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

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

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.

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)

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

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.

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...

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

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

Estimating carbon flux phenology with satellite-derived land surface phenology and climate drivers for different biomes: a synthesis of AmeriFlux observations.

Directory of Open Access Journals (Sweden)

Wenquan Zhu

Full Text Available Carbon Flux Phenology (CFP can affect the interannual variation in Net Ecosystem Exchange (NEE of carbon between terrestrial ecosystems and the atmosphere. In this study, we proposed a methodology to estimate CFP metrics with satellite-derived Land Surface Phenology (LSP metrics and climate drivers for 4 biomes (i.e., deciduous broadleaf forest, evergreen needleleaf forest, grasslands and croplands, using 159 site-years of NEE and climate data from 32 AmeriFlux sites and MODIS vegetation index time-series data. LSP metrics combined with optimal climate drivers can explain the variability in Start of Carbon Uptake (SCU by more than 70% and End of Carbon Uptake (ECU by more than 60%. The Root Mean Square Error (RMSE of the estimations was within 8.5 days for both SCU and ECU. The estimation performance for this methodology was primarily dependent on the optimal combination of the LSP retrieval methods, the explanatory climate drivers, the biome types, and the specific CFP metric. This methodology has a potential for allowing extrapolation of CFP metrics for biomes with a distinct and detectable seasonal cycle over large areas, based on synoptic multi-temporal optical satellite data and climate data.

Radiological soil survey adjacent to TA-35, TA-48, TA-50, and TA-55

International Nuclear Information System (INIS)

Purtymun, W.D.; Becker, N.M.; Maes, M.N.

1985-01-01

The 137 Cs concentrations in soil from five new locations (in technical areas where radioactive materials are processed or have been processed) are at or below the maximum levels (1.4 pCi/g) found in regional soils. The 238 Pu and /sup 239,240/Pu soil concentrations at Station 2 were greater than were those found in regional soils (1977 and 1978-1982 Summaries). Station 2 is located south of TA-50. The total uranium soil concentrations exceed regional background concentrations at all stations. However, these levels do not indicate contamination but reflect natural uranium leached from soil derived from the tuff. These concentrations are similar to the data collected in 1977. Uranium concentrations in soils vary and depend on the rock type that has weathered to form the soil. A comparison of the averages and standard deviations of radiochemical analyses collected in 1977 and 1983 indicates only slight variations between the 2 yr. The five new stations established in 1983 will provide long-term monitoring of the possible airborne deposition of contaminants in the areas around TA-35, TA-48, TA-50, and TA-55. Comparing 1977 with 1983 data indicates no significant increase in radioactivity of the soil adjacent to these technical areas

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.

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

vegetation cover (taken for vegetation temperature) Ta and efficient radiation temperature Ts.eff, as well as land surface emissivity E, normalized difference vegetation index NDVI, vegetation cover fraction B, and leaf area index LAI. The SEVIRI-based retrievals have included precipitation, LST Tls and Ta, E at daylight and nighttime, LAI (daily), and B. From the MSU-MR data there have been retrieved values of all the same characteristics as from the AVHRR data. The MSU-MR-based daily and monthly sums of precipitation have been calculated using the developed earlier and modified Multi Threshold Method (MTM) intended for the cloud detection and identification of its types around the clock as well as allocation of precipitation zones and determination of instantaneous maximum rainfall intensities for each pixel at that the transition from assessing rainfall intensity to estimating their daily values is a key element of the MTM. Measurement data from 3 IR MSU-MR channels (3.8, 11 i 12 μm) as well as their differences have been used in the MTM as predictors. Controlling the correctness of the MSU-MR-derived rainfall estimates has been carried out when comparing with analogous AVHRR- and SEVIRI-based retrievals and with precipitation amounts measured at the agricultural meteorological station of the study region. Probability of rainfall zones determination from the MSU-MR data, to match against the actual ones, has been 75-85% as well as for the AVHRR and SEVIRI data. The time behaviors of satellite-derived and ground-measured daily and monthly precipitation sums for vegetation season and yeaŗ correspondingly, have been in good agreement with each other although the first ones have been smoother than the latter. Discrepancies have existed for a number of local maxima for which satellite-derived precipitation estimates have been less than ground-measured values. It may be due to the different spatial scales of areal satellite-derived and point ground-based estimates. Some

Harmonizing estimates of forest land area from national-level forest inventory and satellite imagery

Science.gov (United States)

Bonnie Ruefenacht; Mark D. Nelson; Mark Finco

2009-01-01

Estimates of forest land area are derived both from national-level forest inventories and satellite image-based map products. These estimates can differ substantially within subregional extents (e.g., states or provinces) primarily due to differences in definitions of forest land between inventory- and image-based approaches. We present a geospatial modeling approach...

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.

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.

Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery (Draft)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Estimated shallow-water, depth maps were produced using rule-based, semi-automated image analysis of high-resolution satellite imagery for nine locations in the...

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

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.

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.

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.

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.

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.

Estimating Global Ecosystem Isohydry/Anisohydry Using Active and Passive Microwave Satellite Data

Science.gov (United States)

Li, Yan; Guan, Kaiyu; Gentine, Pierre; Konings, Alexandra G.; Meinzer, Frederick C.; Kimball, John S.; Xu, Xiangtao; Anderegg, William R. L.; McDowell, Nate G.; Martinez-Vilalta, Jordi; Long, David G.; Good, Stephen P.

2017-12-01

The concept of isohydry/anisohydry describes the degree to which plants regulate their water status, operating from isohydric with strict regulation to anisohydric with less regulation. Though some species level measures of isohydry/anisohydry exist at a few locations, ecosystem-scale information is still largely unavailable. In this study, we use diurnal observations from active (Ku-Band backscatter from QuikSCAT) and passive (X-band vegetation optical depth (VOD) from Advanced Microwave Scanning Radiometer on EOS Aqua) microwave satellite data to estimate global ecosystem isohydry/anisohydry. Here diurnal observations from both satellites approximate predawn and midday plant canopy water contents, which are used to estimate isohydry/anisohydry. The two independent estimates from radar backscatter and VOD show reasonable agreement at low and middle latitudes but diverge at high latitudes. Grasslands, croplands, wetlands, and open shrublands are more anisohydric, whereas evergreen broadleaf and deciduous broadleaf forests are more isohydric. The direct validation with upscaled in situ species isohydry/anisohydry estimates indicates that the VOD-based estimates have much better agreement than the backscatter-based estimates. The indirect validation with prior knowledge suggests that both estimates are generally consistent in that vegetation water status of anisohydric ecosystems more closely tracks environmental fluctuations of water availability and demand than their isohydric counterparts. However, uncertainties still exist in the isohydry/anisohydry estimate, primarily arising from the remote sensing data and, to a lesser extent, from the methodology. The comprehensive assessment in this study can help us better understand the robustness, limitation, and uncertainties of the satellite-derived isohydry/anisohydry estimates. The ecosystem isohydry/anisohydry has the potential to reveal new insights into spatiotemporal ecosystem response to droughts.

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...

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

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...

Observing System Simulations for Small Satellite Formations Estimating Bidirectional Reflectance

Science.gov (United States)

Nag, Sreeja; Gatebe, Charles K.; de Weck, Olivier

2015-01-01

The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: Use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.

Observing system simulations for small satellite formations estimating bidirectional reflectance

Science.gov (United States)

Nag, Sreeja; Gatebe, Charles K.; Weck, Olivier de

2015-12-01

The bidirectional reflectance distribution function (BRDF) gives the reflectance of a target as a function of illumination geometry and viewing geometry, hence carries information about the anisotropy of the surface. BRDF is needed in remote sensing for the correction of view and illumination angle effects (for example in image standardization and mosaicing), for deriving albedo, for land cover classification, for cloud detection, for atmospheric correction, and other applications. However, current spaceborne instruments provide sparse angular sampling of BRDF and airborne instruments are limited in the spatial and temporal coverage. To fill the gaps in angular coverage within spatial, spectral and temporal requirements, we propose a new measurement technique: use of small satellites in formation flight, each satellite with a VNIR (visible and near infrared) imaging spectrometer, to make multi-spectral, near-simultaneous measurements of every ground spot in the swath at multiple angles. This paper describes an observing system simulation experiment (OSSE) to evaluate the proposed concept and select the optimal formation architecture that minimizes BRDF uncertainties. The variables of the OSSE are identified; number of satellites, measurement spread in the view zenith and relative azimuth with respect to solar plane, solar zenith angle, BRDF models and wavelength of reflection. Analyzing the sensitivity of BRDF estimation errors to the variables allow simplification of the OSSE, to enable its use to rapidly evaluate formation architectures. A 6-satellite formation is shown to produce lower BRDF estimation errors, purely in terms of angular sampling as evaluated by the OSSE, than a single spacecraft with 9 forward-aft sensors. We demonstrate the ability to use OSSEs to design small satellite formations as complements to flagship mission data. The formations can fill angular sampling gaps and enable better BRDF products than currently possible.

