M.; Yahaya, N. A. Z.; Pa'suya, M. F.

    2016-06-01

    The GOCE satellite mission has significantly contributed to various applications such as solid earth physics, oceanography and geodesy. Some substantial applications of geodesy are to improve the gravity field knowledge and the precise geoid modelling towards realising global height unification. This paper aims to evaluate GOCE geoid model based on the recent GOCE Global Geopotential Model (GGM), as well as EGM2008, using GPS levelling data over East Malaysia, i.e. Sabah and Sarawak. The satellite GGMs selected in this study are the GOCE GGM models which include GOCE04S, TIM_R5 and SPW_R4, and the EGM2008 model. To assess these models, the geoid heights from these GGMs are compared to the local geometric geoid height. The GGM geoid heights was derived using EGMLAB1 software and the geometric geoid height was computed by available GPS levelling information obtained from the Department Survey and Mapping Malaysia. Generally, the GOCE models performed better than EGM2008 over East Malaysia and the best fit GOCE model for this region is the TIM_R5 model. The TIM_R5 GOCE model demonstrated the lowest R.M.S. of ± 16.5 cm over Sarawak, comparatively. For further improvement, this model should be combined with the local gravity data for optimum geoid modelling over East Malaysia.

  6. Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

    Science.gov (United States)

    Drusch, M.

    2007-02-01

    Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

  7. "Using Satellite Remote Sensing to Derive Numeric Criteria in Coastal and Inland Waters of the United States"

    Science.gov (United States)

    Crawford, T. N.; Schaeffer, B. A.

    2016-12-01

    Anthropogenic nutrient pollution is a major stressor of aquatic ecosystems around the world. In the United States, states and tribes can adopt numeric water quality values (i.e. criteria) into their water quality management standards to protect aquatic life from eutrophication impacts. However, budget and resource constraints have limited the ability of many states and tribes to collect the water quality monitoring data needed to derive numeric criteria. Over the last few decades, satellite technology has provided water quality measurements on a global scale over long time periods. Water quality managers are finding the data provided by satellite technology useful in managing eutrophication impacts in coastal waters, estuaries, lakes, and reservoirs. In recent years EPA has worked with states and tribes to derive remotely sensed numeric Chl-a criteria for coastal waters with limited field-based data. This approach is now being expanded and used to derive Chl-a criteria in freshwater systems across the United States. This presentation will cover EPA's approach to derive numeric Chl-a criteria using satellite remote sensing, recommendations to improve satellite sensors to expand applications, potential areas of interest, and the challenges of using remote sensing to establish water quality management goals, as well as provide a case in which this approach has been applied.

  8. On the use of satellite-derived CH4 : CO2 columns in a joint inversion of CH4 and CO2 fluxes

    NARCIS (Netherlands)

    Pandey, S.

    2015-01-01

    We present a method for assimilating total column CH4 : CO2 ratio measurements from satellites for inverse modeling of CH4 and CO2 fluxes using the variational approach. Unlike conventional approaches, in which retrieved CH4 : CO2 are multiplied by model-derived total column CO2 and only the

  9. Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2013-12-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme

  10. Incorporation of Satellite Data and Uncertainty in a Nationwide Groundwater Recharge Model in New Zealand

    Directory of Open Access Journals (Sweden)

    Rogier Westerhoff

    2018-01-01

    Full Text Available A nationwide model of groundwater recharge for New Zealand (NGRM, as described in this paper, demonstrated the benefits of satellite data and global models to improve the spatial definition of recharge and the estimation of recharge uncertainty. NGRM was inspired by the global-scale WaterGAP model but with the key development of rainfall recharge calculation on scales relevant to national- and catchment-scale studies (i.e., a 1 km × 1 km cell size and a monthly timestep in the period 2000–2014 provided by satellite data (i.e., MODIS-derived evapotranspiration, AET and vegetation in combination with national datasets of rainfall, elevation, soil and geology. The resulting nationwide model calculates groundwater recharge estimates, including their uncertainty, consistent across the country, which makes the model unique compared to all other New Zealand estimates targeted towards groundwater recharge. At the national scale, NGRM estimated an average recharge of 2500 m 3 /s, or 298 mm/year, with a model uncertainty of 17%. Those results were similar to the WaterGAP model, but the improved input data resulted in better spatial characteristics of recharge estimates. Multiple uncertainty analyses led to these main conclusions: the NGRM model could give valuable initial estimates in data-sparse areas, since it compared well to most ground-observed lysimeter data and local recharge models; and the nationwide input data of rainfall and geology caused the largest uncertainty in the model equation, which revealed that the satellite data could improve spatial characteristics without significantly increasing the uncertainty. Clearly the increasing volume and availability of large-scale satellite data is creating more opportunities for the application of national-scale models at the catchment, and smaller, scales. This should result in improved utility of these models including provision of initial estimates in data-sparse areas. Topics for future

  11. The Effect of Seasonal and Long-Period Geopotential Variations on the GPS Orbits

    Science.gov (United States)

    Melachroinos, Stavros A.; Lemoine, Frank G.; Chinn, Douglas S.; Zelensky, Nikita P.; Nicholas, Joseph B.; Beckley, Brian D.

    2013-01-01

    We examine the impact of using seasonal and long-period time-variable gravity field (TVG) models on GPS orbit determination, through simulations from 1994 to 2012. The models of time-variable gravity that we test include the GRGS release RL02 GRACE-derived 10-day gravity field models up to degree and order 20 (grgs20x20), a 4 x 4 series of weekly coefficients using GGM03S as a base derived from SLR and DORIS tracking to 11 satellites (tvg4x4), and a harmonic fit to the above 4 x 4 SLR-DORIS time series (goco2s_fit2). These detailed models are compared to GPS orbit simulations using a reference model (stdtvg) based on the International Earth Rotation Service (IERS) and International GNSS Service (IGS) repro1 standards. We find that the new TVG modeling produces significant along, cross-track orbit differences as well as annual, semi-annual, draconitic and long-period effects in the Helmert translation parameters (Tx, Ty, Tz) of the GPS orbits with magnitudes of several mm. We show that the simplistic TVG modeling approach used by all of the IGS Analysis Centers, which is based on the models provided by the IERS standards, becomes progressively less adequate following 2006 when compared to the seasonal and long-period TVG models.

  12. Use of satellite gravimetry for estimating recent solid Earth changes

    Science.gov (United States)

    Ramillien, Guillaume

    2014-05-01

    Since its launch in March 2002, the Gravity Recovery & Climate Experiment (GRACE) satellite mission provides a global mapping of the time variations of the Earth's gravity field for the recent period. Official centers such as Center of Space Research (CSR) in Austin, TX, Jet Propulsion Laboratory (JPL) in Pasadena, CA and GeoForschungZentrum (GFZ) in Potsdam, Germany, provide 10-day and monthly solutions of Stokes coefficients (i.e., spherical harmonic coefficients of the geopotential) up to harmonic degree 50-60 (or, equivalently, a spatial resolution of 300-400 km) for the timespan 2002-2012. Tiny variations of the gravity measured by GRACE are mainly due to the total water storage change on continents. Therefore, these solutions of water mass can be used to correct other datasets, and then isolate the gravity signatures of large and sudden earthquakes, as well as of the continuous Post Glacial Rebound (PGR) rate. As these measured seasonal variations of continental hydrology represent the variations of water mass load, it is also possible to derive the deformation of the terrestrial surface associated to this varying load using Love numbers. These latter numbers are obtained by assuming an elastic Earth model. In the center of the Amazon basin, the seasonal displacements of the surface due to hydrology reach amplitudes of a few centimeters typically. Time-series of GRACE-based radial displacement of the surface can be analysed and compared with independent local GPS records for validation.

  13. A European satellite-derived UV climatology available for impact studies

    International Nuclear Information System (INIS)

    Verdebout, J.

    2004-01-01

    This paper presents a satellite-derived climatology of the surface UV radiation, intended to support impact studies on the environment and human health. As of today, the dataset covers the period from 1 January 1984 to 31 August 2003, with daily dose maps covering Europe with a spatial resolution of 0.05 deg.. A comparison between the modelled erythemal daily dose and measurements in Ispra yields an r.m.s value with a relative difference of 29% and a bias of 3%. The seemingly large dispersion is, however, due to a restricted number of days for which the relative difference is very high. The climatological dataset documents systematic patterns in the geographical distribution of the surface UV radiation due to cloudiness, altitude and snow. It also shows a large year-to-year variability in monthly doses of up to ±50% in spring and ±30% in summer. (authors)

  14. Nearshore Benthic Habitats of Timor-Leste Derived from WorldView-2 Satellite Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Benthic habitat classes were derived for nearshore waters (< 20 m depths) around Timor-Leste from DigitalGlobe WorldView-2 satellite imagery, acquired from Jan 26...

  15. A Comparison of Satellite Based, Modeled Derived Daily Solar Radiation Data with Observed Data for the Continental US

    Science.gov (United States)

    White, Jeffrey W.; Hoogenboom, Gerrit; Wilkens, Paul W.; Stackhouse, Paul W., Jr.; Hoell, James M.

    2010-01-01

    Many applications of simulation models and related decision support tools for agriculture and natural resource management require daily meteorological data as inputs. Availability and quality of such data, however, often constrain research and decision support activities that require use of these tools. Daily solar radiation (SRAD) data are especially problematic because the instruments require electronic integrators, accurate sensors are expensive, and calibration standards are seldom available. The Prediction Of Worldwide Energy Resources (NASA/POWER; power.larc.nasa.gov) project at the NASA Langley Research Center estimates daily solar radiation based on data that are derived from satellite observations of outgoing visible radiances and atmospheric parameters based upon satellite observations and assimilation models. The solar data are available for a global 1 degree x 1 degree coordinate grid. SRAD can also be estimated based on attenuation of extraterrestrial radiation (Q0) using daily temperature and rainfall data to estimate the optical thickness of the atmosphere. This study compares daily solar radiation data from NASA/POWER (SRADNP) with instrument readings from 295 stations (SRADOB), as well as with values that were estimated with the WGENR solar generator. WGENR was used both with daily temperature and precipitation records from the stations reporting solar data and records from the NOAA Cooperative Observer Program (COOP), thus providing two additional sources of solar data, SRADWG and SRADCO. Values of SRADNP for different grid cells consistently showed higher correlations (typically 0.85 to 0.95) with SRADOB data than did SRADWG or SRADCO for sites within the corresponding cells. Mean values of SRADOB, SRADWG and SRADNP for sites within a grid cell usually were within 1 MJm-2d-1 of each other, but NASA/POWER values averaged 1.1 MJm-2d-1 lower than SRADOB. The magnitude of this bias was greater at lower latitudes and during summer months and may be at

  16. Comparing soil moisture memory in satellite observations and models

    Science.gov (United States)

    Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

    2013-04-01

    A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the

  17. Customised search and comparison of in situ, satellite and model data for ocean modellers

    Science.gov (United States)

    Hamre, Torill; Vines, Aleksander; Lygre, Kjetil

    2014-05-01

    For the ocean modelling community, the amount of available data from historical and upcoming in situ sensor networks and satellite missions, provides an rich opportunity to validate and improve their simulation models. However, the problem of making the different data interoperable and intercomparable remains, due to, among others, differences in terminology and format used by different data providers and the different granularity provided by e.g. in situ data and ocean models. The GreenSeas project (Development of global plankton data base and model system for eco-climate early warning) aims to advance the knowledge and predictive capacities of how marine ecosystems will respond to global change. In the project, one specific objective has been to improve the technology for accessing historical plankton and associated environmental data sets, along with earth observation data and simulation outputs. To this end, we have developed a web portal enabling ocean modellers to easily search for in situ or satellite data overlapping in space and time, and compare the retrieved data with their model results. The in situ data are retrieved from a geo-spatial repository containing both historical and new physical, biological and chemical parameters for the Southern Ocean, Atlantic, Nordic Seas and the Arctic. The satellite-derived quantities of similar parameters from the same areas are retrieved from another geo-spatial repository established in the project. Both repositories are accessed through standard interfaces, using the Open Geospatial Consortium (OGC) Web Map Service (WMS) and Web Feature Service (WFS), and OPeNDAP protocols, respectively. While the developed data repositories use standard terminology to describe the parameters, especially the measured in situ biological parameters are too fine grained to be immediately useful for modelling purposes. Therefore, the plankton parameters were grouped according to category, size and if available by element. This grouping

  18. Sensitivity study of land biosphere CO2 exchange through an atmospheric tracer transport model using satellite-derived vegetation index data

    International Nuclear Information System (INIS)

    Knorr, W.; Heimann, M.

    1994-01-01

    We develop a simple, globally uniform model of CO 2 exchange between the atmosphere and the terrestrial biosphere by coupling the model with a three-dimensional atmospheric tracer transport model using observed winds, and checking results against observed concentrations of CO 2 at various monitoring sites. CO 2 fluxes are derived from observed greenness using satellite-derived Global Vegetation Index data, combined with observations of temperature, radiation, and precipitation. We explore a range of CO 2 flux formulations together with some modifications of the modelled atmospheric transport. We find that while some formulations can be excluded, it cannot be decided whether or not to make CO 2 uptake and release dependent on water stress. It appears that the seasonality of net CO 2 fluxes in the tropics, which would be expected to be driven by water availability, is small and is therefore not visible in the seasonal cycle of atmospheric CO 2 . The latter is dominated largely by northern temperate and boreal vegetation, where seasonality is mostly temperature determined. We find some evidence that there is still considerable CO 2 release from soils during northern-hemisphere winter. An exponential air temperature dependence of soil release with a Q 10 of 1.5 is found to be most appropriate, with no cutoff at low freezing temperatures. This result is independent of the year from which observed winds were taken. This is remarkable insofar as year-to-year changes in modelled CO 2 concentrations caused by changes in the wind data clearly outweigh those caused by year-to-year variability in the climate and vegetation index data. (orig.)

  19. Linear mixing model applied to coarse resolution satellite data

    Science.gov (United States)

    Holben, Brent N.; Shimabukuro, Yosio E.

    1992-01-01

    A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.

  20. Quantifying the clear-sky bias of satellite-derived infrared LST

    Science.gov (United States)

    Ermida, S. L.; Trigo, I. F.; DaCamara, C.

    2017-12-01

    Land surface temperature (LST) is one of the most relevant parameters when addressing the physical processes that take place at the surface of the Earth. Satellite data are particularly appropriate for measuring LST over the globe with high temporal resolution. Remote-sensed LST estimation from space-borne sensors has been systematically performed over the Globe for nearly 3 decades and geostationary LST climate data records are now available. The retrieval of LST from satellite observations generally relies on measurements in the thermal infrared (IR) window. Although there is a large number of IR sensors on-board geostationary satellites and polar orbiters suitable for LST retrievals with different temporal and spatial resolutions, the use of IR observations limits LST estimates to clear sky conditions. As a consequence, climate studies based on IR LST are likely to be affected by the restriction of LST data to cloudless conditions. However, such "clear sky bias" has never been quantified and, therefore, the actual impact of relying only on clear sky data is still to be determined. On the other hand, an "all-weather" global LST database may be set up based on passive microwave (MW) measurements which are much less affected by clouds. An 8-year record of all-weather MW LST is here used to quantify the clear-sky bias of IR LST at global scale based on MW observations performed by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) onboard NASA's Aqua satellite. Selection of clear-sky and cloudy pixels is based on information derived from measurements performed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the same satellite.

  1. Solar resources and power potential mapping in Vietnam using satellite-derived and GIS-based information

    International Nuclear Information System (INIS)

    Polo, J.; Bernardos, A.; Navarro, A.A.; Fernandez-Peruchena, C.M.; Ramírez, L.; Guisado, María V.; Martínez, S.

    2015-01-01

    Highlights: • Satellite-based, reanalysis data and measurements are combined for solar mapping. • Plant output modeling for PV and CSP results in simple expressions of solar potential. • Solar resource, solar potential are used in a GIS for determine technical solar potential. • Solar resource and potential maps of Vietnam are presented. - Abstract: The present paper presents maps of the solar resources in Vietnam and of the solar potential for concentrating solar power (CSP) and for grid-connected photovoltaic (PV) technology. The mapping of solar radiation components has been calculated from satellite-derived data combined with solar radiation derived from sunshine duration and other additional sources of information based on reanalysis for several atmospheric and meteorological parameters involved. Two scenarios have been selected for the study of the solar potential: CSP Parabolic Trough of 50 MWe and grid-connected Flat Plate PV plant of around 1 MWe. For each selected scenario plant performance simulations have been computed for developing simple expressions that allow the estimation of the solar potential from the annual solar irradiation and the latitude of every site in Vietnam. Finally, Geographic Information Systems (GIS) have been used for combining the solar potential with the land availability according each scenario to deliver the technical solar potential maps of Vietnam

  2. Environmental Satellite Models for a Macroeconomic Model

    International Nuclear Information System (INIS)

    Moeller, F.; Grinderslev, D.; Werner, M.

    2003-01-01

    To support national environmental policy, it is desirable to forecast and analyse environmental indicators consistently with economic variables. However, environmental indicators are physical measures linked to physical activities that are not specified in economic models. One way to deal with this is to develop environmental satellite models linked to economic models. The system of models presented gives a frame of reference where emissions of greenhouse gases, acid gases, and leaching of nutrients to the aquatic environment are analysed in line with - and consistently with - macroeconomic variables. This paper gives an overview of the data and the satellite models. Finally, the results of applying the model system to calculate the impacts on emissions and the economy are reviewed in a few illustrative examples. The models have been developed for Denmark; however, most of the environmental data used are from the CORINAIR system implemented in numerous countries

  3. Regional model simulation of the North Atlantic cyclone "Caroline" and comparisons with satellite data

    Directory of Open Access Journals (Sweden)

    E. Keup-Thiel

    2003-03-01

    Full Text Available An individual regional model simulation of cyclone "Caroline" has been carried out to study water cycle components over the North Atlantic Ocean. The uncertainties associated with quantitative estimates of the water cycle components are highlighted by a comparison of the model results with SSM/I (Special Sensor Microwave Imager satellite data. The vertically integrated water vapor of the REgional MOdel REMO is in good agreement with the SSM/I satellite data. The simulation results for other water budget components like the vertically integrated liquid water content and precipitation compare also reasonably well within the frontal system. However, the high precipitation rate in the cold air outbreak on the backside of the cold front derived from SSM/I satellite data is generally underestimated by REMO. This results in a considerable deficit of the total precipitation amount accumulated for the cyclone "Caroline". While REMO simulates 24.3 108 m3 h-1 for 09:00 UTC, the total areal precipitation from SSM/I satellite data amounts to 54.7 08 m3 h-1.Key words. Meteorology and atmospheric dynamics (precipitation; mesoscale meteorology – Radio science (remote sensing

  4. Precision Orbit Derived Atmospheric Density: Development and Performance

    Science.gov (United States)

    McLaughlin, C.; Hiatt, A.; Lechtenberg, T.; Fattig, E.; Mehta, P.

    2012-09-01

    Precision orbit ephemerides (POE) are used to estimate atmospheric density along the orbits of CHAMP (Challenging Minisatellite Payload) and GRACE (Gravity Recovery and Climate Experiment). The densities are calibrated against accelerometer derived densities and considering ballistic coefficient estimation results. The 14-hour density solutions are stitched together using a linear weighted blending technique to obtain continuous solutions over the entire mission life of CHAMP and through 2011 for GRACE. POE derived densities outperform the High Accuracy Satellite Drag Model (HASDM), Jacchia 71 model, and NRLMSISE-2000 model densities when comparing cross correlation and RMS with accelerometer derived densities. Drag is the largest error source for estimating and predicting orbits for low Earth orbit satellites. This is one of the major areas that should be addressed to improve overall space surveillance capabilities; in particular, catalog maintenance. Generally, density is the largest error source in satellite drag calculations and current empirical density models such as Jacchia 71 and NRLMSISE-2000 have significant errors. Dynamic calibration of the atmosphere (DCA) has provided measurable improvements to the empirical density models and accelerometer derived densities of extremely high precision are available for a few satellites. However, DCA generally relies on observations of limited accuracy and accelerometer derived densities are extremely limited in terms of measurement coverage at any given time. The goal of this research is to provide an additional data source using satellites that have precision orbits available using Global Positioning System measurements and/or satellite laser ranging. These measurements strike a balance between the global coverage provided by DCA and the precise measurements of accelerometers. The temporal resolution of the POE derived density estimates is around 20-30 minutes, which is significantly worse than that of accelerometer

  5. Satellite-derived SIF and CO2 Observations Show Coherent Responses to Interannual Climate Variations

    Science.gov (United States)

    Butterfield, Z.; Hogikyan, A.; Kulawik, S. S.; Keppel-Aleks, G.

    2017-12-01

    Gross primary production (GPP) is the single largest carbon flux in the Earth system, but its sensitivity to changes in climate is subject to significant uncertainty. Satellite measurements of solar-induced chlorophyll fluorescence (SIF) offer insight into spatial and temporal patterns in GPP at a global scale and, combined with other satellite-derived datasets, provide unprecedented opportunity to explore interactions between atmospheric CO2, GPP, and climate variability. To explore potential drivers of GPP in the Northern Hemisphere (NH), we compare monthly-averaged SIF data from the Global Ozone Monitoring Experiment 2 (GOME-2) with observed anomalies in temperature (T; CRU-TS), liquid water equivalent (LWE) from the Gravity Recovery and Climate Experiment (GRACE), and photosynthetically active radiation (PAR; CERES SYN1deg). Using observations from 2007 through 2015 for several NH regions, we calculate month-specific sensitivities of SIF to variability in T, LWE, and PAR. These sensitivities provide insight into the seasonal progression of how productivity is affected by climate variability and can be used to effectively model the observed SIF signal. In general, we find that high temperatures are beneficial to productivity in the spring, but detrimental in the summer. The influences of PAR and LWE are more heterogeneous between regions; for example, higher LWE in North American temperate forest leads to decreased springtime productivity, while exhibiting a contrasting effect in water-limited regions. Lastly, we assess the influence of variations in terrestrial productivity on atmospheric carbon using a new lower tropospheric CO2 product derived from the Greenhouse Gases Observing Satellite (GOSAT). Together, these data shed light on the drivers of interannual variability in the annual cycle of NH atmospheric CO2, and may provide improved constraints on projections of long-term carbon cycle responses to climate change.

  6. Integrating global satellite-derived data products as a pre-analysis for hydrological modelling studies : a case study for the Red River Basin

    NARCIS (Netherlands)

    Simons, G.W.H.; Bastiaanssen, W.G.M.; Ngô, L.A.; Hain, C.R.; Anderson, M.; Senay, G.

    2016-01-01

    With changes in weather patterns and intensifying anthropogenic water use, there is an increasing need for spatio-temporal information on water fluxes and stocks in river basins. The assortment of satellite-derived open-access information sources on rainfall (P) and land use/land cover (LULC) is

  7. Impact of Satellite Remote Sensing Data on Simulations of ...

    Science.gov (United States)

    We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS) near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM) were used for the salinity flux, and the diffuse attenuation coefficient (Kd) from Moderate Resolution Imaging Spectroradiometer (MODIS) were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability wasmissed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the

  8. Exploration of satellite-derived data products for atmospheric turbulence studies

    CSIR Research Space (South Africa)

    Griffith, DJ

    2014-09-01

    Full Text Available reasonable proxy in the absence of in-situ measurements. 3.2 ORNL DAAC The Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) provides a global subsetting and time-series derivation for Moderate Resolution Imaging Spectrometer... (MODIS) data from the NASA Terra and Aqua satellite platforms. The products available for subsetting and time-series generation from the ORNL DAAC are given in Table 2. Moreover, this MODIS facility is available programmatically using the Simple Object...

  9. Estimation of biogenic emissions with satellite-derived land use and land cover data for air quality modeling of Houston-Galveston ozone nonattainment area.

    Science.gov (United States)

    Byun, Daewon W; Kim, Soontae; Czader, Beata; Nowak, David; Stetson, Stephen; Estes, Mark

    2005-06-01

    The Houston-Galveston Area (HGA) is one of the most severe ozone non-attainment regions in the US. To study the effectiveness of controlling anthropogenic emissions to mitigate regional ozone nonattainment problems, it is necessary to utilize adequate datasets describing the environmental conditions that influence the photochemical reactivity of the ambient atmosphere. Compared to the anthropogenic emissions from point and mobile sources, there are large uncertainties in the locations and amounts of biogenic emissions. For regional air quality modeling applications, biogenic emissions are not directly measured but are usually estimated with meteorological data such as photo-synthetically active solar radiation, surface temperature, land type, and vegetation database. In this paper, we characterize these meteorological input parameters and two different land use land cover datasets available for HGA: the conventional biogenic vegetation/land use data and satellite-derived high-resolution land cover data. We describe the procedures used for the estimation of biogenic emissions with the satellite derived land cover data and leaf mass density information. Air quality model simulations were performed using both the original and the new biogenic emissions estimates. The results showed that there were considerable uncertainties in biogenic emissions inputs. Subsequently, ozone predictions were affected up to 10 ppb, but the magnitudes and locations of peak ozone varied each day depending on the upwind or downwind positions of the biogenic emission sources relative to the anthropogenic NOx and VOC sources. Although the assessment had limitations such as heterogeneity in the spatial resolutions, the study highlighted the significance of biogenic emissions uncertainty on air quality predictions. However, the study did not allow extrapolation of the directional changes in air quality corresponding to the changes in LULC because the two datasets were based on vastly different

  10. Suitability Assessment of Satellite-Derived Drought Indices for Mongolian Grassland

    Directory of Open Access Journals (Sweden)

    Sheng Chang

    2017-06-01

    %. The VHI is a combination of constructed VCI and TCI, and can be used instead of them. Finally, the mode method was adopted to identify appropriate drought indices. The best two indices (VHI and NDWI can be utilized to develop a combination drought model for accurately monitoring and quantifying drought in the future. Additionally, the new framework can be adopted to investigate and analyze the suitability of satellite-derived drought indices and determine the most appropriate index/indices for other countries or areas.

  11. Distribution and Variability of Satellite-Derived Signals of Isolated Convection Initiation Events Over Central Eastern China

    Science.gov (United States)

    Huang, Yipeng; Meng, Zhiyong; Li, Jing; Li, Wanbiao; Bai, Lanqiang; Zhang, Murong; Wang, Xi

    2017-11-01

    This study combined measurements from the Chinese operational geostationary satellite Fengyun-2E (FY-2E) and ground-based weather radars to conduct a statistical survey of isolated convection initiation (CI) over central eastern China (CEC). The convective environment in CEC is modulated by the complex topography and monsoon climate. From May to August 2010, a total of 1,630 isolated CI signals were derived from FY-2E using a semiautomated method. The formation of these satellite-derived CI signals peaks in the early afternoon and occurs with high frequency in areas with remarkable terrain inhomogeneity (e.g., mountain, water, and mountain-water areas). The high signal frequency areas shift from northwest CEC (dry, high altitude) in early summer to southeast CEC (humid, low altitude) in midsummer along with an increasing monthly mean frequency. The satellite-derived CI signals tend to have longer lead times (the time difference between satellite-derived signal formation and radar-based CI) in the late morning and afternoon than in the early morning and night. During the early morning and night, the distinction between cloud top signatures and background terrestrial radiation becomes less apparent, resulting in delayed identification of the signals and thus short and even negative lead times. A decline in the lead time is observed from May to August, likely due to the increasing cloud growth rate and warm-rain processes. Results show increasing lead times with increasing landscape elevation, likely due to more warm-rain processes over the coastal sea and plain, along with a decreasing cloud growth rate from hill and mountain to the plateau.

  12. Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization

    Science.gov (United States)

    Smith, W. Kolby; Reed, Sasha C.; Cleveland, Cory C.; Ballantyne, Ashley P; Anderegg, William R. L.; Wieder, William R.; Liu, Yi Y; Running, Steven W.

    2015-01-01

    Atmospheric mass balance analyses suggest that terrestrial carbon (C) storage is increasing, partially abating the atmospheric [CO2] growth rate, although the continued strength of this important ecosystem service remains uncertain. Some evidence suggests that these increases will persist owing to positive responses of vegetation growth (net primary productivity; NPP) to rising atmospheric [CO2] (that is, ‘CO2 fertilization’). Here, we present a new satellite-derived global terrestrial NPP data set, which shows a significant increase in NPP from 1982 to 2011. However, comparison against Earth system model (ESM) NPP estimates reveals a significant divergence, with satellite-derived increases (2.8 ± 1.50%) less than half of ESM-derived increases (7.6  ±  1.67%) over the 30-year period. By isolating the CO2 fertilization effect in each NPP time series and comparing it against a synthesis of available free-air CO2 enrichment data, we provide evidence that much of the discrepancy may be due to an over-sensitivity of ESMs to atmospheric [CO2], potentially reflecting an under-representation of climatic feedbacks and/or a lack of representation of nutrient constraints. Our understanding of CO2 fertilization effects on NPP needs rapid improvement to enable more accurate projections of future C cycle–climate feedbacks; we contend that better integration of modelling, satellite and experimental approaches offers a promising way forward.

  13. Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain

    Directory of Open Access Journals (Sweden)

    Yiwen Mei

    2016-03-01

    Full Text Available The error in satellite precipitation-driven complex terrain flood simulations is characterized in this study for eight different global satellite products and 128 flood events over the Eastern Italian Alps. The flood events are grouped according to two flood types: rain floods and flash floods. The satellite precipitation products and runoff simulations are evaluated based on systematic and random error metrics applied on the matched event pairs and basin-scale event properties (i.e., rainfall and runoff cumulative depth and time series shape. Overall, error characteristics exhibit dependency on the flood type. Generally, timing of the event precipitation mass center and dispersion of the time series derived from satellite precipitation exhibits good agreement with the reference; the cumulative depth is mostly underestimated. The study shows a dampening effect in both systematic and random error components of the satellite-driven hydrograph relative to the satellite-retrieved hyetograph. The systematic error in shape of the time series shows a significant dampening effect. The random error dampening effect is less pronounced for the flash flood events and the rain flood events with a high runoff coefficient. This event-based analysis of the satellite precipitation error propagation in flood modeling sheds light on the application of satellite precipitation in mountain flood hydrology.

  14. Regional model simulation of the North Atlantic cyclone "Caroline" and comparisons with satellite data

    Directory of Open Access Journals (Sweden)

    E. Keup-Thiel

    Full Text Available An individual regional model simulation of cyclone "Caroline" has been carried out to study water cycle components over the North Atlantic Ocean. The uncertainties associated with quantitative estimates of the water cycle components are highlighted by a comparison of the model results with SSM/I (Special Sensor Microwave Imager satellite data.

    The vertically integrated water vapor of the REgional MOdel REMO is in good agreement with the SSM/I satellite data. The simulation results for other water budget components like the vertically integrated liquid water content and precipitation compare also reasonably well within the frontal system. However, the high precipitation rate in the cold air outbreak on the backside of the cold front derived from SSM/I satellite data is generally underestimated by REMO. This results in a considerable deficit of the total precipitation amount accumulated for the cyclone "Caroline". While REMO simulates 24.3 108 m3 h-1 for 09:00 UTC, the total areal precipitation from SSM/I satellite data amounts to 54.7 08 m3 h-1.

    Key words. Meteorology and atmospheric dynamics (precipitation; mesoscale meteorology – Radio science (remote sensing

  15. Toward Seamless Weather-Climate Prediction with a Global Cloud Resolving Model

    Science.gov (United States)

    2016-01-14

    PAGE 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON Tim Li 19b. TELEPHONE NUMBER (Include area code) 808...The coupled model initial condition was derived based on a nudging scheme in which the model prognostic variables such as U, V, SLP, geopotential...height, air temperature and SST were nudged toward NCEP final analysis (FNL) fields. There were 24 ensemble forecast members each day. TCs in the model

  16. Merging of airborne gravity and gravity derived from satellite altimetry: Test cases along the coast of greenland

    DEFF Research Database (Denmark)

    Olesen, Arne Vestergaard; Andersen, Ole Baltazar; Tscherning, C.C.

    2002-01-01

    for the use of gravity data especially, when computing geoid models in coastal regions. The presence of reliable marine gravity data for independent control offers an opportunity to study procedures for the merging of airborne and satellite data around Greenland. Two different merging techniques, both based......The National Survey and Cadastre - Denmark (KMS) has for several years produced gravity anomaly maps over the oceans derived from satellite altimetry. During the last four years, KMS has also conducted airborne gravity surveys along the coast of Greenland dedicated to complement the existing...... onshore gravity coverage and fill in new data in the very-near coastal area, where altimetry data may contain gross errors. The airborne surveys extend from the coastline to approximately 100 km offshore, along 6000 km of coastline. An adequate merging of these different data sources is important...

  17. A model for calculating hourly global solar radiation from satellite data in the tropics

    International Nuclear Information System (INIS)

    Janjai, S.; Pankaew, P.; Laksanaboonsong, J.

    2009-01-01

    A model for calculating global solar radiation from geostationary satellite data is presented. The model is designed to calculate the monthly average hourly global radiation in the tropics with high aerosol load. This model represents a physical relation between the earth-atmospheric albedo derived from GMS5 satellite data and the absorption and scattering coefficients of various atmospheric constituents. The absorption of solar radiation by water vapour which is important for the tropics, was calculated from ambient temperature and relative humidity. The relationship between the visibility and solar radiation depletion due to aerosols was developed for a high aerosol load environment. This relationship was used to calculate solar radiation depletion by aerosols in the model. The total column ozone from TOMS/EP satellite was employed for the determination of solar radiation absorbed by ozone. Solar radiation from four pyranometer stations was used to formulate the relationship between the satellite band earth-atmospheric albedo and broadband earth-atmospheric albedo required by the model. To test its performance, the model was used to compute the monthly average hourly global radiation at 25 solar radiation monitoring stations in tropical areas in Thailand. It was found that the values of monthly average of hourly global radiations calculated from the model were in good agreement with those obtained from the measurements, with the root mean square difference of 10%. After the validation the model was employed to generate hourly solar radiation maps of Thailand. These maps reveal the diurnal and season variation of solar radiation over the country.

  18. A model for calculating hourly global solar radiation from satellite data in the tropics

    Energy Technology Data Exchange (ETDEWEB)

    Janjai, S.; Pankaew, P.; Laksanaboonsong, J. [Solar Energy Research Laboratory, Department of Physics, Faculty of Science, Silpakorn University, Nakhon Pathom 73000 (Thailand)

    2009-09-15

    A model for calculating global solar radiation from geostationary satellite data is presented. The model is designed to calculate the monthly average hourly global radiation in the tropics with high aerosol load. This model represents a physical relation between the earth-atmospheric albedo derived from GMS5 satellite data and the absorption and scattering coefficients of various atmospheric constituents. The absorption of solar radiation by water vapour which is important for the tropics, was calculated from ambient temperature and relative humidity. The relationship between the visibility and solar radiation depletion due to aerosols was developed for a high aerosol load environment. This relationship was used to calculate solar radiation depletion by aerosols in the model. The total column ozone from TOMS/EP satellite was employed for the determination of solar radiation absorbed by ozone. Solar radiation from four pyranometer stations was used to formulate the relationship between the satellite band earth-atmospheric albedo and broadband earth-atmospheric albedo required by the model. To test its performance, the model was used to compute the monthly average hourly global radiation at 25 solar radiation monitoring stations in tropical areas in Thailand. It was found that the values of monthly average of hourly global radiations calculated from the model were in good agreement with those obtained from the measurements, with the root mean square difference of 10%. After the validation the model was employed to generate hourly solar radiation maps of Thailand. These maps reveal the diurnal and season variation of solar radiation over the country. (author)

  19. Modeling and simulation of satellite subsystems for end-to-end spacecraft modeling

    Science.gov (United States)

    Schum, William K.; Doolittle, Christina M.; Boyarko, George A.

    2006-05-01

    During the past ten years, the Air Force Research Laboratory (AFRL) has been simultaneously developing high-fidelity spacecraft payload models as well as a robust distributed simulation environment for modeling spacecraft subsystems. Much of this research has occurred in the Distributed Architecture Simulation Laboratory (DASL). AFRL developers working in the DASL have effectively combined satellite power, attitude pointing, and communication link analysis subsystem models with robust satellite sensor models to create a first-order end-to-end satellite simulation capability. The merging of these two simulation areas has advanced the field of spacecraft simulation, design, and analysis, and enabled more in-depth mission and satellite utility analyses. A core capability of the DASL is the support of a variety of modeling and analysis efforts, ranging from physics and engineering-level modeling to mission and campaign-level analysis. The flexibility and agility of this simulation architecture will be used to support space mission analysis, military utility analysis, and various integrated exercises with other military and space organizations via direct integration, or through DOD standards such as Distributed Interaction Simulation. This paper discusses the results and lessons learned in modeling satellite communication link analysis, power, and attitude control subsystems for an end-to-end satellite simulation. It also discusses how these spacecraft subsystem simulations feed into and support military utility and space mission analyses.

  20. A GOCE only gravity model GOSG01S and the validation of GOCE related satellite gravity models

    Directory of Open Access Journals (Sweden)

    Xinyu Xu

    2017-07-01

    Full Text Available We compile the GOCE-only satellite model GOSG01S complete to spherical harmonic degree of 220 using Satellite Gravity Gradiometry (SGG data and the Satellite-to-Satellite Tracking (SST observations along the GOCE orbit based on applying a least-squares analysis. The diagonal components (Vxx, Vyy, Vzz of the gravitational gradient tensor are used to form the system of observation equations with the band-pass ARMA filter. The point-wise acceleration observations (ax, ay, az along the orbit are used to form the system of observation equations up to the maximum spherical harmonic degree/order 130. The analysis of spectral accuracy characteristics of the newly derived gravitational model GOSG01S and the existing models GOTIM04S, GODIR04S, GOSPW04S and JYY_GOCE02S based on their comparison with the ultra-high degree model EIGEN-6C2 reveals a significant consistency at the spectral window approximately between 80 and 190 due to the same period SGG data used to compile these models. The GOCE related satellite gravity models GOSG01S, GOTIM05S, GODIR05S, GOTIM04S, GODIR04S, GOSPW04S, JYY_GOCE02S, EIGEN-6C2 and EGM2008 are also validated by using GPS-leveling data in China and USA. According to the truncation at degree 200, the statistic results show that all GGMs have very similar differences at GPS-leveling points in USA, and all GOCE related gravity models have better performance than EGM2008 in China. This suggests that all these models provide much more information on the gravity field than EGM2008 in areas with low terrestrial gravity coverage. And STDs of height anomaly differences in China for the selected truncation degrees show that GOCE has improved the accuracy of the global models beyond degree 90 and the accuracies of the models improve from 24 cm to 16 cm. STDs of geoid height differences in USA show that GOSG01S model has best consistency comparing with GPS-leveling data for the frequency band of the degree between 20 and 160.

  1. Satellite data driven modeling system for predicting air quality and visibility during wildfire and prescribed burn events

    Science.gov (United States)

    Nair, U. S.; Keiser, K.; Wu, Y.; Maskey, M.; Berendes, D.; Glass, P.; Dhakal, A.; Christopher, S. A.

    2012-12-01

    The Alabama Forestry Commission (AFC) is responsible for wildfire control and also prescribed burn management in the state of Alabama. Visibility and air quality degradation resulting from smoke are two pieces of information that are crucial for this activity. Currently the tools available to AFC are the dispersion index available from the National Weather Service and also surface smoke concentrations. The former provides broad guidance for prescribed burning activities but does not provide specific information regarding smoke transport, areas affected and quantification of air quality and visibility degradation. While the NOAA operational air quality guidance includes surface smoke concentrations from existing fire events, it does not account for contributions from background aerosols, which are important for the southeastern region including Alabama. Also lacking is the quantification of visibility. The University of Alabama in Huntsville has developed a state-of-the-art integrated modeling system to address these concerns. This system based on the Community Air Quality Modeling System (CMAQ) that ingests satellite derived smoke emissions and also assimilates NASA MODIS derived aerosol optical thickness. In addition, this operational modeling system also simulates the impact of potential prescribed burn events based on location information derived from the AFC prescribed burn permit database. A lagrangian model is used to simulate smoke plumes for the prescribed burns requests. The combined air quality and visibility degradation resulting from these smoke plumes and background aerosols is computed and the information is made available through a web based decision support system utilizing open source GIS components. This system provides information regarding intersections between highways and other critical facilities such as old age homes, hospitals and schools. The system also includes satellite detected fire locations and other satellite derived datasets

  2. Estimation of Satellite-Based SO42- and NH4+ Composition of Ambient Fine Particulate Matter Over China Using Chemical Transport Model

    Science.gov (United States)

    Si, Y.; Li, S.; Chen, L.; Yu, C.; Zhu, W.

    2018-04-01

    Epidemiologic and health impact studies have examined the chemical composition of ambient PM2.5 in China but have been constrained by the paucity of long-term ground measurements. Using the GEOS-Chem chemical transport model and satellite-derived PM2.5 data, sulfate and ammonium levels were estimated over China from 2004 to 2014. A comparison of the satellite-estimated dataset with model simulations based on ground measurements obtained from the literature indicated our results are more accurate. Using satellite-derived PM2.5 data with a spatial resolution of 0.1° × 0.1°, we further presented finer satellite-estimated sulfate and ammonium concentrations in anthropogenic polluted regions, including the NCP (the North China Plain), the SCB (the Sichuan Basin) and the PRD (the Pearl River Delta). Linear regression results obtained on a national scale yielded an r value of 0.62, NMB of -35.9 %, NME of 48.2 %, ARB_50 % of 53.68 % for sulfate and an r value of 0.63, slope of 0.67, and intercept of 5.14 for ammonium. In typical regions, the satellite-derived dataset was significantly robust. Based on the satellite-derived dataset, the spatial-temporal variation of 11-year annual average satellite-derived SO42- and NH4+ concentrations and time series of monthly average concentrations were also investigated. On a national scale, both exhibited a downward trend each year between 2004 and 2014 (SO42-: -0.61 %; NH4+: -0.21 %), large values were mainly concentrated in the NCP and SCB. For regions captured at a finer resolution, the inter-annual variation trends presented a positive trend over the periods 2004-2007 and 2008-2011, followed by a negative trend over the period 2012-2014, and sulfate concentrations varied appreciably. Moreover, the seasonal distributions of the 11-year satellite-derived dataset over China were presented. The distribution of both sulfate and ammonium concentrations exhibited seasonal characteristics, with the seasonal concentrations ranking as

  3. Applications of Satellite Remote Sensing Products to Enhance and Evaluate the AIRPACT Regional Air Quality Modeling System

    Science.gov (United States)

    Herron-Thorpe, F. L.; Mount, G. H.; Emmons, L. K.; Lamb, B. K.; Jaffe, D. A.; Wigder, N. L.; Chung, S. H.; Zhang, R.; Woelfle, M.; Vaughan, J. K.; Leung, F. T.

    2013-12-01

    The WSU AIRPACT air quality modeling system for the Pacific Northwest forecasts hourly levels of aerosols and atmospheric trace gases for use in determining potential health and ecosystem impacts by air quality managers. AIRPACT uses the WRF/SMOKE/CMAQ modeling framework, derives dynamic boundary conditions from MOZART-4 forecast simulations with assimilated MOPITT CO, and uses the BlueSky framework to derive fire emissions. A suite of surface measurements and satellite-based remote sensing data products across the AIRPACT domain are used to evaluate and improve model performance. Specific investigations include anthropogenic emissions, wildfire simulations, and the effects of long-range transport on surface ozone. In this work we synthesize results for multiple comparisons of AIRPACT with satellite products such as IASI ammonia, AIRS carbon monoxide, MODIS AOD, OMI tropospheric ozone and nitrogen dioxide, and MISR plume height. Features and benefits of the newest version of AIRPACT's web-interface are also presented.

  4. Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

    Energy Technology Data Exchange (ETDEWEB)

    Clark, B.

    2010-07-01

    The Taita Hills in southeastern Kenya form the northernmost part of Africa's Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor (rho{sub s}). Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable (rho{sub s}) throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular (rho{sub s}) field measurements were taken and where horizontal visibility meteorological data concurrent with image

  5. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-04-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

  6. Poverty, health and satellite-derived vegetation indices: their inter-spatial relationship in West Africa

    Science.gov (United States)

    Sedda, Luigi; Tatem, Andrew J.; Morley, David W.; Atkinson, Peter M.; Wardrop, Nicola A.; Pezzulo, Carla; Sorichetta, Alessandro; Kuleszo, Joanna; Rogers, David J.