Estimation and quantification of mangrove forest extent by using different spatial resolution satellite data for the sandspit area of Karachi coast

International Nuclear Information System (INIS)

Saeed, U.; Daud, A.; Ashraf, S.; Mahmood, A.

2006-01-01

Mangrove forest is an integral part of inter-tidal zone of the coastal environment extending throughout the tropics and subtropics of the world. In Pakistan, for the last thirty years, remote-sensing data has significantly been used for area estimation of mangrove forests. In the previous studies medium resolution satellite data have been used for the area estimation of mangrove forests that revealed some of the discrepancies in terms of recognition of the subtle variations of landcover features in the satellite imagery. Current study aims at the classification techniques employed for the area estimation using high and medium resolution satellite imageries. To study the effects of spatial resolution on classification results, three different satellite data were used, including Quickbird, TERRA and Landsat satellites. Thematic map derived from Quickbird data was comprised of maximum number of land cover classes with a definite zone of mangroves that extends from regeneration to mature canopies. Total estimated mangroves extent was 370 ha with 57.45, 125.9, 180.89, and 5.35 ha of tall, medium, small, and new recruitment mangrove plants respectively. While mangrove area estimations from thematic maps derived using TERRA and Landsat satellite data, showed a gradual increase in the mangrove extent from 390.95 ha to 417.92 ha. This increase in area is an indicative of the fact that some of the landcover classes may have been miss-classified and hence added to the area under mangrove forests. This study also showed that high-resolution satellite data could be used for identifying different height zones of mangrove forests, along with an accurate delineation of classes like salt bushes and algae, which could not be classified otherwise. (author)

The associations between birth outcomes and satellite-estimated maternal PM2.5 exposure in Shanghai, China

Science.gov (United States)

Xiao, Q.; Liu, Y.; Strickland, M. J.; Chang, H. H.; Kan, H.

2017-12-01

Background: Satellite remote sensing data have been employed for air pollution exposure assessment, with the intent of better characterizing exposure spatio-temproal variations. However, non-random missingness in satellite data may lead to exposure error. Objectives: We explored the differences in health effect estimates due to different exposure metrics, with and without satellite data, when analyzing the associations between maternal PM2.5 exposure and birth outcomes. Methods: We obtained birth registration records of 132,783 singleton live births during 2011-2014 in Shanghai. Trimester-specific and total pregnancy exposures were estimated from satellite PM2.5 predictions with missingness, gap-filled satellite PM2.5 predictions with complete coverage and regional average PM2.5 measurements from monitoring stations. Linear regressions estimated associations between birth weight and maternal PM2.5 exposure. Logistic regressions estimated associations between preterm birth and the first and second trimester exposure. Discrete-time models estimated third trimester and total pregnancy associations with preterm birth. Effect modifications by maternal age and parental education levels were investigated. Results: we observed statistically significant associations between maternal PM2.5 exposure during all exposure windows and adverse birth outcomes. A 10 µg/m3 increase in pregnancy PM2.5 exposure was associated with a 12.85 g (95% CI: 18.44, 7.27) decrease in birth weight for term births, and a 27% (95% CI: 20%, 36%) increase in the risk of preterm birth. Greater effects were observed between first and third trimester exposure and birth weight, as well as between first trimester exposure and preterm birth. Mothers older than 35 years and without college education tended to have higher associations with preterm birth. Conclusions: Gap-filled satellite data derived PM2.5 exposure estimates resulted in reduced exposure error and more precise health effect estimates.

Connecting Satellite-Based Precipitation Estimates to Users

Science.gov (United States)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric

2018-01-01

Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

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

Incorporating Satellite Precipitation Estimates into a Radar-Gauge Multi-Sensor Precipitation Estimation Algorithm

Directory of Open Access Journals (Sweden)

Yuxiang He

2018-01-01

Full Text Available This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE that would objectively blend real-time satellite quantitative precipitation estimates (SQPE with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a five-year period between 2003–2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS (National Weather Service operations over two regions: (I Inside radar effective coverage and (II immediately outside radar coverage. The outcomes of the evaluation indicate (a ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and (b blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

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

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.

Estimating Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations

Directory of Open Access Journals (Sweden)

Bradley C. Reed

2013-02-01

Full Text Available Winter annual plants in southwestern North America influence fire regimes, provide forage, and help prevent erosion. Exotic annuals may also threaten native species. Monitoring winter annuals is difficult because of their ephemeral nature, making the development of a satellite monitoring tool valuable. We mapped winter annual aboveground biomass in the Desert Southwest from satellite observations, evaluating 18 algorithms using time-series vegetation indices (VI. Field-based biomass estimates were used to calibrate and evaluate each algorithm. Winter annual biomass was best estimated by calculating a base VI across the period of record and subtracting it from the peak VI for each winter season (R2 = 0.92. The normalized difference vegetation index (NDVI derived from 8-day reflectance data provided the best estimate of winter annual biomass. It is important to account for the timing of peak vegetation when relating field-based estimates to satellite VI data, since post-peak field estimates may indicate senescent biomass which is inaccurately represented by VI-based estimates. Images generated from the best-performing algorithm show both spatial and temporal variation in winter annual biomass. Efforts to manage this variable resource would be enhanced by a tool that allows the monitoring of changes in winter annual resources over time.

Superstructure Ta2O5 mesocrystals derived from (NH4)2Ta2O3F6 mesocrystals with efficient photocatalytic activity.

Science.gov (United States)

Yu, Xin; Li, Wei; Huang, Jian; Li, Zhonghua; Liu, Jiawen; Hu, PingAn

2018-02-06

Superstructured mesocrystalline Ta 2 O 5 nanosheets were successfully prepared from mesocrystalline (NH 4 ) 2 Ta 2 O 3 F 6 nanorods by the annealing method for the first time. The as-prepared mesocrystalline Ta 2 O 5 nanosheets in this work showed remarkable visible light absorption, mainly due to the formation of oxygen vacancy defects in the mesocrystalline Ta 2 O 5 nanosheets, which was also confirmed by XPS spectra, Raman spectra and EPR spectra. Besides, the mesocrystalline Ta 2 O 5 nanosheets showed a highly enhanced photocatalytic activity of 11 268.24 μmol g -1 h -1 , about 3.95 times that of commercial Ta 2 O 5 . Moreover, the specific surface area of the mesocrystalline Ta 2 O 5 -800 nanosheets was 16.34 m 2 g -1 , about 5.32 times that of the commercial Ta 2 O 5 (3.072 m 2 g -1 ). The valence band XPS spectra indicated a strong oxidizing ability of the mesocrystalline Ta 2 O 5 nanosheets in comparison to that of commercial Ta 2 O 5 . The formation of superstructured Ta 2 O 5 mesocrystals generated long lifetime carriers and effective conduction pathways, which greatly enhanced the photocatalytic activity for hydrogen production.

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 ...

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.

A Study on Fuel Estimation Algorithms for a Geostationary Communication & Broadcasting Satellite

Directory of Open Access Journals (Sweden)

Jong Won Eun

2000-12-01

Full Text Available It has been developed to calculate fuel budget for a geostationary communication and broadcasting satellite. It is quite essential that the pre-launch fuel budget estimation must account for the deterministic transfer and drift orbit maneuver requirements. After on-station, the calculation of satellite lifetime should be based on the estimation of remaining fuel and assessment of actual performance. These estimations step from the proper algorithms to produce the prediction of satellite lifetime. This paper concentrates on the fuel estimation method that was studied for calculation of the propellant budget by using the given algorithms. Applications of this method are discussed for a communication and broadcasting satellite.

Determining Optimal New Generation Satellite Derived Metrics for Accurate C3 and C4 Grass Species Aboveground Biomass Estimation in South Africa

Directory of Open Access Journals (Sweden)

Cletah Shoko

2018-04-01

Full Text Available While satellite data has proved to be a powerful tool in estimating C3 and C4 grass species Aboveground Biomass (AGB, finding an appropriate sensor that can accurately characterize the inherent variations remains a challenge. This limitation has hampered the remote sensing community from continuously and precisely monitoring their productivity. This study assessed the potential of a Sentinel 2 MultiSpectral Instrument, Landsat 8 Operational Land Imager, and WorldView-2 sensors, with improved earth imaging characteristics, in estimating C3 and C4 grasses AGB in the Cathedral Peak, South Africa. Overall, all sensors have shown considerable potential in estimating species AGB; with the use of different combinations of the derived spectral bands and vegetation indices producing better accuracies. However, WorldView-2 derived variables yielded better predictive accuracies (R2 ranging between 0.71 and 0.83; RMSEs between 6.92% and 9.84%, followed by Sentinel 2, with R2 between 0.60 and 0.79; and an RMSE 7.66% and 14.66%. Comparatively, Landsat 8 yielded weaker estimates, with R2 ranging between 0.52 and 0.71 and high RMSEs ranging between 9.07% and 19.88%. In addition, spectral bands located within the red edge (e.g., centered at 0.705 and 0.745 µm for Sentinel 2, SWIR, and NIR, as well as the derived indices, were found to be very important in predicting C3 and C4 AGB from the three sensors. The competence of these bands, especially of the free-available Landsat 8 and Sentinel 2 dataset, was also confirmed from the fusion of the datasets. Most importantly, the three sensors managed to capture and show the spatial variations in AGB for the target C3 and C4 grassland area. This work therefore provides a new horizon and a fundamental step towards C3 and C4 grass productivity monitoring for carbon accounting, forage mapping, and modelling the influence of environmental changes on their productivity.

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.

A Study on Fuel Estimation Algorithms for a Geostationary Communication & Broadcasting Satellite

OpenAIRE

Jong Won Eun

2000-01-01

It has been developed to calculate fuel budget for a geostationary communication and broadcasting satellite. It is quite essential that the pre-launch fuel budget estimation must account for the deterministic transfer and drift orbit maneuver requirements. After on-station, the calculation of satellite lifetime should be based on the estimation of remaining fuel and assessment of actual performance. These estimations step from the proper algorithms to produce the prediction of satellite lifet...

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.

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.

Estimating Regional Scale Hydroclimatic Risk Conditions from the Soil Moisture Active-Passive (SMAP Satellite

Directory of Open Access Journals (Sweden)

Catherine Champagne

2018-04-01

Full Text Available Satellite soil moisture is a critical variable for identifying susceptibility to hydroclimatic risks such as drought, dryness, and excess moisture. Satellite soil moisture data from the Soil Moisture Active/Passive (SMAP mission was used to evaluate the sensitivity to hydroclimatic risk events in Canada. The SMAP soil moisture data sets in general capture relative moisture trends with the best estimates from the passive-only derived soil moisture and little difference between the data at different spatial resolutions. In general, SMAP data sets overestimated the magnitude of moisture at the wet extremes of wetting events. A soil moisture difference from average (SMDA was calculated from SMAP and historical Soil Moisture and Ocean Salinity (SMOS data showed a relatively good delineation of hydroclimatic risk events, although caution must be taken due to the large variability in the data within risk categories. Satellite soil moisture data sets are more sensitive to short term water shortages than longer term water deficits. This was not improved by adding “memory” to satellite soil moisture indices to improve the sensitivity of the data to drought, and there is a large variability in satellite soil moisture values with the same drought severity rating.

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.

Calibration of Ocean Forcing with satellite Flux Estimates (COFFEE)

Science.gov (United States)

Barron, Charlie; Jan, Dastugue; Jackie, May; Rowley, Clark; Smith, Scott; Spence, Peter; Gremes-Cordero, Silvia

2016-04-01

Predicting the evolution of ocean temperature in regional ocean models depends on estimates of surface heat fluxes and upper-ocean processes over the forecast period. Within the COFFEE project (Calibration of Ocean Forcing with satellite Flux Estimates, real-time satellite observations are used to estimate shortwave, longwave, sensible, and latent air-sea heat flux corrections to a background estimate from the prior day's regional or global model forecast. These satellite-corrected fluxes are used to prepare a corrected ocean hindcast and to estimate flux error covariances to project the heat flux corrections for a 3-5 day forecast. In this way, satellite remote sensing is applied to not only inform the initial ocean state but also to mitigate errors in surface heat flux and model representations affecting the distribution of heat in the upper ocean. While traditional assimilation of sea surface temperature (SST) observations re-centers ocean models at the start of each forecast cycle, COFFEE endeavors to appropriately partition and reduce among various surface heat flux and ocean dynamics sources. A suite of experiments in the southern California Current demonstrates a range of COFFEE capabilities, showing the impact on forecast error relative to a baseline three-dimensional variational (3DVAR) assimilation using operational global or regional atmospheric forcing. Experiment cases combine different levels of flux calibration with assimilation alternatives. The cases use the original fluxes, apply full satellite corrections during the forecast period, or extend hindcast corrections into the forecast period. Assimilation is either baseline 3DVAR or standard strong-constraint 4DVAR, with work proceeding to add a 4DVAR expanded to include a weak constraint treatment of the surface flux errors. Covariance of flux errors is estimated from the recent time series of forecast and calibrated flux terms. While the California Current examples are shown, the approach is

Powder Metallurgy Processing of a WxTaTiVCr High-Entropy Alloy and Its Derivative Alloys for Fusion Material Applications.

Science.gov (United States)

Waseem, Owais Ahmed; Ryu, Ho Jin

2017-05-16

The W x TaTiVCr high-entropy alloy with 32at.% of tungsten (W) and its derivative alloys with 42 to 90at.% of W with in-situ TiC were prepared via the mixing of elemental W, Ta, Ti, V and Cr powders followed by spark plasma sintering for the development of reduced-activation alloys for fusion plasma-facing materials. Characterization of the sintered samples revealed a BCC lattice and a multi-phase structure. The selected-area diffraction patterns confirmed the formation of TiC in the high-entropy alloy and its derivative alloys. It revealed the development of C15 (cubic) Laves phases as well in alloys with 71 to 90at.% W. A mechanical examination of the samples revealed a more than twofold improvement in the hardness and strength due to solid-solution strengthening and dispersion strengthening. This study explored the potential of powder metallurgy processing for the fabrication of a high-entropy alloy and other derived compositions with enhanced hardness and strength.

Discharge estimation in arid areas with the help of optical satellite data

Science.gov (United States)

Mett, M.; Aufleger, M.

2009-04-01

The MENA region is facing severe water scarcity. Overexploitation of groundwater resources leads to an ongoing drawdown of the water tables, salinisation and desertification of vast areas. To make matters worse enormous birth-rates, economic growth and refugees from conflict areas let the need for water explode. In the context of climate change this situation will even worsen and armed conflicts are within the bounds of possibility. To ease water scarcity many innovative techniques like artificial groundwater recharge are being developed or already state of the art. But missing hydrological information (for instance discharge data) often prevents design and efficient operation of such measures. Especially in poor countries hydrological measuring devices like gage stations are often missing, in a bad status or professionals of the water sector are absent. This leads to the paradox situation that in many arid regions water resources are indeed available but they cannot be utilised because they are not known. Nowadays different approaches are being designed to obtain hydrological information from perennial river systems with the help of satellite techniques. Mostly they are based on hydraulic parameters like river dimensions, roughness and water levels which can be derived from satellite data. By using conventional flow formulas and additional field investigations the discharge can be estimated. Another methodology derived information about maximum flow depth and flow width from optical sensors of high resolution to calculate discharge of the rivers whilst the flood. Attempts to derive discharge information from structural components of the river and fluviomorphologic changes due to changing flow regimes are in the focus of recent research. One attempt used Synthetic Aperture Radar (SAR) data to estimate discharge in braided river systems. Other attempts used airborne SAR imagery to obtain information about sinuosity and total river width of perennial braided river

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

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.

Carbonitrides in the system Ta-TaC-TaN

International Nuclear Information System (INIS)

Ritzhaupt-Kleissl, H.J.