    2015-01-01

    Background Previous analyses have shown the individual correlations between poverty, health and satellite-derived vegetation indices such as the normalized difference vegetation index (NDVI). However, generally these analyses did not explore the statistical interconnections between poverty, health outcomes and NDVI. Methods In this research aspatial methods (principal component analysis) and spatial models (variography, factorial kriging and cokriging) were applied to investigate the correlations and spatial relationships between intensity of poverty, health (expressed as child mortality and undernutrition), and NDVI for a large area of West Africa. Results This research showed that the intensity of poverty (and hence child mortality and nutrition) varies inversely with NDVI. From the spatial point-of-view, similarities in the spatial variation of intensity of poverty and NDVI were found. Conclusions These results highlight the utility of satellite-based metrics for poverty models including health and ecological components and, in general for large scale analysis, estimation and optimisation of multidimensional poverty metrics. However, it also stresses the need for further studies on the causes of the association between NDVI, health and poverty. Once these relationships are confirmed and better understood, the presence of this ecological component in poverty metrics has the potential to facilitate the analysis of the impacts of climate change on the rural populations afflicted by poverty and child mortality. PMID:25733559

  7. Comparisons of Satellite Soil Moisture, an Energy Balance Model Driven by LST Data and Point Measurements

    Science.gov (United States)

    Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia

    2013-04-01

    Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.

  8. On the estimation of physical height changes using GRACE satellite mission data – A case study of Central Europe

    Directory of Open Access Journals (Sweden)

    Godah Walyeldeen

    2017-12-01

    Full Text Available The dedicated gravity satellite missions, in particular the GRACE (Gravity Recovery and Climate Experiment mission launched in 2002, provide unique data for studying temporal variations of mass distribution in the Earth’s system, and thereby, the geometry and the gravity fi eld changes of the Earth. The main objective of this contribution is to estimate physical height (e.g. the orthometric/normal height changes over Central Europe using GRACE satellite mission data as well as to analyse them and model over the selected study area. Physical height changes were estimated from temporal variations of height anomalies and vertical displacements of the Earth surface being determined over the investigated area. The release 5 (RL05 GRACE-based global geopotential models as well as load Love numbers from the Preliminary Reference Earth Model (PREM were used as input data. Analysis of the estimated physical height changes and their modelling were performed using two methods: the seasonal decomposition method and the PCA/ EOF (Principal Component Analysis/Empirical Orthogonal Function method and the differences obtained were discussed. The main fi ndings reveal that physical height changes over the selected study area reach up to 22.8 mm. The obtained physical height changes can be modelled with an accuracy of 1.4 mm using the seasonal decomposition method.

  9. Volcanic SO2 fluxes derived from satellite data: a survey using OMI, GOME-2, IASI and MODIS

    Directory of Open Access Journals (Sweden)

    N. Theys

    2013-06-01

    Full Text Available Sulphur dioxide (SO2 fluxes of active degassing volcanoes are routinely measured with ground-based equipment to characterize and monitor volcanic activity. SO2 of unmonitored volcanoes or from explosive volcanic eruptions, can be measured with satellites. However, remote-sensing methods based on absorption spectroscopy generally provide integrated amounts of already dispersed plumes of SO2 and satellite derived flux estimates are rarely reported. Here we review a number of different techniques to derive volcanic SO2 fluxes using satellite measurements of plumes of SO2 and investigate the temporal evolution of the total emissions of SO2 for three very different volcanic events in 2011: Puyehue-Cordón Caulle (Chile, Nyamulagira (DR Congo and Nabro (Eritrea. High spectral resolution satellite instruments operating both in the ultraviolet-visible (OMI/Aura and GOME-2/MetOp-A and thermal infrared (IASI/MetOp-A spectral ranges, and multispectral satellite instruments operating in the thermal infrared (MODIS/Terra-Aqua are used. We show that satellite data can provide fluxes with a sampling of a day or less (few hours in the best case. Generally the flux results from the different methods are consistent, and we discuss the advantages and weaknesses of each technique. Although the primary objective of this study is the calculation of SO2 fluxes, it also enables us to assess the consistency of the SO2 products from the different sensors used.

  10. Satellite-derived land surface parameters for mesoscale modelling of the Mexico City basin

    Directory of Open Access Journals (Sweden)

    B. de Foy

    2006-01-01

    Full Text Available Mesoscale meteorological modelling is an important tool to help understand air pollution and heat island effects in urban areas. Accurate wind simulations are difficult to obtain in areas of weak synoptic forcing. Local factors have a dominant role in the circulation and include land surface parameters and their interaction with the atmosphere. This paper examines an episode during the MCMA-2003 field campaign held in the Mexico City Metropolitan Area (MCMA in April of 2003. Because the episode has weak synoptic forcing, there is the potential for the surface heat budget to influence the local meteorology. High resolution satellite observations are used to specify the land use, vegetation fraction, albedo and surface temperature in the MM5 model. Making use of these readily available data leads to improved meteorological simulations in the MCMA, both for the wind circulation patterns and the urban heat island. Replacing values previously obtained from land-use tables with actual measurements removes the number of unknowns in the model and increases the accuracy of the energy budget. In addition to improving the understanding of local meteorology, this sets the stage for the use of advanced urban modules.

  11. Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets

    Science.gov (United States)

    Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y.

    2018-04-01

    Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

  12. The local ionospheric modeling by integration ground GPS observations and satellite altimetry data

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Sharifi

    2017-01-01

    Full Text Available The free electrons in the ionosphere have a strong impact on the propagation of radio waves. When the signals pass through the ionosphere, both their group and phase velocity are disturbed. Several space geodetic techniques such as satellite altimetry, low Earth orbit (LEO satellite and very long baseline interferometry (VLBI can be used to model the total electron content. At present, the classical input data for development of ionospheric models are based on dual-frequency GPS observations, However, a major problem with this observation type is the nonuniform distribution of the terrestrial GPS reference stations with large gaps notably over the sea surface and ocean where only some single stations are located on islands, leading to lower the precision of the model over these areas. In these regions the dual-frequency satellite altimeters provide precise information about the parameters of the ionosphere. Combination of GPS and satellite altimetry observations allows making best use of the advantages of their different spatial and temporal distributions. In this study, the local ionosphere modeling was done by the combination of space geodetic observations using spherical Slepian function. The combination of the data from ground GPS observations over the western part of the USA and the altimetry mission Jason-2 was performed on the normal equation level in the least-square procedure and a least-square variance component estimation (LS-VCE was applied to take into account the different accuracy levels of the observations. The integrated ionosphere model is more accurate and more reliable than the results derived from the ground GPS observations over the oceans.

  13. Development of a funding, cost, and spending model for satellite projects

    Science.gov (United States)

    Johnson, Jesse P.

    1989-01-01

    The need for a predictive budget/funging model is obvious. The current models used by the Resource Analysis Office (RAO) are used to predict the total costs of satellite projects. An effort to extend the modeling capabilities from total budget analysis to total budget and budget outlays over time analysis was conducted. A statistical based and data driven methodology was used to derive and develop the model. Th budget data for the last 18 GSFC-sponsored satellite projects were analyzed and used to build a funding model which would describe the historical spending patterns. This raw data consisted of dollars spent in that specific year and their 1989 dollar equivalent. This data was converted to the standard format used by the RAO group and placed in a database. A simple statistical analysis was performed to calculate the gross statistics associated with project length and project cost ant the conditional statistics on project length and project cost. The modeling approach used is derived form the theory of embedded statistics which states that properly analyzed data will produce the underlying generating function. The process of funding large scale projects over extended periods of time is described by Life Cycle Cost Models (LCCM). The data was analyzed to find a model in the generic form of a LCCM. The model developed is based on a Weibull function whose parameters are found by both nonlinear optimization and nonlinear regression. In order to use this model it is necessary to transform the problem from a dollar/time space to a percentage of total budget/time space. This transformation is equivalent to moving to a probability space. By using the basic rules of probability, the validity of both the optimization and the regression steps are insured. This statistically significant model is then integrated and inverted. The resulting output represents a project schedule which relates the amount of money spent to the percentage of project completion.

  14. The geopotential value W 0 for specifying the relativistic atomic time scale and a global vertical reference system

    Czech Academy of Sciences Publication Activity Database

    Burša, Milan; Kenyon, S.; Kouba, J.; Šíma, Zdislav; Vatrt, V.; Vítek, V.; Vojtíšková, M.

    2007-01-01

    Roč. 81, č. 2 (2007), s. 103-110 ISSN 0949-7714 R&D Projects: GA ČR GA205/05/2381 Institutional research plan: CEZ:AV0Z10030501 Keywords : geopotential * vertical datum unification * relativistic atomic time scale Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.636, year: 2007

  15. Incorporating Satellite Time-Series Data into Modeling

    Science.gov (United States)

    Gregg, Watson

    2008-01-01

    In situ time series observations have provided a multi-decadal view of long-term changes in ocean biology. These observations are sufficiently reliable to enable discernment of even relatively small changes, and provide continuous information on a host of variables. Their key drawback is their limited domain. Satellite observations from ocean color sensors do not suffer the drawback of domain, and simultaneously view the global oceans. This attribute lends credence to their use in global and regional model validation and data assimilation. We focus on these applications using the NASA Ocean Biogeochemical Model. The enhancement of the satellite data using data assimilation is featured and the limitation of tongterm satellite data sets is also discussed.

  16. Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM2.5 in the Northeastern USA

    Directory of Open Access Journals (Sweden)

    Allan C. Just

    2018-05-01

    Full Text Available Satellite-derived estimates of aerosol optical depth (AOD are key predictors in particulate air pollution models. The multi-step retrieval algorithms that estimate AOD also produce quality control variables but these have not been systematically used to address the measurement error in AOD. We compare three machine-learning methods: random forests, gradient boosting, and extreme gradient boosting (XGBoost to characterize and correct measurement error in the Multi-Angle Implementation of Atmospheric Correction (MAIAC 1 × 1 km AOD product for Aqua and Terra satellites across the Northeastern/Mid-Atlantic USA versus collocated measures from 79 ground-based AERONET stations over 14 years. Models included 52 quality control, land use, meteorology, and spatially-derived features. Variable importance measures suggest relative azimuth, AOD uncertainty, and the AOD difference in 30–210 km moving windows are among the most important features for predicting measurement error. XGBoost outperformed the other machine-learning approaches, decreasing the root mean squared error in withheld testing data by 43% and 44% for Aqua and Terra. After correction using XGBoost, the correlation of collocated AOD and daily PM2.5 monitors across the region increased by 10 and 9 percentage points for Aqua and Terra. We demonstrate how machine learning with quality control and spatial features substantially improves satellite-derived AOD products for air pollution modeling.

  17. Geomagnetic field models for satellite angular motion studies

    Science.gov (United States)

    Ovchinnikov, M. Yu.; Penkov, V. I.; Roldugin, D. S.; Pichuzhkina, A. V.

    2018-03-01

    Four geomagnetic field models are discussed: IGRF, inclined, direct and simplified dipoles. Geomagnetic induction vector expressions are provided in different reference frames. Induction vector behavior is compared for different models. Models applicability for the analysis of satellite motion is studied from theoretical and engineering perspectives. Relevant satellite dynamics analysis cases using analytical and numerical techniques are provided. These cases demonstrate the benefit of a certain model for a specific dynamics study. Recommendations for models usage are summarized in the end.

  18. Validation of satellite derived LHF using coare_3.0 scheme and time series data over north-east Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Muraleedharan, P.M.; Pankajakshan, T.; Sathe, P.V.

    to the scientific community as it call for near perfect observational platforms and sensors to Page 1 of 10Gayana (Concepción) - VALIDATION OF SATELLITE DERIVED LHF USING C... 8/11/2006http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717...>VALIDATION OF SATELLITE DERIVED LHF USING C... 8/11/2006http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-65382004000300019&lng=... Day and night passes of SSMI (wind speed and columnar water vapor) and TMI (sea surface temperature) data for the period July...

  19. Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass

    Science.gov (United States)

    Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.

    2017-07-01

    Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

  20. Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

    Science.gov (United States)

    Sure, A.; Dikshit, O.

    2017-12-01

    Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

  1. LIMS/Nimbus-7 Level 2 Vertical Profiles of O3, NO2, H2O, HNO3, Geopotential Height, and Temperature V006

    Data.gov (United States)

    National Aeronautics and Space Administration — The Limb Infrared Monitor of the Stratosphere (LIMS) version 6 Level-2 data product consists of daily, geolocated, vertical profiles of temperature, geopotential...

  2. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    Energy Technology Data Exchange (ETDEWEB)

    Zarzalejo, L.F.; Ramirez, L.; Polo, J. [DER-CIEMAT, Madrid (Spain). Renewable Energy Dept.

    2005-07-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models. (author)

  3. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    International Nuclear Information System (INIS)

    Zarzalejo, Luis F.; Ramirez, Lourdes; Polo, Jesus

    2005-01-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models

  4. Nudging Satellite Altimeter Data Into Quasi-Geostrophic Ocean Models

    Science.gov (United States)

    Verron, Jacques

    1992-05-01

    This paper discusses the efficiency of several variants of the nudging technique (derived from the technique of the same name developed by meteorologists) for assimilating altimeter data into numerical ocean models based on quasi-geostrophic formulation. Assimilation experiments are performed with data simulated in the nominal sampling conditions of the Topex-Poseidon satellite mission. Under experimental conditions it is found that nudging on the altimetric sea level is as efficient as nudging on the vorticity (second derivative in space of the dynamic topography), the technique used thus far in studies of this type. The use of altimetric residuals only, instead of the total altimetric sea level signal, is also explored. The critical importance of having an adequate reference mean sea level is largely confirmed. Finally, the possibility of nudging only the signal of sea level tendency (i.e., the successive time differences of the sea level height) is examined. Apart from the barotropic mode, results are not very successful compared with those obtained by assimilating the residuals.

  5. Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

    Science.gov (United States)

    Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

    2015-08-01

    Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia's cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

  6. Radial diffusion in the Uranian radiatian belts - Inferences from satellite absorption loss models

    Science.gov (United States)

    Hood, L. L.

    1989-01-01

    Low-energy charged particle (LECP) phase space density profiles available from the Voyager/1986 Uranus encounter are analyzed, using solutions of the time-averaged radial diffusion equation for charged particle transport in a dipolar planetary magnetic field. Profiles for lower-energy protons and electrons are first analyzed to infer radial diffusion rate as a function of L, assuming that satellite absorption is the dominant loss process and local sources for these particles are negligible. Satellite macrosignatures present in the experimentally derived profiles are approximately reproduced in several cases, lending credence to the loss model and indicating that magnetospheric distributed losses are not as rapid as satellite absorption near the minimum satellite L shells for the particles. Diffusion rates and L dependences are found to be similar to those previously inferred in the inner Jovian magnetosphere (Thomsen et al., 1977) and for the inner Saturnian magnetosphere (Hood, 1985). Profiles for higher energy electrons and protons are also analyzed using solutions that allow for the existence of significant particle sources as well as sinks. Possible implications for radial diffusion mechanisms in the Uranian radiation belts are discussed.

  7. A Bayesian kriging approach for blending satellite and ground precipitation observations

    Science.gov (United States)

    Verdin, Andrew P.; Rajagopalan, Balaji; Kleiber, William; Funk, Christopher C.

    2015-01-01

    Drought and flood management practices require accurate estimates of precipitation. Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite-derived precipitation data are an attractive alternative, though they tend to underestimate the magnitude of wet events due to their dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates for Central America, Colombia, and Venezuela. First, the gauge observations are modeled as a linear function of satellite-derived estimates and any number of other variables—for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. We show that this blending method significantly improves upon the satellite-derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution

  8. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Science.gov (United States)

    Fita, L.; Romero, R.; Luque, A.; Ramis, C.

    2009-08-01

    The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA). An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity on temporal and

  9. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Directory of Open Access Journals (Sweden)

    L. Fita

    2009-08-01

    Full Text Available The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA. An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity

  10. Effects of assimilating precipitation zones derived from satellite and lightning data on numerical simulations of tropical-like Mediterranean storms

    Energy Technology Data Exchange (ETDEWEB)

    Fita, L.; Romero, R.; Luque, A.; Ramis, C. [Univ. de les Illes Balears, Palma de Mallorca (Spain). Grup de Meteorologia

    2009-07-01

    The scarcity of meteorological observations in maritime areas is a well-known problem that can be an important limitation in the study of different phenomena. Tropical-like storms or medicanes developed over the Mediterranean sea are intense storms with some similarities to the tropical ones. Although they do not reach the hurricane intensity, their potential for damage is very high, due to the densely populated Mediterranean coastal regions. In this study, the two notable cases of medicane development which occurred in the western Mediterranean basin in September 1996 and October 2003, are considered. The capability of mesoscale numerical models to simulate general aspects of such a phenomena has been previously shown. With the aim of improving the numerical results, an adjustment of the humidity vertical profiles in MM5 simulations is performed by means of satellite derived precipitation. Convective and stratiform precipitation types obtained from satellite images are used to individually adjust the profiles. Lightning hits are employed to identify convective grid points. The adjustment of the vertical humidity profiles is carried out in the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses used as initial conditions for the simulations. Analyses nudging to ECMWF analyses and to the satellite-based humidity-corrected version of these analyses has also been applied using Four Dimensional Data Assimilation (FDDA). An additional adjustment is applied as observation nudging of satellite/lightning information at different time and spatial resolutions. Statistical parameters are proposed and tested as an objective way to intercompare satellite-derived and simulated trajectories. Simulations of medicanes exhibit a strong sensitivity to vertical humidity profiles. Trajectories of the storms are improved or worsened by using FDDA. A case dependence is obtained on the characteristics of the humidity-corrected medicanes. FDDA sensitivity on temporal and

  11. Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

    2017-04-01

    Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze

  12. Satellite Derived Bathymetry as a Coastal Geo-Intelligence Tool for Alaska

    Science.gov (United States)

    Ventura, D. C.

    2017-12-01

    What do marine rescue, navigation safety, resource management, coastal infrastructure management, climate adaptation and resilience, economic investment, habitat protection agencies and institutions all have in common? They all benefit from accurate coastal bathymetric data As Arctic-Related Incidents of National Significance (IoNS) workshop points out, reducing time and cost of collecting coastal bathymetry in the Arctic is fundamental to addressing needs of a multitude of stakeholders. Until recently, high resolution coastal data acquisition involved field mobilization of planes, vessels, and people. Given limited resources, short season and remoteness, this approach results in very modest progress toward filling the Alaska's coastal bathymetry data gap and updating vintage data from circa Captain Cook.After successfully executing Satellite Derived Bathymetry (SDB) projects in other more environmentally suitable locations, Fugro and its partner EOMAP are now assessing suitability SDB technique along the Alaska coast. This includes aaccessing archived satellite data and understanding best environmental conditions for the mapping and defining maximum mapping depth as an initial action to understand potentials for Alaska. Here we leverage the physics-based approach to satellite imagery data extraction to derive water depth and complimentary intelligence such as seafloor habitat mapping and certain water quality parameters, such as clarity, turbidity, sediment and chlorophyll-a concentrations, and seasonal changes. Both new and archive imagery are utilized as part of the process. If successful, the benefits and cost savings of this approach are enormous as repeat rate for data collects like this can be measured in months/years as opposed to decades/centuries. Arctic coasts have multiple vulnerabilities and the rate of change will continue to outpace the budgets. As innovative and learning organizations, Fugro and EOMAP strive to not only share the results of this

  13. A new 1 km digital elevation model of the Antarctic derived from combined satellite radar and laser data – Part 1: Data and methods

    Directory of Open Access Journals (Sweden)

    J. L. Bamber

    2009-05-01

    Full Text Available Digital elevation models (DEMs of the whole of Antarctica have been derived, previously, from satellite radar altimetry (SRA and limited terrestrial data. Near the ice sheet margins and in other areas of steep relief the SRA data tend to have relatively poor coverage and accuracy. To remedy this and to extend the coverage beyond the latitudinal limit of the SRA missions (81.5° S we have combined laser altimeter measurements from the Geosciences Laser Altimeter System onboard ICESat with SRA data from the geodetic phase of the ERS-1 satellite mission. The former provide decimetre vertical accuracy but with poor spatial coverage. The latter have excellent spatial coverage but a poorer vertical accuracy. By combining the radar and laser data using an optimal approach we have maximised the vertical accuracy and spatial resolution of the DEM and minimised the number of grid cells with an interpolated elevation estimate. We assessed the optimum resolution for producing a DEM based on a trade-off between resolution and interpolated cells, which was found to be 1 km. This resulted in just under 32% of grid cells having an interpolated value. The accuracy of the final DEM was assessed using a suite of independent airborne altimeter data and used to produce an error map. The RMS error in the new DEM was found to be roughly half that of the best previous 5 km resolution, SRA-derived DEM, with marked improvements in the steeper marginal and mountainous areas and between 81.5 and 86° S. The DEM contains a wealth of information related to ice flow. This is particularly apparent for the two largest ice shelves – the Filchner-Ronne and Ross – where the surface expression of flow of ice streams and outlet glaciers can be traced from the grounding line to the calving front. The surface expression of subglacial lakes and other basal features are also illustrated. We also use the DEM to derive new estimates of balance velocities and ice divide locations.

  14. The mount Cameroon height determined from ground gravity data ...

    African Journals Online (AJOL)

    Abstract This paper deals with the accurate determination of mount Cameroon orthometric height, by combining ground gravity data, global navigation satellite system (GNSS) observations and global geopotential models. The elevation of the highest point (Fako) is computed above the WGS84 reference ellipsoid.

  15. A refined gravity model from Lageos /GEM-L2/

    Science.gov (United States)

    Lerch, F. J.; Klosko, S. M.; Patel, G. B.

    1982-01-01

    Lageos satellite laser ranging (SLR) data taken over a 2.5 yr period were employed to develop the Goddard Earth Model GEM-L2, a refined gravity field model. Additional data was gathered with 30 other satellites, resulting in spherical harmonics through degree and order 20, based on over 600,000 measurements. The Lageos data was accurate down to 10 cm, after which the GEM 9 data were used to make adjustments past order 7. The resolution of long wavelength activity, through degree and order 4, was made possible by the Lageos data. The GEM-L2 model features a 20 x 20 geopotential, tracking station coordinates (20), 5-day polar motion and A1-UT1 values, and a GM value of 398,600.607 cu km/sq sec. The accuracy of station positioning has been raised to within 6 cm total position globally and within 1.8 cm in baselines. It is concluded that SLR is useful for measuring tectonic plate motions and inter-plate deformations.

  16. Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

    Science.gov (United States)

    Anand, Jasdeep S.; Monks, Paul S.

    2017-07-01

    Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

  17. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  18. Comparison of the characteristic energy of precipitating electrons derived from ground-based and DMSP satellite data

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

    Full Text Available Energy maps are important for ionosphere-magnetosphere coupling studies, because quantitative determination of field-aligned currents requires knowledge of the conductances and their spatial gradients. By combining imaging riometer absorption and all-sky auroral optical data it is possible to produce high temporal and spatial resolution maps of the Maxwellian characteristic energy of precipitating electrons within a 240240 common field of view. These data have been calibrated by inverting EISCAT electron density profiles into equivalent energy spectra. In this paper energy maps produced by ground-based instruments (optical and riometer are compared with DMSP satellite data during geomagnetic conjunctions. For the period 1995-2002, twelve satellite passes over the ground-based instruments' field of view for the cloud-free conditions have been considered. Four of the satellite conjunctions occurred during moderate geomagnetic, steady-state conditions and without any ion precipitation. In these cases with Maxwellian satellite spectra, there is 71% agreement between the characteristic energies derived from the satellite and the ground-based energy map method.

  19. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2014-10-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

  20. Design and Fabrication of DebriSat - A Representative LEO Satellite for Improvements to Standard Satellite Breakup Models

    Science.gov (United States)

    Clark, S.; Dietrich, A.; Fitz-Coy, N.; Weremeyer, M.; Liou, J.-C.

    2012-01-01

    This paper discusses the design and fabrication of DebriSat, a 50 kg satellite developed to be representative of a modern low Earth orbit satellite in terms of its components, materials used, and fabrication procedures. DebriSat will be the target of a future hypervelocity impact experiment to determine the physical characteristics of debris generated after an on-orbit collision of a modern LEO satellite. The major ground-based satellite impact experiment used by DoD and NASA in their development of satellite breakup models was SOCIT, conducted in 1992. The target used for that experiment was a Navy transit satellite (40 cm, 35 kg) fabricated in the 1960's. Modern satellites are very different in materials and construction techniques than those built 40 years ago. Therefore, there is a need to conduct a similar experiment using a modern target satellite to improve the fidelity of the satellite breakup models. To ensure that DebriSat is truly representative of typical LEO missions, a comprehensive study of historical LEO satellite designs and missions within the past 15 years for satellites ranging from 1 kg to 5000 kg was conducted. This study identified modern trends in hardware, material, and construction practices utilized in recent LEO missions. Although DebriSat is an engineering model, specific attention is placed on the quality, type, and quantity of the materials used in its fabrication to ensure the integrity of the outcome. With the exception of software, all other aspects of the satellite s design, fabrication, and assembly integration and testing will be as rigorous as that of an actual flight vehicle. For example, to simulate survivability of launch loads, DebriSat will be subjected to a vibration test. As well, the satellite will undergo thermal vacuum tests to verify that the components and overall systems meet typical environmental standards. Proper assembly and integration techniques will involve comprehensive joint analysis, including the precise

  1. Passive correlation ranging of a geostationary satellite using DVB-S payload signals.

    Science.gov (United States)

    Shakun, Leonid; Shulga, Alexandr; Sybiryakova, Yevgeniya; Bushuev, Felix; Kaliuzhnyi, Mykola; Bezrukovs, Vladislavs; Moskalenko, Sergiy; Kulishenko, Vladislav; Balagura, Oleg

    2016-07-01

    Mukacheve-Mykolaiv. The standard deviations do not exceed 10 ns for the both pairs and the average values are equal +10 ns and -106 ns respectively for Kharkiv-Mykolaiv and Mukacheve-Mykolaiv. We discuss the residuals between the observed TDOA and estimates of the TDOA that are calculated by fitted models of satellite motion: the SGP4/SDP4 model and the model based on the numerical integration of the equations of motion taking into account the geopotential, and the perturbation from the Moon and the Sun. We note that residuals from the model SGP4/SDP4 have periodic deviations due to the inaccuracy of the SGP4/SDP4 model. As a result, estimation of the standard deviation of the satellite position is about 60 m for the epoch of the SGP4/SDP4 orbit elements. The residuals for the numerical model in the interval of one day do not show low-frequency deviation. In this case, the estimate of the standard deviation of the satellite position is about 12 m for the epoch of the numerical orbit elements. Keywords. DVB-S, geostationary satellite, orbit determination, passive ranging.

  2. Western Continental Margin of India - Re-look using potential field data

    Science.gov (United States)

    Rajaram, M.; S P, A.

    2008-05-01

    The Western Continental Margin of India (WCMI) evolved as a result of rifting between India and Madagascar that took place during mid Cretaceous (~88Ma).The WCMI is equally important in terms of natural resources as well as research point of view. The major tectonic elements in the western offshore includes the Laxmi and Chagos- Laccadive ridge dividing the WCMI and the adjoining Arabian sea into two basins, Pratap Ridge, Alleppey platform etc. Different theories have been proposed for the evolution of each of these tectonic elements. In the current paper we look at geopotential data on the west coast of India and the western off-shore. The data sets utilized include Satellite derived High Resolution Free Air Gravity data over the off-shore, Bouguer data onland, Champ Satellite Magnetic data, published Marine Magnetic data collected by ONGC, NIO, ground magnetic data over west cost collected by IIG and available aeromagnetic data. From the free air gravity anomaly the structural details of the western offshore can be delineated. The Euler depths of FAG depict deep solutions associated with Pratap Ridge, Comorin Ridge, the west coast fault and the Laxmi Ridge. These may be associated with continental margin and continental fragments. From the aeromagnetic and marine magnetic data it is evident that the West Coast Fault is dissected at several places. The shallow circular feature associated with Bombay High is evident both on the FAG and the analytic signal derived from satellite Magnetic data. The crustal magnetic thickness from MF5 lithospheric model of the Champ appears to suggest that the continental crust extends up to the Chagos- Laccadive ridge. Based on the analysis of these geopotential data sets the various theories for the evolution of the WCMI will be evaluated and these results will be presented.

  3. Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts

    Science.gov (United States)

    Alcaraz-Segura, Domingo; Lomba, Angela; Sousa-Silva, Rita; Nieto-Lugilde, Diego; Alves, Paulo; Georges, Damien; Vicente, Joana R.; Honrado, João P.

    2017-05-01

    In a world facing rapid environmental changes, anticipating their impacts on biodiversity is of utmost relevance. Remotely-sensed Ecosystem Functional Attributes (EFAs) are promising predictors for Species Distribution Models (SDMs) by offering an early and integrative response of vegetation performance to environmental drivers. Species of high conservation concern would benefit the most from a better ability to anticipate changes in habitat suitability. Here we illustrate how yearly projections from SDMs based on EFAs could reveal short-term changes in potential habitat suitability, anticipating mid-term shifts predicted by climate-change-scenario models. We fitted two sets of SDMs for 41 plant species of conservation concern in the Iberian Peninsula: one calibrated with climate variables for baseline conditions and projected under two climate-change-scenarios (future conditions); and the other calibrated with EFAs for 2001 and projected annually from 2001 to 2013. Range shifts predicted by climate-based models for future conditions were compared to the 2001-2013 trends from EFAs-based models. Projections of EFAs-based models estimated changes (mostly contractions) in habitat suitability that anticipated, for the majority (up to 64%) of species, the mid-term shifts projected by traditional climate-change-scenario forecasting, and showed greater agreement with the business-as-usual scenario than with the sustainable-development one. This study shows how satellite-derived EFAs can be used as meaningful essential biodiversity variables in SDMs to provide early-warnings of range shifts and predictions of short-term fluctuations in suitable conditions for multiple species.

  4. Measurement-based perturbation theory and differential equation parameter estimation with applications to satellite gravimetry

    Science.gov (United States)

    Xu, Peiliang

    2018-06-01

    The numerical integration method has been routinely used by major institutions worldwide, for example, NASA Goddard Space Flight Center and German Research Center for Geosciences (GFZ), to produce global gravitational models from satellite tracking measurements of CHAMP and/or GRACE types. Such Earth's gravitational products have found widest possible multidisciplinary applications in Earth Sciences. The method is essentially implemented by solving the differential equations of the partial derivatives of the orbit of a satellite with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical and statistical point of view, satellite gravimetry from satellite tracking is essentially the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in mathematics and statistics, chemistry and physics, and satellite gravimetry, is groundless, mathematically and physically. Given the Newton's nonlinear governing differential equations of satellite motion with unknown equation parameters and unknown initial conditions, we develop three methods to derive new local solutions around a nominal reference orbit, which are linked to measurements to estimate the unknown corrections to approximate values of the unknown parameters and the unknown initial conditions. Bearing in mind that satellite orbits can now be tracked almost continuously at unprecedented accuracy, we propose the measurement-based perturbation theory and derive global uniformly convergent solutions to the Newton's nonlinear governing differential equations of satellite motion for the next generation of global gravitational models. Since the solutions are global uniformly convergent, theoretically speaking

  5. SACRA - global data sets of satellite-derived crop calendars for agricultural simulations: an estimation of a high-resolution crop calendar using satellite-sensed NDVI

    Science.gov (United States)

    Kotsuki, S.; Tanaka, K.

    2015-01-01

    To date, many studies have performed numerical estimations of food production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC) is an essential input datum to estimate food production and agricultural water demand accurately with the numerical estimations. CC defines the date or month when farmers plant and harvest in cropland. This study aims to develop a new global data set of a satellite-derived crop calendar for agricultural simulations (SACRA) and reveal advantages and disadvantages of the satellite-derived CC compared to other global products. We estimate global CC at a spatial resolution of 5 min (≈10 km) using the satellite-sensed NDVI data, which corresponds well to vegetation growth and death on the land surface. We first demonstrate that SACRA shows similar spatial pattern in planting date compared to a census-based product. Moreover, SACRA reflects a variety of CC in the same administrative unit, since it uses high-resolution satellite data. However, a disadvantage is that the mixture of several crops in a grid is not considered in SACRA. We also address that the cultivation period of SACRA clearly corresponds to the time series of NDVI. Therefore, accuracy of SACRA depends on the accuracy of NDVI used for the CC estimation. Although SACRA shows different CC from a census-based product in some regions, multiple usages of the two products are useful to take into consideration the uncertainty of the CC. An advantage of SACRA compared to the census-based products is that SACRA provides not only planting/harvesting dates but also a peak date from the time series of NDVI data.

  6. Modelling of charged satellite motion in Earth's gravitational and magnetic fields

    Science.gov (United States)

    Abd El-Bar, S. E.; Abd El-Salam, F. A.

    2018-05-01

    In this work Lagrange's planetary equations for a charged satellite subjected to the Earth's gravitational and magnetic force fields are solved. The Earth's gravity, and magnetic and electric force components are obtained and expressed in terms of orbital elements. The variational equations of orbit with the considered model in Keplerian elements are derived. The solution of the problem in a fully analytical way is obtained. The temporal rate of changes of the orbital elements of the spacecraft are integrated via Lagrange's planetary equations and integrals of the normalized Keplerian motion obtained by Ahmed (Astron. J. 107(5):1900, 1994).

  7. Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

    Science.gov (United States)

    Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.; hide

    2014-01-01

    Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

  8. Can Airborne Laser Scanning (ALS and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest?

    Directory of Open Access Journals (Sweden)

    Eva Lindberg

    2015-04-01

    Full Text Available In managed landscapes, conservation planning requires effective methods to identify high-biodiversity areas. The objective of this study was to evaluate the potential of airborne laser scanning (ALS and forest estimates derived from satellite images extracted at two spatial scales for predicting the stand-scale abundance and species richness of birds and beetles in a managed boreal forest landscape. Multiple regression models based on forest data from a 50-m radius (i.e., corresponding to a homogenous forest stand had better explanatory power than those based on a 200-m radius (i.e., including also parts of adjacent stands. Bird abundance and species richness were best explained by the ALS variables “maximum vegetation height” and “vegetation cover between 0.5 and 3 m” (both positive. Flying beetle abundance and species richness, as well as epigaeic (i.e., ground-living beetle richness were best explained by a model including the ALS variable “maximum vegetation height” (positive and the satellite-derived variable “proportion of pine” (negative. Epigaeic beetle abundance was best explained by “maximum vegetation height” at 50 m (positive and “stem volume” at 200 m (positive. Our results show that forest estimates derived from satellite images and ALS data provide complementary information for explaining forest biodiversity patterns. We conclude that these types of remote sensing data may provide an efficient tool for conservation planning in managed boreal landscapes.

  9. Utilization of satellite remote sensing data on land surface characteristics in water and heat balance component modeling for vegetation covered territories

    Science.gov (United States)

    Muzylev, Eugene; Uspensky, Alexander; Startseva, Zoya; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2010-05-01

    The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the

  10. Assessment of Satellite-Derived Surface Reflectances by NASA's CAR Airborne Radiometer over Railroad Valley, Nevada

    Science.gov (United States)

    Kharbouche, Said; Muller, Jan-Peter; Gatebe, Charles K.; Scanlon, Tracy; Banks, Andrew C.

    2017-01-01

    CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada (38.504 deg N, 115.692 deg W).The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CARs land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol

  11. A climate index derived from satellite measured spectral infrared radiation. Ph.D. Thesis

    Science.gov (United States)

    Abel, M. D.; Fox, S. K.

    1982-01-01

    The vertical infrared radiative emitting structure (VIRES) climate index, based on radiative transfer theory and derived from the spectral radiances typically used to retrieve temperature profiles, is introduced. It is assumed that clouds and climate are closely related and a change in one will result in a change in the other. The index is a function of the cloud, temperature, and moisture distributions. It is more accurately retrieved from satellite data than is cloudiness per se. The VIRES index is based upon the shape and relative magnitude of the broadband weighting function of the infrared radiative transfer equation. The broadband weighting curves are retrieved from simulated satellite infrared sounder data (spectral radiances). The retrieval procedure is described and the error error sensitivities of the method investigated. Index measuring options and possible applications of the VIRES index are proposed.

  12. Validation of satellite-derived tropical cyclone heat potential with in situ observations in the North Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Nagamani, P.V.; Ali, M.M.; Goni, G.J.; Dinezio, P.N.; Pezzullo, J.C.; UdayaBhaskar, T.V.S.; Gopalakrishna, V.V.; Nisha, K.

    validation with in situ estimations for quantification of their reliability and consistency. Once the validation has been carried out, the satellite-derived TCHP values with their improved tempo- ral and spatial properties can be conveniently used...

  13. A support for the existence of paleolakes and paleorivers buried under Saharan sand by means of “gravitational signal” from EIGEN 6C4

    Czech Academy of Sciences Publication Activity Database

    Klokočník, Jaroslav; Kostelecký, J.; Cílek, Václav; Bezděk, Aleš; Pešek, I.

    2017-01-01

    Roč. 10, č. 9 (2017), 199/1-199/28 ISSN 1866-7511 Institutional support: RVO:67985815 ; RVO:67985831 Keywords : gravitational field model EIGEN 6C4 * functions of disturbing geopotential * satellite digital topography models Subject RIV: DE - Earth Magnetism, Geodesy, Geography OBOR OECD: Physical geography; Geology (GLU-S) Impact factor: 0.955, year: 2016

  14. Modeling Earth Albedo for Satellites in Earth Orbit

    DEFF Research Database (Denmark)

    Bhanderi, Dan; Bak, Thomas

    2005-01-01

    Many satellite are influences by the Earthøs albedo, though very few model schemes exist.in order to predict this phenomenon. Earth albedo is often treated as noise, or ignored completely. When applying solar cells in the attitude hardware, Earth albedo can cause the attitude estimate to deviate...... with as much as 20 deg. Digital Sun sensors with Earth albedo correction in hardware exist, but are expensive. In addition, albedo estimates are necessary in thermal calculations and power budgets. We present a modeling scheme base4d on Eartht reflectance, measured by NASA's Total Ozone Mapping Spectrometer......, in which the Earth Probe Satellite has recorded reflectivity data daily since mid 1996. The mean of these data can be used to calculate the Earth albedo given the positions of the satellite and the Sun. Our results show that the albedo varies highly with the solar angle to the satellite's field of view...

  15. A simple model for yield prediction of rice based on vegetation index derived from satellite and AMeDAS data during ripening period

    International Nuclear Information System (INIS)

    Wakiyama, Y.; Inoue, K.; Nakazono, K.

    2003-01-01

    The present study was conducted to show a simple model for rice yield predicting by using a vegetation index (NDVI) derived from satellite and meteorological data. In a field experiment, the relationship between the vegetation index and radiation absorbed by the rice canopy was investigated from transplanting to maturity. Their correlation held. This result revealed that the vegetation index could be used as a measure of absorptance of solar radiation by rice canopy. NDVI multiplied by solar radiation (SR) every day was accumulated (Σ(SR·NDVI)) from the field experiment. Σ(SR·NDVI) was plotted against above ground dry matter. It was obvious that they had a strong relationship. Rice yield largely depends on solar radiation and air temperature during the ripening period. Air temperature affects dry matter production. Relationships between Y SR -1 (Y: rice yield, SR: solar radiation) and mean air temperature were investigated from meteorological data and statistical data on rice yield. There was an optimum air temperature, 21.3°C, for ripening. When it was near 21.3°C in the ripening period, the rice yield was higher. We proposed a simple model for yield prediction of rice based on these results. The model is composed with SR·NDVI and the optimum air temperature. Vegetation index was derived from 3 years, LANDSAT TM data in Toyama, Ishikawa, Fukui and Nagano prefectures at heading. The meteorological data was used from AMeDAS data. The model was described as follows: Y = 0.728 SR·NDVI−2.04(T−21.3) 2 + 282 (r 2 = 0.65, n = 43) where Y is rice yield (kg 10a -1 ), SR is solar radiation (MJ m -2 ) during the ripening period (from 10 days before heading to 30 days after heading), T is mean air temperature (°C) during the ripening period. RMSE was 33.7kg 10a -1 . The model revealed good precision. (author)

  16. Advancing land surface model development with satellite-based Earth observations

    Science.gov (United States)

    Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

    2017-05-01

    The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts, we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability, and understanding of climate system feedbacks.

  17. Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP

    KAUST Repository

    Houborg, Rasmus; Cescatti, Alessandro; Migliavacca, Mirco; Kustas, W.P.

    2013-01-01

    This study investigates the utility of in situ and satellite-based leaf chlorophyll (Chl) estimates for quantifying leaf photosynthetic capacity and for constraining model simulations of Gross Primary Productivity (GPP) over a corn field in Maryland, U.S.A. The maximum rate of carboxylation (V-max) represents a key control on leaf photosynthesis within the widely employed C-3 and C-4 photosynthesis models proposed by Farquhar et al. (1980) and Collatz et al. (1992), respectively. A semi-mechanistic relationship between V-max(5) (V-max normalized to 25 degrees C) and Chl is derived based on interlinkages between V-max(25), Rubisco enzyme kinetics, leaf nitrogen, and Chl reported in the experimental literature. The resulting linear V-max(25) - Chl relationship is embedded within the photosynthesis scheme of the Community Land Model (CLM), thereby bypassing the use of fixed plant functional type (PFT) specific V-max(25) values. The effect of the updated parameterization on simulated carbon fluxes is tested over a corn field growing season using: (1) a detailed Chl time-series established on the basis of intensive field measurements and (2) Chl estimates derived from Landsat imagery using the REGularized canopy reFLECtance (REGFLEC) tool. Validations against flux tower observations demonstrate benefit of using Chl to parameterize V-max(25) to account for variations in nitrogen availability imposed by severe environmental conditions. The use of V-max(25) that varied seasonally as a function of satellite-based Chl, rather than a fixed PFT-specific value, significantly improved the agreement with observed tower fluxes with Pearson's correlation coefficient (r) increasing from 0.88 to 0.93 and the root-mean-square-deviation decreasing from 4.77 to 3.48 mu mol m(-2) s(-1). The results support the use of Chl as a proxy for photosynthetic capacity using generalized relationships between V-max(25) and Chl, and advocate the potential of satellite retrieved Chl for constraining

  18. Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP

    KAUST Repository

    Houborg, Rasmus

    2013-08-01

    This study investigates the utility of in situ and satellite-based leaf chlorophyll (Chl) estimates for quantifying leaf photosynthetic capacity and for constraining model simulations of Gross Primary Productivity (GPP) over a corn field in Maryland, U.S.A. The maximum rate of carboxylation (V-max) represents a key control on leaf photosynthesis within the widely employed C-3 and C-4 photosynthesis models proposed by Farquhar et al. (1980) and Collatz et al. (1992), respectively. A semi-mechanistic relationship between V-max(5) (V-max normalized to 25 degrees C) and Chl is derived based on interlinkages between V-max(25), Rubisco enzyme kinetics, leaf nitrogen, and Chl reported in the experimental literature. The resulting linear V-max(25) - Chl relationship is embedded within the photosynthesis scheme of the Community Land Model (CLM), thereby bypassing the use of fixed plant functional type (PFT) specific V-max(25) values. The effect of the updated parameterization on simulated carbon fluxes is tested over a corn field growing season using: (1) a detailed Chl time-series established on the basis of intensive field measurements and (2) Chl estimates derived from Landsat imagery using the REGularized canopy reFLECtance (REGFLEC) tool. Validations against flux tower observations demonstrate benefit of using Chl to parameterize V-max(25) to account for variations in nitrogen availability imposed by severe environmental conditions. The use of V-max(25) that varied seasonally as a function of satellite-based Chl, rather than a fixed PFT-specific value, significantly improved the agreement with observed tower fluxes with Pearson\\'s correlation coefficient (r) increasing from 0.88 to 0.93 and the root-mean-square-deviation decreasing from 4.77 to 3.48 mu mol m(-2) s(-1). The results support the use of Chl as a proxy for photosynthetic capacity using generalized relationships between V-max(25) and Chl, and advocate the potential of satellite retrieved Chl for

  19. A satellite and model based flood inundation climatology of Australia

    Science.gov (United States)

    Schumann, G.; Andreadis, K.; Castillo, C. J.

    2013-12-01

    To date there is no coherent and consistent database on observed or simulated flood event inundation and magnitude at large scales (continental to global). The only compiled data set showing a consistent history of flood inundation area and extent at a near global scale is provided by the MODIS-based Dartmouth Flood Observatory. However, MODIS satellite imagery is only available from 2000 and is hampered by a number of issues associated with flood mapping using optical images (e.g. classification algorithms, cloud cover, vegetation). Here, we present for the first time a proof-of-concept study in which we employ a computationally efficient 2-D hydrodynamic model (LISFLOOD-FP) complemented with a sub-grid channel formulation to generate a complete flood inundation climatology of the past 40 years (1973-2012) for the entire Australian continent. The model was built completely from freely available SRTM-derived data, including channel widths, bank heights and floodplain topography, which was corrected for vegetation canopy height using a global ICESat canopy dataset. Channel hydraulics were resolved using actual channel data and bathymetry was estimated within the model using hydraulic geometry. On the floodplain, the model simulated the flow paths and inundation variables at a 1 km resolution. The developed model was run over a period of 40 years and a floodplain inundation climatology was generated and compared to satellite flood event observations. Our proof-of-concept study demonstrates that this type of model can reliably simulate past flood events with reasonable accuracies both in time and space. The Australian model was forced with both observed flow climatology and VIC-simulated flows in order to assess the feasibility of a model-based flood inundation climatology at the global scale.