1975-04-01

Specimens have been prepared in the binary section TaC-TaN and the carbon-rich region of the Ta-TaC-TaN system by hot pressing and subsequent homogenisation. It was possible to prepare nitrogen-rich carbonitrides by homogenizing them at 1,800 0 C under a nitrogen-pressure of 50 at up to the composition of 70 mol% TaN/30 mol% TaC. Those carbonitrides containing less than 25 at% nitrogen could be prepared by homogenisation at 2,000 0 C under a nitrogen-pressure of 600 Torr. Subsequent ageing at temperatures of 1,200, 1,300 and 1,400 0 C in high vacuum as well as at 1 at nitrogen resulted in the appearance of precipitations of epsilon-TaN, β-Ta 2 (C,N) and of the zeta-phase. The type amount and shape of the precipitated phases are dependent on the ageing conditions and on the composition the specimens. Single phase specimens with compositions close to the non-metal deficient phase boundary as well as multi-phase carbonitrides with high nitrogen contents and very fine precipitates showed values of the Vickers-hardness up to 3,000 kp/mm 2 at room temperature. With regard to the hot hardness up to a temperature of 1,300 0 C specimens aged in high vacuum were superior to those which were only homogenized as well as to those aged under a nitrogen-pressure of 1 at. On an average the best hardness-values have been found at room temperature as well as at temperatures up to 1,300 0 C for carbonitrides consisting of 50 mol% TaC/50 mol% TaN after homogenisation and subsequent ageing for 40 h at 1,300 0 C. (orig.) [de

Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

Science.gov (United States)

Husak, G. J.; Marshall, M. T.; Michaelsen, J.; Pedreros, D.; Funk, C.; Galu, G.

2008-07-01

Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

Size-dependent disproportionation (in 2-20 nm regime) and hybrid Bond Valence derived interatomic potentials for BaTaO2N

Science.gov (United States)

Anbalagan, Kousika; Thomas, Tiju

2018-05-01

Interatomic potentials for complex materials (like ceramic systems) are important for realistic molecular dynamics (MD) simulations. Such simulations are relevant for understanding equilibrium, transport and dynamical properties of materials, especially in the nanoregime. Here we derive a hybrid interatomic potential (based on bond valence (BV) derived Morse and Coulomb terms), for modeling a complex ceramic, barium tantalum oxynitride (BaTaO2N). This material has been chosen due to its relevance for capacitive and photoactive applications. However, the material presents processing challenges such as the emergence of non-stoichiometric phases during processing, demonstrating complex processing-property correlations. This makes MD investigations of this material both scientifically and technologically relevant. The BV based hybrid potential presented here has been used for simulating sintering of BaTaO2N nanoparticles ( 2-20 nm) under different conditions (using the relevant canonical ensemble). Notably, we show that sintering of particles of diameter 10 nm in size results in the formation of a cluster of tantalum and oxygen atoms at the interface of the BaTaO2N particles. This is in agreement with the experimental reports. The results presented here suggest that the potential proposed can be used to explore dynamical properties of BaTaO2N and related systems. This work will also open avenues for development of nanoscience-enabled aid-free sintering approaches to this and related materials.

Comparative study of Ta, TaN and Ta/TaN bi-layer barriers for Cu-ultra low-k porous polymer integration

International Nuclear Information System (INIS)

Yang, L.Y.; Zhang, D.H.; Li, C.Y.; Foo, P.D.

2004-01-01

Tantalum (Ta), TaN and bilayer Ta/TaN barriers deposited on ultra-low-k porous polymer (ULKPP) and the thermal stability of their structures are comparatively investigated using various techniques. The Ta/ultra-low-k polymer shows the smallest sheet resistance, but the poorest thermal stability, while TaN on the ultra-low-k polymer shows the highest resistance but the best thermal stability. The bi-layer Ta/TaN barrier takes the advantage of both Ta and TaN barriers and gives reasonable resistance and thermal stability. The electrical tests indicate that the Cu lines with the TaN and bi-layer Ta/TaN barriers exhibit the smaller leakage current and higher breakdown voltage compared with the Cu lines with the Ta barrier. The better thermal stability of the TaN and the bi-layer Ta/TaN barriers is mainly due to the amorphous/nanostructure and less grain boundaries of the barriers. In addition, the texture discontinuity at the Ta/TaN interfaces in the bi-layers barrier also plays an important role in reducing mutual diffusion of Ta atoms in the Ta barrier and some atoms in the ultra-low-k porous polymer

Burst Format Design for Optimum Joint Estimation of Doppler-Shift and Doppler-Rate in Packet Satellite Communications

Directory of Open Access Journals (Sweden)

Luca Giugno

2007-05-01

Full Text Available This paper considers the problem of optimizing the burst format of packet transmission to perform enhanced-accuracy estimation of Doppler-shift and Doppler-rate of the carrier of the received signal, due to relative motion between the transmitter and the receiver. Two novel burst formats that minimize the Doppler-shift and the Doppler-rate Cramér-Rao bounds (CRBs for the joint estimation of carrier phase/Doppler-shift and of the Doppler-rate are derived, and a data-aided (DA estimation algorithm suitable for each optimal burst format is presented. Performance of the newly derived estimators is evaluated by analysis and by simulation, showing that such algorithms attain their relevant CRBs with very low complexity, so that they can be directly embedded into new-generation digital modems for satellite communications at low SNR.

A Method for Estimating BeiDou Inter-frequency Satellite Clock Bias

Directory of Open Access Journals (Sweden)

LI Haojun

2016-02-01

Full Text Available A new method for estimating the BeiDou inter-frequency satellite clock bias is proposed, considering the shortage of the current methods. The constant and variable parts of the inter-frequency satellite clock bias are considered in the new method. The data from 10 observation stations are processed to validate the new method. The characterizations of the BeiDou inter-frequency satellite clock bias are also analyzed using the computed results. The results of the BeiDou inter-frequency satellite clock bias indicate that it is stable in the short term. The estimated BeiDou inter-frequency satellite clock bias results are molded. The model results show that the 10 parameters of model for each satellite can express the BeiDou inter-frequency satellite clock bias well and the accuracy reaches cm level. When the model parameters of the first day are used to compute the BeiDou inter-frequency satellite clock bias of the second day, the accuracy also reaches cm level. Based on the stability and modeling, a strategy for the BeiDou satellite clock service is presented to provide the reference of our BeiDou.

Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast

International Nuclear Information System (INIS)

Escrig, H.; Batlles, F.J.; Alonso, J.; Baena, F.M.; Bosch, J.L.; Salbidegoitia, I.B.; Burgaleta, J.I.

2013-01-01

Considering that clouds are the greatest causes to solar radiation blocking, short term cloud forecasting can help power plant operation and therefore improve benefits. Cloud detection, classification and motion vector determination are key to forecasting sun obstruction by clouds. Geostationary satellites provide cloud information covering wide areas, allowing cloud forecast to be performed for several hours in advance. Herein, the methodology developed and tested in this study is based on multispectral tests and binary cross correlations followed by coherence and quality control tests over resulting motion vectors. Monthly synthetic surface albedo image and a method to reject erroneous correlation vectors were developed. Cloud classification in terms of opacity and height of cloud top is also performed. A whole-sky camera has been used for validation, showing over 85% of agreement between the camera and the satellite derived cloud cover, whereas error in motion vectors is below 15%. - Highlights: ► A methodology for detection, classification and movement of clouds is presented. ► METEOSAT satellite images are used to obtain a cloud mask. ► The prediction of cloudiness is estimated with 90% in overcast conditions. ► Results for partially covered sky conditions showed a 75% accuracy. ► Motion vectors are estimated from the clouds with a success probability of 86%

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

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

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

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.

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.

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.

Utilizing remote sensing data for modeling water and heat regimes of the Black Earth Region territory of the European Russia

Science.gov (United States)

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

2014-05-01

At present physical-mathematical modeling processes of water and heat exchange between vegetation covered land surfaces and atmosphere is the most appropriate method to describe peculiarities of water and heat regime formation for large territories. The developed model of such processes (Land Surface Model, LSM) is intended for calculation evaporation, transpiration by vegetation, soil water content and other water and heat regime characteristics, as well as distributions of the soil temperature and humidity in depth utilizing remote sensing data from satellites on land surface and meteorological conditions. The model parameters and input variables are the soil and vegetation characteristics and the meteorological characteristics, correspondingly. Their values have been determined from ground-based observations or satellite-based measurements by radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/Meteosat-9, -10. The case study has been carried out for the part of the agricultural Central Black Earth region with coordinates 49.5 deg. - 54 deg. N, 31 deg. - 43 deg. E and a total area of 227,300 km2 located in the steppe-forest zone of the European Russia for years 2009-2012 vegetation seasons. From AVHRR data there have been derived the estimates of three types of land surface temperature (LST): land surface skin temperature Tsg, air-foliage temperature Ta and efficient radiation temperature Ts.eff, emissivity E, normalized vegetation index NDVI, vegetation cover fraction B, leaf area index LAI, cloudiness and precipitation. From MODIS data the estimates of LST Tls, E, NDVI and LAI have been obtained. The SEVIRI data have been used to build the estimates of Tls, Ta, E, LAI and precipitation. Previously developed method and technology of above AVHRR-derived estimates have been improved and adapted to the study area. To check the reliability of the Ts.eff and Ta estimations for named seasons the error statistics of their definitions has been analyzed through

Estimating Zenith Tropospheric Delays from BeiDou Navigation Satellite System Observations

Directory of Open Access Journals (Sweden)

Xin Sui

2013-04-01

Full Text Available The GNSS derived Zenith Tropospheric Delay (ZTD plays today a very critical role in meteorological study and weather forecasts, as ZTDs of thousands of GNSS stations are operationally assimilated into numerical weather prediction models. Recently, the Chinese BeiDou Navigation Satellite System (BDS was officially announced to provide operational services around China and its neighborhood and it was demonstrated to be very promising for precise navigation and positioning. In this contribution, we concentrate on estimating ZTD using BDS observations to assess its capacity for troposphere remote sensing. A local network which is about 250 km from Beijing and comprised of six stations equipped with GPS- and BDS-capable receivers is utilized. Data from 5 to 8 November 2012 collected on the network is processed in network mode using precise orbits and in Precise Point Positioning mode using precise orbits and clocks. The precise orbits and clocks are generated from a tracking network with most of the stations in China and several stations around the world. The derived ZTDs are compared with that estimated from GPS data using the final products of the International GNSS Service (IGS. The comparison shows that the bias and the standard deviation of the ZTD differences are about 2 mm and 5 mm, respectively, which are very close to the differences of GPS ZTD estimated using different software packages.

Assessment of satellite-based precipitation estimates over Paraguay

Science.gov (United States)

Oreggioni Weiberlen, Fiorella; Báez Benítez, Julián

2018-04-01

Satellite-based precipitation estimates represent a potential alternative source of input data in a plethora of meteorological and hydrological applications, especially in regions characterized by a low density of rain gauge stations. Paraguay provides a good example of a case where the use of satellite-based precipitation could be advantageous. This study aims to evaluate the version 7 of the Tropical Rainfall Measurement Mission Multi-Satellite Precipitation Analysis (TMPA V7; 3B42 V7) and the version 1.0 of the purely satellite-based product of the Climate Prediction Center Morphing Technique (CMORPH RAW) through their comparison with daily in situ precipitation measurements from 1998 to 2012 over Paraguay. The statistical assessment is conducted with several commonly used indexes. Specifically, to evaluate the accuracy of daily precipitation amounts, mean error (ME), root mean square error (RMSE), BIAS, and coefficient of determination (R 2) are used, and to analyze the capability to correctly detect different precipitation intensities, false alarm ratio (FAR), frequency bias index (FBI), and probability of detection (POD) are applied to various rainfall rates (0, 0.1, 0.5, 1, 2, 5, 10, 20, 40, 60, and 80 mm/day). Results indicate that TMPA V7 has a better performance than CMORPH RAW over Paraguay. TMPA V7 has higher accuracy in the estimation of daily rainfall volumes and greater precision in the detection of wet days (> 0 mm/day). However, both satellite products show a lower ability to appropriately detect high intensity precipitation events.

Satellite telemetry reveals higher fishing mortality rates than previously estimated, suggesting overfishing of an apex marine predator.

Science.gov (United States)

Byrne, Michael E; Cortés, Enric; Vaudo, Jeremy J; Harvey, Guy C McN; Sampson, Mark; Wetherbee, Bradley M; Shivji, Mahmood

2017-08-16

Overfishing is a primary cause of population declines for many shark species of conservation concern. However, means of obtaining information on fishery interactions and mortality, necessary for the development of successful conservation strategies, are often fisheries-dependent and of questionable quality for many species of commercially exploited pelagic sharks. We used satellite telemetry as a fisheries-independent tool to document fisheries interactions, and quantify fishing mortality of the highly migratory shortfin mako shark ( Isurus oxyrinchus ) in the western North Atlantic Ocean. Forty satellite-tagged shortfin mako sharks tracked over 3 years entered the Exclusive Economic Zones of 19 countries and were harvested in fisheries of five countries, with 30% of tagged sharks harvested. Our tagging-derived estimates of instantaneous fishing mortality rates ( F = 0.19-0.56) were 10-fold higher than previous estimates from fisheries-dependent data (approx. 0.015-0.024), suggesting data used in stock assessments may considerably underestimate fishing mortality. Additionally, our estimates of F were greater than those associated with maximum sustainable yield, suggesting a state of overfishing. This information has direct application to evaluations of stock status and for effective management of populations, and thus satellite tagging studies have potential to provide more accurate estimates of fishing mortality and survival than traditional fisheries-dependent methodology. © 2017 The Author(s).

Estimations of distribution and zoning for air temperature using satellite data over Liaoning province, China

International Nuclear Information System (INIS)

Wang, X.; Horiguchi, I.; Takeda, T.; Yazawa, M.; Liu, X.; Yang, Y.; Wang, Q.

1999-01-01

The distribution and zoning of air temperature over Liaoning Province, China were examined using the calculated values of air temperature derived from satellite data (GMS data) as well as from altitude data. The results are summarized as follows. At 02:00 LST the correlation coefficients for the air temperatures calculated from altitude compared with the observed air temperatures were the same as those of the air temperatures derived from GMS data. At 14:00 LST, however, the correlation coefficients for air temperatures calculated from altitude were less than those of the air temperatures derived from GMS data. This fact verifies that the distribution of air temperature in the day-time is affected by other factors than altitude. The distribution of air temperature in a cell of approximately 5'(latitude) x 7.5'(longitude) over Liaoning Province, china was estimated by using the regression equations between surface temperature derived from GMS and the observed air temperature. The distribution of air temperature was classified into 5 types, and the types are obtained at 14:00 LST are seasonal ones but the types at 02:00 LST are not related to season. Also, the regional classification for the air temperature was examined using this distribution of air temperature. This regional classification for the air temperature was similar to the published zoning of the agricultural climate. It became clear that the characteristic distribution of air temperature in a cell unit can be obtained by satellite data. And it is possible to define the zoning of air temperature for a cell unit by the accumulated analyses of satellite data over an extended period

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.

Toward a Satellite-Based System of Sugarcane Yield Estimation and Forecasting in Smallholder Farming Conditions: A Case Study on Reunion Island

Directory of Open Access Journals (Sweden)

Julien Morel

2014-07-01

Full Text Available Estimating sugarcane biomass is difficult to achieve when working with highly variable spatial distributions of growing conditions, like on Reunion Island. We used a dataset of in-farm fields with contrasted climatic conditions and farming practices to compare three methods of yield estimation based on remote sensing: (1 an empirical relationship method with a growing season-integrated Normalized Difference Vegetation Index NDVI, (2 the Kumar-Monteith efficiency model, and (3 a forced-coupling method with a sugarcane crop model (MOSICAS and satellite-derived fraction of absorbed photosynthetically active radiation. These models were compared with the crop model alone and discussed to provide recommendations for a satellite-based system for the estimation of yield at the field scale. Results showed that the linear empirical model produced the best results (RMSE = 10.4 t∙ha−1. Because this method is also the simplest to set up and requires less input data, it appears that it is the most suitable for performing operational estimations and forecasts of sugarcane yield at the field scale. The main limitation is the acquisition of a minimum of five satellite images. The upcoming open-access Sentinel-2 Earth observation system should overcome this limitation because it will provide 10-m resolution satellite images with a 5-day frequency.