  20. Northern South China Sea Surface Circulation and its Variability Derived by Combining Satellite Altimetry and Surface Drifter Data

    Directory of Open Access Journals (Sweden)

    N. Peter Benny

    2015-01-01

    Full Text Available The present study analyses the mean and seasonal mesoscale surface circulation of the Northern South China Sea (NSCS and determines the influence of El Niño/SouthernNiño/Southern Oscillation (ENSO. High resolution Eulerian velocity field is derived by combining the available satellite tracked surface drifter data with satellite altimetry during 1993 - 2012. The wind driven current is computed employing the weekly ocean surface mean wind fields derived from the scatterometers on board ERS 1/2, QuikSCAT and ASCAT. The derived mean velocity field exhibits strong boundary currents and broad zonal flow across NSCS. The anomalous field is quite strong in the southern part and the Seasonal circulation clearly depicts the monsoonal forcing. Eddy Kinetic Energy (EKE distribution and its spatial and temporal structures are determined employing Empirical Orthogonal Function (EOF analysis. The ENSO influence on NSCS surface circulation has been analyzed using monthly absolute geostrophic velocity fields during 1996 - 1999.

  1. GRAVTool, a Package to Compute Geoid Model by Remove-Compute-Restore Technique

    Science.gov (United States)

    Marotta, G. S.; Blitzkow, D.; Vidotti, R. M.

    2015-12-01

    Currently, there are several methods to determine geoid models. They can be based on terrestrial gravity data, geopotential coefficients, astro-geodetic data or a combination of them. Among the techniques to compute a precise geoid model, the Remove-Compute-Restore (RCR) has been widely applied. It considers short, medium and long wavelengths derived from altitude data provided by Digital Terrain Models (DTM), terrestrial gravity data and global geopotential coefficients, respectively. In order to apply this technique, it is necessary to create procedures that compute gravity anomalies and geoid models, by the integration of different wavelengths, and that adjust these models to one local vertical datum. This research presents a developed package called GRAVTool based on MATLAB software to compute local geoid models by RCR technique and its application in a study area. The studied area comprehends the federal district of Brazil, with ~6000 km², wavy relief, heights varying from 600 m to 1340 m, located between the coordinates 48.25ºW, 15.45ºS and 47.33ºW, 16.06ºS. The results of the numerical example on the studied area show the local geoid model computed by the GRAVTool package (Figure), using 1377 terrestrial gravity data, SRTM data with 3 arc second of resolution, and geopotential coefficients of the EIGEN-6C4 model to degree 360. The accuracy of the computed model (σ = ± 0.071 m, RMS = 0.069 m, maximum = 0.178 m and minimum = -0.123 m) matches the uncertainty (σ =± 0.073) of 21 points randomly spaced where the geoid was computed by geometrical leveling technique supported by positioning GNSS. The results were also better than those achieved by Brazilian official regional geoid model (σ = ± 0.099 m, RMS = 0.208 m, maximum = 0.419 m and minimum = -0.040 m).

  2. A multi-source satellite data approach for modelling Lake Turkana water level: calibration and validation using satellite altimetry data

    Directory of Open Access Journals (Sweden)

    N. M. Velpuri

    2012-01-01

    Full Text Available Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE of 0.80 during the validation period (2004–2009. Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated

  3. Validation of Satellite-Derived Sea Surface Temperatures for Waters around Taiwan

    Directory of Open Access Journals (Sweden)

    Ming-An Lee

    2005-01-01

    Full Text Available In order to validate the Advanced Very High Resolution Radiometer (AVHRR-derived sea surface temperatures (SST of the waters around Taiwan, we generated a match-up data set of 961 pairs, which included in situ SSTs and concurrent AVHRR measurements for the period of 1998 to 2002. Availability of cloud-free images, i.e., images with more than 85% of cloud-free area in their coverage, was about 2.23% of all AVHRR images during the study period. The range of in situ SSTs was from _ to _ The satellite derived-SSTs through MCSST and NLSST algorithms were linearly related to the in situ SSTs with correlation coefficients of 0.985 and 0.98, respectively. The MCSSTs and NLSSTs had small biases of 0.009 _ and 0.256 _ with root mean square deviations of 0.64 _ and 0.801 _ respectively, therefore the AVHRR-based MCSSTs and NLSSTs had high accuracy in the seas around Taiwan.

  4. Investigations in Satellite MIMO Channel Modeling: Accent on Polarization

    Directory of Open Access Journals (Sweden)

    Karagiannidis George K

    2007-01-01

    Full Text Available Due to the much different environment in satellite and terrestrial links, possibilities in and design of MIMO systems are rather different as well. After pointing out these differences and problems arising from them, two MIMO designs are shown rather well adapted to satellite link characteristics. Cooperative diversity seems to be applicable; its concept is briefly presented without a detailed discussion, leaving solving particular satellite problems to later work. On the other hand, a detailed discussion of polarization time-coded diversity (PTC is given. A physical-statistical model for dual-polarized satellite links is presented together with measuring results validating the model. The concept of 3D polarization is presented as well as briefly describing compact 3D-polarized antennas known from the literature and applicable in satellite links. A synthetic satellite-to-indoor link is constructed and its electromagnetic behavior is simulated via the FDTD (finite-difference time-domain method. Previous result of the authors states that in 3D-PTC situations, MIMO capacity can be about two times higher than SIMO (single-input multiple-output capacity while a diversity gain of nearly is further verified via extensive FDTD computer simulation.

  5. Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

    Science.gov (United States)

    Shrestha, M.S.; Artan, Guleid A.; Bajracharya, S.R.; Sharma, R. R.

    2008-01-01

    In this study, we have described a hydrologic modelling system that uses satellite-based rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived from weather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets – the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

  6. An application of GOCE satellite gravity to resolve mantle heterogeneity in Europe

    DEFF Research Database (Denmark)

    Herceg, Matija; Artemieva, Irina; Thybo, Hans

    2015-01-01

    The aim of this study is to obtain new information on the density structure of the European upper mantle by incorporating the state-of-the-art global gravity data derived from the GOCE satellite gravity mission and recently released seismic model for the crustal structure, EUNAseis. The residual ...... by seismic tomography. Furthermore, we compare our regional upper mantle density model with petrological studies of mantle-derived xenoliths from the Baltic shield and the Arkhangelsk region.......The aim of this study is to obtain new information on the density structure of the European upper mantle by incorporating the state-of-the-art global gravity data derived from the GOCE satellite gravity mission and recently released seismic model for the crustal structure, EUNAseis. The residual...

  7. Improving Satellite-Driven PM2.5 Models with VIIRS Nighttime Light Data in the Beijing–Tianjin–Hebei Region, China

    Directory of Open Access Journals (Sweden)

    Xiya Zhang

    2017-08-01

    Full Text Available Previous studies have estimated ground-level concentrations of particulate matter 2.5 (PM2.5 using satellite-derived aerosol optical depth (AOD in conjunction with meteorological and land use variables. However, the impacts of urbanization on air pollution for predicting PM2.5 are seldom considered. Nighttime light (NTL data, acquired with the Visible Infrared Imaging Radiometer Suite (VIIRS aboard the Suomi National Polar-orbiting Partnership (S-NPP satellite, could be useful for predictions because they have been shown to be good indicators of the urbanization and human activity that can affect PM2.5 concentrations. This study investigated the potential of incorporating VIIRS NTL data in statistical models for PM2.5 concentration predictions. We developed a mixed-effects model to derive daily estimations of surface PM2.5 levels in the Beijing–Tianjin–Hebei region using 3 km resolution satellite AOD and VIIRS NTL data. The results showed the addition of NTL information could improve the performance of the PM2.5 prediction model. The NTL data revealed additional details for predication results in areas with low PM2.5 concentrations and greater apparent seasonal variation due to the seasonal variability of human activity. Comparison showed prediction accuracy was improved more substantially for the model using NTL directly than for the model using the vegetation-adjusted NTL urban index that included NTL. Our findings indicate that VIIRS NTL data have potential for predicting PM2.5 and that they could constitute a useful supplemental data source for estimating ground-level PM2.5 distributions.

  8. Land-atmosphere interaction patterns in southeastern South America using satellite products and climate models

    Science.gov (United States)

    Spennemann, P. C.; Salvia, M.; Ruscica, R. C.; Sörensson, A. A.; Grings, F.; Karszenbaum, H.

    2018-02-01

    In regions of strong Land-Atmosphere (L-A) interaction, soil moisture (SM) conditions can impact the atmosphere through modulating the land surface fluxes. The importance of the identification of L-A interaction regions lies in the potential improvement of the weather/seasonal forecast and the better understanding of the physical mechanisms involved. This study aims to compare the terrestrial segment of the L-A interaction from satellite products and climate models, motivated by previous modeling studies pointing out southeastern South America (SESA) as a L-A hotspot during austral summer. In addition, the L-A interaction under dry or wet anomalous conditions over SESA is analyzed. To identify L-A hotspots the AMSRE-LPRM SM and MODIS land surface temperature products; coupled climate models and uncoupled land surface models were used. SESA highlights as a strong L-A interaction hotspot when employing different metrics, temporal scales and independent datasets, showing consistency between models and satellite estimations. Both AMSRE-LPRM bands (X and C) are consistent showing a strong L-A interaction hotspot over the Pampas ecoregion. Intensification and a larger spatial extent of the L-A interaction for dry summers was observed in both satellite products and models compared to wet summers. These results, which were derived from measured physical variables, are encouraging and promising for future studies analyzing L-A interactions. L-A interaction analysis is proposed here as a meeting point between remote sensing and climate modelling communities of Argentina, within a region with the highest agricultural and livestock production of the continent, but with an important lack of in-situ SM observations.

  9. Using Satellite Remote Sensing and Modelling for Insights into N02 Air Pollution and NO2 Emissions

    Science.gov (United States)

    Lamsal, L. N.; Martin, R. V.; Krotkov, N. A.; Bucsela, E. J.; Celarier, E. A.; vanDonkelaar, A.; Parrish, D.

    2012-01-01

    Nitrogen oxides (NO(x)) are key actors in air quality and climate change. Satellite remote sensing of tropospheric NO2 has developed rapidly with enhanced spatial and temporal resolution since initial observations in 1995. We have developed an improved algorithm and retrieved tropospheric NO2 columns from Ozone Monitoring Instrument. Column observations of tropospheric NO2 from the nadir-viewing satellite sensors contain large contributions from the boundary layer due to strong enhancement of NO2 in the boundary layer. We infer ground-level NO2 concentrations from the OMI satellite instrument which demonstrate significant agreement with in-situ surface measurements. We examine how NO2 columns measured by satellite, ground-level NO2 derived from satellite, and NO(x) emissions obtained from bottom-up inventories relate to world's urban population. We perform inverse modeling analysis of NO2 measurements from OMI to estimate "top-down" surface NO(x) emissions, which are used to evaluate and improve "bottom-up" emission inventories. We use NO2 column observations from OMI and the relationship between NO2 columns and NO(x) emissions from a GEOS-Chem model simulation to estimate the annual change in bottom-up NO(x) emissions. The emission updates offer an improved estimate of NO(x) that are critical to our understanding of air quality, acid deposition, and climate change.

  10. Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

    2017-04-01

    The model of water and heat exchange between vegetation covered territory and atmosphere (LSM, Land Surface Model) for vegetation season has been developed to calculate soil water content, evapotranspiration, infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat balances components as well as soil surface and vegetation cover temperatures and depth distributions of moisture and temperature. The LSM is suited for utilizing satellite-derived estimates of precipitation, land surface temperature and vegetation characteristics and soil surface humidity for each pixel. Vegetation and meteorological characteristics being the model parameters and input variables, correspondingly, have been estimated by ground observations and thematic processing measurement data of scanning radiometers AVHRR/NOAA, SEVIRI/Meteosat-9, -10 (MSG-2, -3) and MSU-MR/Meteor-M № 2. Values of soil surface humidity has been calculated from remote sensing data of scatterometers ASCAT/MetOp-A, -B. The case study has been carried out for the territory of part of the agricultural Central Black Earth Region of European Russia with area of 227300 km2 located in the forest-steppe zone for years 2012-2015 vegetation seasons. The main objectives of the study have been: - to built estimates of precipitation, land surface temperatures (LST) and vegetation characteristics from MSU-MR measurement data using the refined technologies (including algorithms and programs) of thematic processing satellite information matured on AVHRR and SEVIRI data. All technologies have been adapted to the area of interest; - to investigate the possibility of utilizing satellite-derived estimates of values above in the LSM including verification of obtained estimates and development of procedure of their inputting into the model. From the AVHRR data there have been built the estimates of precipitation, three types of LST: land skin temperature Tsg, air temperature at a level of

  11. Donor Satellite Cell Engraftment is Significantly Augmented When the Host Niche is Preserved and Endogenous Satellite Cells are Incapacitated

    Science.gov (United States)

    Boldrin, Luisa; Neal, Alice; Zammit, Peter S; Muntoni, Francesco; Morgan, Jennifer E

    2012-01-01

    Stem cell transplantation is already in clinical practice for certain genetic diseases and is a promising therapy for dystrophic muscle. We used the mdx mouse model of Duchenne muscular dystrophy to investigate the effect of the host satellite cell niche on the contribution of donor muscle stem cells (satellite cells) to muscle regeneration. We found that incapacitation of the host satellite cells and preservation of the muscle niche promote donor satellite cell contribution to muscle regeneration and functional reconstitution of the satellite cell compartment. But, if the host niche is not promptly refilled, or is filled by competent host satellite cells, it becomes nonfunctional and donor engraftment is negligible. Application of this regimen to aged host muscles also promotes efficient regeneration from aged donor satellite cells. In contrast, if the niche is destroyed, yet host satellite cells remain proliferation-competent, donor-derived engraftment is trivial. Thus preservation of the satellite cell niche, concomitant with functional impairment of the majority of satellite cells within dystrophic human muscles, may improve the efficiency of stem cell therapy. Stem Cells2012;30:1971–1984 PMID:22730231

  12. Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

    Science.gov (United States)

    Aulov, O.; Halem, M.; Lary, D. J.

    2011-12-01

    We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly

  13. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tutuila Island, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  14. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Rose Atoll, American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry were...

  15. Using Satellite Remote Sensing Data in a Spatially Explicit Price Model

    Science.gov (United States)

    Brown, Molly E.; Pinzon, Jorge E.; Prince, Stephen D.

    2007-01-01

    Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the World. In this paper we integrate several indicators that are available to enhance the information for preparation for and responses to food security emergencies. The assessment uses a price model based on the relationship between the suitability of the growing season and market prices for coarse grain. The model is then used to create spatially continuous maps of millet prices. The model is applied to the dry central and northern areas of West Africa, using satellite-derived vegetation indices for the entire region. By coupling the model with vegetation data estimated for one to four months into the future, maps are created of a leading indicator of potential price movements. It is anticipated that these maps can be used to enable early warning of famine and for planning appropriate responses.

  16. Assimilation of GMS-5 satellite winds using nudging method with MM5

    Science.gov (United States)

    Gao, Shanhong; Wu, Zengmao; Yang, Bo

    2006-09-01

    With the aid of Meteorological Information Composite and Processing System (MICAPS), satellite wind vectors derived from the Geostationary Meteorological Statellite-5 (GMS-5) and retrieved by National Satellite Meteorology Center of China (NSMC) can be obtained. Based on the nudging method built in the fifth-generation Mesoscale Model (MM5) of Pennsylvania State University and National Center for Atmospheric Research, a data preprocessor is developed to convert these satellite wind vectors to those with specified format required in MM5. To examine the data preprocessor and evaluate the impact of satellite winds from GMS-5 on MM5 simulations, a series of numerical experimental forecasts consisting of four typhoon cases in 2002 are designed and implemented. The results show that the preprocessor can process satellite winds smoothly and MM5 model runs successfully with a little extra computational load during ingesting these winds, and that assimilation of satellite winds by MM5 nudging method can obviously improve typhoon track forecast but contributes a little to typhoon intensity forecast. The impact of the satellite winds depends heavily upon whether the typhoon bogussing scheme in MM5 was turned on or not. The data preprocessor developed in this paper not only can treat GMS-5 satellite winds but also has capability with little modification to process derived winds from other geostationary satellites.

  17. How robust are in situ observations for validating satellite-derived albedo over the dark zone of the Greenland Ice Sheet?

    Science.gov (United States)

    Ryan, J.; Hubbard, A., II; Irvine-Fynn, T. D.; Doyle, S. H.; Cook, J.; Stibal, M.; Smith, L. C.; Box, J. E.

    2017-12-01

    Calibration and validation of satellite-derived ice sheet albedo data require high-quality, in situ measurements commonly acquired by up and down facing pyranometers mounted on automated weather stations (AWS). However, direct comparison between ground and satellite-derived albedo can only be justified when the measured surface is homogeneous at the length-scale of both satellite pixel and in situ footprint. We used digital imagery acquired by an unmanned aerial vehicle to evaluate point-to-pixel albedo comparisons across the western, ablating margin of the Greenland Ice Sheet. Our results reveal that in situ measurements overestimate albedo by up to 0.10 at the end of the melt season because the ground footprints of AWS-mounted pyranometers are insufficient to capture the spatial heterogeneity of the ice surface as it progressively ablates and darkens. Statistical analysis of 21 AWS across the entire Greenland Ice Sheet reveals that almost half suffer from this bias, including some AWS located within the wet snow zone.

  18. A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data

    Science.gov (United States)

    Velpuri, N.M.; Senay, G.B.; Asante, K.O.

    2012-01-01

    Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of interand intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellitedriven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004-2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1-2m. The lake level fluctuated in the range up to 4m between the years 1998-2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance

  19. CM5, a pre-Swarm comprehensive geomagnetic field model derived from over 12 yr of CHAMP, Ørsted, SAC-C and observatory data

    DEFF Research Database (Denmark)

    Sabaka, Terence J.; Olsen, Nils; Tyler, Robert H.

    2015-01-01

    A comprehensive magnetic field model named CM5 has been derived from CHAMP, Orsted and SAC-C satellite and observatory hourly-means data from 2000 August to 2013 January using the Swarm Level-2 Comprehensive Inversion (CI) algorithm. Swarm is a recently launched constellation of three satellites ...

  20. Satellite-derived land covers for runoff estimation using SCS-CN method in Chen-You-Lan Watershed, Taiwan

    Science.gov (United States)

    Zhang, Wen-Yan; Lin, Chao-Yuan

    2017-04-01

    The Soil Conservation Service Curve Number (SCS-CN) method, which was originally developed by the USDA Natural Resources Conservation Service, is widely used to estimate direct runoff volume from rainfall. The runoff Curve Number (CN) parameter is based on the hydrologic soil group and land use factors. In Taiwan, the national land use maps were interpreted from aerial photos in 1995 and 2008. Rapid updating of post-disaster land use map is limited due to the high cost of production, so the classification of satellite images is the alternative method to obtain the land use map. In this study, Normalized Difference Vegetation Index (NDVI) in Chen-You-Lan Watershed was derived from dry and wet season of Landsat imageries during 2003 - 2008. Land covers were interpreted from mean value and standard deviation of NDVI and were categorized into 4 groups i.e. forest, grassland, agriculture and bare land. Then, the runoff volume of typhoon events during 2005 - 2009 were estimated using SCS-CN method and verified with the measured runoff data. The result showed that the model efficiency coefficient is 90.77%. Therefore, estimating runoff by using the land cover map classified from satellite images is practicable.

  1. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

    Science.gov (United States)

    Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

    2016-06-01

    The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

  2. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  3. The relationship of field burn severity measures to satellite-derived Burned Area Reflectance Classification (BARC) maps

    Science.gov (United States)

    Andrew Hudak; Penelope Morgan; Carter Stone; Pete Robichaud; Terrie Jain; Jess Clark

    2004-01-01

    Preliminary results are presented from ongoing research on spatial variability of fire effects on soils and vegetation from the Black Mountain Two and Cooney Ridge wildfires, which burned in western Montana during the 2003 fire season. Extensive field fractional cover data were sampled to assess the efficacy of quantitative satellite image-derived indicators of burn...

  4. Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

    Science.gov (United States)

    Vierling, Lee A.; Vierling, Kerri T.; Adam, Patrick; Hudak, Andrew T.

    2013-01-01

    Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2

  5. Modeling water and heat balance components of large territory for vegetation season using information from polar-orbital and geostationary meteorological satellites

    Science.gov (United States)

    Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

    2015-04-01

    To date, physical-mathematical modeling processes of land surface-atmosphere interaction is considered to be the most appropriate tool for obtaining reliable estimates of water and heat balance components of large territories. The model of these processes (Land Surface Model, LSM) developed for vegetation period is destined for simulating soil water content W, evapotranspiration Ev, vertical latent LE and heat fluxes from land surface as well as vertically distributed soil temperature and moisture, soil surface Tg and foliage Tf temperatures, and land surface skin temperature (LST) Ts. The model is suitable for utilizing remote sensing data on land surface and meteorological conditions. In the study these data have been obtained from measurements by scanning radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/geostationary satellites Meteosat-9, -10 (MSG-2, -3). The heterogeneity of the land surface and meteorological conditions has been taken into account in the model by using soil and vegetation characteristics as parameters and meteorological characteristics as input variables. Values of these characteristics have been determined from ground observations and remote sensing information. So, AVHRR data have been used to build the estimates of effective land surface temperature (LST) Ts.eff and emissivity E, vegetation-air temperature (temperature at the vegetation level) Ta, normalized vegetation index NDVI, vegetation cover fraction B, the leaf area index LAI, and precipitation. From MODIS data the values of LST Tls, Å, NDVI, LAI have been derived. From SEVIRI data there have been retrieved Tls, E, Ta, NDVI, LAI and precipitation. All named retrievals covered the vast territory of the part of the agricultural Central Black Earth Region located in the steppe-forest zone of European Russia. This territory with coordinates 49°30'-54°N, 31°-43°E and a total area of 227,300 km2 has been chosen for investigation. It has been carried out for years 2009

  6. Effects of air-sea interaction on extended-range prediction of geopotential height at 500 hPa over the northern extratropical region

    Science.gov (United States)

    Wang, Xujia; Zheng, Zhihai; Feng, Guolin

    2018-04-01

    The contribution of air-sea interaction on the extended-range prediction of geopotential height at 500 hPa in the northern extratropical region has been analyzed with a coupled model form Beijing Climate Center and its atmospheric components. Under the assumption of the perfect model, the extended-range prediction skill was evaluated by anomaly correlation coefficient (ACC), root mean square error (RMSE), and signal-to-noise ratio (SNR). The coupled model has a better prediction skill than its atmospheric model, especially, the air-sea interaction in July made a greater contribution for the improvement of prediction skill than other months. The prediction skill of the extratropical region in the coupled model reaches 16-18 days in all months, while the atmospheric model reaches 10-11 days in January, April, and July and only 7-8 days in October, indicating that the air-sea interaction can extend the prediction skill of the atmospheric model by about 1 week. The errors of both the coupled model and the atmospheric model reach saturation in about 20 days, suggesting that the predictable range is less than 3 weeks.

  7. An evolutionary framework for the Jovian and Saturnian satellites

    International Nuclear Information System (INIS)

    Stevenson, R.J.

    1987-01-01

    The position of the satellite within the protonebula, the influence of the parent planet, particularly the relative effects of tidal (gravitational) as opposed to radiogenic (internal) heat generating processes, as well as the type of ice, exert a control on the evolutionary histories of the Jovian and Saturnian satellites. The landscapes of the moons are modified by surface deformational processes (tectonic activity derived from within the body) and externally derived cratering. The geological history of the Galilean satellites is deduced from surface stratigraphic successions of geological units. Io and Europa, with crater-free surfaces, are tectonically more advanced than crater-saturated Callisto. Two thermal-drive models are proposed based on: an expression for externally derived gravitational influences between two bodies; and internal heat generation via radiogenic decay (expressed by surface area/volume ratio). Both parameters, for the Galilean satellites, are plotted against an inferred product of tectonic processes - the age of the surface terrain. From these diagrams, the tectonic evolutionary state of the more distant Saturnian system are predicted. These moons are fitted into an evolutionary framework for the Solar System. 34 refs.; 4 figs.; 2 tabs

  8. Estimation of solar radiation over Cambodia from long-term satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Janjai, S.; Pankaew, P.; Laksanaboonsong, J. [Solar Energy Research Laboratory, Department of Physics, Faculty of Science, Silpakorn University, Nakhon Pathom 73000 (Thailand); Kitichantaropas, P. [Department of Alternative Energy Development and Efficiency, Ministry of Energy, 17 Rama 1 Road, Patumwan, Bangkok 10330 (Thailand)

    2011-04-15

    In this work, monthly average daily global solar irradiation over Cambodia was estimated from a long-term satellite data. A 14-year period (1995-2008) of visible channel data from GMS5, GOES9 and MTSAT-1R satellites were used to provide earth-atmospheric reflectivity. A satellite-based solar radiation model developed for a tropical environment was used to estimate surface solar radiation. The model relates the satellite-derived earth-atmospheric reflectivity to absorption and scattering coefficients of various atmospheric constituents. The absorption of solar radiation due to water vapour was calculated from precipitable water derived from ambient relative humidity and temperature. Ozone data from the TOMS and OMI satellite data were employed to compute the solar radiation absorption by ozone. The depletion of radiation due to aerosols was estimated from the visibility data. Five new solar radiation measuring stations were established at Cambodian cities, namely Siem Reap (13.87 N, 103.85 E), Kompong Thom (12.68 N, 104.88 E), Phnom Penh (11.55 N, 104.83 E), Sihanouke Ville (10.67 N, 103.63 E) and Kampot (10.70 N, 104.28 E). Global solar radiation measured at these stations was used to validate the model. The validation was also carried out by using solar radiation measured at four Thai meteorological stations. These stations are situated near the Cambodian border. Monthly average daily global irradiation from these stations was compared with that calculated from the model. The measured and calculated irradiation is in good agreement, with the root mean square difference of 6.3%, with respect to the mean values. After the validation, the model was used to calculate monthly average daily global solar irradiation over Cambodia. Based on this satellite-derived irradiation, solar radiation maps for Cambodia were generated. These maps show that solar radiation climate of this country is strongly influenced by the monsoons. A solar radiation database was also generated

  9. Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

    Science.gov (United States)

    Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

    2015-01-01

    Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia’s cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal

  10. Evaluation of Satellite and Model Precipitation Products Over Turkey

    Science.gov (United States)

    Yilmaz, M. T.; Amjad, M.

    2017-12-01

    Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14

  11. Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

    Science.gov (United States)

    Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

    2015-09-01

    The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

  12. Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale

    Science.gov (United States)

    Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

    2015-03-01

    The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

  13. Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model.

    Science.gov (United States)

    Migliavacca, Mirco; Meroni, Michele; Busetto, Lorenzo; Colombo, Roberto; Zenone, Terenzio; Matteucci, Giorgio; Manca, Giovanni; Seufert, Guenther

    2009-01-01

    In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

  14. Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

    Directory of Open Access Journals (Sweden)

    Guenther Seufert

    2009-02-01

    Full Text Available In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC with the aims of i improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale.

  15. Orbit Determination of the SELENE Satellites Using Multi-Satellite Data Types and Evaluation of SELENE Gravity Field Models

    Science.gov (United States)

    Goossens, S.; Matsumoto, K.; Noda, H.; Araki, H.; Rowlands, D. D.; Lemoine, F. G.

    2011-01-01

    The SELENE mission, consisting of three separate satellites that use different terrestrial-based tracking systems, presents a unique opportunity to evaluate the contribution of these tracking systems to orbit determination precision. The tracking data consist of four-way Doppler between the main orbiter and one of the two sub-satellites while the former is over the far side, and of same-beam differential VLBI tracking between the two sub-satellites. Laser altimeter data are also used for orbit determination. The contribution to orbit precision of these different data types is investigated through orbit overlap analysis. It is shown that using four-way and VLBI data improves orbit consistency for all satellites involved by reducing peak values in orbit overlap differences that exist when only standard two-way Doppler and range data are used. Including laser altimeter data improves the orbit precision of the SELENE main satellite further, resulting in very smooth total orbit errors at an average level of 18m. The multi-satellite data have also resulted in improved lunar gravity field models, which are assessed through orbit overlap analysis using Lunar Prospector tracking data. Improvements over a pre-SELENE model are shown to be mostly in the along-track and cross-track directions. Orbit overlap differences are at a level between 13 and 21 m with the SELENE models, depending on whether l-day data overlaps or I-day predictions are used.

  16. Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset

    Science.gov (United States)

    Czernecki, Bartosz; Nowosad, Jakub; Jabłońska, Katarzyna

    2018-04-01

    Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models' accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For

  17. An enhanced approach for the use of satellite-derived leaf area index values in dry deposition modeling in the Athabasca oil sands region.

    Science.gov (United States)

    Davies, Mervyn; Cho, Sunny; Spink, David; Pauls, Ron; Desilets, Michael; Shen, Yan; Bajwa, Kanwardeep; Person, Reid

    2016-12-15

    In the Athabasca oil sands region (AOSR) of Northern Alberta, the dry deposition of sulphur and nitrogen compounds represents a major fraction of total (wet plus dry) deposition due to oil sands emissions. The leaf area index (LAI) is a critical parameter that affects the dry deposition of these gaseous and particulate compounds to the surrounding boreal forest canopy. For this study, LAI values based on Moderate Resolution Imaging Spectroradiometer satellite imagery were obtained and compared to ground-based measurements, and two limitations with the satellite data were identified. The satellite LAI data firstly represents one-sided LAI values that do not account for the enhanced LAI associated with needle leaf geometry, and secondly, underestimates LAI in winter-time northern latitude regions. An approach for adjusting satellite LAI values for different boreal forest cover types, as a function of time of year, was developed to produce more representative LAI values that can be used by air quality sulphur and nitrogen deposition models. The application of the approach increases the AOSR average LAI for January from 0.19 to 1.40, which represents an increase of 637%. Based on the application of the CALMET/CALPUFF model system, this increases the predicted regional average dry deposition of sulphur and nitrogen compounds for January by factors of 1.40 to 1.30, respectively. The corresponding AOSR average LAI for July increased from 2.8 to 4.0, which represents an increase of 43%. This increases the predicted regional average dry deposition of sulphur and nitrogen compounds for July by factors of 1.28 to 1.22, respectively. These findings reinforce the importance of the LAI metric for predicting the dry deposition of sulphur and nitrogen compounds. While satellite data can provide enhanced spatial and temporal resolution, adjustments are identified to overcome associated limitations. This work is considered to have application for other deposition model studies where

  18. Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

    Directory of Open Access Journals (Sweden)

    T. Cohen Liechti

    2012-02-01

    Full Text Available In the framework of the African DAms ProjecT (ADAPT, an integrated water resource management study in the Zambezi Basin is currently under development. In view of the sparse gauging network for rainfall monitoring, the observations from spaceborne instrumentation currently produce the only available rainfall data for a large part of the basin.

    Three operational and acknowledged high resolution satellite derived estimates: the Tropical Rainfall Measuring Mission product 3B42 (TRMM 3B42, the Famine Early Warning System product 2.0 (FEWS RFE2.0 and the National Oceanic and Atmospheric Administration/Climate Prediction Centre (NOAA/CPC morphing technique (CMORPH are analyzed in terms of spatial and temporal repartition of the precipitations. They are compared to ground data for the wet seasons of the years 2003 to 2009 on a point to pixel basis at daily, 10-daily and monthly time steps and on a pixel to pixel basis for the wet seasons of the years 2003 to 2007 at monthly time steps.

    The general North-South gradient of precipitation is captured by all the analyzed products. Regarding the spatial heterogeneity, FEWS pixels are much more inter-correlated than TRMM and CMORPH pixels. For a rainfall homogeneity threshold criterion of 0.5 global mean correlation coefficient, the area of each sub-basin should not exceed a circle of 2.5° latitude/longitude radius for FEWS and a circle of 0.75° latitude/longitude radius for TRMM and CMORPH considering rectangular meshes.

    In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating the rainfall by nearly 50%. The statistics of TRMM and FEWS estimates show quite similar results.

    Due to its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin.

  19. Integration of Ground, Buoys, Satellite and Model data to map the Changes in Meteorological Parameters Associated with Harvey Hurricane

    Science.gov (United States)

    Chauhan, A.; Sarkar, S.; Singh, R. P.

    2017-12-01

    The coastal areas have dense onshore and marine observation network and are also routinely monitored by constellation of satellites. The monitoring of ocean, land and atmosphere through a range of meteorological parameters, provides information about the land and ocean surface. Satellite data also provide information at different pressure levels that help to access the development of tropical storms and formation of hurricanes at different categories. Integration of ground, buoys, satellite and model data showing the changes in meteorological parameters during the landfall stages of hurricane Harvey will be discussed. Hurricane Harvey was one of the deadliest hurricanes at the Gulf coast which caused intense flooding from the precipitation. The various observation networks helped city administrators to evacuate the coastal areas, that minimized the loss of lives compared to the Galveston hurricane of 1900 which took 10,000 lives. Comparison of meteorological parameters derived from buoys, ground stations and satellites associated with Harvey and 2005 Katrina hurricane present some of the interesting features of the two hurricanes.

  20. Building a satellite climate diagnostics data base for real-time climate monitoring

    International Nuclear Information System (INIS)

    Ropelewski, C.F.

    1991-01-01

    The paper discusses the development of a data base, the Satellite Climate Diagnostic Data Base (SCDDB), for real time operational climate monitoring utilizing current satellite data. Special attention is given to the satellite-derived quantities useful for monitoring global climate changes, the requirements of SCDDB, and the use of conventional meteorological data and model assimilated data in developing the SCDDB. Examples of prototype SCDDB products are presented. 10 refs

  1. Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

    Science.gov (United States)

    Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

    2012-12-01

    Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

  2. Validation of Earth atmosphere models using solar EUV observations from the CORONAS and PROBA2 satellites in occultation mode

    Science.gov (United States)

    Slemzin, Vladimir; Ulyanov, Artyom; Gaikovich, Konstantin; Kuzin, Sergey; Pertsov, Andrey; Berghmans, David; Dominique, Marie

    2016-02-01

    Aims: Knowledge of properties of the Earth's upper atmosphere is important for predicting the lifetime of low-orbit spacecraft as well as for planning operation of space instruments whose data may be distorted by atmospheric effects. The accuracy of the models commonly used for simulating the structure of the atmosphere is limited by the scarcity of the observations they are based on, so improvement of these models requires validation under different atmospheric conditions. Measurements of the absorption of the solar extreme ultraviolet (EUV) radiation in the upper atmosphere below 500 km by instruments operating on low-Earth orbits (LEO) satellites provide efficient means for such validation as well as for continuous monitoring of the upper atmosphere and for studying its response to the solar and geomagnetic activity. Method: This paper presents results of measurements of the solar EUV radiation in the 17 nm wavelength band made with the SPIRIT and TESIS telescopes on board the CORONAS satellites and the SWAP telescope on board the PROBA2 satellite in the occulted parts of the satellite orbits. The transmittance profiles of the atmosphere at altitudes between 150 and 500 km were derived from different phases of solar activity during solar cycles 23 and 24 in the quiet state of the magnetosphere and during the development of a geomagnetic storm. We developed a mathematical procedure based on the Tikhonov regularization method for solution of ill-posed problems in order to retrieve extinction coefficients from the transmittance profiles. The transmittance profiles derived from the data and the retrieved extinction coefficients are compared with simulations carried out with the NRLMSISE-00 atmosphere model maintained by Naval Research Laboratory (USA) and the DTM-2013 model developed at CNES in the framework of the FP7 project ATMOP. Results: Under quiet and slightly disturbed magnetospheric conditions during high and low solar activity the extinction coefficients

  3. Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates

    Energy Technology Data Exchange (ETDEWEB)

    Sengupta, Manajit [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gotseff, Peter [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-12-01

    This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear sky model performance.

  4. Spatially Explicit Estimation of Optimal Light Use Efficiency for Improved Satellite Data Driven Ecosystem Productivity Modeling

    Science.gov (United States)

    Madani, N.; Kimball, J. S.; Running, S. W.

    2014-12-01

    Remote sensing based light use efficiency (LUE) models, including the MODIS (MODerate resolution Imaging Spectroradiometer) MOD17 algorithm are commonly used for regional estimation and monitoring of vegetation gross primary production (GPP) and photosynthetic carbon (CO2) uptake. A common model assumption is that plants in a biome matrix operate at their photosynthetic capacity under optimal climatic conditions. A prescribed biome maximum light use efficiency parameter defines the maximum photosynthetic carbon conversion rate under prevailing climate conditions and is a large source of model uncertainty. Here, we used tower (FLUXNET) eddy covariance measurement based carbon flux data for estimating optimal LUE (LUEopt) over a North American domain. LUEopt was first estimated using tower observed daily carbon fluxes, meteorology and satellite (MODIS) observed fraction of photosynthetically active radiation (FPAR). LUEopt was then spatially interpolated over the domain using empirical models derived from independent geospatial data including global plant traits, surface soil moisture, terrain aspect, land cover type and percent tree cover. The derived LUEopt maps were then used as primary inputs to the MOD17 LUE algorithm for regional GPP estimation; these results were evaluated against tower observations and alternate MOD17 GPP estimates determined using Biome-specific LUEopt constants. Estimated LUEopt shows large spatial variability within and among different land cover classes indicated from a sparse North American tower network. Leaf nitrogen content and soil moisture are two important factors explaining LUEopt spatial variability. GPP estimated from spatially explicit LUEopt inputs shows significantly improved model accuracy against independent tower observations (R2 = 0.76; Mean RMSE plant trait information can explain spatial heterogeneity in LUEopt, leading to improved GPP estimates from satellite based LUE models.

  5. Rainfall variability over southern Africa: an overview of current research using satellite and climate model data

    Science.gov (United States)

    Williams, C.; Kniveton, D.; Layberry, R.

    2009-04-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.

  6. Hydrological Utility and Uncertainty of Multi-Satellite Precipitation Products in the Mountainous Region of South Korea

    Directory of Open Access Journals (Sweden)

    Jong Pil Kim

    2016-07-01

    Full Text Available Satellite-derived precipitation can be a potential source of forcing data for assessing water availability and managing water supply in mountainous regions of East Asia. This study investigates the hydrological utility of satellite-derived precipitation and uncertainties attributed to error propagation of satellite products in hydrological modeling. To this end, four satellite precipitation products (tropical rainfall measuring mission (TRMM multi-satellite precipitation analysis (TMPA version 6 (TMPAv6 and version 7 (TMPAv7, the global satellite mapping of precipitation (GSMaP, and the climate prediction center (CPC morphing technique (CMORPH were integrated into a physically-based hydrologic model for the mountainous region of South Korea. The satellite precipitation products displayed different levels of accuracy when compared to the intra- and inter-annual variations of ground-gauged precipitation. As compared to the GSMaP and CMORPH products, superior performances were seen when the TMPA products were used within streamflow simulations. Significant dry (negative biases in the GSMaP and CMORPH products led to large underestimates of streamflow during wet-summer seasons. Although the TMPA products displayed a good level of performance for hydrologic modeling, there were some over/underestimates of precipitation by satellites during the winter season that were induced by snow accumulation and snowmelt processes. These differences resulted in streamflow simulation uncertainties during the winter and spring seasons. This study highlights the crucial need to understand hydrological uncertainties from satellite-derived precipitation for improved water resource management and planning in mountainous basins. Furthermore, it is suggested that a reliable snowfall detection algorithm is necessary for the new global precipitation measurement (GPM mission.

  7. A corotation electric field model of the Earth derived from Swarm satellite magnetic field measurements

    Science.gov (United States)

    Maus, Stefan

    2017-08-01

    Rotation of the Earth in its own geomagnetic field sets up a primary corotation electric field, compensated by a secondary electric field of induced electrical charges. For the geomagnetic field measured by the Swarm constellation of satellites, a derivation of the global corotation electric field inside and outside of the corotation region is provided here, in both inertial and corotating reference frames. The Earth is assumed an electrical conductor, the lower atmosphere an insulator, followed by the corotating ionospheric E region again as a conductor. Outside of the Earth's core, the induced charge is immediately accessible from the spherical harmonic Gauss coefficients of the geomagnetic field. The charge density is positive at high northern and southern latitudes, negative at midlatitudes, and increases strongly toward the Earth's center. Small vertical electric fields of about 0.3 mV/m in the insulating atmospheric gap are caused by the corotation charges located in the ionosphere above and the Earth below. The corotation charges also flow outward into the region of closed magnetic field lines, forcing the plasmasphere to corotate. The electric field of the corotation charges further extends outside of the corotating regions, contributing radial outward electric fields of about 10 mV/m in the northern and southern polar caps. Depending on how the magnetosphere responds to these fields, the Earth may carry a net electric charge.

  8. Geomagnetic core field models in the satellite era

    DEFF Research Database (Denmark)

    Lesur, Vincent; Olsen, Nils; Thomson, Alan W. P.

    2011-01-01

    After a brief review of the theoretical basis and difficulties that modelers are facing, we present three recent models of the geomagnetic field originating in the Earth’s core. All three modeling approaches are using recent observatory and near-Earth orbiting survey satellite data. In each case...

  9. Neuron-Derived ADAM10 Production Stimulates Peripheral Nerve Injury-Induced Neuropathic Pain by Cleavage of E-Cadherin in Satellite Glial Cells.

    Science.gov (United States)

    Li, Jian; Ouyang, Qing; Chen, Cheng-Wen; Chen, Qian-Bo; Li, Xiang-Nan; Xiang, Zheng-Hua; Yuan, Hong-Bin

    2017-09-01

    Increasing evidence suggests the potential involvement of metalloproteinase family proteins in the pathogenesis of neuropathic pain, although the underlying mechanisms remain elusive. Using the spinal nerve ligation model, we investigated whether ADAM10 proteins participate in pain regulation. By implementing invitro methods, we produced a purified culture of satellite glial cells to study the underlying mechanisms of ADAM10 in regulating neuropathic pain. Results showed that the ADAM10 protein was expressed in calcitonin gene-related peptide (CGRP)-containing neurons of the dorsal root ganglia, and expression was upregulated following spinal nerve ligation surgery invivo. Intrathecal administration of GI254023X, an ADAM10 selective inhibitor, to the rats one to three days after spinal nerve ligation surgery attenuated the spinal nerve ligation-induced mechanical allodynia and thermal hyperalgesia. Intrathecal injection of ADAM10 recombinant protein simulated pain behavior in normal rats to a similar extent as those treated by spinal nerve ligation surgery. These results raised a question about the relative contribution of ADAM10 in pain regulation. Further results showed that ADAM10 might act by cleaving E-cadherin, which is mainly expressed in satellite glial cells. GI254023X reversed spinal nerve ligation-induced downregulation of E-cadherin and activation of cyclooxygenase 2 after spinal nerve ligation. β-catenin, which creates a complex with E-cadherin in the membranes of satellite glial cells, was also downregulated by spinal nerve ligation surgery in satellite glial cells. Finally, knockdown expression of β-catenin by lentiviral infection in purified satellite glial cells increased expression of inducible nitric oxide synthase and cyclooxygenase 2. Our findings indicate that neuron-derived ADAM10 production stimulates peripheral nerve injury-induced neuropathic pain by cleaving E-cadherin in satellite glial cells. © 2017 American Academy of Pain Medicine

  10. A Simple Semi-Empirical Model for the Estimation of Photosynthetically Active Radiation from Satellite Data in the Tropics

    Directory of Open Access Journals (Sweden)

    S. Janjai

    2013-01-01

    Full Text Available This paper presents a simple semi-empirical model for estimating global photosynthetically active radiation (PAR under all sky conditions. The model expresses PAR as a function of cloud index, aerosol optical depth, total ozone column, solar zenith angle, and air mass. The formulation of the model was based on a four-year period (2008–2011 of PAR data obtained from the measurements at four solar monitoring stations in a tropical environment of Thailand. These are Chiang Mai (18.78°N, 98.98°E, Ubon Ratchathani (15.25°N, 104.87°E, Nakhon Pathom (13.82°N, 100.04°E, and Songkhla (7.20°N, 100.60°E. The cloud index was derived from MTSAT-1R satellite, whereas the aerosol optical depth was obtained from MODIS/Terra satellite. For the total ozone column, it was retrieved from OMI/Aura satellite. The model was validated against independent data set from the four stations. It was found that hourly PAR estimated from the proposed model and that obtained from the measurements were in reasonable agreement, with the root mean square difference (RMSD and mean bias difference (MBD of 14.3% and −5.8%, respectively. In addition, for the case of monthly average hourly PAR, RMSD and MBD were reduced to 11.1% and −5.1%, respectively.

  11. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  12. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multispectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  13. Sea ice-atmospheric interaction: Application of multispectral satellite data in polar surface energy flux estimates

    Science.gov (United States)

    Steffen, Konrad; Key, J.; Maslanik, J.; Schweiger, A.

    1993-01-01

    This is the third annual report on: Sea Ice-Atmosphere Interaction - Application of Multispectral Satellite Data in Polar Surface Energy Flux Estimates. The main emphasis during the past year was on: radiative flux estimates from satellite data; intercomparison of satellite and ground-based cloud amounts; radiative cloud forcing; calibration of the Advanced Very High Resolution Radiometer (AVHRR) visible channels and comparison of two satellite derived albedo data sets; and on flux modeling for leads. Major topics covered are arctic clouds and radiation; snow and ice albedo, and leads and modeling.

  14. Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

    Science.gov (United States)

    Piretzidis, Dimitrios; Sideris, Michael G.

    2017-09-01

    Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63-84 mEötvös (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10-30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be

  15. Assessing modelled spatial distributions of ice water path using satellite data

    Science.gov (United States)

    Eliasson, S.; Buehler, S. A.; Milz, M.; Eriksson, P.; John, V. O.

    2010-05-01

    The climate models used in the IPCC AR4 show large differences in monthly mean cloud ice. The most valuable source of information that can be used to potentially constrain the models is global satellite data. For this, the data sets must be long enough to capture the inter-annual variability of Ice Water Path (IWP). PATMOS-x was used together with ISCCP for the annual cycle evaluation in Fig. 7 while ECHAM-5 was used for the correlation with other models in Table 3. A clear distinction between ice categories in satellite retrievals, as desired from a model point of view, is currently impossible. However, long-term satellite data sets may still be used to indicate the climatology of IWP spatial distribution. We evaluated satellite data sets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, to determine which data sets can be used to evaluate the climate models. IWP data from CloudSat cloud profiling radar provides the most advanced data set on clouds. As CloudSat data are too short to evaluate the model data directly, it was mainly used here to evaluate IWP from the other satellite data sets. ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the best of the two. As PATMOS-x extends over more than 25 years and is in fairly close agreement with CloudSat, it was chosen as the reference data set for the model evaluation. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is the GCM from IPCC AR4 closest to satellite observations.

  16. Extracting Urban Morphology for Atmospheric Modeling from Multispectral and SAR Satellite Imagery

    Science.gov (United States)

    Wittke, S.; Karila, K.; Puttonen, E.; Hellsten, A.; Auvinen, M.; Karjalainen, M.

    2017-05-01

    This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1) Digital Elevation Model (DEM) and 2) land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP).

  17. EXTRACTING URBAN MORPHOLOGY FOR ATMOSPHERIC MODELING FROM MULTISPECTRAL AND SAR SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    S. Wittke

    2017-05-01

    Full Text Available This paper presents an approach designed to derive an urban morphology map from satellite data while aiming to minimize the cost of data and user interference. The approach will help to provide updates to the current morphological databases around the world. The proposed urban morphology maps consist of two layers: 1 Digital Elevation Model (DEM and 2 land cover map. Sentinel-2 data was used to create a land cover map, which was realized through image classification using optical range indices calculated from image data. For the purpose of atmospheric modeling, the most important classes are water and vegetation areas. The rest of the area includes bare soil and built-up areas among others, and they were merged into one class in the end. The classification result was validated with ground truth data collected both from field measurements and aerial imagery. The overall classification accuracy for the three classes is 91 %. TanDEM-X data was processed into two DEMs with different grid sizes using interferometric SAR processing. The resulting DEM has a RMSE of 3.2 meters compared to a high resolution DEM, which was estimated through 20 control points in flat areas. Comparing the derived DEM with the ground truth DEM from airborne LIDAR data, it can be seen that the street canyons, that are of high importance for urban atmospheric modeling are not detectable in the TanDEM-X DEM. However, the derived DEM is suitable for a class of urban atmospheric models. Based on the numerical modeling needs for regional atmospheric pollutant dispersion studies, the generated files enable the extraction of relevant parametrizations, such as Urban Canopy Parameters (UCP.

  18. Polar clouds and radiation in satellite observations, reanalyses, and climate models

    NARCIS (Netherlands)

    Lenaerts, JTM; Van Tricht, Kristof; Lhermitte, S.L.M.; L'Ecuyer, T.S.

    2017-01-01

    Clouds play a pivotal role in the surface energy budget of the polar regions. Here we use two largely independent data sets of cloud and surface downwelling radiation observations derived by satellite remote sensing (2007–2010) to evaluate simulated clouds and radiation over both polar ice sheets

  19. Hurricane Satellite (HURSAT) from International Satellite Cloud Climatology Project (ISCCP) B1, Version 6

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Hurricane Satellite (HURSAT) from derived International Satellite Cloud Climatology Project (ISCCP) B1 observations of tropical cyclones worldwide. The B1 data...

  20. Using Deep Learning for Targeted Data Selection, Improving Satellite Observation Utilization for Model Initialization

    Science.gov (United States)

    Lee, Y. J.; Bonfanti, C. E.; Trailovic, L.; Etherton, B.; Govett, M.; Stewart, J.

    2017-12-01

    At present, a fraction of all satellite observations are ultimately used for model assimilation. The satellite data assimilation process is computationally expensive and data are often reduced in resolution to allow timely incorporation into the forecast. This problem is only exacerbated by the recent launch of Geostationary Operational Environmental Satellite (GOES)-16 satellite and future satellites providing several order of magnitude increase in data volume. At the NOAA Earth System Research Laboratory (ESRL) we are researching the use of machine learning the improve the initial selection of satellite data to be used in the model assimilation process. In particular, we are investigating the use of deep learning. Deep learning is being applied to many image processing and computer vision problems with great success. Through our research, we are using convolutional neural network to find and mark regions of interest (ROI) to lead to intelligent extraction of observations from satellite observation systems. These targeted observations will be used to improve the quality of data selected for model assimilation and ultimately improve the impact of satellite data on weather forecasts. Our preliminary efforts to identify the ROI's are focused in two areas: applying and comparing state-of-art convolutional neural network models using the analysis data from the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) weather model, and using these results as a starting point to optimize convolution neural network model for pattern recognition on the higher resolution water vapor data from GOES-WEST and other satellite. This presentation will provide an introduction to our convolutional neural network model to identify and process these ROI's, along with the challenges of data preparation, training the model, and parameter optimization.

  1. Satellite Monitoring of Ash and Sulphur Dioxide for the mitigation of Aviation Hazards: Part II. Validation of satellite-derived Volcanic Sulphur Dioxide Levels.

    Science.gov (United States)

    Koukouli, MariLiza; Balis, Dimitris; Dimopoulos, Spiros; Clarisse, Lieven; Carboni, Elisa; Hedelt, Pascal; Spinetti, Claudia; Theys, Nicolas; Tampellini, Lucia; Zehner, Claus

    2014-05-01

    The eruption of the Icelandic volcano Eyjafjallajökull in the spring of 2010 turned the attention of both the public and the scientific community to the susceptibility of the European airspace to the outflows of large volcanic eruptions. The ash-rich plume from Eyjafjallajökull drifted towards Europe and caused major disruptions of European air traffic for several weeks affecting the everyday life of millions of people and with a strong economic impact. This unparalleled situation revealed limitations in the decision making process due to the lack of information on the tolerance to ash of commercial aircraft engines as well as limitations in the ash monitoring and prediction capabilities. The European Space Agency project Satellite Monitoring of Ash and Sulphur Dioxide for the mitigation of Aviation Hazards, was introduced to facilitate the development of an optimal End-to-End System for Volcanic Ash Plume Monitoring and Prediction. This system is based on comprehensive satellite-derived ash plume and sulphur dioxide [SO2] level estimates, as well as a widespread validation using supplementary satellite, aircraft and ground-based measurements. The validation of volcanic SO2 levels extracted from the sensors GOME-2/MetopA and IASI/MetopA are shown here with emphasis on the total column observed right before, during and after the Eyjafjallajökull 2010 eruptions. Co-located ground-based Brewer Spectrophotometer data extracted from the World Ozone and Ultraviolet Radiation Data Centre, WOUDC, were compared to the different satellite estimates. The findings are presented at length, alongside a comprehensive discussion of future scenarios.

  2. Earth's dimension specified by geoidal geopotential

    Czech Academy of Sciences Publication Activity Database

    Burša, Milan; Groten, E.; Kenyon, S.; Kouba, J.; Raděj, K.; Vatra, V.; Vojtíšková, M.

    2002-01-01

    Roč. 46, č. 1 (2002), s. 1-8 ISSN 0039-3169 Institutional research plan: CEZ:AV0Z1003909 Keywords : TOPEX/POSEIDON satellite * analyse Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 0.571, year: 2002

  3. Modeling net ecosystem carbon exchange of alpine grasslands with a satellite-driven model.

    Directory of Open Access Journals (Sweden)

    Wei Yan

    Full Text Available Estimate of net ecosystem carbon exchange (NEE between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP and ecosystem respiration (Reco has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model.

  4. Improved Solar-Radiation-Pressure Models for GPS Satellites

    Science.gov (United States)

    Bar-Sever, Yoaz; Kuang, Da

    2006-01-01

    A report describes a series of computational models conceived as an improvement over prior models for determining effects of solar-radiation pressure on orbits of Global Positioning System (GPS) satellites. These models are based on fitting coefficients of Fourier functions of Sun-spacecraft- Earth angles to observed spacecraft orbital motions.

  5. Minimizing Gaps of Daily Ndvi Map with Geostationary Satellite Remote Sensing Data

    Science.gov (United States)

    Lee, S.; Ryu, Y.; Jiang, C.

    2015-12-01

    Satellite based remote sensing has been used to monitor plant phenology. Numerous studies have generally utilized normalized difference vegetation index (NDVI) to quantify phenological patterns and changes in regional to the global scales. Obtaining the NDVI values during summer in East Asian Monsoon regions is important because most plants grow vigorously in this season. However, satellite derived NDVI data are error prone to clouds during most of the period. Various methods have attempted to reduce the effect of cloud in temporal and spatial NDVI monitoring; the fundamental solution is to have a large data pool that includes multiple images in short period and supplements NDVI values in same period. Multiple images of geostationary satellite in a day can be a method to expand the pool. In this study, we suggest an approach that minimizes data gaps in NDVI of the day through geostationary satellite derived NDVI composition. We acquired data from Geostationary Ocean Color Imager (GOCI) which is a satellite that was launched to monitor ocean around the Korean peninsula, China, Japan and Russia. The satellite observes eight times per day (09:00 - 16:00, every hour) at 500 x 500 m resolution from 2011 to 2015. GOCI red- and near infrared radiance was converted into surface reflectance by using 6S Radiative Transfer Model (6S). We calculated NDVI tiles for each of observed eight tiles per day and made one day NDVI through maximum-value composite method. We evaluated the composite GOCI derived NDVI by comparing with daily MODIS-derived NDVI (composited from MOD09GA and MYD09GA), 16-day Landsat 8-derived NDVI, and in-situ light emitting diode (LED) NDVI measurements at a homogeneous deciduous forest and rice paddy sites. We found that GOCI-derived NDVI maps revealed little data gaps compared to MODIS and Landsat, and GOCI derived NDVI time series were smoother than MODIS derived NDVI time series in summer. GOCI-derived NDVI agreed well with in-situ observations of NDVI

  6. Quantifying the decadal changes of PM2.5 over New York through a combination of satellite, model and in-situ measurements

    Science.gov (United States)

    Jin, X.; Fiore, A. M.; Curci, G.; Lyapustin, A.; Wang, Y.; Civerolo, K.; Ku, M.; van Donkelaar, A.; Martin, R.

    2017-12-01

    Ambient exposure to fine particulate matter (PM2.5) is one of the top global health concerns. Efforts have been made to regulate PM2.5 precursor emissions across the U.S.A, which are expected to mitigate the air pollution related health impacts. However, quantifying the health outcomes from emission controls requires robust estimates of PM2.5 exposures that accurately describe the spatial and temporal variability of PM2.5. Satellite remote sensing offers the potential to fill the gaps of the sparse, limited sampling of in situ measurement networks and is increasingly being used in health assessments. We provide new estimates of PM2.5 over New York State with 1 km spatial resolution that use Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD and a regional air quality model (CMAQ) to estimate the AOD-PM2.5 scaling factors. Next, we evaluate three major sources of uncertainties of satellite-derived PM2.5 data and their impacts on the derived decadal changes: 1) satellite retrieval of AOD, 2) optical properties of the particles, 3) relationships between the aerosol burden in the planetary boundary layer and full atmospheric column. Finally, we analyze the decadal changes of PM2.5 over New York State using the newly developed PM2.5 data, alongside four other PM2.5 estimates including satellite-derived PM2.5 developed by van Donkelaar et al. (2015), statistical land use regression developed by Beckerman et al. (2013), CMAQ simulations, and a Bayesian fusion of CMAQ and ground-based measurements. By evaluating the decadal changes of PM2.5 from multiple datasets over areas with dense (e.g. New York City area) and sparse ground-based measurements (e.g. upstate New York), we evaluate the extent to which satellite remote sensing could help better quantify the health outcomes of emission controls. References: Beckerman et al., (2013), A Hybrid Approach to Estimating National Scale Spatiotemporal Variability of PM2.5 in the Contiguous United States, Environ. Sci

  7. Modeling and control of a gravity gradient stabilised satellite

    Directory of Open Access Journals (Sweden)

    Aage Skullestad

    1999-01-01

    Full Text Available This paper describes attitude control, i.e., 3-axes stabilisation and pointing, of a proposed Norwegian small gravity gradient stabilized satellite to be launched into low earth orbit. Generally, a gravity gradient stabilised system has limited stability and pointing capabilities, and wheels and/or magnetic coils are added in order to improve the attitude control. The best attitude accuracy is achieved using wheels, which can give accuracies down to less than one degree, but wheels increase the complexity and cost of the satellite. Magnetic coils allow cheaper satellites, and are an attractive solution to small, inexpensive satellites in low earth orbits and may provide an attitude control accuracy of a few degrees. Scientific measurements often require accurate attitude control in one or two axes only. Combining wheel and coil control may, in these cases, provide the best solutions. The simulation results are based on a linearised mathematical model of the satellite.

  8. Real-Time and Seamless Monitoring of Ground-Level PM2.5 Using Satellite Remote Sensing

    Science.gov (United States)

    Li, Tongwen; Zhang, Chengyue; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei

    2018-04-01

    Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.

  9. A standard library for modeling satellite orbits on a microcomputer

    Science.gov (United States)

    Beutel, Kenneth L.

    1988-03-01

    Introductory students of astrodynamics and the space environment are required to have a fundamental understanding of the kinematic behavior of satellite orbits. This thesis develops a standard library that contains the basic formulas for modeling earth orbiting satellites. This library is used as a basis for implementing a satellite motion simulator that can be used to demonstrate orbital phenomena in the classroom. Surveyed are the equations of orbital elements, coordinate systems and analytic formulas, which are made into a standard method for modeling earth orbiting satellites. The standard library is written in the C programming language and is designed to be highly portable between a variety of computer environments. The simulation draws heavily on the standards established by the library to produce a graphics-based orbit simulation program written for the Apple Macintosh computer. The simulation demonstrates the utility of the standard library functions but, because of its extensive use of the Macintosh user interface, is not portable to other operating systems.

  10. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Palmyra Atoll, Pacific Remote Island Area, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  11. Large-scale dynamics of the stratosphere and mesosphere during the MAP/WINE campaign winter 1983 to 1984 in comparison with other winters

    Science.gov (United States)

    Petzoldt, K.

    1989-04-01

    For the MAP/WINE winter temperature and wind measurements of rockets were combined with SSU radiances (Stratospheric Sounder Unit onboard the NOAA satellites) and stratopause heights from the Solar Mesosphere Explorer (SME) to get a retrieved data set including all available information. By means of this data set a hemispheric geopotential height, temperature and geostrophic wind fields eddy transports for wave mean flow interaction and potential vorticity for the interpretation of nonlinear wave breaking could be computed. Wave reflection at critical lines was investigated with respect of stratospheric warmings. The meridional gradient of the potential vorticity and focusing of wave activity is compared with derived data from satellite observations during other winters.

  12. Particulate matter concentration mapping from MODIS satellite data: a Vietnamese case study

    Science.gov (United States)

    Nguyen, Thanh T. N.; Bui, Hung Q.; Pham, Ha V.; Luu, Hung V.; Man, Chuc D.; Pham, Hai N.; Le, Ha T.; Nguyen, Thuy T.

    2015-09-01

    Particulate Matter (PM) pollution is one of the most important air quality concerns in Vietnam. In this study, we integrate ground-based measurements, meteorological and satellite data to map temporal PM concentrations at a 10 × 10 km grid for the entire of Vietnam. We specifically used MODIS Aqua and Terra data and developed statistically-significant regression models to map and extend the ground-based PM concentrations. We validated our models over diverse geographic provinces i.e., North East, Red River Delta, North Central Coast and South Central Coast in Vietnam. Validation suggested good results for satellite-derived PM2.5 data compared to ground-based PM2.5 (n = 285, r2 = 0.411, RMSE = 20.299 μg m-3 and RE = 39.789%). Further, validation of satellite-derived PM2.5 on two independent datasets for North East and South Central Coast suggested similar results (n = 40, r2 = 0.455, RMSE = 21.512 μg m-3, RE = 45.236% and n = 45, r2 = 0.444, RMSE = 8.551 μg m-3, RE = 46.446% respectively). Also, our satellite-derived PM2.5 maps were able to replicate seasonal and spatial trends of ground-based measurements in four different regions. Our results highlight the potential use of MODIS datasets for PM estimation at a regional scale in Vietnam. However, model limitation in capturing maximal or minimal PM2.5 peaks needs further investigations on ground data, atmospheric conditions and physical aspects.

  13. Modelling patterns of pollinator species richness and diversity using satellite image texture.

    Directory of Open Access Journals (Sweden)

    Sylvia Hofmann

    Full Text Available Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013 from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees. While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

  14. Modelling patterns of pollinator species richness and diversity using satellite image texture.

    Science.gov (United States)

    Hofmann, Sylvia; Everaars, Jeroen; Schweiger, Oliver; Frenzel, Mark; Bannehr, Lutz; Cord, Anna F

    2017-01-01

    Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS) can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013) from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees). While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

  15. Monitoring Cyanobacteria with Satellites Webinar

    Science.gov (United States)

    real-world satellite applications can quantify cyanobacterial harmful algal blooms and related water quality parameters. Provisional satellite derived cyanobacteria data and different software tools are available to state environmental and health agencies.

  16. Hurricane Satellite (HURSAT) Microwave (MW)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Hurricane Satellite (HURSAT) from Microwave (MW) observations of tropical cyclones worldwide data consist of raw satellite observations. The data derive from the...

  17. Derivation of inner magnetospheric electric field (UNH-IMEF model using Cluster data set

    Directory of Open Access Journals (Sweden)

    H. Matsui

    2008-09-01

    Full Text Available We derive an inner magnetospheric electric field (UNH-IMEF model at L=2–10 using primarily Cluster electric field data for more than 5 years between February 2001 and October 2006. This electric field data set is divided into several ranges of the interplanetary electric field (IEF values measured by ACE. As ring current simulations which require electric field as an input parameter are often performed at L=2–6.6, we have included statistical results from ground radars and low altitude satellites inside the perigee of Cluster in our data set (L~4. Electric potential patterns are derived from the average electric fields by solving an inverse problem. The electric potential pattern for small IEF values is probably affected by the ionospheric dynamo. The magnitudes of the electric field increase around the evening local time as IEF increases, presumably due to the sub-auroral polarization stream (SAPS. Another region with enhanced electric fields during large IEF periods is located around 9 MLT at L>8, which is possibly related to solar wind-magnetosphere coupling. Our potential patterns are consistent with those derived from self-consistent simulations. As the potential patterns can be interpolated/extrapolated to any discrete IEF value within measured ranges, we thus derive an empirical electric potential model. The performance of the model is evaluated by comparing the electric field derived from the model with original one measured by Cluster and mapped to the equator. The model is open to the public through our website.

  18. Derivation of inner magnetospheric electric field (UNH-IMEF model using Cluster data set

    Directory of Open Access Journals (Sweden)

    H. Matsui

    2008-09-01

    Full Text Available We derive an inner magnetospheric electric field (UNH-IMEF model at L=2–10 using primarily Cluster electric field data for more than 5 years between February 2001 and October 2006. This electric field data set is divided into several ranges of the interplanetary electric field (IEF values measured by ACE. As ring current simulations which require electric field as an input parameter are often performed at L=2–6.6, we have included statistical results from ground radars and low altitude satellites inside the perigee of Cluster in our data set (L~4. Electric potential patterns are derived from the average electric fields by solving an inverse problem. The electric potential pattern for small IEF values is probably affected by the ionospheric dynamo. The magnitudes of the electric field increase around the evening local time as IEF increases, presumably due to the sub-auroral polarization stream (SAPS. Another region with enhanced electric fields during large IEF periods is located around 9 MLT at L>8, which is possibly related to solar wind-magnetosphere coupling. Our potential patterns are consistent with those derived from self-consistent simulations. As the potential patterns can be interpolated/extrapolated to any discrete IEF value within measured ranges, we thus derive an empirical electric potential model. The performance of the model is evaluated by comparing the electric field derived from the model with original one measured by Cluster and mapped to the equator. The model is open to the public through our website.

  19. The gravity field and GGOS

    DEFF Research Database (Denmark)

    Forsberg, René; Sideris, M.G.; Shum, C.K.

    2005-01-01

    The gravity field of the earth is a natural element of the Global Geodetic Observing System (GGOS). Gravity field quantities are like spatial geodetic observations of potential very high accuracy, with measurements, currently at part-per-billion (ppb) accuracy, but gravity field quantities are also...... unique as they can be globally represented by harmonic functions (long-wavelength geopotential model primarily from satellite gravity field missions), or based on point sampling (airborne and in situ absolute and superconducting gravimetry). From a GGOS global perspective, one of the main challenges...... is to ensure the consistency of the global and regional geopotential and geoid models, and the temporal changes of the gravity field at large spatial scales. The International Gravity Field Service, an umbrella "level-2" IAG service (incorporating the International Gravity Bureau, International Geoid Service...

  20. Comparing satellite SAR and wind farm wake models

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Vincent, P.; Husson, R.

    2015-01-01

    . These extend several tens of kilometres downwind e.g. 70 km. Other SAR wind maps show near-field fine scale details of wake behind rows of turbines. The satellite SAR wind farm wake cases are modelled by different wind farm wake models including the PARK microscale model, the Weather Research and Forecasting...... (WRF) model in high resolution and WRF with coupled microscale parametrization....

  1. Satellite-based Flood Modeling Using TRMM-based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Greg Easson

    2007-12-01

    Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

  2. Application of the Coastal and Marine Ecological Classification Standard (CMECS) Water Column Component (WC) to data derived by the Naval Research Lab (NRL) Automated Processing System (APS) modeling of Moderate Resolution Imaging Spectroradiometer (MODIS) Imagery from the Aqua Earth Orbiting Satellite (EOS) PM in the Northern Gulf of Mexico from 2005-01 to 2009-12 (NODC Accession 0094007)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Satellite-derived data for sea surface temperature, salinity, chlorophyll; euphotic depth; and modeled bottom to surface temperature differences were evaluated to...

  3. Recent variations in geopotential height associated with West African monsoon variability

    Science.gov (United States)

    Okoro, Ugochukwu K.; Chen, Wen; Nath, Debashis

    2018-02-01

    In the present study, the atmospheric circulation patterns associated with the seasonal West Africa (WA) monsoon (WAM) rainfall variability has been investigated. The observational rainfall data from the Climatic Research Unit (CRU) and atmospheric fields from the National Center for Environmental Prediction (NCEP) reanalysis 2, from 1979 to 2014, have been used. The rainfall variability extremes, classified as wet or dry years, are the outcomes of simultaneous 6-month SPI at the three rainfall zones, which shows increasing trends [Guinea Coast (GC = 0.012 year-1), Eastern Sudano Sahel (ESS = 0.045 year-1) and Western Sudano Sahel (WSS = 0.056 year-1) from Sen's slope]; however, it is significant only in the Sahel region (α = 0.05 and α = 0.001 at ESS and WSS, respectively, from Mann-Kendall test). The vertical profile of the geopotential height (GpH) during the wet and dry years reveals that the 700 hPa anomalies show remarkable pattern at about 8°N to 13°N. This shows varying correlation with the zonal averaged vertically integrated moisture flux convergence and rainfall anomalies, respectively, as well as the oceanic pulsations indexes [Ocean Nino Index (ONI) and South Atlantic Ocean dipole index (SAODI), significant from t test], identified as precursors to the Sahel and GC rainfall variability respectively. The role of GpH anomalies at 700 hPa has been identified as the facilitator to the West African Westerly Jet's input to the moisture flux transported over the WA. This is a new perspective of the circulation processes associated with WAM and serves as a basis for modeling investigations.

  4. Impact of Satellite Remote Sensing Data on Simulations of Coastal Circulation and Hypoxia on the Louisiana Continental Shelf

    Directory of Open Access Journals (Sweden)

    Dong S. Ko

    2016-05-01

    Full Text Available We estimated surface salinity flux and solar penetration from satellite data, and performed model simulations to examine the impact of including the satellite estimates on temperature, salinity, and dissolved oxygen distributions on the Louisiana continental shelf (LCS near the annual hypoxic zone. Rainfall data from the Tropical Rainfall Measurement Mission (TRMM were used for the salinity flux, and the diffuse attenuation coefficient (Kd from Moderate Resolution Imaging Spectroradiometer (MODIS were used for solar penetration. Improvements in the model results in comparison with in situ observations occurred when the two types of satellite data were included. Without inclusion of the satellite-derived surface salinity flux, realistic monthly variability in the model salinity fields was observed, but important inter-annual variability was missed. Without inclusion of the satellite-derived light attenuation, model bottom water temperatures were too high nearshore due to excessive penetration of solar irradiance. In general, these salinity and temperature errors led to model stratification that was too weak, and the model failed to capture observed spatial and temporal variability in water-column vertical stratification. Inclusion of the satellite data improved temperature and salinity predictions and the vertical stratification was strengthened, which improved prediction of bottom-water dissolved oxygen. The model-predicted area of bottom-water hypoxia on the Louisiana shelf, an important management metric, was substantially improved in comparison to observed hypoxic area by including the satellite data.

  5. Species distribution models for a migratory bird based on citizen science and satellite tracking data

    Directory of Open Access Journals (Sweden)

    Christopher L. Coxen

    2017-07-01

    Full Text Available Species distribution models can provide critical baseline distribution information for the conservation of poorly understood species. Here, we compared the performance of band-tailed pigeon (Patagioenas fasciata species distribution models created using Maxent and derived from two separate presence-only occurrence data sources in New Mexico: 1 satellite tracked birds and 2 observations reported in eBird basic data set. Both models had good accuracy (test AUC > 0.8 and True Skill Statistic > 0.4, and high overlap between suitability scores (I statistic 0.786 and suitable habitat patches (relative rank 0.639. Our results suggest that, at the state-wide level, eBird occurrence data can effectively model similar species distributions as satellite tracking data. Climate change models for the band-tailed pigeon predict a 35% loss in area of suitable climate by 2070 if CO2 emissions drop to 1990 levels by 2100, and a 45% loss by 2070 if we continue current CO2 emission levels through the end of the century. These numbers may be conservative given the predicted increase in drought, wildfire, and forest pest impacts to the coniferous forests the species inhabits in New Mexico. The northern portion of the species’ range in New Mexico is predicted to be the most viable through time.

  6. Species distribution models for a migratory bird based on citizen science and satellite tracking data

    Science.gov (United States)

    Coxen, Christopher L.; Frey, Jennifer K.; Carleton, Scott A.; Collins, Daniel P.

    2017-01-01

    Species distribution models can provide critical baseline distribution information for the conservation of poorly understood species. Here, we compared the performance of band-tailed pigeon (Patagioenas fasciata) species distribution models created using Maxent and derived from two separate presence-only occurrence data sources in New Mexico: 1) satellite tracked birds and 2) observations reported in eBird basic data set. Both models had good accuracy (test AUC > 0.8 and True Skill Statistic > 0.4), and high overlap between suitability scores (I statistic 0.786) and suitable habitat patches (relative rank 0.639). Our results suggest that, at the state-wide level, eBird occurrence data can effectively model similar species distributions as satellite tracking data. Climate change models for the band-tailed pigeon predict a 35% loss in area of suitable climate by 2070 if CO2 emissions drop to 1990 levels by 2100, and a 45% loss by 2070 if we continue current CO2 emission levels through the end of the century. These numbers may be conservative given the predicted increase in drought, wildfire, and forest pest impacts to the coniferous forests the species inhabits in New Mexico. The northern portion of the species’ range in New Mexico is predicted to be the most viable through time.

  7. Satellite-Based Derivation of High-Resolution Forest Information Layers for Operational Forest Management

    Directory of Open Access Journals (Sweden)

    Johannes Stoffels

    2015-06-01

    Full Text Available A key factor for operational forest management and forest monitoring is the availability of up-to-date spatial information on the state of forest resources. Earth observation can provide valuable contributions to these information needs. The German federal state of Rhineland-Palatinate transferred its inherited forest information system to a new architecture that is better able to serve the needs of centralized inventory and planning services, down to the level of forest districts. During this process, a spatially adaptive classification approach was developed to derive high-resolution forest information layers (e.g., forest type, tree species distribution, development stages based on multi-temporal satellite data. This study covers the application of the developed approach to a regional scale (federal state level and the further adaptation of the design to meet the information needs of the state forest service. The results confirm that the operational requirements for mapping accuracy can, in principle, be fulfilled. However, the state-wide mapping experiment also revealed that the ability to meet the required level of accuracy is largely dependent on the availability of satellite observations within the optimum phenological time-windows.

  8. High spatial resolution radiation budget for Europe: derived from satellite data, validation of a regional model; Raeumlich hochaufgeloeste Strahlungsbilanz ueber Europa: Ableitung aus Satellitendaten, Validation eines regionalen Modells

    Energy Technology Data Exchange (ETDEWEB)

    Hollmann, R. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Atmosphaerenphysik

    2000-07-01

    Since forty years instruments onboard satellites have been demonstrated their usefulness for many applications in the field of meteorology and oceanography. Several experiments, like ERBE, are dedicated to establish a climatology of the global Earth radiation budget at the top of the atmosphere. Now the focus has been changed to the regional scale, e.g. GEWEX with its regional sub-experiments like BALTEX. To obtain a regional radiation budget for Europe in the first part of the work the well calibrated measurements from ScaRaB (scanner for radiation budget) are used to derive a narrow-to-broadband conversion, which is applicable to the AVHRR (advanced very high resolution radiometer). It is shown, that the accuracy of the method is in the order of that from SCaRaB itself. In the second part of the work, results of REMO have been compared with measurements of ScaRaB and AVHRR for March 1994. The model reproduces the measurements overall well, but it is overestimating the cold areas and underestimating the warm areas in the longwave spectral domain. Similarly it is overestimating the dark areas and underestimating the bright areas in the solar spectral domain. (orig.)

  9. Thematic mapping from satellite imagery

    CERN Document Server

    Denègre, J

    2013-01-01

    Thematic Mapping from Satellite Imagery: A Guidebook discusses methods in producing maps using satellite images. The book is comprised of five chapters; each chapter covers one stage of the process. Chapter 1 tackles the satellite remote sensing imaging and its cartographic significance. Chapter 2 discusses the production processes for extracting information from satellite data. The next chapter covers the methods for combining satellite-derived information with that obtained from conventional sources. Chapter 4 deals with design and semiology for cartographic representation, and Chapter 5 pre

  10. A new CM SAF Solar Surface Radiation Climate Data Set derived from Meteosat Satellite Observations

    Science.gov (United States)

    Trentmann, J.; Mueller, R. W.; Pfeifroth, U.; Träger-Chatterjee, C.; Cremer, R.

    2014-12-01

    The incoming surface solar radiation has been defined as an essential climate variable by GCOS. It is mandatory to monitor this part of the earth's energy balance, and thus gain insights on the state and variability of the climate system. In addition, data sets of the surface solar radiation have received increased attention over the recent years as an important source of information for the planning of solar energy applications. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving surface solar radiation from geostationary and polar-orbiting satellite instruments. While CM SAF is focusing on the generation of high-quality long-term climate data records, also operationally data is provided in short time latency within 8 weeks. Here we present SARAH (Solar Surface Radiation Dataset - Heliosat), i.e. the new CM SAF Solar Surface Radiation data set based on Meteosat satellite observations. SARAH provides instantaneous, daily- and monthly-averaged data of the effective cloud albedo (CAL), the direct normalized solar radiation (DNI) and the solar irradiance (SIS) from 1983 to 2013 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05 deg allowing for detailed regional studies, and are available in netcdf-format at no cost without restrictions at www.cmsaf.eu. We provide an overview of the data sets, including a validation against reference measurements from the BSRN and GEBA surface station networks.

  11. Real-Time Estimation of Volcanic ASH/SO2 Cloud Height from Combined Uv/ir Satellite Observations and Numerical Modeling

    Science.gov (United States)

    Vicente, Gilberto A.

    An efficient iterative method has been developed to estimate the vertical profile of SO2 and ash clouds from volcanic eruptions by comparing near real-time satellite observations with numerical modeling outputs. The approach uses UV based SO2 concentration and IR based ash cloud images, the volcanic ash transport model PUFF and wind speed, height and directional information to find the best match between the simulated and the observed displays. The method is computationally fast and is being implemented for operational use at the NOAA Volcanic Ash Advisory Centers (VAACs) in Washington, DC, USA, to support the Federal Aviation Administration (FAA) effort to detect, track and measure volcanic ash cloud heights for air traffic safety and management. The presentation will show the methodology, results, statistical analysis and SO2 and Aerosol Index input products derived from the Ozone Monitoring Instrument (OMI) onboard the NASA EOS/Aura research satellite and from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument in the MetOp-A. The volcanic ash products are derived from AVHRR instruments in the NOAA POES-16, 17, 18, 19 as well as MetOp-A. The presentation will also show how a VAAC volcanic ash analyst interacts with the system providing initial condition inputs such as location and time of the volcanic eruption, followed by the automatic real-time tracking of all the satellite data available, subsequent activation of the iterative approach and the data/product delivery process in numerical and graphical format for operational applications.

  12. Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

    Science.gov (United States)

    Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

    2007-01-01

    Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for

  13. Incorporating GOES Satellite Photosynthetically Active Radiation (PAR) Retrievals to Improve Biogenic Emission Estimates in Texas

    Science.gov (United States)

    Zhang, Rui; White, Andrew T.; Pour Biazar, Arastoo; McNider, Richard T.; Cohan, Daniel S.

    2018-01-01

    This study examines the influence of insolation and cloud retrieval products from the Geostationary Operational Environmental Satellite (GOES) system on biogenic emission estimates and ozone simulations in Texas. Compared to surface pyranometer observations, satellite-retrieved insolation and photosynthetically active radiation (PAR) values tend to systematically correct the overestimation of downwelling shortwave radiation in the Weather Research and Forecasting (WRF) model. The correlation coefficient increases from 0.93 to 0.97, and the normalized mean error decreases from 36% to 21%. The isoprene and monoterpene emissions estimated by the Model of Emissions of Gases and Aerosols from Nature are on average 20% and 5% less, respectively, when PAR from the direct satellite retrieval is used rather than the control WRF run. The reduction in biogenic emission rates using satellite PAR reduced the predicted maximum daily 8 h ozone concentration by up to 5.3 ppbV over the Dallas-Fort Worth (DFW) region on some days. However, episode average ozone response is less sensitive, with a 0.6 ppbV decrease near DFW and 0.3 ppbV increase over East Texas. The systematic overestimation of isoprene concentrations in a WRF control case is partially corrected by using satellite PAR, which observes more clouds than are simulated by WRF. Further, assimilation of GOES-derived cloud fields in WRF improved CAMx model performance for ground-level ozone over Texas. Additionally, it was found that using satellite PAR improved the model's ability to replicate the spatial pattern of satellite-derived formaldehyde columns and aircraft-observed vertical profiles of isoprene.

  14. Algorithm Development and Validation for Satellite-Derived Distributions of DOC and CDOM in the US Middle Atlantic Bight

    Science.gov (United States)

    Mannino, Antonio; Russ, Mary E.; Hooker, Stanford B.

    2007-01-01

    In coastal ocean waters, distributions of dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) vary seasonally and interannually due to multiple source inputs and removal processes. We conducted several oceanographic cruises within the continental margin of the U.S. Middle Atlantic Bight (MAB) to collect field measurements in order to develop algorithms to retrieve CDOM and DOC from NASA's MODIS-Aqua and SeaWiFS satellite sensors. In order to develop empirical algorithms for CDOM and DOC, we correlated the CDOM absorption coefficient (a(sub cdom)) with in situ radiometry (remote sensing reflectance, Rrs, band ratios) and then correlated DOC to Rrs band ratios through the CDOM to DOC relationships. Our validation analyses demonstrate successful retrieval of DOC and CDOM from coastal ocean waters using the MODIS-Aqua and SeaWiFS satellite sensors with mean absolute percent differences from field measurements of cdom)(355)1,6 % for a(sub cdom)(443), and 12% for the CDOM spectral slope. To our knowledge, the algorithms presented here represent the first validated algorithms for satellite retrieval of a(sub cdom) DOC, and CDOM spectral slope in the coastal ocean. The satellite-derived DOC and a(sub cdom) products demonstrate the seasonal net ecosystem production of DOC and photooxidation of CDOM from spring to fall. With accurate satellite retrievals of CDOM and DOC, we will be able to apply satellite observations to investigate interannual and decadal-scale variability in surface CDOM and DOC within continental margins and monitor impacts of climate change and anthropogenic activities on coastal ecosystems.

  15. Warm Inflation with Nonminimal Derivative Coupling

    International Nuclear Information System (INIS)

    Rashidi, N.; Nozari, Kourosh; Shoukrani, M.

    2014-01-01

    We study the effects of the nonminimal derivative coupling on the dissipative dynamics of the warm inflation where the scalar field is nonminimally coupled to gravity via its kinetic term. We present a detailed calculation of the cosmological perturbations in this setup. We use the recent observational data from the joint data set of WMAP9 + BAO + H 0 and also the Planck satellite data to constrain our model parameters for natural and chaotic inflation potentials. We study also the levels of non-Gaussianity in this warm inflation model and we confront the result with recent observational data from the Planck satellite

  16. Urban thermal environment and its biophysical parameters derived from satellite remote sensing imagery

    Science.gov (United States)

    Zoran, Maria A.; Savastru, Roxana S.; Savastru, Dan M.; Tautan, Marina N.; Baschir, Laurentiu V.

    2013-10-01

    In frame of global warming, the field of urbanization and urban thermal environment are important issues among scientists all over the world. This paper investigated the influences of urbanization on urban thermal environment as well as the relationships of thermal characteristics to other biophysical variables in Bucharest metropolitan area of Romania based on satellite remote sensing imagery Landsat TM/ETM+, time series MODIS Terra/Aqua data and IKONOS acquired during 1990 - 2012 period. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also retrieved from thermal infrared band of Landsat TM/ETM+, from MODIS Terra/Aqua datasets. Based on these parameters, the urban growth, urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. Results indicated that the metropolitan area ratio of impervious surface in Bucharest increased significantly during two decades investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

  17. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Sarigan Island, Territory of Mariana, USA.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  18. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Rota Island, Territory of Mariana, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  19. An estimation model of population in China using time series DMSP night-time satellite imagery from 2002-2010

    Science.gov (United States)

    Zhang, Xiaoyong; Zhang, Zhijie; Chang, Yuguang; Chen, Zhengchao

    2015-12-01

    Accurate data on the spatial distribution and potential growth estimation of human population are playing pivotal role in addressing and mitigating heavy lose caused by earthquake. Traditional demographic data is limited in its spatial resolution and is extremely hard to update. With the accessibility of massive DMSP/OLS night time imagery, it is possible to model population distribution at the county level across China. In order to compare and improve the continuity and consistency of time-series DMSP night-time satellite imagery obtained by different satellites in same year or different years by the same satellite from 2002-2010, normalized method was deployed for the inter-correction among imageries. And we referred to the reference F162007 Jixi city, whose social-economic has been relatively stable. Through binomial model, with average R2 0.90, then derived the correction factor of each year. The normalization obviously improved consistency comparing to previous data, which enhanced the correspondent accuracy of model. Then conducted the model of population density between average night-time light intensity in eight-economic districts. According to the two parameters variation law of consecutive years, established the prediction model of next following years with R2of slope and constant typically 0.85 to 0.95 in different regions. To validate the model, taking the year of 2005 as example, retrieved quantitatively population distribution in per square kilometer based on the model, then compared the results to the statistical data based on census, the difference of the result is acceptable. In summary, the estimation model facilitates the quick estimation and prediction in relieving the damage to people, which is significant in decision-making.

  20. Formation of Ice Giant Satellites During Thommes Model Mirgration

    Science.gov (United States)

    Fuse, Christopher; Spiegelberg, Josephine

    2018-01-01

    Inconsistencies between ice giant planet characteristics and classic planet formation theories have led to a re-evaluation of the formation of the outer Solar system. Thommes model migration delivers proto-Uranus and Neptune from orbits interior to Saturn to their current locations. The Thommes model has also been able to reproduce the large Galilean and Saturnian moons via interactions between the proto-ice giants and the gas giant moon disks.As part of a series of investigations examining the effects of Thommes model migration on the formation of moons, N-body simulations of the formation of the Uranian and Neptunian satellite systems were performed. Previous research has yielded conflicting results as to whether satellite systems are stable during planetary migration. Some studies, such as Beaugé (2002) concluded that the system was not stable over the proposed duration of migration. Conversely, Fuse and Neville (2011) and Yokoyama et al. (2011) found that moons were retained, though the nature of the resulting system was heavily influenced by interactions with planetesimals and other large objects. The results of the current study indicate that in situ simulations of the Uranus and Neptune systems can produce stable moons. Whether with current orbital parameters or located at pre-migration, inner Solar system semi-major axes, the simulations end with 5.8 ± 0.15 or 5.9 ± 0.7 regular satellites around Uranus and Neptune, respectively. Preliminary simulations of a proto-moon disk around a single planet migrating via the Thommes model have failed to retain moons. Furthermore, simulations of ejection of the current Uranian satellite system retained at most one moon. Thus, for the Thommes model to be valid, it is likely that moon formation did not begin until after migration ended. Future work will examine the formation of gas and ice giant moons through other migration theories, such as the Nice model (Tsiganis et al. 2006).

  1. A Satellite-Based Surface Radiation Climatology Derived by Combining Climate Data Records and Near-Real-Time Data

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-09-01

    Full Text Available This study presents a method for adjusting long-term climate data records (CDRs for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS. Recently, a 23-year long (1983–2005 continuous SIS CDR has been generated based on the visible channel (0.45–1 μm of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF. Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005 and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present was applied that combines the Standard Normal Homogeneity Test (SNHT and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN and about 50 stations of the Global Energy Balance Archive (GEBA over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of

  2. Millimeter wave propagation modeling of inhomogeneous rain media for satellite communications systems

    Science.gov (United States)

    Persinger, R. R.; Stutzman, W. L.

    1978-01-01

    A theoretical propagation model that represents the scattering properties of an inhomogeneous rain often found on a satellite communications link is presented. The model includes the scattering effects of an arbitrary distribution of particle type (rain or ice), particle shape, particle size, and particle orientation within a given rain cell. An associated rain propagation prediction program predicts attenuation, isolation and phase shift as a function of ground rain rate. A frequency independent synthetic storm algorithm is presented that models nonuniform rain rates present on a satellite link. Antenna effects are included along with a discussion of rain reciprocity. The model is verified using the latest available multiple frequency data from the CTS and COMSTAR satellites. The data covers a wide range of frequencies, elevation angles, and ground site locations.

  3. Mosaic of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of the Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  4. Assessment of the most recent satellite based digital elevation models of Egypt

    Science.gov (United States)

    Rabah, Mostafa; El-Hattab, Ahmed; Abdallah, Mohamed

    2017-12-01

    Digital Elevation Model (DEM) is crucial to a wide range of surveying and civil engineering applications worldwide. Some of the DEMs such as ASTER, SRTM1 and SRTM3 are freely available open source products. In order to evaluate the three DEMs, the contribution of EGM96 are removed and all DEMs heights are becoming ellipsoidal height. This step was done to avoid the errors occurred due to EGM96. 601 points of observed ellipsoidal heights compared with the three DEMs, the results show that the SRTM1 is the most accurate one, that produces mean height difference and standard deviations equal 2.89 and ±8.65 m respectively. In order to increase the accuracy of SRTM1 in EGYPT, a precise Global Geopotential Model (GGM) is needed to convert the SRTM1 ellipsoidal height to orthometric height, so that, we quantify the precision of most-recent released GGM (five models). The results show that, the GECO model is the best fit global models over Egypt, which produces a standard deviation of geoid undulation differences equals ±0.42 m over observed 17 HARN GPS/leveling stations. To confirm an enhanced DEM in EGYPT, the two orthometric height models (SRTM1 ellipsoidal height + EGM96) and (SRTM1 ellipsoidal height + GECO) are assessment with 17 GPS/leveling stations and 112 orthometric height stations, the results show that the estimated height differences between the SRTM1 before improvements and the enhanced model are at rate of 0.44 m and 0.06 m respectively.