Evaluation of short-period rainfall estimates from Kalpana-1 satellite

Indian Academy of Sciences (India)

The INSAT Multispectral Rainfall Algorithm (IMSRA) technique for rainfall estimation, has recently been developed to meet the shortcomings of the Global Precipitation Index (GPI) technique of rainfall estimation from the data of geostationary satellites; especially for accurate short period rainfall estimates. This study ...

Estimation of Supraglacial Dust and Debris Geochemical Composition via Satellite Reflectance and Emissivity

Science.gov (United States)

Casey, Kimberly Ann; Kaab, Andreas

2012-01-01

We demonstrate spectral estimation of supraglacial dust, debris, ash and tephra geochemical composition from glaciers and ice fields in Iceland, Nepal, New Zealand and Switzerland. Surface glacier material was collected and analyzed via X-ray fluorescence spectroscopy (XRF) and X-ray diffraction (XRD) for geochemical composition and mineralogy. In situ data was used as ground truth for comparison with satellite derived geochemical results. Supraglacial debris spectral response patterns and emissivity-derived silica weight percent are presented. Qualitative spectral response patterns agreed well with XRF elemental abundances. Quantitative emissivity estimates of supraglacial SiO2 in continental areas were 67% (Switzerland) and 68% (Nepal), while volcanic supraglacial SiO2 averages were 58% (Iceland) and 56% (New Zealand), yielding general agreement. Ablation season supraglacial temperature variation due to differing dust and debris type and coverage was also investigated, with surface debris temperatures ranging from 5.9 to 26.6 C in the study regions. Applications of the supraglacial geochemical reflective and emissive characterization methods include glacier areal extent mapping, debris source identification, glacier kinematics and glacier energy balance considerations.

Estimation of Supraglacial Dust and Debris Geochemical Composition via Satellite Reflectance and Emissivity

Directory of Open Access Journals (Sweden)

Kimberly Casey

2012-09-01

Full Text Available We demonstrate spectral estimation of supraglacial dust, debris, ash and tephra geochemical composition from glaciers and ice fields in Iceland, Nepal, New Zealand and Switzerland. Surface glacier material was collected and analyzed via X-ray fluorescence spectroscopy (XRF and X-ray diffraction (XRD for geochemical composition and mineralogy. In situ data was used as ground truth for comparison with satellite derived geochemical results. Supraglacial debris spectral response patterns and emissivity-derived silica weight percent are presented. Qualitative spectral response patterns agreed well with XRF elemental abundances. Quantitative emissivity estimates of supraglacial SiO2 in continental areas were 67% (Switzerland and 68% (Nepal, while volcanic supraglacial SiO2 averages were 58% (Iceland and 56% (New Zealand, yielding general agreement. Ablation season supraglacial temperature variation due to differing dust and debris type and coverage was also investigated, with surface debris temperatures ranging from 5.9 to 26.6 C in the study regions. Applications of the supraglacial geochemical reflective and emissive characterization methods include glacier areal extent mapping, debris source identification, glacier kinematics and glacier energy balance considerations.

Analysis on BDS Satellite Internal Multipath and Its Impact on Wide-lane FCB Estimation

Directory of Open Access Journals (Sweden)

RUAN Rengui

2017-08-01

Full Text Available To the issue of the satellite internal multipath (SIMP of BeiDou satellites, it proposed and emphasized that the SIMP model should be established as a function of the nadir angle with respect to the observed satellite rather than the elevation of the measurement, so that it can be used for receivers at various altitude. BDS data from global distributed stations operated by the International Monitoring and Assessment System (iGMAS and the Multi-GNSS Experiment (MGEX of the International GNSS Service (IGS are collected and a new SIMP model as a piece-wise linear function of the nadir angle is released for the IGSO-and MEO-satellite groups and for B1, B2 and B3 frequency band individually. The SIMP of GEO,IGSO and MEO satellites is further analyzed with B1/B2 dual-frequency data onboard the FengYun-3 C(FY3C satellite at an altitude of~830 km, and it showed that, for nadir angles smaller than 7°, the SIMP values for GEO is quite close to the IGSO's, especially for B2, which may suggest that the SIMP model for IGSO satellites possibly also works for GEO satellites. It also demonstrated that, when the nadir angle is smaller than 12°for the MEO and 7°for the IGSO, the estimated SIMP model with data from FY3C is considerable consistent with that estimated with data collected at ground stations. Experiments are carried out to investigate the impacts of the SIMP on wide-lane fractional cycle bias (FCB estimation for BDS satellites. The result indicates that, with the correction of the estimated SIMP, the repeatability of the FCB series is significantly improved by more than 60% for all satellites. Specifically, for the MEO and IGSO satellites, the repeatability is smaller than 0.05 cycle; the repeatability of 0.023 and 0.068 cycles achieved for GEO satellites C01 and C02 respectively with the estimated SIMP model for IGSO satellites.

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.

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

Rugosity grid derived from gridded bathymetry of Ta'u Island of the Manu'a Island group, American Samoa

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Rugosity is derived from gridded (5 m cell size) multibeam bathymetry, collected aboard R/V AHI, and bathymetry derived from multispectral IKONOS satellite imagery...

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.

Estimating Daily Maximum and Minimum Land Air Surface Temperature Using MODIS Land Surface Temperature Data and Ground Truth Data in Northern Vietnam

Directory of Open Access Journals (Sweden)

Phan Thanh Noi

2016-12-01

Full Text Available This study aims to evaluate quantitatively the land surface temperature (LST derived from MODIS (Moderate Resolution Imaging Spectroradiometer MOD11A1 and MYD11A1 Collection 5 products for daily land air surface temperature (Ta estimation over a mountainous region in northern Vietnam. The main objective is to estimate maximum and minimum Ta (Ta-max and Ta-min using both TERRA and AQUA MODIS LST products (daytime and nighttime and auxiliary data, solving the discontinuity problem of ground measurements. There exist no studies about Vietnam that have integrated both TERRA and AQUA LST of daytime and nighttime for Ta estimation (using four MODIS LST datasets. In addition, to find out which variables are the most effective to describe the differences between LST and Ta, we have tested several popular methods, such as: the Pearson correlation coefficient, stepwise, Bayesian information criterion (BIC, adjusted R-squared and the principal component analysis (PCA of 14 variables (including: LST products (four variables, NDVI, elevation, latitude, longitude, day length in hours, Julian day and four variables of the view zenith angle, and then, we applied nine models for Ta-max estimation and nine models for Ta-min estimation. The results showed that the differences between MODIS LST and ground truth temperature derived from 15 climate stations are time and regional topography dependent. The best results for Ta-max and Ta-min estimation were achieved when we combined both LST daytime and nighttime of TERRA and AQUA and data from the topography analysis.

Estimating Advective Near-surface Currents from Ocean Color Satellite Images

Science.gov (United States)

2015-01-01

on the SuomiNational Polar-Orbiting Partner- ship (S- NPP ) satellite. The GOCI is the world’s first geostationary orbit satellite sensor over the...radiance Lwn at several wave - lengths. These spectral Lwn channels are used to derive several in- water bio-optical properties (Lee, Carder, & Arnone...the same surface flow, it is the inter-product similarities, instead of the differences, that are more likely to stand for the surface advection. If

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

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.

Phase Velocity Estimation of a Microstrip Line in a Stoichiometric Periodically Domain-Inverted LiTaO3 Modulator Using Electro-Optic Sampling Technique

Directory of Open Access Journals (Sweden)

Shintaro Hisatake

2008-01-01

Full Text Available We estimate the phase velocity of a modulation microwave in a quasi-velocity-matched (QVM electro-optic (EO phase modulator (QVM-EOM using EO sampling which is accurate and the most reliable technique for measuring voltage waveforms at an electrode. The substrate of the measured QVM-EOM is a stoichiometric periodically domain-inverted LiTaO3 crystal. The electric field of a standing wave in a resonant microstrip line (width: 0.5 mm, height: 0.5 mm is measured by employing a CdTe crystal as an EO sensor. The wavelength of the traveling microwave at 16.0801 GHz is determined as 3.33 mm by fitting the theoretical curve to the measured electric field distribution. The phase velocity is estimated as vm=5.35×107 m/s, though there exists about 5% systematic error due to the perturbation by the EO sensor. Relative dielectric constant of εr=41.5 is led as the maximum likelihood value that derives the estimated phase velocity.