  5. Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

    Science.gov (United States)

    Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

    2012-12-01

    Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent

  6. Satellite Dynamics and Control in a Quaternion Formulation (2nd edition)

    DEFF Research Database (Denmark)

    Blanke, Mogens; Larsen, Martin Birkelund

    to represent rotation. A general linearised model is derived such that the user can specify an arbitrary point of operation in angular velocity and wheel angular momentum, specifying the a inertia matrix for a rigid satellite. A set of Simulink® models that simulate the satellite’s nonlinear behaviour...

  7. Oceanic geoid and tides derived from GEOS 3 satellite data in the Northwestern Atlantic Ocean

    Science.gov (United States)

    Won, I. J.; Miller, L. S.

    1979-01-01

    Two sets of GEOS 3 altimeter data which fall within about a 2.5-deg width are analyzed for ocean geoid and tides. One set covers a path from Newfoundland to Cuba, and the other a path from Puerto Rico to the North Carolina coast. Forty different analyses using various parameters are performed in order to investigate convergence. Profiles of the geoid and four tides, M2, O1, S2, and K1, are derived along the two strips. While the analyses produced convergent solutions for all 40 cases, the uncertainty caused by the linear orbital bias error of the satellite is too large to claim that the solutions represent the true ocean tides in the area. A spot check of the result with the Mode deep-sea tide gauge data shows poor agreement. A positive conclusion of this study is that despite the uncertain orbital error the oceanic geoid obtained through this analysis can improve significantly the short-wavelength structure over existing spherical harmonic geoid models.

  8. Satellite-Based Sunshine Duration for Europe

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-06-01

    Full Text Available In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG SEVIRI (Spinning Enhanced Visible and Infrared Imager. The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.

  9. Preliminary hard and soft bottom seafloor substrate map derived from an supervised classification of bathymetry derived from multispectral World View-2 satellite imagery of Ni'ihau Island, Territory of Main Hawaiian Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary hard and soft seafloor substrate map derived from a supervised classification from multispectral World View-2 satellite imagery of Ni'ihau Island,...

  10. Satellite Derived Water Quality Observations Are Related to River Discharge and Nitrogen Loads in Pensacola Bay, Florida

    OpenAIRE

    John C. Lehrter; John C. Lehrter; Chengfeng Le

    2017-01-01

    Relationships between satellite-derived water quality variables and river discharges, concentrations and loads of nutrients, organic carbon, and sediments were investigated over a 9-year period (2003–2011) in Pensacola Bay, Florida, USA. These analyses were conducted to better understand which river forcing factors were the primary drivers of estuarine variability in several water quality variables. Remote sensing reflectance time-series data were retrieved from the MEdium Resolution Imaging ...

  11. Assessing performance of Bayesian state-space models fit to Argos satellite telemetry locations processed with Kalman filtering.

    Directory of Open Access Journals (Sweden)

    Mónica A Silva

    Full Text Available Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF. The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km was nearly half that of LS estimates (11.6 ± 8.4 km. Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.

  12. Assessing the Impact of Earth Radiation Pressure Acceleration on Low-Earth Orbit Satellites

    Science.gov (United States)

    Vielberg, Kristin; Forootan, Ehsan; Lück, Christina; Kusche, Jürgen; Börger, Klaus

    2017-04-01

    The orbits of satellites are influenced by several external forces. The main non-gravitational forces besides thermospheric drag, acting on the surface of satellites, are accelerations due to the Earth and Solar Radiation Pres- sure (SRP and ERP, respectively). The sun radiates visible and infrared light reaching the satellite directly, which causes the SRP. Earth also emits and reflects the sunlight back into space, where it acts on satellites. This is known as ERP acceleration. The influence of ERP increases with decreasing distance to the Earth, and for low-earth orbit (LEO) satellites ERP must be taken into account in orbit and gravity computations. Estimating acceler- ations requires knowledge about energy emitted from the Earth, which can be derived from satellite remote sensing data, and also by considering the shape and surface material of a satellite. In this sensitivity study, we assess ERP accelerations based on different input albedo and emission fields and their modelling for the satellite missions Challenging Mini-Satellite Payload (CHAMP) and Gravity Recovery and Climate Experiment (GRACE). As input fields, monthly 1°x1° products of Clouds and the Earth's Radiant En- ergy System (CERES), L3 are considered. Albedo and emission models are generated as latitude-dependent, as well as in terms of spherical harmonics. The impact of different albedo and emission models as well as the macro model and the altitude of satellites on ERP accelerations will be discussed.

  13. Heterogeneous benefits of precision nitrogen management over the Midwestern US: evidence from 1,000 fields derived by satellite imagery and crop modeling

    Science.gov (United States)

    Jin, Z.; Archontoulis, S.; Lobell, D. B.

    2017-12-01

    The wise management of nitrogen (N) fertilizer is important for both economic and environmental considerations. The variable rate technology (VRT) that applies different rates of N fertilizer by fully taking account of the spatial heterogeneity within fields has gained popularity with the recent advent of high-resolution satellites and spectrometers, but its profitability is still uncertain given the dependence of corn-nitrogen responses to soil and climate. To our knowledge, the benefits of adopting VRT in the vast Midwestern US agricultural zones have only been assessed at a very limited number of fields based on labor-costing on-farm samplings. Here we present a study that integrates a range of geospatial tools and data to quantifying the economic benefit of VRT versus uniform N application over 1,000 randomly selected corn fields in the US Midwest. We employed the Google Earth Engine (GEE) and Landsat-5, 7 and 8 collections to derive 30m-resolution yield map for years 2007-2015, and used the multi-year averaged yields to characterize the yield variation and hence the management zones for each field and zone-specific yield goal. The yield goals as well as the Soil Survey Geographic Database (SSURGO) data were then used to calibrate the Agricultural Production Systems sIMulator (APSIM) model, which generated a range of variables such as yields, N balance and leaching. Our preliminary results showed that the calibrated APSIM model was able to capture about 60% of the variation in the satellite-based yield estimates, and more than 70% of the yield spread (i.e. maximum - minimum yield). Regardless of the overall environmental benefits of less N loss through leaching, the economic difference between adopting VRT and uniform application ranged from -50 to 200 per acre, with the majority lay between -10 and 40 per acre. Fields with a wider range of yield spread benefited more from adopting VRT, yet the conclusion varies upon weather, especially the precipitation. Our

  14. A practical approach for deriving all-weather soil moisture content using combined satellite and meteorological data

    Science.gov (United States)

    Leng, Pei; Li, Zhao-Liang; Duan, Si-Bo; Gao, Mao-Fang; Huo, Hong-Yuan

    2017-09-01

    Soil moisture has long been recognized as one of the essential variables in the water cycle and energy budget between Earth's surface and atmosphere. The present study develops a practical approach for deriving all-weather soil moisture using combined satellite images and gridded meteorological products. In this approach, soil moisture over the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky pixels are estimated from the Vegetation Index/Temperature (VIT) trapezoid scheme in which theoretical dry and wet edges were determined pixel to pixel by China Meteorological Administration Land Data Assimilation System (CLDAS) meteorological products, including air temperature, solar radiation, wind speed and specific humidity. For cloudy pixels, soil moisture values are derived by the calculation of surface and aerodynamic resistances from wind speed. The approach is capable of filling the soil moisture gaps over remaining cloudy pixels by traditional optical/thermal infrared methods, allowing for a spatially complete soil moisture map over large areas. Evaluation over agricultural fields indicates that the proposed approach can produce an overall generally reasonable distribution of all-weather soil moisture. An acceptable accuracy between the estimated all-weather soil moisture and in-situ measurements at different depths could be found with an Root Mean Square Error (RMSE) varying from 0.067 m3/m3 to 0.079 m3/m3 and a slight bias ranging from 0.004 m3/m3 to -0.011 m3/m3. The proposed approach reveals significant potential to derive all-weather soil moisture using currently available satellite images and meteorological products at a regional or global scale in future developments.

  15. Advanced Satellite-Derived Wind Observations, Assimilation, and Targeting Strategies during TCS-08 for Developing Improved Operational Analysis and Prediction of Western Pacific Tropical Cyclones

    Science.gov (United States)

    2013-09-30

    TC structure evolve up to landfall or extratropical transition. In particular, winds derived from geostationary satellites have been shown to be an... extratropical transition, it is clear that a dedicated research effort is needed to optimize the satellite data processing strategies, assimilation, and...applications to better understand the behavior of the near- storm environmental flow fields during these evolutionary TC stages. To our knowledge, this

  16. Combining Satellite and in Situ Data with Models to Support Climate Data Records in Ocean Biology

    Science.gov (United States)

    Gregg, Watson

    2011-01-01

    The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected

  17. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multipectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  18. Phase Error Modeling and Its Impact on Precise Orbit Determination of GRACE Satellites

    Directory of Open Access Journals (Sweden)

    Jia Tu

    2012-01-01

    Full Text Available Limiting factors for the precise orbit determination (POD of low-earth orbit (LEO satellite using dual-frequency GPS are nowadays mainly encountered with the in-flight phase error modeling. The phase error is modeled as a systematic and a random component each depending on the direction of GPS signal reception. The systematic part and standard deviation of random part in phase error model are, respectively, estimated by bin-wise mean and standard deviation values of phase postfit residuals computed by orbit determination. By removing the systematic component and adjusting the weight of phase observation data according to standard deviation of random component, the orbit can be further improved by POD approach. The GRACE data of 1–31 January 2006 are processed, and three types of orbit solutions, POD without phase error model correction, POD with mean value correction of phase error model, and POD with phase error model correction, are obtained. The three-dimensional (3D orbit improvements derived from phase error model correction are 0.0153 m for GRACE A and 0.0131 m for GRACE B, and the 3D influences arisen from random part of phase error model are 0.0068 m and 0.0075 m for GRACE A and GRACE B, respectively. Thus the random part of phase error model cannot be neglected for POD. It is also demonstrated by phase postfit residual analysis, orbit comparison with JPL precise science orbit, and orbit validation with KBR data that the results derived from POD with phase error model correction are better than another two types of orbit solutions generated in this paper.

  19. Online Assessment of Satellite-Derived Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Teng, W.; Kempler, S.

    2012-01-01

    Precipitation is difficult to measure and predict. Each year droughts and floods cause severe property damages and human casualties around the world. Accurate measurement and forecast are important for mitigation and preparedness efforts. Significant progress has been made over the past decade in satellite precipitation product development. In particular, products' spatial and temporal resolutions as well as timely availability have been improved by blended techniques. Their resulting products are widely used in various research and applications. However biases and uncertainties are common among precipitation products and an obstacle exists in quickly gaining knowledge of product quality, biases and behavior at a local or regional scale, namely user defined areas or points of interest. Current online inter-comparison and validation services have not addressed this issue adequately. To address this issue, we have developed a prototype to inter-compare satellite derived daily products in the TRMM Online Visualization and Analysis System (TOVAS). Despite its limited functionality and datasets, users can use this tool to generate customized plots within the United States for 2005. In addition, users can download customized data for further analysis, e.g. comparing their gauge data. To meet increasing demands, we plan to increase the temporal coverage and expanded the spatial coverage from the United States to the globe. More products have been added as well. In this poster, we present two new tools: Inter-comparison of 3B42RT and 3B42 Inter-comparison of V6 and V7 TRMM L-3 monthly products The future plans include integrating IPWG (International Precipitation Working Group) Validation Algorithms/statistics, allowing users to generate customized plots and data. In addition, we will expand the current daily products to monthly and their climatology products. Whenever the TRMM science team changes their product version number, users would like to know the differences by

  20. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean - New constraints from high-resolution satellite-derived gravity data

    Science.gov (United States)

    Sreejith, K. M.; Chaubey, A. K.; Mishra, Akhil; Kumar, Shravan; Rajawat, A. S.

    2016-12-01

    Marine gravity data derived from satellite altimeters are effective tools in mapping fine-scale tectonic features of the ocean basins such as pseudofaults, fracture zones and seamounts, particularly when the ocean basins are carpeted with thick sediments. We use high-resolution satellite-generated gravity and seismic reflection data to map boundaries of pseudofaults and transferred crust related to the Paleocene spreading ridge propagation in the Arabian and its conjugate Eastern Somali basins. The study has provided refinement in the position of previously reported pseudofaults and their spatial extensions in the conjugate basins. It is observed that the transferred crustal block bounded by inner pseudofault and failed spreading ridge is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned along NE-SW direction forming ∼300 km long seamount chain. Admittance analysis and Flexural model studies indicated that the seamount chain is isostatically compensated locally with Effective Elastic Thickness (Te) of 3-4 km. Based on the present results and published plate tectonic models, we interpret that the seamounts in the Arabian Basin are formed by spreading ridge propagation and are associated with pseudofaults, whereas the seamount chain in the Eastern Somali Basin might have probably originated due to melting and upwelling of upper mantle heterogeneities in advance of migrating/propagating paleo Carlsberg Ridge.

  1. Particulate matter concentration mapping from MODIS satellite data: a Vietnamese case study

    International Nuclear Information System (INIS)

    Nguyen, Thanh T N; Bui, Hung Q; Pham, Ha V; Luu, Hung V; Man, Chuc D; Pham, Hai N; Le, Ha T; Nguyen, Thuy T

    2015-01-01

    Particulate Matter (PM) pollution is one of the most important air quality concerns in Vietnam. In this study, we integrate ground-based measurements, meteorological and satellite data to map temporal PM concentrations at a 10 × 10 km grid for the entire of Vietnam. We specifically used MODIS Aqua and Terra data and developed statistically-significant regression models to map and extend the ground-based PM concentrations. We validated our models over diverse geographic provinces i.e., North East, Red River Delta, North Central Coast and South Central Coast in Vietnam. Validation suggested good results for satellite-derived PM 2.5 data compared to ground-based PM 2.5 (n = 285, r 2  = 0.411, RMSE = 20.299 μg m −3 and RE = 39.789%). Further, validation of satellite-derived PM 2.5 on two independent datasets for North East and South Central Coast suggested similar results (n = 40, r 2  = 0.455, RMSE = 21.512 μg m −3 , RE = 45.236% and n = 45, r 2  = 0.444, RMSE = 8.551 μg m −3 , RE = 46.446% respectively). Also, our satellite-derived PM 2.5 maps were able to replicate seasonal and spatial trends of ground-based measurements in four different regions. Our results highlight the potential use of MODIS datasets for PM estimation at a regional scale in Vietnam. However, model limitation in capturing maximal or minimal PM 2.5 peaks needs further investigations on ground data, atmospheric conditions and physical aspects. (letter)

  2. MODELING AND SIMULATION OF HIGH RESOLUTION OPTICAL REMOTE SENSING SATELLITE GEOMETRIC CHAIN

    Directory of Open Access Journals (Sweden)

    Z. Xia

    2018-04-01

    Full Text Available The high resolution satellite with the longer focal length and the larger aperture has been widely used in georeferencing of the observed scene in recent years. The consistent end to end model of high resolution remote sensing satellite geometric chain is presented, which consists of the scene, the three line array camera, the platform including attitude and position information, the time system and the processing algorithm. The integrated design of the camera and the star tracker is considered and the simulation method of the geolocation accuracy is put forward by introduce the new index of the angle between the camera and the star tracker. The model is validated by the geolocation accuracy simulation according to the test method of the ZY-3 satellite imagery rigorously. The simulation results show that the geolocation accuracy is within 25m, which is highly consistent with the test results. The geolocation accuracy can be improved about 7 m by the integrated design. The model combined with the simulation method is applicable to the geolocation accuracy estimate before the satellite launching.

  3. A new digital elevation model of Antarctica derived from CryoSat-2 altimetry

    Science.gov (United States)

    Slater, Thomas; Shepherd, Andrew; McMillan, Malcolm; Muir, Alan; Gilbert, Lin; Hogg, Anna E.; Konrad, Hannes; Parrinello, Tommaso

    2018-05-01

    We present a new digital elevation model (DEM) of the Antarctic ice sheet and ice shelves based on 2.5 × 108 observations recorded by the CryoSat-2 satellite radar altimeter between July 2010 and July 2016. The DEM is formed from spatio-temporal fits to elevation measurements accumulated within 1, 2, and 5 km grid cells, and is posted at the modal resolution of 1 km. Altogether, 94 % of the grounded ice sheet and 98 % of the floating ice shelves are observed, and the remaining grid cells north of 88° S are interpolated using ordinary kriging. The median and root mean square difference between the DEM and 2.3 × 107 airborne laser altimeter measurements acquired during NASA Operation IceBridge campaigns are -0.30 and 13.50 m, respectively. The DEM uncertainty rises in regions of high slope, especially where elevation measurements were acquired in low-resolution mode; taking this into account, we estimate the average accuracy to be 9.5 m - a value that is comparable to or better than that of other models derived from satellite radar and laser altimetry.

  4. Interim Service ISDN Satellite (ISIS) simulator development for advanced satellite designs and experiments

    Science.gov (United States)

    Pepin, Gerard R.

    1992-01-01

    The simulation development associated with the network models of both the Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) and the Full Service ISDN Satellite (FSIS) architectures is documented. The ISIS Network Model design represents satellite systems like the Advanced Communications Technology Satellite (ACTS) orbiting switch. The FSIS architecture, the ultimate aim of this element of the Satellite Communications Applications Research (SCAR) Program, moves all control and switching functions on-board the next generation ISDN communications satellite. The technical and operational parameters for the advanced ISDN communications satellite design will be obtained from the simulation of ISIS and FSIS engineering software models for their major subsystems. Discrete event simulation experiments will be performed with these models using various traffic scenarios, design parameters, and operational procedures. The data from these simulations will be used to determine the engineering parameters for the advanced ISDN communications satellite.

  5. a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

    Science.gov (United States)

    Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

    2018-04-01

    Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.

  6. Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

    Science.gov (United States)

    Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

    2017-04-01

    In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a

  7. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed...... by the sensor. This is further complicated by temperature differences between the sunlit and shaded parts of each of the components, controlled by the exposure of the components to direct sunlight. As the SEVIRI sensor is onboard a geostationary platform, the viewing geometry is fixed (for each pixel), while...

  8. Satellite Derived Water Quality Observations Are Related to River Discharge and Nitrogen Loads in Pensacola Bay, Florida

    Directory of Open Access Journals (Sweden)

    John C. Lehrter

    2017-09-01

    Full Text Available Relationships between satellite-derived water quality variables and river discharges, concentrations and loads of nutrients, organic carbon, and sediments were investigated over a 9-year period (2003–2011 in Pensacola Bay, Florida, USA. These analyses were conducted to better understand which river forcing factors were the primary drivers of estuarine variability in several water quality variables. Remote sensing reflectance time-series data were retrieved from the MEdium Resolution Imaging Spectrometer (MERIS and used to calculate monthly and annual estuarine time-series of chlorophyll a (Chla, colored dissolved organic matter (CDOM, and total suspended sediments (TSS. Monthly MERIS Chla varied from 2.0 mg m−3 in the lower region of the bay to 17.2 mg m−3 in the upper bay. MERIS CDOM and TSS exhibited similar patterns with ranges of 0.51–2.67 (m−1 and 0.11–8.9 (g m−3. Variations in the MERIS-derived monthly and annual Chla, CDOM, and TSS time-series were significantly related to monthly and annual river discharge and loads of nitrogen, organic carbon, and suspended sediments from the Escambia and Yellow rivers. Multiple regression models based on river loads (independent variables and MERIS Chla, CDOM, or TSS (dependent variables explained significant fractions of the variability (up to 62% at monthly and annual scales. The most significant independent variables in the regressions were river nitrogen loads, which were associated with increased MERIS Chla, CDOM, and TSS concentrations, and river suspended sediment loads, which were associated with decreased concentrations. In contrast, MERIS water quality variations were not significantly related to river total phosphorus loads. The spatially synoptic, nine-year satellite record expanded upon the spatial extent of past field studies to reveal previously unseen system-wide responses to river discharge and loading variation. The results indicated that variations in Pensacola Bay Chla

  9. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek; De, Swarup; Bowman, Kenneth P.; Sang, Huiyan; Genton, Marc G.; Mallick, Bani K.

    2015-01-01

    South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision

  10. Sciences of geodesy II innovations and future developments

    CERN Document Server

    Xu, Guochang

    2014-01-01

    This series of reference books describes the sciences of different fields in and around geodesy. Each chapter, is written by experts in the respective fields and covers an individual field and describes the history, theory, the objective, the technology, and the development, the highlight of the research, the applications, the problems, as well as future directions. Contents of Volume II include: Geodetic LEO Satellite Missions, Satellite Altimetry, Airborne Lidar, GNSS Software Receiver, Geodetic Boundary Problem, GPS and INS, VLBI, Geodetic Reference Systems, Spectral Analysis, Earth Tide and Ocean Loading Tide, Remote Sensing, Photogrammetry, Occultation, Geopotential Determination, Geoid Determination, Local Gravity Field, Geopotential Determination, Magnet Field, Mobile Mapping, General Relativity, Wide-area Precise Positioning etc.

  11. Statistical variability comparison in MODIS and AERONET derived aerosol optical depth over Indo-Gangetic Plains using time series modeling.

    Science.gov (United States)

    Soni, Kirti; Parmar, Kulwinder Singh; Kapoor, Sangeeta; Kumar, Nishant

    2016-05-15

    A lot of studies in the literature of Aerosol Optical Depth (AOD) done by using Moderate Resolution Imaging Spectroradiometer (MODIS) derived data, but the accuracy of satellite data in comparison to ground data derived from ARrosol Robotic NETwork (AERONET) has been always questionable. So to overcome from this situation, comparative study of a comprehensive ground based and satellite data for the period of 2001-2012 is modeled. The time series model is used for the accurate prediction of AOD and statistical variability is compared to assess the performance of the model in both cases. Root mean square error (RMSE), mean absolute percentage error (MAPE), stationary R-squared, R-squared, maximum absolute percentage error (MAPE), normalized Bayesian information criterion (NBIC) and Ljung-Box methods are used to check the applicability and validity of the developed ARIMA models revealing significant precision in the model performance. It was found that, it is possible to predict the AOD by statistical modeling using time series obtained from past data of MODIS and AERONET as input data. Moreover, the result shows that MODIS data can be formed from AERONET data by adding 0.251627 ± 0.133589 and vice-versa by subtracting. From the forecast available for AODs for the next four years (2013-2017) by using the developed ARIMA model, it is concluded that the forecasted ground AOD has increased trend. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Post-processing scheme for modelling the lithospheric magnetic field

    Directory of Open Access Journals (Sweden)

    V. Lesur

    2013-03-01

    Full Text Available We investigated how the noise in satellite magnetic data affects magnetic lithospheric field models derived from these data in the special case where this noise is correlated along satellite orbit tracks. For this we describe the satellite data noise as a perturbation magnetic field scaled independently for each orbit, where the scaling factor is a random variable, normally distributed with zero mean. Under this assumption, we have been able to derive a model for errors in lithospheric models generated by the correlated satellite data noise. Unless the perturbation field is known, estimating the noise in the lithospheric field model is a non-linear inverse problem. We therefore proposed an iterative post-processing technique to estimate both the lithospheric field model and its associated noise model. The technique has been successfully applied to derive a lithospheric field model from CHAMP satellite data up to spherical harmonic degree 120. The model is in agreement with other existing models. The technique can, in principle, be extended to all sorts of potential field data with "along-track" correlated errors.

  13. Evaluation of Modeling NO2 Concentrations Driven by Satellite-Derived and Bottom-Up Emission Inventories Using In-Situ Measurements Over China

    Science.gov (United States)

    Liu, Fei; van der A, Ronald J.; Eskes, Henk; Ding, Jieying; Mijling, Bas

    2018-01-01

    Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slopeD0.74 and 0.64 for the daily mean and daytime only) and the MIX (slopeD1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40% higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0% on average and more firmly establishes that the MIX inventory is biased high over major cities. The performance of

  14. Evaluation of modeling NO2 concentrations driven by satellite-derived and bottom-up emission inventories using in situ measurements over China

    Science.gov (United States)

    Liu, Fei; van der A, Ronald J.; Eskes, Henk; Ding, Jieying; Mijling, Bas

    2018-03-01

    Chemical transport models together with emission inventories are widely used to simulate NO2 concentrations over China, but validation of the simulations with in situ measurements has been extremely limited. Here we use ground measurements obtained from the air quality monitoring network recently developed by the Ministry of Environmental Protection of China to validate modeling surface NO2 concentrations from the CHIMERE regional chemical transport model driven by the satellite-derived DECSO and the bottom-up MIX emission inventories. We applied a correction factor to the observations to account for the interferences of other oxidized nitrogen compounds (NOz), based on the modeled ratio of NO2 to NOz. The model accurately reproduces the spatial variability in NO2 from in situ measurements, with a spatial correlation coefficient of over 0.7 for simulations based on both inventories. A negative and positive bias is found for the simulation with the DECSO (slope = 0.74 and 0.64 for the daily mean and daytime only) and the MIX (slope = 1.3 and 1.1) inventories, respectively, suggesting an underestimation and overestimation of NOx emissions from corresponding inventories. The bias between observed and modeled concentrations is reduced, with the slope dropping from 1.3 to 1.0 when the spatial distribution of NOx emissions in the DECSO inventory is applied as the spatial proxy for the MIX inventory, which suggests an improvement of the distribution of emissions between urban and suburban or rural areas in the DECSO inventory compared to that used in the bottom-up inventory. A rough estimate indicates that the observed concentrations, from sites predominantly placed in the populated urban areas, may be 10-40 % higher than the corresponding model grid cell mean. This reduces the estimate of the negative bias of the DECSO-based simulation to the range of -30 to 0 % on average and more firmly establishes that the MIX inventory is biased high over major cities. The

  15. Some European capabilities in satellite cinema exhibition

    Science.gov (United States)

    Bock, Wolfgang

    1990-08-01

    The likely performance envelope and architecture for satellite cinema systems are derived from simple practical assumptions. A case is made for possible transatlantic cooperation towards establishing a satellite cinema standard.

  16. A Regional-Scale Assessment of Satellite Derived Precipitable Water Vapor Across The Amazon Basin

    Science.gov (United States)

    DeLiberty, Tracy; Callahan, John; Guillory, Anthony R.; Jedlovec, Gary

    2000-01-01

    Atmospheric water vapor is widely recognized as a key climate variable, linking an assortment of poorly understood and complex processes. It is a major element of the hydrological cycle and provides a mechanism for energy exchange among many of the Earth system components. Reducing uncertainty in our current knowledge of water vapor and its role in the climate system requires accurate measurement, improved modeling techniques, and long-term prediction. Satellites have the potential to satisfy these criteria, as well as provide high resolution measurements that are not available from conventional sources. The focus of this paper is to examine the temporal and mesoscale variations of satellite derived precipitable water vapor (PW) across the Amazon Basin. This region is pivotal in the functioning of the global climate system through its abundant release of latent heat associated with heavy precipitation events. In addition, anthropogenic deforestation and biomass burning activities in recent decades are altering the conditions of the atmosphere, especially in the planetary boundary layer. A physical split-window (PSW) algorithm estimates PW using images from the GOES satellites along with the NCEP/NCAR Reanalysis data that provides the first guess information. Retrievals are made at a three-hourly time step during daylight hours in the Amazon Basin and surrounding areas for the months of June and October in 1988 (dry year) and 1995 (wet year). Spatially continuous fields are generated 5 times daily at 12Z, 15Z, 18Z, 21Z, and 00Z. These fields are then averaged to create monthly and 3 hourly monthly grids. Overall, the PSW estimates PW reasonable well in the Amazon with MAE ranging from 3.0 - 9.0 mm and MAE/observed mean around 20% in comparison to radiosonde observations. The distribution of PW generally mimics that of precipitation. Maximum values (42 - 52 mm) are located in the Northwest whereas minimum values (18 - 27 mm) are found along Brazil's East coast. Aside

  17. Technical Report Series on Global Modeling and Data Assimilation. Volume 12; Comparison of Satellite Global Rainfall Algorithms

    Science.gov (United States)

    Suarez, Max J. (Editor); Chang, Alfred T. C.; Chiu, Long S.

    1997-01-01

    Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates.

  18. The retrieval of cloud microphysical properties using satellite measurements and an in situ database

    Directory of Open Access Journals (Sweden)

    C. Poix

    1996-01-01

    Full Text Available By combining AVHRR data from the NOAA satellites with information from a database of in situ measurements, large-scale maps can be generated of the microphysical parameters most immediately significant for the modelling of global circulation and climate. From the satellite data, the clouds can be classified into cumuliform, stratiform and cirrus classes and then into further sub-classes by cloud top temperature. At the same time a database of in situ measurements made by research aircraft is classified into the same sub-classes and a statistical analysis is used to derive relationships between the sub-classes and the cloud microphysical properties. These two analyses are then linked to give estimates of the microphysical properties of the satellite observed clouds. Examples are given of the application of this technique to derive maps of the probability of occurrence of precipitating clouds and of precipitating water content derived from a case study within the International Cirrus Experiment (ICE held in 1989 over the North Sea.

  19. The retrieval of cloud microphysical properties using satellite measurements and an in situ database

    Directory of Open Access Journals (Sweden)

    Christophe Poix

    Full Text Available By combining AVHRR data from the NOAA satellites with information from a database of in situ measurements, large-scale maps can be generated of the microphysical parameters most immediately significant for the modelling of global circulation and climate. From the satellite data, the clouds can be classified into cumuliform, stratiform and cirrus classes and then into further sub-classes by cloud top temperature. At the same time a database of in situ measurements made by research aircraft is classified into the same sub-classes and a statistical analysis is used to derive relationships between the sub-classes and the cloud microphysical properties. These two analyses are then linked to give estimates of the microphysical properties of the satellite observed clouds. Examples are given of the application of this technique to derive maps of the probability of occurrence of precipitating clouds and of precipitating water content derived from a case study within the International Cirrus Experiment (ICE held in 1989 over the North Sea.

  20. Initial results of centralized autonomous orbit determination of the new-generation BDS satellites with inter-satellite link measurements

    Science.gov (United States)

    Tang, Chengpan; Hu, Xiaogong; Zhou, Shanshi; Liu, Li; Pan, Junyang; Chen, Liucheng; Guo, Rui; Zhu, Lingfeng; Hu, Guangming; Li, Xiaojie; He, Feng; Chang, Zhiqiao

    2018-01-01

    Autonomous orbit determination is the ability of navigation satellites to estimate the orbit parameters on-board using inter-satellite link (ISL) measurements. This study mainly focuses on data processing of the ISL measurements as a new measurement type and its application on the centralized autonomous orbit determination of the new-generation Beidou navigation satellite system satellites for the first time. The ISL measurements are dual one-way measurements that follow a time division multiple access (TDMA) structure. The ranging error of the ISL measurements is less than 0.25 ns. This paper proposes a derivation approach to the satellite clock offsets and the geometric distances from TDMA dual one-way measurements without a loss of accuracy. The derived clock offsets are used for time synchronization, and the derived geometry distances are used for autonomous orbit determination. The clock offsets from the ISL measurements are consistent with the L-band two-way satellite, and time-frequency transfer clock measurements and the detrended residuals vary within 0.5 ns. The centralized autonomous orbit determination is conducted in a batch mode on a ground-capable server for the feasibility study. Constant hardware delays are present in the geometric distances and become the largest source of error in the autonomous orbit determination. Therefore, the hardware delays are estimated simultaneously with the satellite orbits. To avoid uncertainties in the constellation orientation, a ground anchor station that "observes" the satellites with on-board ISL payloads is introduced into the orbit determination. The root-mean-square values of orbit determination residuals are within 10.0 cm, and the standard deviation of the estimated ISL hardware delays is within 0.2 ns. The accuracy of the autonomous orbits is evaluated by analysis of overlap comparison and the satellite laser ranging (SLR) residuals and is compared with the accuracy of the L-band orbits. The results indicate

  1. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  2. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  3. SAT-MAP-CLIMATE project results[SATellite base bio-geophysical parameter MAPping and aggregation modelling for CLIMATE models

    Energy Technology Data Exchange (ETDEWEB)

    Bay Hasager, C.; Woetmann Nielsen, N.; Soegaard, H.; Boegh, E.; Hesselbjerg Christensen, J.; Jensen, N.O.; Schultz Rasmussen, M.; Astrup, P.; Dellwik, E.

    2002-08-01

    Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI). The observed parameters are used in the DMI-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronounced land-sea breeze effect which is also observable in field observations. The albedo maps from NOAA AVHRR are rather similar to the climatological mean values so for the HIRLAM model this is insignicant, yet most likely of some importance in the HIRHAM regional climate model. Land cover type maps are assigned local roughness values determined from meteorological field observations. Only maps with a spatial resolution around 25 m can adequately map the roughness variations of the typical patch size distribution in Denmark. A roughness map covering Denmark is aggregated (ie area-average non-linearly) by a microscale aggregation model that takes the non-linear turbulent responses of each roughness step change between patches in an arbitrary pattern into account. The effective roughnesses are calculated into a 15 km by 15 km grid for the HIRLAM model. The effect of hedgerows is included as an added roughness effect as a function of hedge density mapped from a digital vector map. Introducing the new effective roughness maps into the HIRLAM model appears to remedy on the seasonal wind speed bias over land and sea in spring. A new parameterisation on the effective roughness for scalar surface fluxes is developed and tested on synthetic data. Further is a method for the estimation the evapotranspiration from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of

  4. Satellite constraints on surface concentrations of particulate matter

    Science.gov (United States)

    Ford Hotmann, Bonne

    (below 700 hPa), which cannot be explained by vertical mixing; we conclude that the discrepancy is due to a missing source of aerosols above the surface layer in summer. Next, we examine the usefulness of deriving premature mortality estimates from "satellite-based" PM2.5 concentrations. In particular, we examine how uncertainties in the model AOD-to-surface-PM2.5 relationship, satellite retrieved AOD, and particulars of the concentration-response function can impact these mortality estimates. We find that the satellite-based estimates suggest premature mortality due to chronic PM2.5 exposure is 2-16% higher in the U.S. and 4-13% lower in China compared to model-based estimates. However, this difference is overshadowed by the uncertainty in the methodology, which we quantify to be on order of 20% for the model-to- surface-PM2.5 relationship, 10% for the satellite AOD and 30-60% or greater with regards to the application of concentration response functions. Because there is a desire for acute exposure estimates, especially with regards to extreme events, we also examine how premature mortality due to acute exposure can be estimated from global models and satellite-observations. We find similar differences between model and satellite-based mortality estimates as with chronic exposure. However the range of uncertainty is much larger on these shorter timescales. This work suggests that although satellites can be useful for constraining model estimates of PM2.5, national mortality estimates from the two methods are not significantly different. In order to improve the efficacy of satellite-based PM2.5 mortality estimates, future work will need to focus on improving the model representation of the regional AOD-to-surface-PM2.5 relationship, reducing biases in satellite-retrieved AOD and advancing our understanding of personal and population-level responses to PM2.5 exposure.

  5. Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

    Science.gov (United States)

    Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

    2018-04-01

    Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0

  6. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (10 m cell size) multibeam bathymetry...

  7. Decadal variation in Earth's oblateness (J2) from satellite laser ranging data

    Science.gov (United States)

    Cheng, Minkang; Ries, John C.

    2018-02-01

    For four decades, satellite laser ranging has recorded the global nature of the long-wavelength hydrological mass redistribution within the Earth system, which results in significant variations in the Earth's dynamical oblateness, characterized by the second degree zonal geopotential spherical harmonic J2 (or C20). Analysis of the J2 time-series has shown a significant variation related to the strong El Niño-Southern Oscillation events with periods of 2-6 yr. In particular, the variation related to the powerful 2015-2016 El Niño that peaked during 2015 November-December was one of the strongest on record, comparable with the 1982-1983 and 1997-1998 events. In this study, we investigate further the hydrological mass transfer between atmosphere-ocean-land and their signature in the decadal variations of J2 with timescales of ˜10 yr. We found that the ˜6.4-yr variations can be accounted for by the atmosphere and ocean mass variations based on the improved Atmosphere-Ocean De-aliasing data, and the observed decadal variation in J2 correlates well with the decadal tropical variability characterized by the 5-yr running mean of the El Niño-Southern Oscillation Index, although existing physical models, especially the land water storage, are limited for the purpose of further studies of the excitation.

  8. LERC-SLAM - THE NASA LEWIS RESEARCH CENTER SATELLITE LINK ATTENUATION MODEL PROGRAM (MACINTOSH VERSION)

    Science.gov (United States)

    Manning, R. M.

    1994-01-01

    The frequency and intensity of rain attenuation affecting the communication between a satellite and an earth terminal is an important consideration in planning satellite links. The NASA Lewis Research Center Satellite Link Attenuation Model Program (LeRC-SLAM) provides a static and dynamic statistical assessment of the impact of rain attenuation on a communications link established between an earth terminal and a geosynchronous satellite. The program is designed for use in the specification, design and assessment of satellite links for any terminal location in the continental United States. The basis for LeRC-SLAM is the ACTS Rain Attenuation Prediction Model, which uses a log-normal cumulative probability distribution to describe the random process of rain attenuation on satellite links. The derivation of the statistics for the rainrate process at the specified terminal location relies on long term rainfall records compiled by the U.S. Weather Service during time periods of up to 55 years in length. The theory of extreme value statistics is also utilized. The user provides 1) the longitudinal position of the satellite in geosynchronous orbit, 2) the geographical position of the earth terminal in terms of latitude and longitude, 3) the height above sea level of the terminal site, 4) the yearly average rainfall at the terminal site, and 5) the operating frequency of the communications link (within 1 to 1000 GHz, inclusive). Based on the yearly average rainfall at the terminal location, LeRC-SLAM calculates the relevant rain statistics for the site using an internal data base. The program then generates rain attenuation data for the satellite link. This data includes a description of the static (i.e., yearly) attenuation process, an evaluation of the cumulative probability distribution for attenuation effects, and an evaluation of the probability of fades below selected fade depths. In addition, LeRC-SLAM calculates the elevation and azimuth angles of the terminal

  9. An alternative ionospheric correction model for global navigation satellite systems

    Science.gov (United States)

    Hoque, M. M.; Jakowski, N.

    2015-04-01

    The ionosphere is recognized as a major error source for single-frequency operations of global navigation satellite systems (GNSS). To enhance single-frequency operations the global positioning system (GPS) uses an ionospheric correction algorithm (ICA) driven by 8 coefficients broadcasted in the navigation message every 24 h. Similarly, the global navigation satellite system Galileo uses the electron density NeQuick model for ionospheric correction. The Galileo satellite vehicles (SVs) transmit 3 ionospheric correction coefficients as driver parameters of the NeQuick model. In the present work, we propose an alternative ionospheric correction algorithm called Neustrelitz TEC broadcast model NTCM-BC that is also applicable for global satellite navigation systems. Like the GPS ICA or Galileo NeQuick, the NTCM-BC can be optimized on a daily basis by utilizing GNSS data obtained at the previous day at monitor stations. To drive the NTCM-BC, 9 ionospheric correction coefficients need to be uploaded to the SVs for broadcasting in the navigation message. Our investigation using GPS data of about 200 worldwide ground stations shows that the 24-h-ahead prediction performance of the NTCM-BC is better than the GPS ICA and comparable to the Galileo NeQuick model. We have found that the 95 percentiles of the prediction error are about 16.1, 16.1 and 13.4 TECU for the GPS ICA, Galileo NeQuick and NTCM-BC, respectively, during a selected quiet ionospheric period, whereas the corresponding numbers are found about 40.5, 28.2 and 26.5 TECU during a selected geomagnetic perturbed period. However, in terms of complexity the NTCM-BC is easier to handle than the Galileo NeQuick and in this respect comparable to the GPS ICA.

  10. Mosaic of 2m bathymetry derived from multispectral IKONOS World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  11. A MATLAB-based graphical user interface program for computing functionals of the geopotential up to ultra-high degrees and orders

    Science.gov (United States)

    Bucha, Blažej; Janák, Juraj

    2013-07-01

    We present a novel graphical user interface program GrafLab (GRAvity Field LABoratory) for spherical harmonic synthesis (SHS) created in MATLAB®. This program allows to comfortably compute 38 various functionals of the geopotential up to ultra-high degrees and orders of spherical harmonic expansion. For the most difficult part of the SHS, namely the evaluation of the fully normalized associated Legendre functions (fnALFs), we used three different approaches according to required maximum degree: (i) the standard forward column method (up to maximum degree 1800, in some cases up to degree 2190); (ii) the modified forward column method combined with Horner's scheme (up to maximum degree 2700); (iii) the extended-range arithmetic (up to an arbitrary maximum degree). For the maximum degree 2190, the SHS with fnALFs evaluated using the extended-range arithmetic approach takes only approximately 2-3 times longer than its standard arithmetic counterpart, i.e. the standard forward column method. In the GrafLab, the functionals of the geopotential can be evaluated on a regular grid or point-wise, while the input coordinates can either be read from a data file or entered manually. For the computation on a regular grid we decided to apply the lumped coefficients approach due to significant time-efficiency of this method. Furthermore, if a full variance-covariances matrix of spherical harmonic coefficients is available, it is possible to compute the commission errors of the functionals. When computing on a regular grid, the output functionals or their commission errors may be depicted on a map using automatically selected cartographic projection.

  12. The ESA climate change initiative: Satellite data records for essential climate variables

    DEFF Research Database (Denmark)

    Hollmann, R.; Merchant, C.J.; Saunders, R.

    2013-01-01

    The European Space Agency (ESA) has launched the Climate Change Initiative (CCI) to provide satellite-based climate data records (CDRs) that meet the challenging requirements of the climate community. The aim is to realize the full potential of the long-term Earth observation (EO) archives...... that both ESA and third parties have established. This includes aspects of producing a CDR, which involve data acquisition, calibration, algorithm development, validation, maintenance, and provision of the data to the climate research community. The CCI is consistent with several international efforts...... targeting the generation of satellite derived climate data records. One focus of the CCI is to provide products for climate modelers who increasingly use satellite data to initialize, constrain, and validate models on a wide range of space and time scales....

  13. Aerosols, Chemistry, and Radiative Forcing: A 3-D Model Analysis of Satellite and ACE-Asia data (ACMAP)

    Science.gov (United States)

    Chin, Mian; Ginoux, Paul; Torres, Omar; Zhao, Xue-Peng

    2005-01-01

    We propose a research project to incorporate a global 3-D model and satellite data into the multi-national Aerosol Characterization Experiment-Asia (ACE-Asia) mission. Our objectives are (1) to understand the physical, chemical, and optical properties of aerosols and the processes that control those properties over the Asian-Pacific region, (2) to investigate the interaction between aerosols and tropospheric chemistry, and (3) to determine the aerosol radiative forcing over the Asia-Pacific region. We will use the Georgia TecWGoddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model to link satellite observations and the ACE-Asia measurements. First, we will use the GOCART model to simulate aerosols and related species, and evaluate the model with satellite and in-situ observations. Second, the model generated aerosol vertical profiles and compositions will be used to validate the satellite products; and the satellite data will be used for during- and post- mission analysis. Third, we will use the model to analyze and interpret both satellite and ACE- Asia field campaign data and investigate the aerosol-chemistry interactions. Finally, we will calculate aerosol radiative forcing over the Asian-Pacific region, and assess the influence of Asian pollution in the global atmosphere. We propose a research project to incorporate a global 3-D model and satellite data into

  14. Generation of Digital Surface Models from satellite photogrammetry: the DSM-OPT service of the ESA Geohazards Exploitation Platform (GEP)

    Science.gov (United States)

    Stumpf, André; Michéa, David; Malet, Jean-Philippe

    2017-04-01

    The continuously increasing fleet of agile stereo-capable very-high resolution (VHR) optical satellites has facilitated the acquisition of multi-view images of the earth surface. Theoretical revisit times have been reduced to less than one day and the highest spatial resolution which is commercially available amounts now to 30 cm/pixel. Digital Surface Models (DSM) and point clouds computed from such satellite stereo-acquisitions can provide valuable input for studies in geomorphology, tectonics, glaciology, hydrology and urban remote sensing The photogrammetric processing, however, still requires significant expertise, computational resources and costly commercial software. To enable a large Earth Science community (researcher and end-users) to process easily and rapidly VHR multi-view images, the work targets the implementation of a fully automatic satellite-photogrammetry pipeline (i.e DSM-OPT) on the ESA Geohazards Exploitation Platform (GEP). The implemented pipeline is based on the open-source photogrammetry library MicMac [1] and is designed for distributed processing on a cloud-based infrastructure. The service can be employed in pre-defined processing modes (i.e. urban, plain, hilly, and mountainous environments) or in an advanced processing mode (i.e. in which expert-users have the possibility to adapt the processing parameters to their specific applications). Four representative use cases are presented to illustrate the accuracy of the resulting surface models and ortho-images as well as the overall processing time. These use cases consisted of the construction of surface models from series of Pléiades images for four applications: urban analysis (Strasbourg, France), landslide detection in mountainous environments (South French Alps), co-seismic deformation in mountain environments (Central Italy earthquake sequence of 2016) and fault recognition for paleo-tectonic analysis (North-East India). Comparisons of the satellite-derived topography to airborne

  15. Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.

    2015-04-01

    We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

  16. Estimation of Chinese surface NO2 concentrations combining satellite data and Land Use Regression

    Science.gov (United States)

    Anand, J.; Monks, P.

    2016-12-01

    Monitoring surface-level air quality is often limited by in-situ instrument placement and issues arising from harmonisation over long timescales. Satellite instruments can offer a synoptic view of regional pollution sources, but in many cases only a total or tropospheric column can be measured. In this work a new technique of estimating surface NO2 combining both satellite and in-situ data is presented, in which a Land Use Regression (LUR) model is used to create high resolution pollution maps based on known predictor variables such as population density, road networks, and land cover. By employing a mixed effects approach, it is possible to take advantage of the spatiotemporal variability in the satellite-derived column densities to account for daily and regional variations in surface NO2 caused by factors such as temperature, elevation, and wind advection. In this work, surface NO2 maps are modelled over the North China Plain and Pearl River Delta during high-pollution episodes by combining in-situ measurements and tropospheric columns from the Ozone Monitoring Instrument (OMI). The modelled concentrations show good agreement with in-situ data and surface NO2 concentrations derived from the MACC-II global reanalysis.

  17. A new digital elevation model of Antarctica derived from CryoSat-2 altimetry

    Directory of Open Access Journals (Sweden)

    T. Slater

    2018-05-01

    Full Text Available We present a new digital elevation model (DEM of the Antarctic ice sheet and ice shelves based on 2.5 × 108 observations recorded by the CryoSat-2 satellite radar altimeter between July 2010 and July 2016. The DEM is formed from spatio-temporal fits to elevation measurements accumulated within 1, 2, and 5 km grid cells, and is posted at the modal resolution of 1 km. Altogether, 94 % of the grounded ice sheet and 98 % of the floating ice shelves are observed, and the remaining grid cells north of 88° S are interpolated using ordinary kriging. The median and root mean square difference between the DEM and 2.3 × 107 airborne laser altimeter measurements acquired during NASA Operation IceBridge campaigns are −0.30 and 13.50 m, respectively. The DEM uncertainty rises in regions of high slope, especially where elevation measurements were acquired in low-resolution mode; taking this into account, we estimate the average accuracy to be 9.5 m – a value that is comparable to or better than that of other models derived from satellite radar and laser altimetry.

  18. Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets

    Directory of Open Access Journals (Sweden)

    V. Pedinotti

    2012-06-01

    Full Text Available During the 1970s and 1980s, West Africa has faced extreme climate variations with extended drought conditions. Of particular importance is the Niger basin, since it traverses a large part of the Sahel and is thus a critical source of water for an ever-increasing local population in this semi arid region. However, the understanding of the hydrological processes over this basin is currently limited by the lack of spatially distributed surface water and discharge measurements. The purpose of this study is to evaluate the ability of the ISBA-TRIP continental hydrologic system to represent key processes related to the hydrological cycle of the Niger basin. ISBA-TRIP is currently used within a coupled global climate model, so that the scheme must represent the first order processes which are critical for representing the water cycle while retaining a limited number of parameters and a simple representation of the physics. To this end, the scheme uses first-order approximations to account explicitly for the surface river routing, the floodplain dynamics, and the water storage using a deep aquifer reservoir. In the current study, simulations are done at a 0.5 by 0.5° spatial resolution over the 2002–2007 period (in order to take advantage of the recent satellite record and data from the African Monsoon Multidisciplinary Analyses project, AMMA. Four configurations of the model are compared to evaluate the separate impacts of the flooding scheme and the aquifer on the water cycle. Moreover, the model is forced by two different rainfall datasets to consider the sensitivity of the model to rainfall input uncertainties. The model is evaluated using in situ discharge measurements as well as satellite derived flood extent, total continental water storage changes and river height changes. The basic analysis of in situ discharges confirms the impact of the inner delta area, known as a significant flooded area, on the discharge, characterized by a strong

  19. VERTICAL ACCURACY COMPARISON OF DIGITAL ELEVATION MODEL FROM LIDAR AND MULTITEMPORAL SATELLITE IMAGERY

    Directory of Open Access Journals (Sweden)

    J. Octariady

    2017-05-01

    Full Text Available Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo satellite imagery DEM. Multitemporal stereo satellite imagery generated semi-automatically by using 3 scene stereo satellite imagery with acquisition 2013–2014. The high value given each of DEM serve as the basis for calculating high accuracy DEM respectively. The results showed the high value differences in the fraction of the meter between LiDAR DEM and multitemporal stereo satellite imagery DEM.

  20. Gravity model development for precise orbit computations for satellite altimetry

    Science.gov (United States)

    Marsh, James G.; Lerch, Francis, J.; Smith, David E.; Klosko, Steven M.; Pavlis, Erricos

    1986-01-01

    Two preliminary gravity models developed as a first step in reaching the TOPEX/Poseidon modeling goals are discussed. They were obtained by NASA-Goddard from an analysis of exclusively satellite tracking observations. With the new Preliminary Gravity Solution-T2 model, an improved global estimate of the field is achieved with an improved description of the geoid.

  1. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  2. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5 m cell size) multibeam bathymetry collected...

  3. Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

    Science.gov (United States)

    Su, X.

    2017-12-01

    A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

  4. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-01-01

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

  5. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-11-17

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

  6. Gravity model improvement using the DORIS tracking system on the SPOT 2 satellite

    Science.gov (United States)

    Nerem, R. S.; Lerch, F. J.; Williamson, R. G.; Klosko, S. M.; Robbins, J. W.; Patel, G. B.

    1994-01-01

    A high-precision radiometric satellite tracking system, Doppler Orbitography and Radio-positioning Integrated by Satellite system (DORIS), has recently been developed by the French space agency, Centre National d'Etudes Spatiales (CNES). DORIS was designed to provide tracking support for missions such as the joint United States/French TOPEX/Poseidon. As part of the flight testing process, a DORIS package was flown on the French SPOT 2 satellite. A substantial quantity of geodetic quality tracking data was obtained on SPOT 2 from an extensive international DORIS tracking network. These data were analyzed to assess their accuracy and to evaluate the gravitational modeling enhancements provided by these data in combination with the Goddard Earth Model-T3 (GEM-T3) gravitational model. These observations have noise levels of 0.4 to 0.5 mm/s, with few residual systematic effects. Although the SPOT 2 satellite experiences high atmospheric drag forces, the precision and global coverage of the DORIS tracking data have enabled more extensive orbit parameterization to mitigate these effects. As a result, the SPOT 2 orbital errors have been reduced to an estimated radial accuracy in the 10-20 cm RMS range. The addition of these data, which encompass many regions heretofore lacking in precision satellite tracking, has significantly improved GEM-T3 and allowed greatly improved orbit accuracies for Sun-synchronous satellites like SPOT 2 (such as ERS 1 and EOS). Comparison of the ensuing gravity model with other contemporary fields (GRIM-4C2, TEG2B, and OSU91A) provides a means to assess the current state of knowledge of the Earth's gravity field. Thus, the DORIS experiment on SPOT 2 has provided a strong basis for evaluating this new orbit tracking technology and has demonstrated the important contribution of the DORIS network to the success of the TOPEX/Poseidon mission.

  7. Potential for a biogenic influence on cloud microphysics over the ocean: a correlation study with satellite-derived data

    Directory of Open Access Journals (Sweden)

    A. Lana

    2012-09-01

    Full Text Available Aerosols have a large potential to influence climate through their effects on the microphysics and optical properties of clouds and, hence, on the Earth's radiation budget. Aerosol–cloud interactions have been intensively studied in polluted air, but the possibility that the marine biosphere plays an important role in regulating cloud brightness in the pristine oceanic atmosphere remains largely unexplored. We used 9 yr of global satellite data and ocean climatologies to derive parameterizations of the temporal variability of (a production fluxes of sulfur aerosols formed by the oxidation of the biogenic gas dimethylsulfide emitted from the sea surface; (b production fluxes of secondary organic aerosols from biogenic organic volatiles; (c emission fluxes of biogenic primary organic aerosols ejected by wind action on sea surface; and (d emission fluxes of sea salt also lifted by the wind upon bubble bursting. Series of global monthly estimates of these fluxes were correlated to series of potential cloud condensation nuclei (CCN numbers derived from satellite (MODIS. More detailed comparisons among weekly series of estimated fluxes and satellite-derived cloud droplet effective radius (re data were conducted at locations spread among polluted and clean regions of the oceanic atmosphere. The outcome of the statistical analysis was that positive correlation to CCN numbers and negative correlation to re were common at mid and high latitude for sulfur and organic secondary aerosols, indicating both might be important in seeding cloud droplet activation. Conversely, primary aerosols (organic and sea salt showed widespread positive correlations to CCN only at low latitudes. Correlations to re were more variable, non-significant or positive, suggesting that, despite contributing to large shares of the marine aerosol mass, primary aerosols are not widespread major drivers of the variability of cloud

  8. Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study

    Science.gov (United States)

    Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso

    2015-04-01

    Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico Semi

  9. UV Stellar Distribution Model for the Derivation of Payload

    Directory of Open Access Journals (Sweden)

    Young-Jun Choi

    1999-12-01

    Full Text Available We present the results of a model calculation of the stellar distribution in a UV and centered at 2175Å corresponding to the well-known bump in the interstellar extinction curve. The stellar distribution model used here is based on the Bahcall-Soneira galaxy model (1980. The source code for model calculation was designed by Brosch (1991 and modified to investigate various designing factors for UV satellite payload. The model predicts UV stellar densities in different sky directions, and its results are compared with the TD-1 star counts for a number of sky regions. From this study, we can determine the field of view, size of optics, angular resolution, and number of stars in one orbit. There will provide the basic constrains in designing a satellite payload for UV observations.

  10. Near-real-time global biomass burning emissions product from geostationary satellite constellation

    Science.gov (United States)

    Zhang, Xiaoyang; Kondragunta, Shobha; Ram, Jessica; Schmidt, Christopher; Huang, Ho-Chun

    2012-07-01

    Near-real-time estimates of biomass burning emissions are crucial for air quality monitoring and forecasting. We present here the first near-real-time global biomass burning emission product from geostationary satellites (GBBEP-Geo) produced from satellite-derived fire radiative power (FRP) for individual fire pixels. Specifically, the FRP is retrieved using WF_ABBA V65 (wildfire automated biomass burning algorithm) from a network of multiple geostationary satellites. The network consists of two Geostationary Operational Environmental Satellites (GOES) which are operated by the National Oceanic and Atmospheric Administration, the Meteosat second-generation satellites (Meteosat-09) operated by the European Organisation for the Exploitation of Meteorological Satellites, and the Multifunctional Transport Satellite (MTSAT) operated by the Japan Meteorological Agency. These satellites observe wildfires at an interval of 15-30 min. Because of the impacts from sensor saturation, cloud cover, and background surface, the FRP values are generally not continuously observed. The missing observations are simulated by combining the available instantaneous FRP observations within a day and a set of representative climatological diurnal patterns of FRP for various ecosystems. Finally, the simulated diurnal variation in FRP is applied to quantify biomass combustion and emissions in individual fire pixels with a latency of 1 day. By analyzing global patterns in hourly biomass burning emissions in 2010, we find that peak fire season varied greatly and that annual wildfires burned 1.33 × 1012 kg dry mass, released 1.27 × 1010 kg of PM2.5 (particulate mass for particles with diameter forest and savanna fires in Africa, South America, and North America. Evaluation of emission result reveals that the GBBEP-Geo estimates are comparable with other FRP-derived estimates in Africa, while the results are generally smaller than most of the other global products that were derived from burned

  11. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  12. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  13. Calculation of charge-state ratios for satellite Tor I

    Science.gov (United States)

    Summers, D.; Siscoe, G. L.

    1985-01-01

    The diffusion of ions in a satellite plasma torus is presently modeled in terms of a one-dimensional random walk in which the particle source is at 0, the particle sink is at an N value that is an integer greater than 2, and the scale size of the diffusion cell is unity. The probability distribution function of the number of steps to exit for an ion is obtained and used in a model which incorporates ionization by electron impact to derive steady state expressions for the ratio of doubly to singly ionized ions, as well as the total number of ions in the torus. The results thus obtained are applied to the torus of the Jovian satellite Io, in order to predict mean residence times for sulfur and oxygen ions.

  14. Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration.

    Science.gov (United States)

    Sadeghian, Amir; Hudson, Jeff; Wheater, Howard; Lindenschmidt, Karl-Erich

    2017-08-01

    In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m 3 /s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

  15. LERC-SLAM - THE NASA LEWIS RESEARCH CENTER SATELLITE LINK ATTENUATION MODEL PROGRAM (IBM PC VERSION)

    Science.gov (United States)

    Manning, R. M.

    1994-01-01

    The frequency and intensity of rain attenuation affecting the communication between a satellite and an earth terminal is an important consideration in planning satellite links. The NASA Lewis Research Center Satellite Link Attenuation Model Program (LeRC-SLAM) provides a static and dynamic statistical assessment of the impact of rain attenuation on a communications link established between an earth terminal and a geosynchronous satellite. The program is designed for use in the specification, design and assessment of satellite links for any terminal location in the continental United States. The basis for LeRC-SLAM is the ACTS Rain Attenuation Prediction Model, which uses a log-normal cumulative probability distribution to describe the random process of rain attenuation on satellite links. The derivation of the statistics for the rainrate process at the specified terminal location relies on long term rainfall records compiled by the U.S. Weather Service during time periods of up to 55 years in length. The theory of extreme value statistics is also utilized. The user provides 1) the longitudinal position of the satellite in geosynchronous orbit, 2) the geographical position of the earth terminal in terms of latitude and longitude, 3) the height above sea level of the terminal site, 4) the yearly average rainfall at the terminal site, and 5) the operating frequency of the communications link (within 1 to 1000 GHz, inclusive). Based on the yearly average rainfall at the terminal location, LeRC-SLAM calculates the relevant rain statistics for the site using an internal data base. The program then generates rain attenuation data for the satellite link. This data includes a description of the static (i.e., yearly) attenuation process, an evaluation of the cumulative probability distribution for attenuation effects, and an evaluation of the probability of fades below selected fade depths. In addition, LeRC-SLAM calculates the elevation and azimuth angles of the terminal

  16. The Satellite Cell Niche Regulates the Balance between Myoblast Differentiation and Self-Renewal via p53.

    Science.gov (United States)

    Flamini, Valentina; Ghadiali, Rachel S; Antczak, Philipp; Rothwell, Amy; Turnbull, Jeremy E; Pisconti, Addolorata

    2018-03-13

    Satellite cells are adult muscle stem cells residing in a specialized niche that regulates their homeostasis. How niche-generated signals integrate to regulate gene expression in satellite cell-derived myoblasts is poorly understood. We undertook an unbiased approach to study the effect of the satellite cell niche on satellite cell-derived myoblast transcriptional regulation and identified the tumor suppressor p53 as a key player in the regulation of myoblast quiescence. After activation and proliferation, a subpopulation of myoblasts cultured in the presence of the niche upregulates p53 and fails to differentiate. When satellite cell self-renewal is modeled ex vivo in a reserve cell assay, myoblasts treated with Nutlin-3, which increases p53 levels in the cell, fail to differentiate and instead become quiescent. Since both these Nutlin-3 effects are rescued by small interfering RNA-mediated p53 knockdown, we conclude that a tight control of p53 levels in myoblasts regulates the balance between differentiation and return to quiescence. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing.

    Science.gov (United States)

    Richardson, Andrew D; Hufkens, Koen; Milliman, Tom; Frolking, Steve

    2018-04-09

    Phenology is a valuable diagnostic of ecosystem health, and has applications to environmental monitoring and management. Here, we conduct an intercomparison analysis using phenological transition dates derived from near-surface PhenoCam imagery and MODIS satellite remote sensing. We used approximately 600 site-years of data, from 128 camera sites covering a wide range of vegetation types and climate zones. During both "greenness rising" and "greenness falling" transition phases, we found generally good agreement between PhenoCam and MODIS transition dates for agricultural, deciduous forest, and grassland sites, provided that the vegetation in the camera field of view was representative of the broader landscape. The correlation between PhenoCam and MODIS transition dates was poor for evergreen forest sites. We discuss potential reasons (including sub-pixel spatial heterogeneity, flexibility of the transition date extraction method, vegetation index sensitivity in evergreen systems, and PhenoCam geolocation uncertainty) for varying agreement between time series of vegetation indices derived from PhenoCam and MODIS imagery. This analysis increases our confidence in the ability of satellite remote sensing to accurately characterize seasonal dynamics in a range of ecosystems, and provides a basis for interpreting those dynamics in the context of tangible phenological changes occurring on the ground.

  18. An artificial neural network ensemble model for estimating global solar radiation from Meteosat satellite images

    International Nuclear Information System (INIS)

    Linares-Rodriguez, Alvaro; Ruiz-Arias, José Antonio; Pozo-Vazquez, David; Tovar-Pescador, Joaquin

    2013-01-01

    An optimized artificial neural network ensemble model is built to estimate daily global solar radiation over large areas. The model uses clear-sky estimates and satellite images as input variables. Unlike most studies using satellite imagery based on visible channels, our model also exploits all information within infrared channels of the Meteosat 9 satellite. A genetic algorithm is used to optimize selection of model inputs, for which twelve are selected – eleven 3-km Meteosat 9 channels and one clear-sky term. The model is validated in Andalusia (Spain) from January 2008 through December 2008. Measured data from 83 stations across the region are used, 65 for training and 18 independent ones for testing the model. At the latter stations, the ensemble model yields an overall root mean square error of 6.74% and correlation coefficient of 99%; the generated estimates are relatively accurate and errors spatially uniform. The model yields reliable results even on cloudy days, improving on current models based on satellite imagery. - Highlights: • Daily solar radiation data are generated using an artificial neural network ensemble. • Eleven Meteosat channels observations and a clear sky term are used as model inputs. • Model exploits all information within infrared Meteosat channels. • Measured data for a year from 83 ground stations are used. • The proposed approach has better performance than existing models on daily basis

  19. A New Model of the Mean Albedo of the Earth: Estimation and Validation from the GRACE Mission and SLR Satellites.

    Science.gov (United States)

    Deleflie, F.; Sammuneh, M. A.; Coulot, D.; Pollet, A.; Biancale, R.; Marty, J. C.

    2017-12-01

    This talk provides new results of a study that we began last year, and that was the subject of a poster by the same authors presented during AGU FM 2016, entitled « Mean Effect of the Albedo of the Earth on Artificial Satellite Trajectories: an Update Over 2000-2015. »The emissivity of the Earth, split into a part in the visible domain (albedo) and the infrared domain (thermic emissivity), is at the origin of non gravitational perturbations on artificial satellite trajectories. The amplitudes and periods of these perturbations can be investigated if precise orbits can be carried out, and reveal some characteristics of the space environment where the satellite is orbiting. Analyzing the perturbations is, hence, a way to characterize how the energy from the Sun is re-emitted by the Earth. When led over a long period of time, such an approach enables to quantify the variations of the global radiation budget of the Earth.Additionally to the preliminary results presented last year, we draw an assessment of the validity of the mean model based on the orbits of the GRACE missions, and, to a certain extent, of some of the SLR satellite orbits. The accelerometric data of the GRACE satellites are used to evaluate the accuracy of the models accounting for non gravitational forces, and the ones induced by the albedo and the thermic emissivity in particular. Three data sets are used to investigate the mean effects on the orbit perturbations: Stephens tables (Stephens, 1980), ECMWF (European Centre for Medium-Range Weather Forecasts) data sets and CERES (Clouds and the Earth's Radiant Energy System) data sets (publickly available). From the trajectography point of view, based on post-fit residual analysis, we analyze what is the data set leading to the lowest residual level, to define which data set appears to be the most suitable one to derive a new « mean albedo model » from accelerometric data sets of the GRACE mission. The period of investigation covers the full GRACE

  20. Analytic Models for Sunlight Charging of a Rapidly Spinning Satellite

    National Research Council Canada - National Science Library

    Tautz, Maurice

    2003-01-01

    ... photoelectrons can be blocked by local potential barriers. In this report, we discuss two analytic models for sunlight charging of a rapidly spinning spherical satellite, both of which are based on blocked photoelectron currents...

  1. Ensemble Assimilation Using Three First-Principles Thermospheric Models as a Tool for 72-hour Density and Satellite Drag Forecasts

    Science.gov (United States)

    Hunton, D.; Pilinski, M.; Crowley, G.; Azeem, I.; Fuller-Rowell, T. J.; Matsuo, T.; Fedrizzi, M.; Solomon, S. C.; Qian, L.; Thayer, J. P.; Codrescu, M.

    2014-12-01

    Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by variability in the density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. As the population of satellites in Earth orbit grows, higher space-weather prediction accuracy is required for critical missions, such as accurate catalog maintenance, collision avoidance for manned and unmanned space flight, reentry prediction, satellite lifetime prediction, defining on-board fuel requirements, and satellite attitude dynamics. We describe ongoing work to build a comprehensive nowcast and forecast system for neutral density, winds, temperature, composition, and satellite drag. This modeling tool will be called the Atmospheric Density Assimilation Model (ADAM). It will be based on three state-of-the-art coupled models of the thermosphere-ionosphere running in real-time, using assimilative techniques to produce a thermospheric nowcast. It will also produce, in realtime, 72-hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition. We will review the requirements for the ADAM system, the underlying full-physics models, the plethora of input options available to drive the models, a feasibility study showing the performance of first-principles models as it pertains to satellite-drag operational needs, and review challenges in designing an assimilative space-weather prediction model. The performance of the ensemble assimilative model is expected to exceed the performance of current empirical and assimilative density models.

  2. Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations

    Science.gov (United States)

    Waliser, Duane

    2011-01-01

    Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.

  3. Oceanic Weather Decision Support for Unmanned Global Hawk Science Missions into Hurricanes with Tailored Satellite Derived Products

    Science.gov (United States)

    Feltz, Wayne; Griffin, Sarah; Velden, Christopher; Zipser, Ed; Cecil, Daniel; Braun, Scott

    2017-04-01

    The purpose of this presentation is to identify in-flight hazards to high-altitude aircraft, namely the Global Hawk. The Global Hawk was used during Septembers 2012-2016 as part of two NASA funded Hurricane Sentinel-3 field campaigns to over-fly hurricanes in the Atlantic Ocean. This talk identifies the cause of severe turbulence experienced over Hurricane Emily (2005) and how a combination of NOAA funded GOES-R algorithm derived cloud top heights/tropical overshooting tops using GOES-13/SEVIRI imager radiances, and lightning information are used to identify areas of potential turbulence for near real-time navigation decision support. Several examples will demonstrate how the Global Hawk pilots remotely received and used real-time satellite derived cloud and lightning detection information to keep the aircraft safely above clouds and avoid regions of potential turbulence.

  4. Mass and power modeling of communication satellites

    Science.gov (United States)

    Price, Kent M.; Pidgeon, David; Tsao, Alex

    1991-01-01

    Analytic estimating relationships for the mass and power requirements for major satellite subsystems are described. The model for each subsystem is keyed to the performance drivers and system requirements that influence their selection and use. Guidelines are also given for choosing among alternative technologies which accounts for other significant variables such as cost, risk, schedule, operations, heritage, and life requirements. These models are intended for application to first order systems analyses, where resources do not warrant detailed development of a communications system scenario. Given this ground rule, the models are simplified to 'smoothed' representation of reality. Therefore, the user is cautioned that cost, schedule, and risk may be significantly impacted where interpolations are sufficiently different from existing hardware as to warrant development of new devices.

  5. Combining satellite derived phenology with climate data for climate change impact assessment

    Science.gov (United States)

    Ivits, E.; Cherlet, M.; Tóth, G.; Sommer, S.; Mehl, W.; Vogt, J.; Micale, F.

    2012-05-01

    The projected influence of climate change on the timing and volume of phytomass production is expected to affect a number of ecosystem services. In order to develop coherent and locally effective adaptation and mitigation strategies, spatially explicit information on the observed changes is needed. Long-term variations of the vegetative growing season in different environmental zones of Europe for 1982-2006 have been derived by analysing time series of GIMMS NDVI data. The associations of phenologically homogenous spatial clusters to time series of temperature and precipitation data were evaluated. North-east Europe showed a trend to an earlier and longer growing season, particularly in the northern Baltic areas. Despite the earlier greening up large areas of Europe exhibited rather stable season length indicating the shift of the entire growing season to an earlier period. The northern Mediterranean displayed a growing season shift towards later dates while some agglomerations of earlier and shorter growing season were also seen. The correlation of phenological time series with climate data shows a cause-and-effect relationship over the semi natural areas consistent with results in literature. Managed ecosystems however appear to have heterogeneous change pattern with less or no correlation to climatic trends. Over these areas climatic trends seemed to overlap in a complex manner with more pronounced effects of local biophysical conditions and/or land management practices. Our results underline the importance of satellite derived phenological observations to explain local nonconformities to climatic trends for climate change impact assessment.

  6. Using satellite observations in performance evaluation for regulatory air quality modeling: Comparison with ground-level measurements

    Science.gov (United States)

    Odman, M. T.; Hu, Y.; Russell, A.; Chai, T.; Lee, P.; Shankar, U.; Boylan, J.

    2012-12-01

    Regulatory air quality modeling, such as State Implementation Plan (SIP) modeling, requires that model performance meets recommended criteria in the base-year simulations using period-specific, estimated emissions. The goal of the performance evaluation is to assure that the base-year modeling accurately captures the observed chemical reality of the lower troposphere. Any significant deficiencies found in the performance evaluation must be corrected before any base-case (with typical emissions) and future-year modeling is conducted. Corrections are usually made to model inputs such as emission-rate estimates or meteorology and/or to the air quality model itself, in modules that describe specific processes. Use of ground-level measurements that follow approved protocols is recommended for evaluating model performance. However, ground-level monitoring networks are spatially sparse, especially for particulate matter. Satellite retrievals of atmospheric chemical properties such as aerosol optical depth (AOD) provide spatial coverage that can compensate for the sparseness of ground-level measurements. Satellite retrievals can also help diagnose potential model or data problems in the upper troposphere. It is possible to achieve good model performance near the ground, but have, for example, erroneous sources or sinks in the upper troposphere that may result in misleading and unrealistic responses to emission reductions. Despite these advantages, satellite retrievals are rarely used in model performance evaluation, especially for regulatory modeling purposes, due to the high uncertainty in retrievals associated with various contaminations, for example by clouds. In this study, 2007 was selected as the base year for SIP modeling in the southeastern U.S. Performance of the Community Multiscale Air Quality (CMAQ) model, at a 12-km horizontal resolution, for this annual simulation is evaluated using both recommended ground-level measurements and non-traditional satellite

  7. Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

    Science.gov (United States)

    Luvall, J. C.; Sprigg, W.; Levetin, E.; Huete, A.; Nickovic, S.; Pejanovic, G. A.; Vukovic, A.; VandeWater, P.; Budge, A.; Hudspeth, W.; hide

    2012-01-01

    Juniperus spp. pollen is a significant aeroallergen that can be transported 200-600 km from the source. Local observations of Juniperus spp. phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Methods: The Dust REgional Atmospheric Model (DREAM)is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust. We successfully modified the DREAM model to incorporate pollen transport (PREAM) and used MODIS satellite images to develop Juniperus ashei pollen input source masks. The Pollen Release Potential Source Map, also referred to as a source mask in model applications, may use different satellite platforms and sensors and a variety of data sets other than the USGS GAP data we used to map J. ashei cover type. MODIS derived percent tree cover is obtained from MODIS Vegetation Continuous Fields (VCF) product (collection 3 and 4, MOD44B, 500 and 250 m grid resolution). We use updated 2010 values to calculate pollen concentration at source (J. ashei ). The original MODIS derived values are converted from native approx. 250 m to 990m (approx. 1 km) for the calculation of a mask to fit the model (PREAM) resolution. Results: The simulation period is chosen following the information that in the last 2 weeks of December 2010. The PREAM modeled near-surface concentrations (Nm-3) shows the transport patterns of J. ashei pollen over a 5 day period (Fig. 2). Typical scales of the simulated transport process are regional.

  8. Gravity Anomalies and Estimated Topography Derived from Satellite Altimetry

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In many areas of the global ocean, the depth of the seafloor is not well known because survey lines by ships are hundreds of kilometers apart. Satellites carrying...

  9. Intraseasonal patterns in coastal plankton biomass off central Chile derived from satellite observations and a biochemical model

    Science.gov (United States)

    Gomez, Fabian A.; Spitz, Yvette H.; Batchelder, Harold P.; Correa-Ramirez, Marco A.

    2017-10-01

    Subseasonal (5-130 days) environmental variability can strongly affect plankton dynamics, but is often overlooked in marine ecology studies. We documented the main subseasonal patterns of plankton biomass in the coastal upwelling system off central Chile, the southern part of the Humboldt System. Subseasonal variability was extracted from temporal patterns in satellite data of wind stress, sea surface temperature, and chlorophyll from the period 2003-2011, and from a realistically forced eddy-resolving physical-biochemical model from 2003 to 2008. Although most of the wind variability occurs at submonthly frequencies (< 30 days), we found that the dominant subseasonal pattern of phytoplankton biomass is within the intraseasonal band (30-90 days). The strongest intraseasonal coupling between wind and plankton is in spring-summer, when increased solar radiation enhances the phytoplankton response to upwelling. Biochemical model outputs show intraseasonal shifts in plankton community structure, mainly associated with the large fluctuations in diatom biomass. Diatom biomass peaks near surface during strong upwelling, whereas small phytoplankton biomass peaks at subsurface depths during relaxation or downwelling periods. Strong intraseasonally forced changes in biomass and species composition could strongly impact trophodynamics connections in the ecosystem, including the recruitment of commercially important fish species such as common sardine and anchovy. The wind-driven variability of chlorophyll concentration was connected to mid- and high-latitude atmospheric anomalies, which resemble disturbances with frequencies similar to the tropical Madden-Julian Oscillation.

  10. Total Discharge Estimation in the Korean Peninsula Using Multi-Satellite Products

    Directory of Open Access Journals (Sweden)

    Jae Young Seo

    2017-07-01

    Full Text Available Estimation of total discharge is necessary to understand the hydrological cycle and to manage water resources efficiently. However, the task is problematic in an area where ground observations are limited. The North Korea region is one example. Here, the total discharge was estimated based on the water balance using multiple satellite products. They are the terrestrial water storage changes (TWSC derived from the Gravity Recovery and Climate Experiment (GRACE, precipitation from the Tropical Rainfall Measuring Mission (TRMM, and evapotranspiration from the Moderate Resolution Imaging Spectroradiometer (MODIS. The satellite-based discharge was compared with land surface model products of the Global Land Data Assimilation System (GLDAS, and a positive relationship between the results was obtained (r = 0.70–0.86; bias = −9.08–16.99 mm/month; RMSE = 36.90–62.56 mm/month; NSE = 0.01–0.62. Among the four land surface models of GLDAS (CLM, Mosaic, Noah, and VIC, CLM corresponded best with the satellite-based discharge, satellite-based discharge has a tendency to slightly overestimate compared to model-based discharge (CLM, Mosaic, Noah, and VIC in the dry season. Also, the total discharge data based on the Precipitation-Runoff Modeling System (PRMS and the in situ discharge for major five river basins in South Korea show comparable seasonality and high correlation with the satellite-based discharge. In spite of the relatively low spatial resolution of GRACE, and loss of information incurred during the process of integrating three different satellite products, the proposed methodology can be a practical tool to estimate the total discharge with reasonable accuracy, especially in a region with scarce hydrologic data.

  11. Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

    Science.gov (United States)

    Albergel, Clément; Munier, Simon; Leroux, Delphine Jennifer; Dewaele, Hélène; Fairbairn, David; Lavinia Barbu, Alina; Gelati, Emiliano; Dorigo, Wouter; Faroux, Stéphanie; Meurey, Catherine; Le Moigne, Patrick; Decharme, Bertrand; Mahfouf, Jean-Francois; Calvet, Jean-Christophe

    2017-10-01

    In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil-biosphere-atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000-2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of

  12. Towards Improving Satellite Tropospheric NO2 Retrieval Products: Impacts of the spatial resolution and lighting NOx production from the a priori chemical transport model

    Science.gov (United States)

    Smeltzer, C. D.; Wang, Y.; Zhao, C.; Boersma, F.

    2009-12-01

    Polar orbiting satellite retrievals of tropospheric nitrogen dioxide (NO2) columns are important to a variety of scientific applications. These NO2 retrievals rely on a priori profiles from chemical transport models and radiative transfer models to derive the vertical columns (VCs) from slant columns measurements. In this work, we compare the retrieval results using a priori profiles from a global model (TM4) and a higher resolution regional model (REAM) at the OMI overpass hour of 1330 local time, implementing the Dutch OMI NO2 (DOMINO) retrieval. We also compare the retrieval results using a priori profiles from REAM model simulations with and without lightning NOx (NO + NO2) production. A priori model resolution and lightning NOx production are both found to have large impact on satellite retrievals by altering the satellite sensitivity to a particular observation by shifting the NO2 vertical distribution interpreted by the radiation model. The retrieved tropospheric NO2 VCs may increase by 25-100% in urban regions and be reduced by 50% in rural regions if the a priori profiles from REAM simulations are used during the retrievals instead of the profiles from TM4 simulations. The a priori profiles with lightning NOx may result in a 25-50% reduction of the retrieved tropospheric NO2 VCs compared to the a priori profiles without lightning. As first priority, a priori vertical NO2 profiles from a chemical transport model with a high resolution, which can better simulate urban-rural NO2 gradients in the boundary layer and make use of observation-based parameterizations of lightning NOx production, should be first implemented to obtain more accurate NO2 retrievals over the United States, where NOx source regions are spatially separated and lightning NOx production is significant. Then as consequence of a priori NO2 profile variabilities resulting from lightning and model resolution dynamics, geostationary satellite, daylight observations would further promote the next

  13. Satellite methods underestimate indirect climate forcing by aerosols

    Science.gov (United States)

    Penner, Joyce E.; Xu, Li; Wang, Minghuai

    2011-01-01

    Satellite-based estimates of the aerosol indirect effect (AIE) are consistently smaller than the estimates from global aerosol models, and, partly as a result of these differences, the assessment of this climate forcing includes large uncertainties. Satellite estimates typically use the present-day (PD) relationship between observed cloud drop number concentrations (Nc) and aerosol optical depths (AODs) to determine the preindustrial (PI) values of Nc. These values are then used to determine the PD and PI cloud albedos and, thus, the effect of anthropogenic aerosols on top of the atmosphere radiative fluxes. Here, we use a model with realistic aerosol and cloud processes to show that empirical relationships for ln(Nc) versus ln(AOD) derived from PD results do not represent the atmospheric perturbation caused by the addition of anthropogenic aerosols to the preindustrial atmosphere. As a result, the model estimates based on satellite methods of the AIE are between a factor of 3 to more than a factor of 6 smaller than model estimates based on actual PD and PI values for Nc. Using ln(Nc) versus ln(AI) (Aerosol Index, or the optical depth times angstrom exponent) to estimate preindustrial values for Nc provides estimates for Nc and forcing that are closer to the values predicted by the model. Nevertheless, the AIE using ln(Nc) versus ln(AI) may be substantially incorrect on a regional basis and may underestimate or overestimate the global average forcing by 25 to 35%. PMID:21808047

  14. Retrieving global aerosol sources from satellites using inverse modeling

    Directory of Open Access Journals (Sweden)

    O. Dubovik

    2008-01-01

    Full Text Available Understanding aerosol effects on global climate requires knowing the global distribution of tropospheric aerosols. By accounting for aerosol sources, transports, and removal processes, chemical transport models simulate the global aerosol distribution using archived meteorological fields. We develop an algorithm for retrieving global aerosol sources from satellite observations of aerosol distribution by inverting the GOCART aerosol transport model.

    The inversion is based on a generalized, multi-term least-squares-type fitting, allowing flexible selection and refinement of a priori algorithm constraints. For example, limitations can be placed on retrieved quantity partial derivatives, to constrain global aerosol emission space and time variability in the results. Similarities and differences between commonly used inverse modeling and remote sensing techniques are analyzed. To retain the high space and time resolution of long-period, global observational records, the algorithm is expressed using adjoint operators.

    Successful global aerosol emission retrievals at 2°×2.5 resolution were obtained by inverting GOCART aerosol transport model output, assuming constant emissions over the diurnal cycle, and neglecting aerosol compositional differences. In addition, fine and coarse mode aerosol emission sources were inverted separately from MODIS fine and coarse mode aerosol optical thickness data, respectively. These assumptions are justified, based on observational coverage and accuracy limitations, producing valuable aerosol source locations and emission strengths. From two weeks of daily MODIS observations during August 2000, the global placement of fine mode aerosol sources agreed with available independent knowledge, even though the inverse method did not use any a priori information about aerosol sources, and was initialized with a "zero aerosol emission" assumption. Retrieving coarse mode aerosol emissions was less successful

  15. Integrating satellite imagery with simulation modeling to improve burn severity mapping

    Science.gov (United States)

    Eva C. Karau; Pamela G. Sikkink; Robert E. Keane; Gregory K. Dillon

    2014-01-01

    Both satellite imagery and spatial fire effects models are valuable tools for generating burn severity maps that are useful to fire scientists and resource managers. The purpose of this study was to test a new mapping approach that integrates imagery and modeling to create more accurate burn severity maps. We developed and assessed a statistical model that combines the...

  16. Quality Improvement of the Satellite Soil Moisture Products by Fusing In Situ and GNSS-R Observation

    Science.gov (United States)

    Yuan, Q.; Xu, H.; Li, T.; Shen, H.; Zhang, L.

    2017-12-01

    Soil moisture plays a fundamental role in the hydrological cycle as well as in the energy partitioning. On this basis, it is of great concern to derive a long-term soil moisture time series on a global scale and monitor its temporal and spatial variations for practical applications. Although passive and active microwave satellites have been shown to provide useful retrievals of near-surface soil moisture at regional and global scales, the limitations in retrieval accuracy prevent them from high-quality applications in specific areas. On the other hand, measuring soil moisture straightly through in situdevices, such as soil moisture probes, is high accuracy, but is not able to derive global soil moisture maps. Recently, the ground-based GNSS-R method is emerging in monitoring near-surface soil moisture variations but still over limited spatial scales. In this paper, a multi-source data fusion method was applied to synthesize regional high-quality soil moisture products from 2015 to 2017 in western parts of the continental United States. Firstly, we put all the three soil moisture datasets into the generalized regression neural network (GRNN) model. The input signals of the model are SMOS and SMAP satellite-derived passive level 3 soil moisture daily products combined with date and latitude and longitude information, while the in situ measured and GNSS-R retrieved soil moisture are used as target. Finally, we apply the model to all the soil moisture time series in the experiment area and obtain two high-quality regional soil moisture products for SMOS and SMAP, respectively. The results before fusion show that the correlation coefficients between site-specific soil moisture and satellite-derived soil moisture are 0.39 for SMOS and 0.27 for SMAP and that unbiased root-mean-square errors (ubRMSE) are 0.113 for SMOS and 0.128 for SMAP, respectively. After applying the GRNN-R, the model fitted correlation coefficients have reached 0.72 for SMOS and 0.75 for SMAP and the

  17. Space transportation. [user needs met by information derived from satellites and the interface with space transportation systems

    Science.gov (United States)

    1975-01-01

    User-oriented panels were formed to examine practical applications of information or services derived from earth orbiting satellites. Topics discussed include: weather and climate; uses of communication; land use planning; agriculture, forest, and range; inland water resources; retractable resources; environmental quality; marine and maritime uses; and materials processing in space. Emphasis was placed on the interface of the space transportation system (STS) with the applications envisioned by the user panels. User requirements were compared with expected STS capabilities in terms of availability, carrying payload to orbit, and estimated costs per launch. Conclusions and recommendations were reported.

  18. Estimation of time-series properties of gourd observed solar irradiance data using cloud properties derived from satellite observations

    Science.gov (United States)

    Watanabe, T.; Nohara, D.

    2017-12-01

    The shorter temporal scale variation in the downward solar irradiance at the ground level (DSI) is not understood well because researches in the shorter-scale variation in the DSI is based on the ground observation and ground observation stations are located coarsely. Use of dataset derived from satellite observation will overcome such defect. DSI data and MODIS cloud properties product are analyzed simultaneously. Three metrics: mean, standard deviation and sample entropy, are used to evaluate time-series properties of the DSI. Three metrics are computed from two-hours time-series centered at the observation time of MODIS over the ground observation stations. We apply the regression methods to design prediction models of each three metrics from cloud properties. The validation of the model accuracy show that mean and standard deviation are predicted with a higher degree of accuracy and that the accuracy of prediction of sample entropy, which represents the complexity of time-series, is not high. One of causes of lower prediction skill of sample entropy is the resolution of the MODIS cloud properties. Higher sample entropy is corresponding to the rapid fluctuation, which is caused by the small and unordered cloud. It seems that such clouds isn't retrieved well.

  19. Thermal imbalance force modelling for a GPS satellite using the finite element method

    Science.gov (United States)

    Vigue, Yvonne; Schutz, Bob E.

    1991-01-01

    Methods of analyzing the perturbation due to thermal radiation and determining its effects on the orbits of GPS satellites are presented, with emphasis on the FEM technique to calculate satellite solar panel temperatures which are used to determine the magnitude and direction of the thermal imbalance force. Although this force may not be responsible for all of the force mismodeling, conditions may work in combination with the thermal imbalance force to produce such accelerations on the order of 1.e-9 m/sq s. If submeter accurate orbits and centimeter-level accuracy for geophysical applications are desired, a time-dependent model of the thermal imbalance force should be used, especially when satellites are eclipsing, where the observed errors are larger than for satellites in noneclipsing orbits.

  20. Effects of solar radiation pressure torque on the rotational motion of an artificial satellite

    Science.gov (United States)

    Zanardi, Maria Cecilia F. P. S.; Vilhenademoraes, Rodolpho

    1992-01-01

    The motion of an artificial satellite about its center of mass is studied considering torques due to the gravity gradient and direct solar radiation pressure. A model for direct solar radiation torque is derived for a circular cylindrical satellite. An analytical solution is obtained by the method of variation of the parameters. This solution shows that the angular variables have secular variation but that the modulus of the rotational angular momentum, the projection of rotational angular momentum on the z axis of the moment of inertia and inertial axis z, suffer only periodic variations. Considering a hypothetical artificial satellite, a numerical application is demonstrated.

  1. Prediction of Communication Outage Period between Satellite and Earth station Due to Sun Interference

    Directory of Open Access Journals (Sweden)

    Yongjun Song

    2010-03-01

    Full Text Available We developed a computer program to predict solar interference period. To calculate Sun‘s position, we used DE406 ephemerides and Earth ellipsoid model. The Sun‘s position error is smaller than 10arcsec. For the verification of the calculation, we used TU media ground station on Seongsu-dong, and MBSAT geostationary communication satellite. We analysis errors, due to satellite perturbation and antenna align. The time error due to antenna align has -35 to +16 seconds at 0.1 degree, and -27 to +41 seconds at 0.25 degree. The time errors derived by satellite perturbation has 30 to 60 seconds.

  2. Multi-Satellite MIMO Communications at Ku-Band and Above: Investigations on Spatial Multiplexing for Capacity Improvement and Selection Diversity for Interference Mitigation

    Directory of Open Access Journals (Sweden)

    Liolis Konstantinos P

    2007-01-01

    Full Text Available This paper investigates the applicability of multiple-input multiple-output (MIMO technology to satellite communications at the Ku-band and above. After introducing the possible diversity sources to form a MIMO matrix channel in a satellite environment, particular emphasis is put on satellite diversity. Two specific different topics from the field of MIMO technology applications to satellite communications at these frequencies are further analyzed: (i capacity improvement achieved by MIMO spatial multiplexing systems and (ii interference mitigation achieved by MIMO diversity systems employing receive antenna selection. In the first case, a single-user capacity analysis of a satellite MIMO spatial multiplexing system is presented and a useful analytical closed form expression is derived for the outage capacity achieved. In the second case, a satellite MIMO diversity system with receive antenna selection is considered, adjacent satellite cochannel interference on its forward link is studied and an analytical model predicting the interference mitigation achieved is presented. In both cases, an appropriate physical MIMO channel model is assumed which takes into account the propagation phenomena related to the frequencies of interest, such as clear line-of-sight operation, high antenna directivity, the effect of rain fading, and the slant path lengths difference. Useful numerical results obtained through the analytical expressions derived are presented to compare the performance of multi-satellite MIMO systems to relevant single-input single-output (SISO ones.