Air-sea fluxes and satellite-based estimation of water masses formation

Science.gov (United States)

Sabia, Roberto; Klockmann, Marlene; Fernandez-Prieto, Diego; Donlon, Craig

2015-04-01

and monthly water mass formation rates for different SST and SSS ranges are presented. The formation peaks are remapped geographically, to analyze the extent of the formation area. Water mass formation derived from SMOS and OSTIA compares well with the results obtained from in-situ data, although slight differences in magnitude and peak location occur. Known water masses can then be identified. Ongoing/future work aims at extending this study along different avenues by: 1) expand systematically the spatial and temporal domain of the study to additional ocean basins and to the entire time period of available SSS observations from SMOS/Aquarius; 2) perform a thorough error propagation to assess how errors in satellite SSS and SST translate into errors in water masses formation rates and geographical areas extent; and 3) explore the different options to connect the surface information to the vertical buoyancy structure to assess potential density instability (e.g., Turner angle). References [1] Sabia, R., M. Klockmann, D. Fernández-Prieto, and C. Donlon (2014), A first estimation of SMOS-based ocean surface T-S diagrams, J. Geophys. Res. Oceans, 119, 7357-7371, doi:10.1002/2014JC010120. [2] Klockmann, M., R. Sabia, D. Fernández-Prieto, C. Donlon, J. Font; Towards an estimation of water masses formation areas from SMOS-based T-S diagrams; EGU general assembly 2014, April 27-May 2, 2014. [3] Klockmann, M., R. Sabia, D. Fernández-Prieto, C. Donlon, Linking satellite SSS and SST to water mass formation; Ocean salinity science and salinity remote sensing workshop, Exeter, UK, November 26-28, 2014. [4] Font, J., A. Camps, A. Borges, M. Martín-Neira, J. Boutin, N. Reul, Y. H. Kerr, A. Hahne, and S. Mecklenburg, "SMOS: The challenging sea surface salinity measurement from space," Proceedings of the IEEE, vol. 98, pp. 649-665, 2010. [5] Le Vine, D.M.; Lagerloef, G.S.E.; Torrusio, S.E.; "Aquarius and Remote Sensing of Sea Surface Salinity from Space," Proceedings of the IEEE

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.

Velocity estimation of an airplane through a single satellite image

Institute of Scientific and Technical Information of China (English)

Zhuxin Zhao; Gongjian Wen; Bingwei Hui; Deren Li

2012-01-01

The motion information of a moving target can be recorded in a single image by a push-broom satellite. A push-broom satellite image is composed of many image lines sensed at different time instants. A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed. Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction). The performance of the method is tested and verified by experiments using a WorldView-1 image.%The motion information of a moving target can be recorded in a single image by a push-broom satellite.A push-broom satellite image is composed of many image lines sensed at different time instants.A method to estimate the velocity of a flying airplane from a single image based on the imagery model of the linear push-broom sensor is proposed.Some key points on the high-resolution image of the plane are chosen to determine the velocity (speed and direction).The performance of the method is tested and verified by experiments using a WorldView-1 image.

An Improved BeiDou-2 Satellite-Induced Code Bias Estimation Method

Directory of Open Access Journals (Sweden)

Jingyang Fu

2018-04-01

Full Text Available Different from GPS, GLONASS, GALILEO and BeiDou-3, it is confirmed that the code multipath bias (CMB, which originate from the satellite end and can be over 1 m, are commonly found in the code observations of BeiDou-2 (BDS IGSO and MEO satellites. In order to mitigate their adverse effects on absolute precise applications which use the code measurements, we propose in this paper an improved correction model to estimate the CMB. Different from the traditional model which considering the correction values are orbit-type dependent (estimating two sets of values for IGSO and MEO, respectively and modeling the CMB as a piecewise linear function with a elevation node separation of 10°, we estimate the corrections for each BDS IGSO + MEO satellite on one hand, and a denser elevation node separation of 5° is used to model the CMB variations on the other hand. Currently, the institutions such as IGS-MGEX operate over 120 stations which providing the daily BDS observations. These large amounts of data provide adequate support to refine the CMB estimation satellite by satellite in our improved model. One month BDS observations from MGEX are used for assessing the performance of the improved CMB model by means of precise point positioning (PPP. Experimental results show that for the satellites on the same orbit type, obvious differences can be found in the CMB at the same node and frequency. Results show that the new correction model can improve the wide-lane (WL ambiguity usage rate for WL fractional cycle bias estimation, shorten the WL and narrow-lane (NL time to first fix (TTFF in PPP ambiguity resolution (AR as well as improve the PPP positioning accuracy. With our improved correction model, the usage of WL ambiguity is increased from 94.1% to 96.0%, the WL and NL TTFF of PPP AR is shorten from 10.6 to 9.3 min, 67.9 to 63.3 min, respectively, compared with the traditional correction model. In addition, both the traditional and improved CMB model have

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

Directory of Open Access Journals (Sweden)

Carolien Toté

2015-02-01

Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

Science.gov (United States)

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Satellite-based estimates of surface water dynamics in the Congo River Basin

Science.gov (United States)

Becker, M.; Papa, F.; Frappart, F.; Alsdorf, D.; Calmant, S.; da Silva, J. Santos; Prigent, C.; Seyler, F.

2018-04-01

In the Congo River Basin (CRB), due to the lack of contemporary in situ observations, there is a limited understanding of the large-scale variability of its present-day hydrologic components and their link with climate. In this context, remote sensing observations provide a unique opportunity to better characterize those dynamics. Analyzing the Global Inundation Extent Multi-Satellite (GIEMS) time series, we first show that surface water extent (SWE) exhibits marked seasonal patterns, well distributed along the major rivers and their tributaries, and with two annual maxima located: i) in the lakes region of the Lwalaba sub-basin and ii) in the "Cuvette Centrale", including Tumba and Mai-Ndombe Lakes. At an interannual time scale, we show that SWE variability is influenced by ENSO and the Indian Ocean dipole events. We then estimate water level maps and surface water storage (SWS) in floodplains, lakes, rivers and wetlands of the CRB, over the period 2003-2007, using a multi-satellite approach, which combines the GIEMS dataset with the water level measurements derived from the ENVISAT altimeter heights. The mean annual variation in SWS in the CRB is 81 ± 24 km3 and contributes to 19 ± 5% of the annual variations of GRACE-derived terrestrial water storage (33 ± 7% in the Middle Congo). It represents also ∼6 ± 2% of the annual water volume that flows from the Congo River into the Atlantic Ocean.

Objective estimation of tropical cyclone innercore surface wind structure using infrared satellite images

Science.gov (United States)

Zhang, Changjiang; Dai, Lijie; Ma, Leiming; Qian, Jinfang; Yang, Bo

2017-10-01

An objective technique is presented for estimating tropical cyclone (TC) innercore two-dimensional (2-D) surface wind field structure using infrared satellite imagery and machine learning. For a TC with eye, the eye contour is first segmented by a geodesic active contour model, based on which the eye circumference is obtained as the TC eye size. A mathematical model is then established between the eye size and the radius of maximum wind obtained from the past official TC report to derive the 2-D surface wind field within the TC eye. Meanwhile, the composite information about the latitude of TC center, surface maximum wind speed, TC age, and critical wind radii of 34- and 50-kt winds can be combined to build another mathematical model for deriving the innercore wind structure. After that, least squares support vector machine (LSSVM), radial basis function neural network (RBFNN), and linear regression are introduced, respectively, in the two mathematical models, which are then tested with sensitivity experiments on real TC cases. Verification shows that the innercore 2-D surface wind field structure estimated by LSSVM is better than that of RBFNN and linear regression.

Comparison of surface energy fluxes with satellite-derived surface energy flux estimates from a shrub-steppe

International Nuclear Information System (INIS)

Kirkham, R.R.