  3. DOA estimation for attitude determination on communication satellites

    Directory of Open Access Journals (Sweden)

    Yang Bin

    2014-06-01

    Full Text Available In order to determine an appropriate attitude of three-axis stabilized communication satellites, this paper describes a novel attitude determination method using direction of arrival (DOA estimation of a ground signal source. It differs from optical measurement, magnetic field measurement, inertial measurement, and global positioning system (GPS attitude determination. The proposed method is characterized by taking the ground signal source as the attitude reference and acquiring attitude information from DOA estimation. Firstly, an attitude measurement equation with DOA estimation is derived in detail. Then, the error of the measurement equation is analyzed. Finally, an attitude determination algorithm is presented using a dynamic model, the attitude measurement equation, and measurement errors. A developing low Earth orbit (LEO satellite which tests mobile communication technology with smart antennas can be stabilized in three axes by corporately using a magnetometer, reaction wheels, and three-axis magnetorquer rods. Based on the communication satellite, simulation results demonstrate the effectiveness of the method. The method could be a backup of attitude determination to prevent a system failure on the satellite. Its precision depends on the number of snapshots and the input signal-to-noise ratio (SNR with DOA estimation.

  4. Using an Altimeter-Derived Internal Tide Model to Remove Tides from in Situ Data

    Science.gov (United States)

    Zaron, Edward D.; Ray, Richard D.

    2017-01-01

    Internal waves at tidal frequencies, i.e., the internal tides, are a prominent source of variability in the ocean associated with significant vertical isopycnal displacements and currents. Because the isopycnal displacements are caused by ageostrophic dynamics, they contribute uncertainty to geostrophic transport inferred from vertical profiles in the ocean. Here it is demonstrated that a newly developed model of the main semidiurnal (M2) internal tide derived from satellite altimetry may be used to partially remove the tide from vertical profile data, as measured by the reduction of steric height variance inferred from the profiles. It is further demonstrated that the internal tide model can account for a component of the near-surface velocity as measured by drogued drifters. These comparisons represent a validation of the internal tide model using independent data and highlight its potential use in removing internal tide signals from in situ observations.

  5. A new stochastic model considering satellite clock interpolation errors in precise point positioning

    Science.gov (United States)

    Wang, Shengli; Yang, Fanlin; Gao, Wang; Yan, Lizi; Ge, Yulong

    2018-03-01

    Precise clock products are typically interpolated based on the sampling interval of the observational data when they are used for in precise point positioning. However, due to the occurrence of white noise in atomic clocks, a residual component of such noise will inevitable reside within the observations when clock errors are interpolated, and such noise will affect the resolution of the positioning results. In this paper, which is based on a twenty-one-week analysis of the atomic clock noise characteristics of numerous satellites, a new stochastic observation model that considers satellite clock interpolation errors is proposed. First, the systematic error of each satellite in the IGR clock product was extracted using a wavelet de-noising method to obtain the empirical characteristics of atomic clock noise within each clock product. Then, based on those empirical characteristics, a stochastic observation model was structured that considered the satellite clock interpolation errors. Subsequently, the IGR and IGS clock products at different time intervals were used for experimental validation. A verification using 179 stations worldwide from the IGS showed that, compared with the conventional model, the convergence times using the stochastic model proposed in this study were respectively shortened by 4.8% and 4.0% when the IGR and IGS 300-s-interval clock products were used and by 19.1% and 19.4% when the 900-s-interval clock products were used. Furthermore, the disturbances during the initial phase of the calculation were also effectively improved.

  6. Determining the Uncertainties in Prescribed Burn Emissions Through Comparison of Satellite Estimates to Ground-based Estimates and Air Quality Model Evaluations in Southeastern US

    Science.gov (United States)

    Odman, M. T.; Hu, Y.; Russell, A. G.

    2016-12-01

    Prescribed burning is practiced throughout the US, and most widely in the Southeast, for the purpose of maintaining and improving the ecosystem, and reducing the wildfire risk. However, prescribed burn emissions contribute significantly to the of trace gas and particulate matter loads in the atmosphere. In places where air quality is already stressed by other anthropogenic emissions, prescribed burns can lead to major health and environmental problems. Air quality modeling efforts are under way to assess the impacts of prescribed burn emissions. Operational forecasts of the impacts are also emerging for use in dynamic management of air quality as well as the burns. Unfortunately, large uncertainties exist in the process of estimating prescribed burn emissions and these uncertainties limit the accuracy of the burn impact predictions. Prescribed burn emissions are estimated by using either ground-based information or satellite observations. When there is sufficient local information about the burn area, the types of fuels, their consumption amounts, and the progression of the fire, ground-based estimates are more accurate. In the absence of such information satellites remain as the only reliable source for emission estimation. To determine the level of uncertainty in prescribed burn emissions, we compared estimates derived from a burn permit database and other ground-based information to the estimates by the Biomass Burning Emissions Product derived from a constellation of NOAA and NASA satellites. Using these emissions estimates we conducted simulations with the Community Multiscale Air Quality (CMAQ) model and predicted trace gas and particulate matter concentrations throughout the Southeast for two consecutive burn seasons (2015 and 2016). In this presentation, we will compare model predicted concentrations to measurements at monitoring stations and evaluate if the differences are commensurate with our emission uncertainty estimates. We will also investigate if

  7. Satellite switched FDMA advanced communication technology satellite program

    Science.gov (United States)

    Atwood, S.; Higton, G. H.; Wood, K.; Kline, A.; Furiga, A.; Rausch, M.; Jan, Y.

    1982-01-01

    The satellite switched frequency division multiple access system provided a detailed system architecture that supports a point to point communication system for long haul voice, video and data traffic between small Earth terminals at Ka band frequencies at 30/20 GHz. A detailed system design is presented for the space segment, small terminal/trunking segment at network control segment for domestic traffic model A or B, each totaling 3.8 Gb/s of small terminal traffic and 6.2 Gb/s trunk traffic. The small terminal traffic (3.8 Gb/s) is emphasized, for the satellite router portion of the system design, which is a composite of thousands of Earth stations with digital traffic ranging from a single 32 Kb/s CVSD voice channel to thousands of channels containing voice, video and data with a data rate as high as 33 Mb/s. The system design concept presented, effectively optimizes a unique frequency and channelization plan for both traffic models A and B with minimum reorganization of the satellite payload transponder subsystem hardware design. The unique zoning concept allows multiple beam antennas while maximizing multiple carrier frequency reuse. Detailed hardware design estimates for an FDMA router (part of the satellite transponder subsystem) indicate a weight and dc power budget of 353 lbs, 195 watts for traffic model A and 498 lbs, 244 watts for traffic model B.

  8. Impact of the assimilation of satellite soil moisture and LST on the hydrological cycle

    Science.gov (United States)

    Laiolo, Paola; Gabellani, Simone; Delogu, Fabio; Silvestro, Francesco; Rudari, Roberto; Campo, Lorenzo; Boni, Giorgio

    2014-05-01

    The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce ground based data. The aim of this work is to investigate the impacts on the performances of a distributed hydrological model (Continuum) of the assimilation of satellite-derived soil moisture products and Land Surface (LST). In this work three different soil moisture (SM) products, derived by ASCAT sensor, are used. These data are provided by the EUMETSAT's H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) program. The considered soil moisture products are: large scale surface soil moisture (SM OBS 1 - H07), small scale surface soil moisture (SM OBS 2 - H08) and profile index in the roots region (SM DAS 2 - H14). These data are compared with soil moisture estimated by Continuum model on the Orba catchment (800 km2), in the northern part of Italy, for the period July 2012-June 2013. Different assimilation experiments have been performed. The first experiment consists in the assimilation of the SM products by using a simple Nudging technique; the second one is the assimilation of only LST data, derived from MSG satellite, and the third is the assimilation of both SM products and LST. The benefits on the model predictions of discharge, LST and soil moisture dynamics were tested.

  9. Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral World View-2 satellite data. Gridded (5 m cell size) multibeam bathymetry...

  10. Bird migration and avian influenza: a comparison of hydrogen stable isotopes and satellite tracking methods

    Science.gov (United States)

    Bridge, Eli S.; Kelly, Jeffrey F.; Xiao, Xiangming; Takekawa, John Y.; Hill, Nichola J.; Yamage, Mat; Haque, Enam Ul; Islam, Mohammad Anwarul; Mundkur, Taej; Yavuz, Kiraz Erciyas; Leader, Paul; Leung, Connie Y.H.; Smith, Bena; Spragens, Kyle A.; Vandegrift, Kurt J.; Hosseini, Parviez R.; Saif, Samia; Mohsanin, Samiul; Mikolon, Andrea; Islam, Ausrafal; George, Acty; Sivananinthaperumal, Balachandran; Daszak, Peter; Newman, Scott H.

    2014-01-01

    Satellite-based tracking of migratory waterfowl is an important tool for understanding the potential role of wild birds in the long-distance transmission of highly pathogenic avian influenza. However, employing this technique on a continental scale is prohibitively expensive. This study explores the utility of stable isotope ratios in feathers in examining both the distances traveled by migratory birds and variation in migration behavior. We compared the satellite-derived movement data of 22 ducks from 8 species captured at wintering areas in Bangladesh, Turkey, and Hong Kong with deuterium ratios (δD) in the feathers of these and other individuals captured at the same locations. We derived likely molting locations from the satellite tracking data and generated expected isotope ratios based on an interpolated map of δD in rainwater. Although δD was correlated with the distance between wintering and molting locations, surprisingly, measured δD values were not correlated with either expected values or latitudes of molting sites. However, population-level parameters derived from the satellite-tracking data, such as mean distance between wintering and molting locations and variation in migration distance, were reflected by means and variation of the stable isotope values. Our findings call into question the relevance of the rainfall isotope map for Asia for linking feather isotopes to molting locations, and underscore the need for extensive ground truthing in the form of feather-based isoscapes. Nevertheless, stable isotopes from feathers could inform disease models by characterizing the degree to which regional breeding populations interact at common wintering locations. Feather isotopes also could aid in surveying wintering locations to determine where high-resolution tracking techniques (e.g. satellite tracking) could most effectively be employed. Moreover, intrinsic markers such as stable isotopes offer the only means of inferring movement information from

  11. The Stackelberg Model for a Leader of Production and Many Satellites

    Directory of Open Access Journals (Sweden)

    Catalin Angelo Ioan

    2015-05-01

    Full Text Available Oligopoly is a market situation where there are a small number of bidders (at least two of a good non-substituent and a sufficient number of consumers. The paper analyses the Stackelberg model for a leader of production and many satellites. There are obtained the equilibrium productions, maximum profits and sales price where one of the company is the leader of quantity, and other satellites. There are also survey the situations where the firm based on its marginal cost of production can effectively take the lead of production.

  12. Validation of satellite SAR offshore wind speed maps to in-situ data, microscale and mesoscale model results

    DEFF Research Database (Denmark)

    Hasager, C.B.; Astrup, Poul; Barthelmie, R.J.

    2002-01-01

    the assumption of no error in the SAR wind speed maps and for an uncertainty of ± 10% at a confidence level of 90%. Around 100 satellite SAR scenes may be available for some sites on Earth but far few at other sites. Currently the numberof available satellite SAR scenes is increasing rapidly with ERS-2, RADARSAT......A validation study has been performed in order to investigate the precision and accuracy of the satellite-derived ERS-2 SAR wind products in offshore regions. The overall project goal is to develop a method for utilizing the satellite wind speed maps foroffshore wind resources, e.g. in future...... band in which the SAR wind speed observations have a strong negative bias. The bathymetry of Horns Rev combined with tidal currents give rise to bias in the SAR wind speed maps near areas of shallow, complex bottom topography in some cases. Atotal of 16 cases were analyzed for Horns Rev. For Maddalena...

  13. Analysis of Multipath Mitigation Techniques with Land Mobile Satellite Channel Model

    Directory of Open Access Journals (Sweden)

    M. Z. H. Bhuiyan J. Zhang

    2012-12-01

    Full Text Available Multipath is undesirable for Global Navigation Satellite System (GNSS receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this is of utmost importance to analyze the performance of different multipath mitigation techniques in some realistic measurement-based channel models, for example, the Land Multipath is undesirable for Global Navigation Satellite System (GNSS receivers, since the reception of multipath can create a significant distortion to the shape of the correlation function leading to an error in the receivers’ position estimate. Many multipath mitigation techniques exist in the literature to deal with the multipath propagation problem in the context of GNSS. The multipath studies in the literature are often based on optimistic assumptions, for example, assuming a static two-path channel or a fading channel with a Rayleigh or a Nakagami distribution. But, in reality, there are a lot of channel modeling issues, for example, satellite-to-user geometry, variable number of paths, variable path delays and gains, Non Line-Of-Sight (NLOS path condition, receiver movements, etc. that are kept out of consideration when analyzing the performance of these techniques. Therefore, this

  14. A satellite simulator for TRMM PR applied to climate model simulations

    Science.gov (United States)

    Spangehl, T.; Schroeder, M.; Bodas-Salcedo, A.; Hollmann, R.; Riley Dellaripa, E. M.; Schumacher, C.

    2017-12-01

    Climate model simulations have to be compared against observation based datasets in order to assess their skill in representing precipitation characteristics. Here we use a satellite simulator for TRMM PR in order to evaluate simulations performed with MPI-ESM (Earth system model of the Max Planck Institute for Meteorology in Hamburg, Germany) performed within the MiKlip project (https://www.fona-miklip.de/, funded by Federal Ministry of Education and Research in Germany). While classical evaluation methods focus on geophysical parameters such as precipitation amounts, the application of the satellite simulator enables an evaluation in the instrument's parameter space thereby reducing uncertainties on the reference side. The CFMIP Observation Simulator Package (COSP) provides a framework for the application of satellite simulators to climate model simulations. The approach requires the introduction of sub-grid cloud and precipitation variability. Radar reflectivities are obtained by applying Mie theory, with the microphysical assumptions being chosen to match the atmosphere component of MPI-ESM (ECHAM6). The results are found to be sensitive to the methods used to distribute the convective precipitation over the sub-grid boxes. Simple parameterization methods are used to introduce sub-grid variability of convective clouds and precipitation. In order to constrain uncertainties a comprehensive comparison with sub-grid scale convective precipitation variability which is deduced from TRMM PR observations is carried out.

  15. Improved Satellite-based Photosysnthetically Active Radiation (PAR) for Air Quality Studies

    Science.gov (United States)

    Pour Biazar, A.; McNider, R. T.; Cohan, D. S.; White, A.; Zhang, R.; Dornblaser, B.; Doty, K.; Wu, Y.; Estes, M. J.

    2015-12-01

    One of the challenges in understanding the air quality over forested regions has been the uncertainties in estimating the biogenic hydrocarbon emissions. Biogenic volatile organic compounds, BVOCs, play a critical role in atmospheric chemistry, particularly in ozone and particulate matter (PM) formation. In southeastern United States, BVOCs (mostly as isoprene) are the dominant summertime source of reactive hydrocarbon. Despite significant efforts in improving BVOC estimates, the errors in emission inventories remain a concern. Since BVOC emissions are particularly sensitive to the available photosynthetically active radiation (PAR), model errors in PAR result in large errors in emission estimates. Thus, utilization of satellite observations to estimate PAR can help in reducing emission uncertainties. Satellite-based PAR estimates rely on the technique used to derive insolation from satellite visible brightness measurements. In this study we evaluate several insolation products against surface pyranometer observations and offer a bias correction to generate a more accurate PAR product. The improved PAR product is then used in biogenic emission estimates. The improved biogenic emission estimates are compared to the emission inventories over Texas and used in air quality simulation over the period of August-September 2013 (NASA's Discover-AQ field campaign). A series of sensitivity simulations will be performed and evaluated against Discover-AQ observations to test the impact of satellite-derived PAR on air quality simulations.

  16. Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite data. Gridded (5 m cell size)...

  17. Simultaneous assimilation of ozone profiles from multiple UV-VIS satellite instruments

    Science.gov (United States)

    van Peet, Jacob C. A.; van der A, Ronald J.; Kelder, Hennie M.; Levelt, Pieternel F.

    2018-02-01

    A three-dimensional global ozone distribution has been derived from assimilation of ozone profiles that were observed by satellites. By simultaneous assimilation of ozone profiles retrieved from the nadir looking satellite instruments Global Ozone Monitoring Experiment 2 (GOME-2) and Ozone Monitoring Instrument (OMI), which measure the atmosphere at different times of the day, the quality of the derived atmospheric ozone field has been improved. The assimilation is using an extended Kalman filter in which chemical transport model TM5 has been used for the forecast. The combined assimilation of both GOME-2 and OMI improves upon the assimilation results of a single sensor. The new assimilation system has been demonstrated by processing 4 years of data from 2008 to 2011. Validation of the assimilation output by comparison with sondes shows that biases vary between -5 and +10 % between the surface and 100 hPa. The biases for the combined assimilation vary between -3 and +3 % in the region between 100 and 10 hPa where GOME-2 and OMI are most sensitive. This is a strong improvement compared to direct retrievals of ozone profiles from satellite observations.

  18. PROBLEMS AND LIMITATIONS OF SATELLITE IMAGE ORIENTATION FOR DETERMINATION OF HEIGHT MODELS

    Directory of Open Access Journals (Sweden)

    K. Jacobsen

    2017-05-01

    Full Text Available The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC. The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3, WorldView-2 (WV2, Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs. The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the

  19. Problems and Limitations of Satellite Image Orientation for Determination of Height Models

    Science.gov (United States)

    Jacobsen, K.

    2017-05-01

    The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC). The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py) for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3), WorldView-2 (WV2), Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs). The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the object height

  20. SpaceWire model development technology for satellite architecture.

    Energy Technology Data Exchange (ETDEWEB)

    Eldridge, John M.; Leemaster, Jacob Edward; Van Leeuwen, Brian P.

    2011-09-01

    Packet switched data communications networks that use distributed processing architectures have the potential to simplify the design and development of new, increasingly more sophisticated satellite payloads. In addition, the use of reconfigurable logic may reduce the amount of redundant hardware required in space-based applications without sacrificing reliability. These concepts were studied using software modeling and simulation, and the results are presented in this report. Models of the commercially available, packet switched data interconnect SpaceWire protocol were developed and used to create network simulations of data networks containing reconfigurable logic with traffic flows for timing system distribution.

  1. Patchiness in semi-arid dwarf shrublands: evidence from satellite ...

    African Journals Online (AJOL)

    ... Plants; Remote sensing; Rhigozum obovatum Burch; Satellite-derived vegetation indices; Woody species; patchiness; semi-arid; dwarf shrubland; shrublands; co2; assimilation; karoo; south africa; ndvi; satellite imagery; geochemical mound; rhigozum obovatum; eriocephalus ericoides; pentzia incana; vegetation; botany

  2. Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

    Directory of Open Access Journals (Sweden)

    C. Albergel

    2017-10-01

    Full Text Available In this study, a global land data assimilation system (LDAS-Monde is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM and leaf area index (LAI observations to constrain the interactions between soil–biosphere–atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere land surface model (LSM coupled with the CNRM (Centre National de Recherches Météorologiques version of the Total Runoff Integrating Pathways (ISBA-CTRIP continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF, which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth. A sensitivity test of the Jacobians over 2000–2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm. The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A

  3. Mobile satellite communications in the 1990's

    Science.gov (United States)

    Singh, Jai

    1992-07-01

    The evolution of Inmarsat global services from a single market and single service of the 1980's to all of the key mobile markets and a wide range of new terminals and services in the 1990's is described. An overview of existing mobile satellite services, as well as new services under implementation for introduction in the near and longer term, including a handheld satellite phone (Inmarsat-P), is provided. The initiative taken by Inmarsat in the integration of its global mobile satellite services with global navigation capability derived from GPS (Global Positioning System) and the GLONASS (Russian GPS) navigation satellite systems and the provision of an international civil overlay for GPS/GLONASS integrity and augmentation is highlighted. To complete the overview of the development of mobile satellite services in the 1990's, the known national and regional mobile satellite system plans and the various recent proposals for both orbiting and geostationary satellite systems for proving handheld satellite phone and/or data messaging services are described.

  4. Real Time Fire Reconnaissance Satellite Monitoring System Failure Model

    Science.gov (United States)

    Nino Prieto, Omar Ariosto; Colmenares Guillen, Luis Enrique

    2013-09-01

    In this paper the Real Time Fire Reconnaissance Satellite Monitoring System is presented. This architecture is a legacy of the Detection System for Real-Time Physical Variables which is undergoing a patent process in Mexico. The methodologies for this design are the Structured Analysis for Real Time (SA- RT) [8], and the software is carried out by LACATRE (Langage d'aide à la Conception d'Application multitâche Temps Réel) [9,10] Real Time formal language. The system failures model is analyzed and the proposal is based on the formal language for the design of critical systems and Risk Assessment; AltaRica. This formal architecture uses satellites as input sensors and it was adapted from the original model which is a design pattern for physical variation detection in Real Time. The original design, whose task is to monitor events such as natural disasters and health related applications, or actual sickness monitoring and prevention, as the Real Time Diabetes Monitoring System, among others. Some related work has been presented on the Mexican Space Agency (AEM) Creation and Consultation Forums (2010-2011), and throughout the International Mexican Aerospace Science and Technology Society (SOMECYTA) international congress held in San Luis Potosí, México (2012). This Architecture will allow a Real Time Fire Satellite Monitoring, which will reduce the damage and danger caused by fires which consumes the forests and tropical forests of Mexico. This new proposal, permits having a new system that impacts on disaster prevention, by combining national and international technologies and cooperation for the benefit of humankind.

  5. Global distribution of urban parameters derived from high-resolution global datasets for weather modelling

    Science.gov (United States)

    Kawano, N.; Varquez, A. C. G.; Dong, Y.; Kanda, M.

    2016-12-01

    Numerical model such as Weather Research and Forecasting model coupled with single-layer Urban Canopy Model (WRF-UCM) is one of the powerful tools to investigate urban heat island. Urban parameters such as average building height (Have), plain area index (λp) and frontal area index (λf), are necessary inputs for the model. In general, these parameters are uniformly assumed in WRF-UCM but this leads to unrealistic urban representation. Distributed urban parameters can also be incorporated into WRF-UCM to consider a detail urban effect. The problem is that distributed building information is not readily available for most megacities especially in developing countries. Furthermore, acquiring real building parameters often require huge amount of time and money. In this study, we investigated the potential of using globally available satellite-captured datasets for the estimation of the parameters, Have, λp, and λf. Global datasets comprised of high spatial resolution population dataset (LandScan by Oak Ridge National Laboratory), nighttime lights (NOAA), and vegetation fraction (NASA). True samples of Have, λp, and λf were acquired from actual building footprints from satellite images and 3D building database of Tokyo, New York, Paris, Melbourne, Istanbul, Jakarta and so on. Regression equations were then derived from the block-averaging of spatial pairs of real parameters and global datasets. Results show that two regression curves to estimate Have and λf from the combination of population and nightlight are necessary depending on the city's level of development. An index which can be used to decide which equation to use for a city is the Gross Domestic Product (GDP). On the other hand, λphas less dependence on GDP but indicated a negative relationship to vegetation fraction. Finally, a simplified but precise approximation of urban parameters through readily-available, high-resolution global datasets and our derived regressions can be utilized to estimate a

  6. Extracting Ocean-Generated Tidal Magnetic Signals from Swarm Data Through Satellite Gradiometry

    Science.gov (United States)

    Sabaka, Terence J.; Tyler, Robert H.; Olsen, Nils

    2016-01-01

    Ocean-generated magnetic field models of the Principal Lunar, M2, and the Larger Lunar elliptic, N2, semidiurnal tidal constituents were estimated through a "Comprehensive Inversion" of the first 20.5 months of magnetic measurements from European Space Agency's (ESA) Swarm satellite constellation mission. While the constellation provides important north-south along-track gradiometry information, it is the unique low-spacecraft pair that allows for east-west cross-track gradiometry. This latter type is crucial in delivering an M2 estimate of similar quality with that derived from over 10 years of CHAMP satellite data but over a shorter interval, at higher altitude, and during more magnetically disturbed conditions. Recovered N2 contains nonoceanic signal but is highly correlated with theoretical models in regions of maximum oceanic amplitude. Thus, satellite magnetic gradiometry may eventually enable the monitoring of ocean electrodynamic properties at temporal resolutions of 1 to 2 years, which may have important implications for the inference of ocean temperature and salinity.

  7. Comparisons of aerosol optical depth provided by seviri satellite observations and CAMx air quality modelling

    Science.gov (United States)

    Fernandes, A.; Riffler, M.; Ferreira, J.; Wunderle, S.; Borrego, C.; Tchepel, O.

    2015-04-01

    Satellite data provide high spatial coverage and characterization of atmospheric components for vertical column. Additionally, the use of air pollution modelling in combination with satellite data opens the challenging perspective to analyse the contribution of different pollution sources and transport processes. The main objective of this work is to study the AOD over Portugal using satellite observations in combination with air pollution modelling. For this purpose, satellite data provided by Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) on-board the geostationary Meteosat-9 satellite on AOD at 550 nm and modelling results from the Chemical Transport Model (CAMx - Comprehensive Air quality Model) were analysed. The study period was May 2011 and the aim was to analyse the spatial variations of AOD over Portugal. In this study, a multi-temporal technique to retrieve AOD over land from SEVIRI was used. The proposed method takes advantage of SEVIRI's high temporal resolution of 15 minutes and high spatial resolution. CAMx provides the size distribution of each aerosol constituent among a number of fixed size sections. For post processing, CAMx output species per size bin have been grouped into total particulate sulphate (PSO4), total primary and secondary organic aerosols (POA + SOA), total primary elemental carbon (PEC) and primary inert material per size bin (CRST1 to CRST_4) to be used in AOD quantification. The AOD was calculated by integration of aerosol extinction coefficient (Qext) on the vertical column. The results were analysed in terms of temporal and spatial variations. The analysis points out that the implemented methodology provides a good spatial agreement between modelling results and satellite observation for dust outbreak studied (10th -17th of May 2011). A correlation coefficient of r=0.79 was found between the two datasets. This work provides relevant background to start the integration of these two different types of the data in order

  8. Nonlinear electromechanical modelling and dynamical behavior analysis of a satellite reaction wheel

    Science.gov (United States)

    Aghalari, Alireza; Shahravi, Morteza

    2017-12-01

    The present research addresses the satellite reaction wheel (RW) nonlinear electromechanical coupling dynamics including dynamic eccentricity of brushless dc (BLDC) motor and gyroscopic effects, as well as dry friction of shaft-bearing joints (relative small slip) and bearing friction. In contrast to other studies, the rotational velocity of the flywheel is considered to be controllable, so it is possible to study the reaction wheel dynamical behavior in acceleration stages. The RW is modeled as a three-phases BLDC motor as well as flywheel with unbalances on a rigid shaft and flexible bearings. Improved Lagrangian dynamics for electromechanical systems is used to obtain the mathematical model of the system. The developed model can properly describe electromechanical nonlinear coupled dynamical behavior of the satellite RW. Numerical simulations show the effectiveness of the presented approach.

  9. Satellite orbits in Levi-Civita space

    Science.gov (United States)

    Humi, Mayer

    2018-03-01

    In this paper we consider satellite orbits in central force field with quadratic drag using two formalisms. The first using polar coordinates in which the satellite angular momentum plays a dominant role. The second is in Levi-Civita coordinates in which the energy plays a central role. We then merge these two formalisms by introducing polar coordinates in Levi-Civita space and derive a new equation for satellite orbits which unifies these two paradigms. In this equation energy and angular momentum appear on equal footing and thus characterize the orbit by its two invariants. Using this formalism we show that equatorial orbits around oblate spheroids can be expressed analytically in terms of Elliptic functions. In the second part of the paper we derive in Levi-Civita coordinates a linearized equation for the relative motion of two spacecrafts whose trajectories are in the same plane. We carry out also a numerical verification of these equations.

  10. Satellite, climatological, and theoretical inputs for modeling of the diurnal cycle of fire emissions

    Science.gov (United States)

    Hyer, E. J.; Reid, J. S.; Schmidt, C. C.; Giglio, L.; Prins, E.

    2009-12-01

    The diurnal cycle of fire activity is crucial for accurate simulation of atmospheric effects of fire emissions, especially at finer spatial and temporal scales. Estimating diurnal variability in emissions is also a critical problem for construction of emissions estimates from multiple sensors with variable coverage patterns. An optimal diurnal emissions estimate will use as much information as possible from satellite fire observations, compensate known biases in those observations, and use detailed theoretical models of the diurnal cycle to fill in missing information. As part of ongoing improvements to the Fire Location and Monitoring of Burning Emissions (FLAMBE) fire monitoring system, we evaluated several different methods of integrating observations with different temporal sampling. We used geostationary fire detections from WF_ABBA, fire detection data from MODIS, empirical diurnal cycles from TRMM, and simple theoretical diurnal curves based on surface heating. Our experiments integrated these data in different combinations to estimate the diurnal cycles of emissions for each location and time. Hourly emissions estimates derived using these methods were tested using an aerosol transport model. We present results of this comparison, and discuss the implications of our results for the broader problem of multi-sensor data fusion in fire emissions modeling.

  11. Improved Assimilation of Streamflow and Satellite Soil Moisture with the Evolutionary Particle Filter and Geostatistical Modeling

    Science.gov (United States)

    Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman

    2017-04-01

    Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a

  12. Forecasting Global Horizontal Irradiance Using the LETKF and a Combination of Advected Satellite Images and Sparse Ground Sensors

    Science.gov (United States)

    Harty, T. M.; Lorenzo, A.; Holmgren, W.; Morzfeld, M.

    2017-12-01

    The irradiance incident on a solar panel is the main factor in determining the power output of that panel. For this reason, accurate global horizontal irradiance (GHI) estimates and forecasts are critical when determining the optimal location for a solar power plant, forecasting utility scale solar power production, or forecasting distributed, behind the meter rooftop solar power production. Satellite images provide a basis for producing the GHI estimates needed to undertake these objectives. The focus of this work is to combine satellite derived GHI estimates with ground sensor measurements and an advection model. The idea is to use accurate but sparsely distributed ground sensors to improve satellite derived GHI estimates which can cover large areas (the size of a city or a region of the United States). We use a Bayesian framework to perform the data assimilation, which enables us to produce irradiance forecasts and associated uncertainties which incorporate both satellite and ground sensor data. Within this framework, we utilize satellite images taken from the GOES-15 geostationary satellite (available every 15-30 minutes) as well as ground data taken from irradiance sensors and rooftop solar arrays (available every 5 minutes). The advection model, driven by wind forecasts from a numerical weather model, simulates cloud motion between measurements. We use the Local Ensemble Transform Kalman Filter (LETKF) to perform the data assimilation. We present preliminary results towards making such a system useful in an operational context. We explain how localization and inflation in the LETKF, perturbations of wind-fields, and random perturbations of the advection model, affect the accuracy of our estimates and forecasts. We present experiments showing the accuracy of our forecasted GHI over forecast-horizons of 15 mins to 1 hr. The limitations of our approach and future improvements are also discussed.

  13. An Object Model for Integrating Diverse Remote Sensing Satellite Sensors: A Case Study of Union Operation

    Directory of Open Access Journals (Sweden)

    Chuli Hu

    2014-01-01

    Full Text Available In the Earth Observation sensor web environment, the rapid, accurate, and unified discovery of diverse remote sensing satellite sensors, and their association to yield an integrated solution for a comprehensive response to specific emergency tasks pose considerable challenges. In this study, we propose a remote sensing satellite sensor object model, based on the object-oriented paradigm and the Open Geospatial Consortium Sensor Model Language. The proposed model comprises a set of sensor resource objects. Each object consists of identification, state of resource attribute, and resource method. We implement the proposed attribute state description by applying it to different remote sensors. A real application, involving the observation of floods at the Yangtze River in China, is undertaken. Results indicate that the sensor inquirer can accurately discover qualified satellite sensors in an accurate and unified manner. By implementing the proposed union operation among the retrieved sensors, the inquirer can further determine how the selected sensors can collaboratively complete a specific observation requirement. Therefore, the proposed model provides a reliable foundation for sharing and integrating multiple remote sensing satellite sensors and their observations.

  14. MODELING OF ADS-B MESSAGES TRANSMISSION THROUGH SATELLITE TELECOMMUNICATION CHANNEL IRIDIUM USING NETCRACKER PROFESSIONAL 4.1

    Directory of Open Access Journals (Sweden)

    В. Харченко

    2012-04-01

    Full Text Available The model for the traffic analysis in a communication channel "aircraft - satellite - ground station" wasbuilt and used for modeling of transfer ADS-B messages with the help low-orbit satellite complex Іrіdіum.Dependences of factor BER on channel average working load and average utilization time were obtained.Dependences of package failure probabilities on average working load, average utilization time and signaltraveling time were analyzed. The developed model was applied for determination of traffic characteristics ina communication channel "aircraft - satellite - ground station": the dependence of average working load,average channel utilization time and message traveling time on the size of transaction, the dependence oftravelling time on channel delay time were built.

  15. Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau

    Directory of Open Access Journals (Sweden)

    Yijian Zeng

    2016-03-01

    Full Text Available The inter-comparison of different soil moisture (SM products over the Tibetan Plateau (TP reveals the inconsistency among different SM products, when compared to in situ measurement. It highlights the need to constrain the model simulated SM with the in situ measured data climatology. In this study, the in situ soil moisture networks, combined with the classification of climate zones over the TP, were used to produce the in situ measured SM climatology at the plateau scale. The generated TP scale in situ SM climatology was then used to scale the model-simulated SM data, which was subsequently used to scale the SM satellite observations. The climatology-scaled satellite and model-simulated SM were then blended objectively, by applying the triple collocation and least squares method. The final blended SM can replicate the SM dynamics across different climatic zones, from sub-humid regions to semi-arid and arid regions over the TP. This demonstrates the need to constrain the model-simulated SM estimates with the in situ measurements before their further applications in scaling climatology of SM satellite products.

  16. Results of the first tests of the SIDRA satellite-borne instrument breadboard model

    International Nuclear Information System (INIS)

    Dudnik, O.V.; Kurbatov, E.V.; Avilov, A.M.; Titov, K.G.; Prieto, M; Sanchez, S.; Spassky, A.V.; Sylwester, J.; Gburek, S.; Podgorski, P.

    2013-01-01

    In this work, the results of the calibration of the solid-state detectors and electronic channels of the SIDRA satellite borne energetic charged particle spectrometer-telescope breadboard model are presented. The block schemes and experimental equipment used to conduct the thermal vacuum and electromagnetic compatibility tests of the assemblies and modules of the compact satellite equipment are described. The results of the measured thermal conditions of operation of the signal analog and digital processing critical modules of the SIDRA instrument prototype are discussed. Finally, the levels of conducted interference generated by the instrument model in the primary vehicle-borne power circuits are presented.

  17. Satellites and Steep Slopes - the challenge of topography in the Himalaya - Karakorum for cryosphere models

    Science.gov (United States)

    Steiner, J. F.; Buri, P.; Miles, E. S.; Immerzeel, W.

    2016-12-01

    The topography in glaciated catchments in the Himalaya - Karakoram range are extreme in a number of aspects that proof to be a challenge for distributed modelling. High altitude regions, where accumulation areas of glaciers are generally located, can at times be very steep, covered in hanging ice and seasonal snow. On the other hand, lower areas, where ablation zones on glacier tongues are located, tend to be very shallow. This has consequences for obtaining glacier areas from satellite derived glacier inventories (e.g. RGI, ICIMOD). As they are taken perpendicular to the center of the earth, these inventories will underestimate the area of steep regions, sometimes quite considerably (Figure 1). This can have consequences for a number of statistics in glaciological modeling, especially when it comes to the relative comparison of accumulation and ablation and hence overall melt from a glacier. Additionally, these steep head walls cause topographic shading. Depending on the exposition of the valley this can result in very divergent amounts of direct solar radiation reaching the glacier surface from valley to valley. Comparisons of melt between different regions and even glaciers have to be taken with considerable caution. Finally, these shallow glacier tongues are increasingly covered in debris. Such glacier surfaces with a debris cover ranging in grain size from sand to boulders several meters in diameter are very hummocky rather than flat bare ice glacier surfaces. This in turn increases local shading but also increases the overall glacier surface. Using high resolution satellite imagery and DEMs ( 5m) from our field site we investigate the effects of areal misrepresentations on the local scale. Decreasing resolution we then take this analysis to the mountain range scale and can identify to what degree these factors are significant and considering literature values determine the quantitative impact for energy and mass balance studies. Figure 1: A schematic

  18. Open Source GIS Connectors to NASA GES DISC Satellite Data

    Science.gov (United States)

    Kempler, Steve; Pham, Long; Yang, Wenli

    2014-01-01

    The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) houses a suite of high spatiotemporal resolution GIS data including satellite-derived and modeled precipitation, air quality, and land surface parameter data. The data are valuable to various GIS research and applications at regional, continental, and global scales. On the other hand, many GIS users, especially those from the ArcGIS community, have difficulties in obtaining, importing, and using our data due to factors such as the variety of data products, the complexity of satellite remote sensing data, and the data encoding formats. We introduce a simple open source ArcGIS data connector that significantly simplifies the access and use of GES DISC data in ArcGIS.

  19. Determination of errors in derived magnetic field directions in geosynchronous orbit: results from a statistical approach

    Science.gov (United States)

    Chen, Yue; Cunningham, Gregory; Henderson, Michael

    2016-09-01

    This study aims to statistically estimate the errors in local magnetic field directions that are derived from electron directional distributions measured by Los Alamos National Laboratory geosynchronous (LANL GEO) satellites. First, by comparing derived and measured magnetic field directions along the GEO orbit to those calculated from three selected empirical global magnetic field models (including a static Olson and Pfitzer 1977 quiet magnetic field model, a simple dynamic Tsyganenko 1989 model, and a sophisticated dynamic Tsyganenko 2001 storm model), it is shown that the errors in both derived and modeled directions are at least comparable. Second, using a newly developed proxy method as well as comparing results from empirical models, we are able to provide for the first time circumstantial evidence showing that derived magnetic field directions should statistically match the real magnetic directions better, with averaged errors ˜ 5°. In addition, our results suggest that the errors in derived magnetic field directions do not depend much on magnetospheric activity, in contrast to the empirical field models. Finally, as applications of the above conclusions, we show examples of electron pitch angle distributions observed by LANL GEO and also take the derived magnetic field directions as the real ones so as to test the performance of empirical field models along the GEO orbits, with results suggesting dependence on solar cycles as well as satellite locations. This study demonstrates the validity and value of the method that infers local magnetic field directions from particle spin-resolved distributions.

  20. mTOR is necessary for proper satellite cell activity and skeletal muscle regeneration

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Pengpeng [Key Laboratory of Swine Genetics and Breeding of Agricultural Ministry & Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070 (China); Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 (United States); Liang, Xinrong; Shan, Tizhong [Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 (United States); Jiang, Qinyang [Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 (United States); College of Animal Science and Technology, Guangxi University, Nanning 530004 (China); Deng, Changyan [Key Laboratory of Swine Genetics and Breeding of Agricultural Ministry & Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070 (China); Zheng, Rong, E-mail: zhengrong@mail.hzau.edu.cn [Key Laboratory of Swine Genetics and Breeding of Agricultural Ministry & Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070 (China); Kuang, Shihuan, E-mail: skuang@purdue.edu [Department of Animal Sciences, Purdue University, West Lafayette, IN 47907 (United States)

    2015-07-17

    The serine/threonine kinase mammalian target of rapamycin (mTOR) is a key regulator of protein synthesis, cell proliferation and energy metabolism. As constitutive deletion of Mtor gene results in embryonic lethality, the function of mTOR in muscle stem cells (satellite cells) and skeletal muscle regeneration remains to be determined. In this study, we established a satellite cell specific Mtor conditional knockout (cKO) mouse model by crossing Pax7{sup CreER} and Mtor{sup flox/flox} mice. Skeletal muscle regeneration after injury was severely compromised in the absence of Mtor, indicated by increased number of necrotic myofibers infiltrated by Evans blue dye, and reduced number and size of regenerated myofibers in the Mtor cKO mice compared to wild type (WT) littermates. To dissect the cellular mechanism, we analyzed satellite cell-derived primary myoblasts grown on single myofibers or adhered to culture plates. The Mtor cKO myoblasts exhibited defective proliferation and differentiation kinetics when compared to myoblasts derived from WT littermates. At the mRNA and protein levels, the Mtor cKO myoblasts expressed lower levels of key myogenic determinant genes Pax7, Myf5, Myod, Myog than did the WT myoblasts. These results suggest that mTOR is essential for satellite cell function and skeletal muscle regeneration through controlling the expression of myogenic genes. - Highlights: • Pax7{sup CreER} was used to delete Mtor gene in satellite cells. • Satellite cell specific deletion of Mtor impairs muscle regeneration. • mTOR is necessary for satellite cell proliferation and differentiation. • Deletion of Mtor leads to reduced expression of key myogenic genes.

  1. mTOR is necessary for proper satellite cell activity and skeletal muscle regeneration

    International Nuclear Information System (INIS)

    Zhang, Pengpeng; Liang, Xinrong; Shan, Tizhong; Jiang, Qinyang; Deng, Changyan; Zheng, Rong; Kuang, Shihuan

    2015-01-01

    The serine/threonine kinase mammalian target of rapamycin (mTOR) is a key regulator of protein synthesis, cell proliferation and energy metabolism. As constitutive deletion of Mtor gene results in embryonic lethality, the function of mTOR in muscle stem cells (satellite cells) and skeletal muscle regeneration remains to be determined. In this study, we established a satellite cell specific Mtor conditional knockout (cKO) mouse model by crossing Pax7 CreER and Mtor flox/flox mice. Skeletal muscle regeneration after injury was severely compromised in the absence of Mtor, indicated by increased number of necrotic myofibers infiltrated by Evans blue dye, and reduced number and size of regenerated myofibers in the Mtor cKO mice compared to wild type (WT) littermates. To dissect the cellular mechanism, we analyzed satellite cell-derived primary myoblasts grown on single myofibers or adhered to culture plates. The Mtor cKO myoblasts exhibited defective proliferation and differentiation kinetics when compared to myoblasts derived from WT littermates. At the mRNA and protein levels, the Mtor cKO myoblasts expressed lower levels of key myogenic determinant genes Pax7, Myf5, Myod, Myog than did the WT myoblasts. These results suggest that mTOR is essential for satellite cell function and skeletal muscle regeneration through controlling the expression of myogenic genes. - Highlights: • Pax7 CreER was used to delete Mtor gene in satellite cells. • Satellite cell specific deletion of Mtor impairs muscle regeneration. • mTOR is necessary for satellite cell proliferation and differentiation. • Deletion of Mtor leads to reduced expression of key myogenic genes

  2. InSAR atmospheric correction using Himawari-8 Geostationary Meteorological Satellite

    Science.gov (United States)

    Kinoshita, Y.; Nimura, T.; Furuta, R.

    2017-12-01

    The atmospheric delay effect is one of the limitations for the accurate surface displacement detection by Synthetic Aperture Radar Interferometry (InSAR). Many previous studies have attempted to mitigate the neutral atmospheric delay in InSAR (e.g. Jolivet et al. 2014; Foster et al. 2006; Kinoshita et al. 2013). Hanssen et al. (2001) investigated the relationship between the 27 hourly observations of GNSS precipitable water vapor (PWV) and the infrared brightness temperature derived from visible satellite imagery, and showed a good correlation. Here we showed a preliminary result of the newly developed method for the neutral atmospheric delay correction using the Himawari-8 Japanese geostationary meteorological satellite data. The Himawari-8 satellite is the Japanese state-of-the-art geostationary meteorological satellite that has 16 observation channels and has spatial resolutions of 0.5 km (visible) and 2.0 km (near-infrared and infrared) with an time interval of 2.5 minutes around Japan. To estimate the relationship between the satellite brightness temperature and the atmospheric delay amount. Since the InSAR atmospheric delay is principally the same as that in GNSS, we at first compared the Himawari-8 data with the GNSS zenith tropospheric delay data derived from the Japanese dense GNSS network. The comparison of them showed that the band with the wavelength of 6.9 μm had the highest correlation to the GNSS observation. Based on this result, we developed an InSAR atmospheric delay model that uses the Himawari-8 6.9 μm band data. For the model validation, we generated InSAR images from the ESA's C-band Sentinel-1 SLC data with the GAMMA SAR software. We selected two regions around Tokyo and Sapporo (both in Japan) as the test sites because of the less temporal decorrelation. The validation result showed that the delay model reasonably estimate large scale phase variation whose spatial scale was on the order of over 20 km. On the other hand, phase variations of

  3. Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations

    Science.gov (United States)

    Kawa, S. R.; Collatz, G. J.; Erickson, D. J.; Denning, A. S.; Wofsy, S. C.; Andrews, A. E.

    2007-01-01

    As we enter the new era of satellite remote sensing for CO2 and other carbon cyclerelated quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at lxi degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its

  4. Improved Orbit Determination and Forecasts with an Assimilative Tool for Atmospheric Density and Satellite Drag Specification

    Science.gov (United States)

    Crowley, G.; Pilinski, M.; Sutton, E. K.; Codrescu, M.; Fuller-Rowell, T. J.; Matsuo, T.; Fedrizzi, M.; Solomon, S. C.; Qian, L.; Thayer, J. P.

    2016-12-01

    Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by the variability in density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of LEO satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. We describe ongoing work to build a comprehensive nowcast and forecast system for specifying the neutral atmospheric state related to orbital drag conditions. The system outputs include neutral density, winds, temperature, composition, and the satellite drag derived from these parameters. This modeling tool is based on several state-of-the-art coupled models of the thermosphere-ionosphere as well as several empirical models running in real-time and uses assimilative techniques to produce a thermospheric nowcast. This software will also produce 72 hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition and using near real-time and predicted space weather data and indices as the inputs. Features of this technique include: • Satellite drag specifications with errors lower than current models • Altitude coverage up to 1000km • Background state representation using both first principles and empirical models • Assimilation of satellite drag and other datatypes • Real time capability • Ability to produce 72-hour forecasts of the atmospheric state In this paper, we will summarize the model design and assimilative architecture, and present preliminary validation results. Validation results will be presented in the context of satellite orbit errors and compared with several leading atmospheric models including the High Accuracy Satellite Drag Model, which is currently used

  5. Dwarf Spheroidal Satellite Formation in a Reionized Local Group

    OpenAIRE

    Milosavljevic, Milos; Bromm, Volker

    2013-01-01

    Dwarf spheroidal satellite galaxies have emerged a powerful probe of small-scale dark matter clustering and of cosmic reionization. They exhibit structural and chemical continuity with dwarf irregular galaxies in the field and with spheroidal galaxies in high-density environments. By combining empirical constraints derived for star formation at low gas column densities and metallicities in the local universe with a model for dark matter and baryonic mass assembly, we provide an analytical des...

  6. A stochastic post-processing method for solar irradiance forecasts derived from NWPs models

    Science.gov (United States)

    Lara-Fanego, V.; Pozo-Vazquez, D.; Ruiz-Arias, J. A.; Santos-Alamillos, F. J.; Tovar-Pescador, J.

    2010-09-01

    Solar irradiance forecast is an important area of research for the future of the solar-based renewable energy systems. Numerical Weather Prediction models (NWPs) have proved to be a valuable tool for solar irradiance forecasting with lead time up to a few days. Nevertheless, these models show low skill in forecasting the solar irradiance under cloudy conditions. Additionally, climatic (averaged over seasons) aerosol loading are usually considered in these models, leading to considerable errors for the Direct Normal Irradiance (DNI) forecasts during high aerosols load conditions. In this work we propose a post-processing method for the Global Irradiance (GHI) and DNI forecasts derived from NWPs. Particularly, the methods is based on the use of Autoregressive Moving Average with External Explanatory Variables (ARMAX) stochastic models. These models are applied to the residuals of the NWPs forecasts and uses as external variables the measured cloud fraction and aerosol loading of the day previous to the forecast. The method is evaluated for a set one-moth length three-days-ahead forecast of the GHI and DNI, obtained based on the WRF mesoscale atmospheric model, for several locations in Andalusia (Southern Spain). The Cloud fraction is derived from MSG satellite estimates and the aerosol loading from the MODIS platform estimates. Both sources of information are readily available at the time of the forecast. Results showed a considerable improvement of the forecasting skill of the WRF model using the proposed post-processing method. Particularly, relative improvement (in terms of the RMSE) for the DNI during summer is about 20%. A similar value is obtained for the GHI during the winter.

  7. GRACE gravity field modeling with an investigation on correlation between nuisance parameters and gravity field coefficients

    Science.gov (United States)

    Zhao, Qile; Guo, Jing; Hu, Zhigang; Shi, Chuang; Liu, Jingnan; Cai, Hua; Liu, Xianglin

    2011-05-01

    The GRACE (Gravity Recovery And Climate Experiment) monthly gravity models have been independently produced and published by several research institutions, such as Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), Centre National d’Etudes Spatiales (CNES) and Delft Institute of Earth Observation and Space Systems (DEOS). According to their processing standards, above institutions use the traditional variational approach except that the DEOS exploits the acceleration approach. The background force models employed are rather similar. The produced gravity field models generally agree with one another in the spatial pattern. However, there are some discrepancies in the gravity signal amplitude between solutions produced by different institutions. In particular, 10%-30% signal amplitude differences in some river basins can be observed. In this paper, we implemented a variant of the traditional variational approach and computed two sets of monthly gravity field solutions using the data from January 2005 to December 2006. The input data are K-band range-rates (KBRR) and kinematic orbits of GRACE satellites. The main difference in the production of our two types of models is how to deal with nuisance parameters. This type of parameters is necessary to absorb low-frequency errors in the data, which are mainly the aliasing and instrument errors. One way is to remove the nuisance parameters before estimating the geopotential coefficients, called NPARB approach in the paper. The other way is to estimate the nuisance parameters and geopotential coefficients simultaneously, called NPESS approach. These two types of solutions mainly differ in geopotential coefficients from degree 2 to 5. This can be explained by the fact that the nuisance parameters and the gravity field coefficients are highly correlated, particularly at low degrees. We compare these solutions with the official and published ones by means of spectral analysis. It is

  8. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA from 2003-08-26 to 2012-05-03 (NODC Accession 0126914)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Bathymetric data derived from a multipectral World View-2 satellite image mosaiced to provide near complete coverage of nearshore terrain around the islands....

  9. Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data

    Directory of Open Access Journals (Sweden)

    Sandra Eckert

    2012-03-01

    Full Text Available Accurate estimation of aboveground biomass and carbon stock has gained importance in the context of the United Nations Framework Convention on Climate Change (UNFCCC and the Kyoto Protocol. In order to develop improved forest stratum–specific aboveground biomass and carbon estimation models for humid rainforest in northeast Madagascar, this study analyzed texture measures derived from WorldView-2 satellite data. A forest inventory was conducted to develop stratum-specific allometric equations for dry biomass. On this basis, carbon was calculated by applying a conversion factor. After satellite data preprocessing, vegetation indices, principal components, and texture measures were calculated. The strength of their relationships with the stratum-specific plot data was analyzed using Pearson’s correlation. Biomass and carbon estimation models were developed by performing stepwise multiple linear regression. Pearson’s correlation coefficients revealed that (a texture measures correlated more with biomass and carbon than spectral parameters, and (b correlations were stronger for degraded forest than for non-degraded forest. For degraded forest, the texture measures of Correlation, Angular Second Moment, and Contrast, derived from the red band, contributed to the best estimation model, which explained 84% of the variability in the field data (relative RMSE = 6.8%. For non-degraded forest, the vegetation index EVI and the texture measures of Variance, Mean, and Correlation, derived from the newly introduced coastal blue band, both NIR bands, and the red band, contributed to the best model, which explained 81% of the variability in the field data (relative RMSE = 11.8%. These results indicate that estimation of tropical rainforest biomass/carbon, based on very high resolution satellite data, can be improved by (a developing and applying forest stratum–specific models, and (b including textural information in addition to spectral information.

  10. Water resource monitoring systems and the role of satellite observations

    Directory of Open Access Journals (Sweden)

    A. I. J. M. van Dijk

    2011-01-01

    Full Text Available Spatial water resource monitoring systems (SWRMS can provide valuable information in support of water management, but current operational systems are few and provide only a subset of the information required. Necessary innovations include the explicit description of water redistribution and water use from river and groundwater systems, achieving greater spatial detail (particularly in key features such as irrigated areas and wetlands, and improving accuracy as assessed against hydrometric observations, as well as assimilating those observations. The Australian water resources assessment (AWRA system aims to achieve this by coupling landscape models with models describing surface water and groundwater dynamics and water use. A review of operational and research applications demonstrates that satellite observations can improve accuracy and spatial detail in hydrological model estimation. All operational systems use dynamic forcing, land cover classifications and a priori parameterisation of vegetation dynamics that are partially or wholly derived from remote sensing. Satellite observations are used to varying degrees in model evaluation and data assimilation. The utility of satellite observations through data assimilation can vary as a function of dominant hydrological processes. Opportunities for improvement are identified, including the development of more accurate and higher spatial and temporal resolution precipitation products, and the use of a greater range of remote sensing products in a priori model parameter estimation, model evaluation and data assimilation. Operational challenges include the continuity of research satellite missions and data services, and the need to find computationally-efficient data assimilation techniques. The successful use of observations critically depends on the availability of detailed information on observational error and understanding of the relationship between remotely-sensed and model variables, as

  11. Validation of satellite SAR offshore wind speed maps to in-situ data, microscala and mesoscale model results

    Energy Technology Data Exchange (ETDEWEB)

    Hasager, C B; Astrup, P; Barthelmie, R; Dellwik, E; Hoffmann Joergensen, B; Gylling Mortensen, N; Nielsen, M; Pryor, S; Rathmann, O

    2002-05-01

    A validation study has been performed in order to investigate the precision and accuracy of the satellite-derived ERS-2 SAR wind products in offshore regions. The overall project goal is to develop a method for utilizing the satellite wind speed maps for offshore wind resources, e.g. in future planning of offshore wind farms. The report describes the validation analysis in detail for three sites in Denmark, Italy and Egypt. The site in Norway is analyzed by the Nansen Environmental and Remote Sensing Centre (NERSC). Wind speed maps and wind direction maps from Earth Observation data recorded by the ERS-2 SAR satellite have been obtained from the NERSC. For the Danish site the wind speed and wind direction maps have been compared to in-situ observations from a met-mast at Horns Rev in the North Sea located 14 km offshore. The SAR wind speeds have been area-averaged by simple and advanced footprint modelling, ie. the upwind conditions to the meteorological mast are explicitly averaged in the SAR wind speed maps before comparison. The comparison results are very promising with a standard error of {+-} 0.61 m s{sup -1}, a bias {approx}2 m s{sup -1} and R{sup 2} {approx}0.88 between in-situ wind speed observations and SAR footprint averaged values at 10 m level. Wind speeds predicted by the local scale model LINCOM and the mesoscale model KAMM2 have been compared to the spatial variations in the SAR wind speed maps. The finding is a good correspondence between SAR observations and model results. Near the coast is an 800 m wide band in which the SAR wind speed observations have a strong negative bias. The bathymetry of Horns Rev combined with tidal currents give rise to bias in the SAR wind speed maps near areas of shallow, complex bottom topography in some cases. A total of 16 cases were analyzed for Horns Rev. For Maddalena in Italy five cases were analyzed. At the Italian site the SAR wind speed maps were compared to WAsP and KAMM2 model results. The WAsP model

  12. A first map of tropical Africa's above-ground biomass derived from satellite imagery

    International Nuclear Information System (INIS)

    Baccini, A; Laporte, N; Goetz, S J; Sun, M; Dong, H

    2008-01-01

    Observations from the moderate resolution imaging spectroradiometer (MODIS) were used in combination with a large data set of field measurements to map woody above-ground biomass (AGB) across tropical Africa. We generated a best-quality cloud-free mosaic of MODIS satellite reflectance observations for the period 2000-2003 and used a regression tree model to predict AGB at 1 km resolution. Results based on a cross-validation approach show that the model explained 82% of the variance in AGB, with a root mean square error of 50.5 Mg ha -1 for a range of biomass between 0 and 454 Mg ha -1 . Analysis of lidar metrics from the Geoscience Laser Altimetry System (GLAS), which are sensitive to vegetation structure, indicate that the model successfully captured the regional distribution of AGB. The results showed a strong positive correlation (R 2 = 0.90) between the GLAS height metrics and predicted AGB.

  13. Deriving the effect of wind speed on clean marine aerosol optical properties using the A-Train satellites

    Directory of Open Access Journals (Sweden)

    V. P. Kiliyanpilakkil

    2011-11-01

    Full Text Available The relationship between "clean marine" aerosol optical properties and ocean surface wind speed is explored using remotely sensed data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP on board the CALIPSO satellite and the Advanced Microwave Scanning Radiometer (AMSR-E on board the AQUA satellite. Detailed data analyses are carried out over 15 regions selected to be representative of different areas of the global ocean for the time period from June 2006 to April 2011. Based on remotely sensed optical properties the CALIPSO algorithm is capable of discriminating "clean marine" aerosols from other types often present over the ocean (such as urban/industrial pollution, desert dust and biomass burning. The global mean optical depth of "clean marine" aerosol at 532 nm (AOD532 is found to be 0.052 ± 0.038 (mean plus or minus standard deviation. The mean layer integrated particulate depolarization ratio of marine aerosols is 0.02 ± 0.016. Integrated attenuated backscatter and color ratio of marine aerosols at 532 nm were found to be 0.003 ± 0.002 sr−1 and 0.530 ± 0.149, respectively. A logistic regression between AOD532 and 10-m surface wind speed (U10 revealed three distinct regimes. For U10 ≤ 4 m s−1 the mean CALIPSO-derived AOD532 is found to be 0.02 ± 0.003 with little dependency on the surface wind speed. For 4 < U10 ≤ 12 m s−1, representing the dominant fraction of all available data, marine aerosol optical depth is linearly correlated with the surface wind speed values, with a slope of 0.006 s m−1. In this intermediate wind speed region, the AOD532 vs. U10 regression slope derived here is comparable to previously reported values. At very high wind speed values (U10 > 18 m s−1, the AOD532-wind speed relationship

  14. Autoregressive spatially varying coefficients model for predicting daily PM2.5 using VIIRS satellite AOT

    Science.gov (United States)

    Schliep, E. M.; Gelfand, A. E.; Holland, D. M.

    2015-12-01

    There is considerable demand for accurate air quality information in human health analyses. The sparsity of ground monitoring stations across the United States motivates the need for advanced statistical models to predict air quality metrics, such as PM2.5, at unobserved sites. Remote sensing technologies have the potential to expand our knowledge of PM2.5 spatial patterns beyond what we can predict from current PM2.5 monitoring networks. Data from satellites have an additional advantage in not requiring extensive emission inventories necessary for most atmospheric models that have been used in earlier data fusion models for air pollution. Statistical models combining monitoring station data with satellite-obtained aerosol optical thickness (AOT), also referred to as aerosol optical depth (AOD), have been proposed in the literature with varying levels of success in predicting PM2.5. The benefit of using AOT is that satellites provide complete gridded spatial coverage. However, the challenges involved with using it in fusion models are (1) the correlation between the two data sources varies both in time and in space, (2) the data sources are temporally and spatially misaligned, and (3) there is extensive missingness in the monitoring data and also in the satellite data due to cloud cover. We propose a hierarchical autoregressive spatially varying coefficients model to jointly model the two data sources, which addresses the foregoing challenges. Additionally, we offer formal model comparison for competing models in terms of model fit and out of sample prediction of PM2.5. The models are applied to daily observations of PM2.5 and AOT in the summer months of 2013 across the conterminous United States. Most notably, during this time period, we find small in-sample improvement incorporating AOT into our autoregressive model but little out-of-sample predictive improvement.

  15. On land-use modeling: A treatise of satellite imagery data and misclassification error

    Science.gov (United States)

    Sandler, Austin M.

    Recent availability of satellite-based land-use data sets, including data sets with contiguous spatial coverage over large areas, relatively long temporal coverage, and fine-scale land cover classifications, is providing new opportunities for land-use research. However, care must be used when working with these datasets due to misclassification error, which causes inconsistent parameter estimates in the discrete choice models typically used to model land-use. I therefore adapt the empirical correction methods developed for other contexts (e.g., epidemiology) so that they can be applied to land-use modeling. I then use a Monte Carlo simulation, and an empirical application using actual satellite imagery data from the Northern Great Plains, to compare the results of a traditional model ignoring misclassification to those from models accounting for misclassification. Results from both the simulation and application indicate that ignoring misclassification will lead to biased results. Even seemingly insignificant levels of misclassification error (e.g., 1%) result in biased parameter estimates, which alter marginal effects enough to affect policy inference. At the levels of misclassification typical in current satellite imagery datasets (e.g., as high as 35%), ignoring misclassification can lead to systematically erroneous land-use probabilities and substantially biased marginal effects. The correction methods I propose, however, generate consistent parameter estimates and therefore consistent estimates of marginal effects and predicted land-use probabilities.

  16. Effect of Terrestrial and Marine Organic Aerosol on Regional and Global Climate: Model Development, Application, and Verification with Satellite Data

    Energy Technology Data Exchange (ETDEWEB)

    Meskhidze, Nicholas; Zhang, Yang; Kamykowski, Daniel

    2012-03-28

    In this DOE project the improvements to parameterization of marine primary organic matter (POM) emissions, hygroscopic properties of marine POM, marine isoprene derived secondary organic aerosol (SOA) emissions, surfactant effects, new cloud droplet activation parameterization have been implemented into Community Atmosphere Model (CAM 5.0), with a seven mode aerosol module from the Pacific Northwest National Laboratory (PNNL)'s Modal Aerosol Model (MAM7). The effects of marine aerosols derived from sea spray and ocean emitted biogenic volatile organic compounds (BVOCs) on microphysical properties of clouds were explored by conducting 10 year CAM5.0-MAM7 model simulations at a grid resolution 1.9° by 2.5° with 30 vertical layers. Model-predicted relationship between ocean physical and biological systems and the abundance of CCN in remote marine atmosphere was compared to data from the A-Train satellites (MODIS, CALIPSO, AMSR-E). Model simulations show that on average, primary and secondary organic aerosol emissions from the ocean can yield up to 20% increase in Cloud Condensation Nuclei (CCN) at 0.2% Supersaturation, and up to 5% increases in droplet number concentration of global maritime shallow clouds. Marine organics were treated as internally or externally mixed with sea salt. Changes associated with cloud properties reduced (absolute value) the model-predicted short wave cloud forcing from -1.35 Wm-2 to -0.25 Wm-2. By using different emission scenarios, and droplet activation parameterizations, this study suggests that addition of marine primary aerosols and biologically generated reactive gases makes an important difference in radiative forcing assessments. All baseline and sensitivity simulations for 2001 and 2050 using global-through-urban WRF/Chem (GU-WRF) were completed. The main objective of these simulations was to evaluate the capability of GU-WRF for an accurate representation of the global atmosphere by exploring the most accurate

  17. Vegetation root zone storage and rooting depth, derived from local calibration of a global hydrological model

    Science.gov (United States)

    van der Ent, R.; Van Beek, R.; Sutanudjaja, E.; Wang-Erlandsson, L.; Hessels, T.; Bastiaanssen, W.; Bierkens, M. F.

    2017-12-01

    The storage and dynamics of water in the root zone control many important hydrological processes such as saturation excess overland flow, interflow, recharge, capillary rise, soil evaporation and transpiration. These processes are parameterized in hydrological models or land-surface schemes and the effect on runoff prediction can be large. Root zone parameters in global hydrological models are very uncertain as they cannot be measured directly at the scale on which these models operate. In this paper we calibrate the global hydrological model PCR-GLOBWB using a state-of-the-art ensemble of evaporation fields derived by solving the energy balance for satellite observations. We focus our calibration on the root zone parameters of PCR-GLOBWB and derive spatial patterns of maximum root zone storage. We find these patterns to correspond well with previous research. The parameterization of our model allows for the conversion of maximum root zone storage to root zone depth and we find that these correspond quite well to the point observations where available. We conclude that climate and soil type should be taken into account when regionalizing measured root depth for a certain vegetation type. We equally find that using evaporation rather than discharge better allows for local adjustment of root zone parameters within a basin and thus provides orthogonal data to diagnose and optimize hydrological models and land surface schemes.

  18. The role of satellite altimetry in gravity field modelling in coastal areas

    DEFF Research Database (Denmark)

    Andersen, Ole Baltazar; Knudsen, Per

    2000-01-01

    global uniform gravity information with very high resolution, and these global marine gravity fields are registered on a two by two minute grid corresponding to 4 by 4 kilometres at the equator. In this presentation several coastal complications in deriving the marine gravity field from satellite...... altimetry will be investigated using the KMS98 gravity field. Comparison with other sources of gravity field information like airborne and marine gravity observations will be carried out and two fundamentally different test areas (Azores and Skagerak) will be studied to investigated the different role...

  19. Convective and large-scale mass flux profiles over tropical oceans determined from synergistic analysis of a suite of satellite observations

    Science.gov (United States)

    Masunaga, Hirohiko; Luo, Zhengzhao Johnny

    2016-07-01

    A new, satellite-based methodology is developed to evaluate convective mass flux and large-scale total mass flux. To derive the convective mass flux, candidate profiles of in-cloud vertical velocity are first constructed with a simple plume model under the constraint of ambient sounding and then narrowed down to the solution that matches satellite-derived cloud top buoyancy. Meanwhile, the large-scale total mass flux is provided separately from satellite soundings by a method developed previously. All satellite snapshots are sorted into a composite time series that delineates the evolution of a vigorous and organized convective system. Principal findings are the following. First, convective mass flux is modulated primarily by convective cloud cover, with the intensity of individual convection being less variable over time. Second, convective mass flux dominates the total mass flux only during the early hours of the convective evolution; as convective system matures, a residual mass flux builds up in the mass flux balance that is reminiscent of stratiform dynamics. The method developed in this study is expected to be of unique utility for future observational diagnosis of tropical convective dynamics and for evaluation of global climate model cumulus parameterizations in a global sense.

  20. On the performance of satellite precipitation products in riverine flood modeling: A review

    Science.gov (United States)

    Maggioni, Viviana; Massari, Christian

    2018-03-01

    This work is meant to summarize lessons learned on using satellite precipitation products for riverine flood modeling and to propose future directions in this field of research. Firstly, the most common satellite precipitation products (SPPs) during the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) eras are reviewed. Secondly, we discuss the main errors and uncertainty sources in these datasets that have the potential to affect streamflow and runoff model simulations. Thirdly, past studies that focused on using SPPs for predicting streamflow and runoff are analyzed. As the impact of floods depends not only on the characteristics of the flood itself, but also on the characteristics of the region (population density, land use, geophysical and climatic factors), a regional analysis is required to assess the performance of hydrologic models in monitoring and predicting floods. The performance of SPP-forced hydrological models was shown to largely depend on several factors, including precipitation type, seasonality, hydrological model formulation, topography. Across several basins around the world, the bias in SPPs was recognized as a major issue and bias correction methods of different complexity were shown to significantly reduce streamflow errors. Model re-calibration was also raised as a viable option to improve SPP-forced streamflow simulations, but caution is necessary when recalibrating models with SPP, which may result in unrealistic parameter values. From a general standpoint, there is significant potential for using satellite observations in flood forecasting, but the performance of SPP in hydrological modeling is still inadequate for operational purposes.

  1. Green leaf phenology at Landsat resolution: scaling from the plot to satellite

    Science.gov (United States)

    Fisher, J. I.; Mustard, J. F.; Vadeboncour, M.

    2005-12-01

    Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In particular, while most phenological patterns and trends derived from satellites appear realistic and coherent, they may not reflect spatial and temporal patterns at the plot level. An obvious explanation is the drastic scale difference from plot-level to most satellite observations. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r2 = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (example, our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. In preliminary work, we validated the Landsat-derived metrics with similar analyses of MODIS and AVHRR, and demonstrate that aggregating diverse local phenologies into coarse grids may convolute interpretations. Despite these complications, the platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows us to effectively scale

  2. Calibration of GOES-derived solar radiation data using a distributed network of surface measurements in Florida, USA

    Science.gov (United States)

    Sumner, David M.; Pathak, Chandra S.; Mecikalski, John R.; Paech, Simon J.; Wu, Qinglong; Sangoyomi, Taiye; Babcock, Roger W.; Walton, Raymond

    2008-01-01

    Solar radiation data are critically important for the estimation of evapotranspiration. Analysis of visible-channel data derived from Geostationary Operational Environmental Satellites (GOES) using radiative transfer modeling has been used to produce spatially- and temporally-distributed datasets of solar radiation. An extensive network of (pyranometer) surface measurements of solar radiation in the State of Florida has allowed refined calibration of a GOES-derived daily integrated radiation data product. This refinement of radiation data allowed for corrections of satellite sensor drift, satellite generational change, and consideration of the highly-variable cloudy conditions that are typical of Florida. To aid in calibration of a GOES-derived radiation product, solar radiation data for the period 1995–2004 from 58 field stations that are located throughout the State were compiled. The GOES radiation product was calibrated by way of a three-step process: 1) comparison with ground-based pyranometer measurements on clear reference days, 2) correcting for a bias related to cloud cover, and 3) deriving month-by-month bias correction factors. Pre-calibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m–2 day–1 (13 percent). Calibration reduced errors to 1.7 MJ m–2 day–1 (10 percent) and also removed time- and cloudiness-related biases. The final dataset has been used to produce Statewide evapotranspiration estimates.

  3. Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications.

    Science.gov (United States)

    Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan

    2015-05-01

    Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  4. Expanded Large-Scale Forcing Properties Derived from the Multiscale Data Assimilation System and Its Application to Single-Column Models

    Science.gov (United States)

    Feng, S.; Li, Z.; Liu, Y.; Lin, W.; Toto, T.; Vogelmann, A. M.; Fridlind, A. M.

    2013-12-01

    We present an approach to derive large-scale forcing that is used to drive single-column models (SCMs) and cloud resolving models (CRMs)/large eddy simulation (LES) for evaluating fast physics parameterizations in climate models. The forcing fields are derived by use of a newly developed multi-scale data assimilation (MS-DA) system. This DA system is developed on top of the NCEP Gridpoint Statistical Interpolation (GSI) System and is implemented in the Weather Research and Forecasting (WRF) model at a cloud resolving resolution of 2 km. This approach has been applied to the generation of large scale forcing for a set of Intensive Operation Periods (IOPs) over the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plains (SGP) site. The dense ARM in-situ observations and high-resolution satellite data effectively constrain the WRF model. The evaluation shows that the derived forcing displays accuracies comparable to the existing continuous forcing product and, overall, a better dynamic consistency with observed cloud and precipitation. One important application of this approach is to derive large-scale hydrometeor forcing and multiscale forcing, which is not provided in the existing continuous forcing product. It is shown that the hydrometeor forcing poses an appreciable impact on cloud and precipitation fields in the single-column model simulations. The large-scale forcing exhibits a significant dependency on domain-size that represents SCM grid-sizes. Subgrid processes often contribute a significant component to the large-scale forcing, and this contribution is sensitive to the grid-size and cloud-regime.

  5. Spatial Dynamic Wideband Modeling of the MIMO Satellite-to-Earth Channel

    OpenAIRE

    Lehner, Andreas; Steingass, Alexander

    2014-01-01

    A novel MIMO (multiple input multiple output) satellite channel model that allows the generation of associated channel impulse response (CIR) time series depending on the movement profile of a land mobile terminal is presented in this paper. Based on high precise wideband measurements in L-band the model reproduces the correlated shadowing and multipath conditions in rich detail. The model includes time and space variant echo signals appearing and disappearing in dependence on the receive ...

  6. Sandmeier model based topographic correction to lunar spectral profiler (SP) data from KAGUYA satellite.

    Science.gov (United States)

    Chen, Sheng-Bo; Wang, Jing-Ran; Guo, Peng-Ju; Wang, Ming-Chang

    2014-09-01

    The Moon may be considered as the frontier base for the deep space exploration. The spectral analysis is one of the key techniques to determine the lunar surface rock and mineral compositions. But the lunar topographic relief is more remarkable than that of the Earth. It is necessary to conduct the topographic correction for lunar spectral data before they are used to retrieve the compositions. In the present paper, a lunar Sandmeier model was proposed by considering the radiance effect from the macro and ambient topographic relief. And the reflectance correction model was also reduced based on the Sandmeier model. The Spectral Profile (SP) data from KAGUYA satellite in the Sinus Iridum quadrangle was taken as an example. And the digital elevation data from Lunar Orbiter Laser Altimeter are used to calculate the slope, aspect, incidence and emergence angles, and terrain-viewing factor for the topographic correction Thus, the lunar surface reflectance from the SP data was corrected by the proposed model after the direct component of irradiance on a horizontal surface was derived. As a result, the high spectral reflectance facing the sun is decreased and low spectral reflectance back to the sun is compensated. The statistical histogram of reflectance-corrected pixel numbers presents Gaussian distribution Therefore, the model is robust to correct lunar topographic effect and estimate lunar surface reflectance.

  7. Minding the gaps: new insights into R&D management and operational transitions of NOAA satellite products

    Science.gov (United States)

    Colton, Marie C.; Powell, Alfred M.; Jordan, Gretchen; Mote, Jonathon; Hage, Jerald; Frank, Donald

    2004-10-01

    The NESDIS Center for Satellite Applications and Research (STAR), formerly ORA, Office of Research and Applications, consists of three research and applications divisions that encompass satellite meteorology, oceanography, climatology, and cooperative research with academic institutions. With such a wide background of talent, and a charter to develop operational algorithms and applications, STAR scientists develop satellite-derived land, ice, ocean, and atmospheric environmental data products in support of all of NOAA"s mission goals. In addition, in close association with the Joint Center for Satellite Data Assimilation, STAR scientists actively work with the numerical modeling communities of NOAA, NASA, and DOD to support the development of new methods for assimilation of satellite data. In this new era of observations from many new satellite instruments, STAR aims to effectively integrate these data into multi-platform data products for utilization by the forecast and applications communities. Much of our work is conducted in close partnerships with other agencies, academic institutes, and industry. In order to support the nearly 400 current satellite-derived products for various users on a routine basis from our sister operations office, and to evolve to future systems requires an ongoing strategic planning approach that maps research and development activities from NOAA goals to user requirements. Since R&D accomplishments are not necessarily amenable to precise schedules, appropriate motivators and measures of scientific progress must be developed to assure that the product development cycle remains aligned with the other engineering segments of a satellite program. This article presents the status and results of this comprehensive effort to chart a course from the present set of operational satellites to the future.

  8. Is the geopotential directly measurable (Gauss, Bruns, Einstein : Je li geopotencijal direktno mjerljiv? (Gaus, Bruns, Ajnštajn

    Directory of Open Access Journals (Sweden)

    Helmut Moritz

    2016-12-01

    Full Text Available It has been pointed out by the great Swedish geodesist Arne Bjerhammar and others around1985 that it is possible to replace the classical method of spirit leveling for determining differences of the geopotential by a much more direct and elegant method, measuring the frequency of atomic clocks. This is impossible by classical physics and requires methods of Einstein’s General Theory of Relativity. The principle is that the geopotential can be “felt” by the “proper time” of this theory, but there remained the problem that the measuring accuracies were unthinkably high in 1985 and even later. To get a leveling accuracy of 1 cm, we must measure these frequencies to a relative accuracy of 10-18. Reaching such accuracies provided a great challenge to high-precision time observation all over the world, from USA to China. Now it seems that the required frequency accuracy is being reached. The author tries to give a short introductory review accessible to geodetic students and surveyors. It is purely didactic. : Veliki švedski geodeta Arne Bjerhammar (i neki drugi, istakao je oko 1985. godine, da je klasičnu metodu geometrijskog nivelmana za određivanje razlika geopotencijala moguće zamijeniti mnogo direktnijom i elegantnom metodom, mjerenjem frekvencije atomskih satova. Ovo nije moguće metodama klasične fizike, te zahtijeva primjenu Ajnštajnove Teorije općeg relativiteta. Princip je da se geopotencijal može “osjetiti” pomoću “pravog vremena” ove teorije, ali ostaje problem što je tačnost mjerenja bila nezamisliva u 1985. godini, pa čak i poslije. Da bi se dobila tačnost nivelanja od 1 cm, frekvencije se moraju mjeriti s relativnom tačnošću od 10-18. Dostizanje ove tačnosti bio je ogroman izazov za sve svjetske opservatorije za visokoprecizno mjerenje vremena, od SAD do Kine. Čini se da je zahtijevana tačnost ipak dostignuta. Autor nastoji dati kratak, potpuno didaktički uvod, pristupačan studentima geodezije i

  9. Advances In Global Aerosol Modeling Applications Through Assimilation of Satellite-Based Lidar Measurements

    Science.gov (United States)

    Campbell, James; Hyer, Edward; Zhang, Jianglong; Reid, Jeffrey; Westphal, Douglas; Xian, Peng; Vaughan, Mark

    2010-05-01

    Modeling the instantaneous three-dimensional aerosol field and its downwind transport represents an endeavor with many practical benefits foreseeable to air quality, aviation, military and science agencies. The recent proliferation of multi-spectral active and passive satellite-based instruments measuring aerosol physical properties has served as an opportunity to develop and refine the techniques necessary to make such numerical modeling applications possible. Spurred by high-resolution global mapping of aerosol source regions, and combined with novel multivariate data assimilation techniques designed to consider these new data streams, operational forecasts of visibility and aerosol optical depths are now available in near real-time1. Active satellite-based aerosol profiling, accomplished using lidar instruments, represents a critical element for accurate analysis and transport modeling. Aerosol source functions, alone, can be limited in representing the macrophysical structure of injection scenarios within a model. Two-dimensional variational (2D-VAR; x, y) assimilation of aerosol optical depth from passive satellite observations significantly improves the analysis of the initial state. However, this procedure can not fully compensate for any potential vertical redistribution of mass required at the innovation step. The expense of an inaccurate vertical analysis of aerosol structure is corresponding errors downwind, since trajectory paths within successive forecast runs will likely diverge with height. In this paper, the application of a newly-designed system for 3D-VAR (x,y,z) assimilation of vertical aerosol extinction profiles derived from elastic-scattering lidar measurements is described [Campbell et al., 2009]. Performance is evaluated for use with the U. S. Navy Aerosol Analysis and Prediction System (NAAPS) by assimilating NASA/CNES satellite-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) 0.532 μm measurements [Winker et al., 2009

  10. Analysis of Satellite AIS Data to Derive Weather Judging Criteria for Voyage Route Selection

    Directory of Open Access Journals (Sweden)

    Michio Fujii

    2017-06-01

    Full Text Available The operational limitations are discussed at the IMO as a part of the second generation intact stability criteria. Since it is a first attempt to introduce operational efforts into safety regulations, comprehensive discussions are necessary to realize practically acceptable ones. Therefore this study investigates actual navigation routes of container ships and pure car carriers in the trans-North Pacific Ocean in winter, because they are prone to suffer significant parametric roll which is one of stability failure modes. Firstly, interviews are made to shipmasters who have experiences to have operated the subject ships to identify major elements for route selection in the North Pacific Ocean. Secondly, sufficient number of actual navigation records is collected from Satellite AIS data to derive the weather criteria for the route selection in severe weather condition. Finally, shipmaster’s on-board decision-making criteria are discussed by analysing the ship tracking data and weather data.

  11. End-to-end network models encompassing terrestrial, wireless, and satellite components

    Science.gov (United States)

    Boyarko, Chandler L.; Britton, John S.; Flores, Phil E.; Lambert, Charles B.; Pendzick, John M.; Ryan, Christopher M.; Shankman, Gordon L.; Williams, Ramon P.

    2004-08-01

    Development of network models that reflect true end-to-end architectures such as the Transformational Communications Architecture need to encompass terrestrial, wireless and satellite component to truly represent all of the complexities in a world wide communications network. Use of best-in-class tools including OPNET, Satellite Tool Kit (STK), Popkin System Architect and their well known XML-friendly definitions, such as OPNET Modeler's Data Type Description (DTD), or socket-based data transfer modules, such as STK/Connect, enable the sharing of data between applications for more rapid development of end-to-end system architectures and a more complete system design. By sharing the results of and integrating best-in-class tools we are able to (1) promote sharing of data, (2) enhance the fidelity of our results and (3) allow network and application performance to be viewed in the context of the entire enterprise and its processes.

  12. Satellite-derived temperature data for monitoring water status in a floodplain forest of the Upper Sabine River, Texas

    Science.gov (United States)

    Lemon, Mary Grace T.; Allen, Scott T.; Edwards, Brandon L.; King, Sammy L.; Keim, Richard F.

    2016-01-01

    Decreased water availability due to hydrologic modifications, groundwater withdrawal, and climate change threaten bottomland hardwood (BLH) forest communities. We used satellite-derived (MODIS) land-surface temperature (LST) data to investigate spatial heterogeneity of canopy temperature (an indicator of plant-water status) in a floodplain forest of the upper Sabine River for 2008–2014. High LST pixels were generally further from the river and at higher topographic locations, indicating lower water-availability. Increasing rainfall-derived soil moisture corresponded with decreased heterogeneity of LST between pixels but there was weaker association between Sabine River stage and heterogeneity. Stronger dependence of LST convergence on rainfall rather than river flow suggests that some regions are less hydrologically connected to the river, and vegetation may rely on local precipitation and other contributions to the riparian aquifer to replenish soil moisture. Observed LST variations associated with hydrology encourage further investigation of the utility of this approach for monitoring forest stress, especially with considerations of climate change and continued river management.

  13. A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 3: A stochastic rain fade control algorithm for satellite link power via non linear Markow filtering theory

    Science.gov (United States)

    Manning, Robert M.

    1991-01-01

    The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.

  14. Comparing offshore wind farm wake observed from satellite SAR and wake model results

    Science.gov (United States)

    Bay Hasager, Charlotte

    2014-05-01

    are modeled by various types of wake models. In the EERA DTOC project the model suite consists of engineering models (Ainslie, DWM, GLC, PARK, WASP/NOJ), simplified CFD models (FUGA, FarmFlow), full CFD models (CRES-flowNS, RANS), mesoscale model (SKIRON, WRF) and coupled meso-scale and microscale models. The comparison analysis between the satellite wind wake and model results will be presented and discussed. It is first time a comprehensive analysis is performed on this subject. The topic gains increasing importance because there is a growing need to precisely model also mid- and far-field wind farms wakes for development and planning of offshore wind farm clusters.

  15. Advances in snow cover distributed modelling via ensemble simulations and assimilation of satellite data

    Science.gov (United States)

    Revuelto, J.; Dumont, M.; Tuzet, F.; Vionnet, V.; Lafaysse, M.; Lecourt, G.; Vernay, M.; Morin, S.; Cosme, E.; Six, D.; Rabatel, A.

    2017-12-01

    Nowadays snowpack models show a good capability in simulating the evolution of snow in mountain areas. However singular deviations of meteorological forcing and shortcomings in the modelling of snow physical processes, when accumulated on time along a snow season, could produce large deviations from real snowpack state. The evaluation of these deviations is usually assessed with on-site observations from automatic weather stations. Nevertheless the location of these stations could strongly influence the results of these evaluations since local topography may have a marked influence on snowpack evolution. Despite the evaluation of snowpack models with automatic weather stations usually reveal good results, there exist a lack of large scale evaluations of simulations results on heterogeneous alpine terrain subjected to local topographic effects.This work firstly presents a complete evaluation of the detailed snowpack model Crocus over an extended mountain area, the Arve upper catchment (western European Alps). This catchment has a wide elevation range with a large area above 2000m a.s.l. and/or glaciated. The evaluation compares results obtained with distributed and semi-distributed simulations (the latter nowadays used on the operational forecasting). Daily observations of the snow covered area from MODIS satellite sensor, seasonal glacier surface mass balance evolution measured in more than 65 locations and the galciers annual equilibrium line altitude from Landsat/Spot/Aster satellites, have been used for model evaluation. Additionally the latest advances in producing ensemble snowpack simulations for assimilating satellite reflectance data over extended areas will be presented. These advances comprises the generation of an ensemble of downscaled high-resolution meteorological forcing from meso-scale meteorological models and the application of a particle filter scheme for assimilating satellite observations. Despite the results are prefatory, they show a good

  16. Spectral evaluation of Earth geopotential models and an experiment ...

    Indian Academy of Sciences (India)

    the models and monitoring the improvements in gravity field recovery are required. This study assesses ... group from the Inter- national Gravity Field Service (IGFS) and the ..... the method, the process may therefore be iter- ated until the ...

  17. Assimilation of satellite altimeter data into an open ocean model

    Science.gov (United States)

    Vogeler, Armin; SchröTer, Jens

    1995-08-01

    Geosat sea surface height data are assimilated into an eddy-resolving quasi-geostrophic open ocean model using the adjoint technique. The method adjusts the initial conditions for all layers and is successful on the timescale of a few weeks. Time-varying values for the open boundaries are prescribed by a much larger quasi-geostrophic model of the Antarctic Circumpolar Current (ACC). Both models have the same resolution of approximately 20×20 km (1/3°×1/6°), have three layers, and include realistic bottom topography and coastlines. The open model box is embedded in the African sector of the ACC. For continuous assimilation of satellite data into the larger model the nudging technique is applied. These results are used for the adjoint optimization procedure as boundary conditions and as a first guess for the initial condition. For the open model box the difference between model and satellite sea surface height that remains after the nudging experiment amounts to a 19-cm root-mean-square error (rmse). By assimilation into the regional model this value can be reduced to a 6-cm rmse for an assimilation period of 20 days. Several experiments which attempt to improve the convergence of the iterative optimization method are reported. Scaling and regularization by smoothing have to be applied carefully. Especially during the first 10 iterations, the convergence can be improved considerably by low-pass filtering of the cost function gradient. The result of a perturbation experiment shows that for longer assimilation periods the influence of the boundary values becomes dominant and they should be determined inversely by data assimilation into the open ocean model.

  18. Refined Use of Satellite Aerosol Optical Depth Snapshots to Constrain Biomass Burning Emissions in the GOCART Model

    Science.gov (United States)

    Petrenko, Mariya; Kahn, Ralph; Chin, Mian; Limbacher, James

    2017-10-01

    Simulations of biomass burning (BB) emissions in global chemistry and aerosol transport models depend on external inventories, which provide location and strength for BB aerosol sources. Our previous work shows that to first order, satellite snapshots of aerosol optical depth (AOD) near the emitted smoke plume can be used to constrain model-simulated AOD, and effectively, the smoke source strength. We now refine the satellite-snapshot method and investigate where applying simple multiplicative emission adjustment factors alone to the widely used Global Fire Emission Database version 3 emission inventory can achieve regional-scale consistency between Moderate Resolution Imaging Spectroradiometer (MODIS) AOD snapshots and the Goddard Chemistry Aerosol Radiation and Transport model. The model and satellite AOD are compared globally, over a set of BB cases observed by the MODIS instrument during the 2004, and 2006-2008 biomass burning seasons. Regional discrepancies between the model and satellite are diverse around the globe yet quite consistent within most ecosystems. We refine our approach to address physically based limitations of our earlier work (1) by expanding the number of fire cases from 124 to almost 900, (2) by using scaled reanalysis-model simulations to fill missing AOD retrievals in the MODIS observations, (3) by distinguishing the BB components of the total aerosol load from background aerosol in the near-source regions, and (4) by including emissions from fires too small to be identified explicitly in the satellite observations. The small-fire emission adjustment shows the complimentary nature of correcting for source strength and adding geographically distinct missing sources. Our analysis indicates that the method works best for fire cases where the BB fraction of total AOD is high, primarily evergreen or deciduous forests. In heavily polluted or agricultural burning regions, where smoke and background AOD values tend to be comparable, this approach

  19. The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange

    Science.gov (United States)

    Joiner, J.; Yoshida, Y.; Vasilkov, A. P.; Schaefer, K.; Jung, M.; Guanter, L.; Zhang, Y; Garrity, S.; Middleton, E. M.; Huemmrich, K. F.; hide

    2014-01-01

    Mapping of terrestrial chlorophyll uorescence from space has shown potentialfor providing global measurements related to gross primary productivity(GPP). In particular, space-based fluorescence may provide information onthe length of the carbon uptake period that can be of use for global carboncycle modeling. Here, we examine the seasonal cycle of photosynthesis asestimated from satellite fluorescence retrievals at wavelengths surroundingthe 740nm emission feature. These retrievals are from the Global OzoneMonitoring Experiment 2 (GOME-2) flying on the MetOp A satellite. Wecompare the fluorescence seasonal cycle with that of GPP as estimated froma diverse set of North American tower gas exchange measurements. Because the GOME-2 has a large ground footprint (40 x 80km2) as compared with that of the flux towers and requires averaging to reduce random errors, we additionally compare with seasonal cycles of upscaled GPP in the satellite averaging area surrounding the tower locations estimated from the Max Planck Institute for Biogeochemistry (MPI-BGC) machine learning algorithm. We also examine the seasonality of absorbed photosynthetically-active radiation(APAR) derived with reflectances from the MODerate-resolution Imaging Spectroradiometer (MODIS). Finally, we examine seasonal cycles of GPP as produced from an ensemble of vegetation models. Several of the data-driven models rely on satellite reflectance-based vegetation parameters to derive estimates of APAR that are used to compute GPP. For forested sites(particularly deciduous broadleaf and mixed forests), the GOME-2 fluorescence captures the spring onset and autumn shutoff of photosynthesis as delineated by the tower-based GPP estimates. In contrast, the reflectance-based indicators and many of the models tend to overestimate the length of the photosynthetically-active period for these and other biomes as has been noted previously in the literature. Satellite fluorescence measurements therefore show potential for

  20. Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

    Science.gov (United States)

    Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

    2011-01-01

    In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to