1993-12-01

This thesis relates the components of the surface energy balance (i.e., net radiation, sensible and latent heat flux densities, soil heat flow) to remotely sensed data for native vegetation in a semi-arid environment. Thematic mapper data from Landsat 4 and 5 were used to estimate net radiation, sensible heat flux (H), and vegetation amount. Several sources of ground truth were employed. They included soil water balance using the neutron thermalization method and weighing lysimeters, and the measurement of energy fluxes with the Bowen ratio energy balance (BREB) technique. Sensible and latent heat flux were measured at four sites on the U.S. Department of Energy's Hanford Site using a weighing lysimeter and/or BREB stations. The objective was to calibrate an aerodynamic transport equation that related H to radiant surface temperature. The transport equation was then used with Landsat thermal data to generate estimates of H and compare these estimates against H values obtained with BREB/lysimeters at the time of overflight. Landsat and surface meteorologic data were used to estimate the radiation budget terms at the surface. Landsat estimates of short-wave radiation reflected from the surface correlate well with reflected radiation measured using inverted Eppley pyranometers. Correlation of net radiation estimates determined from satellite data, pyranometer, air temperature, and vapor pressure compared to net radiometer values obtained at time of overflight were excellent for a single image, but decrease for multiple images. Soil heat flux, G T , is a major component of the energy balance in arid systems and G T generally decreases as vegetation cover increases. Normalized difference vegetation index (NDVI) values generated from Landsat thermatic mapper data were representative of field observations of the presence of green vegetation, but it was not possible to determine a single relationship between NDVI and G T for all sites

Muscle Satellite Cell Protein Teneurin‐4 Regulates Differentiation During Muscle Regeneration

Science.gov (United States)

Ishii, Kana; Suzuki, Nobuharu; Mabuchi, Yo; Ito, Naoki; Kikura, Naomi; Fukada, So‐ichiro; Okano, Hideyuki; Takeda, Shin'ichi

2015-01-01

Abstract Satellite cells are maintained in an undifferentiated quiescent state, but during muscle regeneration they acquire an activated stage, and initiate to proliferate and differentiate as myoblasts. The transmembrane protein teneurin‐4 (Ten‐4) is specifically expressed in the quiescent satellite cells; however, its cellular and molecular functions remain unknown. We therefore aimed to elucidate the function of Ten‐4 in muscle satellite cells. In the tibialis anterior (TA) muscle of Ten‐4‐deficient mice, the number and the size of myofibers, as well as the population of satellite cells, were reduced with/without induction of muscle regeneration. Furthermore, we found an accelerated activation of satellite cells in the regenerated Ten‐4‐deficient TA muscle. The cell culture analysis using primary satellite cells showed that Ten‐4 suppressed the progression of myogenic differentiation. Together, our findings revealed that Ten‐4 functions as a crucial player in maintaining the quiescence of muscle satellite cells. Stem Cells 2015;33:3017–3027 PMID:26013034

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

Development of Deep Learning Based Data Fusion Approach for Accurate Rainfall Estimation Using Ground Radar and Satellite Precipitation Products

Science.gov (United States)

Chen, H.; Chandra, C. V.; Tan, H.; Cifelli, R.; Xie, P.

2016-12-01

Rainfall estimation based on onboard satellite measurements has been an important topic in satellite meteorology for decades. A number of precipitation products at multiple time and space scales have been developed based upon satellite observations. For example, NOAA Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space based rainfall estimates. The CMORPH products are essentially derived based on geostationary satellite IR brightness temperature information and retrievals from passive microwave measurements (Joyce et al. 2004). Although the space-based precipitation products provide an excellent tool for regional and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, its accuracy is limited due to the sampling limitations, particularly for extreme events such as very light and/or heavy rain. On the other hand, ground-based radar is more mature science for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization technique and further enhanced by urban scale radar networks. Therefore, ground radars are often critical for providing local scale rainfall estimation and a "heads-up" for operational forecasters to issue watches and warnings as well as validation of various space measurements and products. The CASA DFW QPE system, which is based on dual-polarization X-band CASA radars and a local S-band WSR-88DP radar, has demonstrated its excellent performance during several years of operation in a variety of precipitation regimes. The real-time CASA DFW QPE products are used extensively for localized hydrometeorological applications such as urban flash flood forecasting. In this paper, a neural network based data fusion mechanism is introduced to improve the satellite-based CMORPH precipitation product by taking into account the ground radar measurements. A deep learning system is

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

Corrosion Characteristics of Ti-xTa Alloys with Ta contents

International Nuclear Information System (INIS)

Kim, H. J.; Choe, H. C.

2013-01-01

The purpose of this study was to investigate corrosion characteristics of Ti-xTa alloys with Ta contents. Ti-xTa alloys used as samples (x=30, 40%) were arc-melted under argon atmosphere of 99.9% purity. Ti-xTa alloys were homogenized for 12hr at 1000 .deg. C and then water quenched. The surface characteristics of Ti-xTa alloys were investigated using optical microscopy (OM) and X-ray diffractometer (XRD). The anodic corrosion behaviors of the specimens were examined through potentiodynamic, potentiostatic and galvanostatic test in 0.9 % NaCl solution at 36.5 ± 1 .deg. C. After corrosion test, the surface characteristics of Ti-xTa alloys were investigated using OM. The microstructure of Ti-Ta alloy showed the beta structure with Ta content. The corrosion resistance of Ti alloy was improved by increasing Ta content and the corrosion morphology of Ti-Ta alloy showed that the site attacked by chloride ion decreased from the active to passive region with Ta content. Potential of Ti-40Ta alloy increased as time increased, whereas, current density of Ti-40Ta alloy decreased as time increased compared to Ti-30 alloy

Spatial estimation of air PM2.5 emissions using activity data, local emission factors and land cover derived from satellite imagery

Science.gov (United States)

Gibe, Hezron P.; Cayetano, Mylene G.

2017-09-01

Exposure to particulate matter (PM) is a serious environmental problem in many urban areas on Earth. In the Philippines, most existing studies and emission inventories have mainly focused on point and mobile sources, while research involving human exposures to particulate pollutants is rare. This paper presents a method for estimating the amount of fine particulate (PM2.5) emissions in a test study site in the city of Cabanatuan, Nueva Ecija, in the Philippines, by utilizing local emission factors, regionally procured data, and land cover/land use (activity data) interpreted from satellite imagery. Geographic information system (GIS) software was used to map the estimated emissions in the study area. The present results suggest that vehicular emissions from motorcycles and tricycles, as well as fuels used by households (charcoal) and burning of agricultural waste, largely contribute to PM2.5 emissions in Cabanatuan. Overall, the method used in this study can be applied in other small urbanizing cities, as long as on-site specific activity, emission factor, and satellite-imaged land cover data are available.

Estimation of land-atmosphere energy transfer over the Tibetan Plateau by a combination use of geostationary and polar-orbiting satellite data

Science.gov (United States)

Zhong, L.; Ma, Y.

2017-12-01

Land-atmosphere energy transfer is of great importance in land-atmosphere interactions and atmospheric boundary layer processes over the Tibetan Plateau (TP). The energy fluxes have high temporal variability, especially in their diurnal cycle, which cannot be acquired by polar-orbiting satellites alone because of their low temporal resolution. Therefore, it's of great practical significance to retrieve land surface heat fluxes by a combination use of geostationary and polar orbiting satellites. In this study, a time series of the hourly LST was estimated from thermal infrared data acquired by the Chinese geostationary satellite FengYun 2C (FY-2C) over the TP. The split window algorithm (SWA) was optimized using a regression method based on the observations from the Enhanced Observing Period (CEOP) of the Asia-Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet) and Tibetan observation and research platform (TORP), the land surface emissivity (LSE) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the water vapor content from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) project. The 10-day composite hourly LST data were generated via the maximum value composite (MVC) method to reduce the cloud effects. The derived LST was validated by the field observations of CAMP/Tibet and TORP. The results show that the retrieved LST and in situ data have a very good correlation (with root mean square error (RMSE), mean bias (MB), mean absolute error (MAE) and correlation coefficient (R) values of 1.99 K, 0.83 K, 1.71 K, and 0.991, respectively). Together with other characteristic parameters derived from polar-orbiting satellites and meteorological forcing data, the energy balance budgets have been retrieved finally. The validation results showed there was a good consistency between estimation results and in-situ measurements over the TP, which prove the robustness of the proposed estimation

Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass

Directory of Open Access Journals (Sweden)

E. Delogu

2012-08-01

Full Text Available Evapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first type estimates a potential evapotranspiration rate from vegetation indices, and adjusts this rate according to water availability derived from either a surface temperature index or a first guess obtained from a rough estimate of the water budget, while the second family of methods relies on the link between the surface temperature and the latent heat flux through the surface energy budget. The latter provides an instantaneous estimate at the time of satellite overpass. In order to compute daily evapotranspiration, one needs an extrapolation algorithm. Since no image is acquired during cloudy conditions, these methods can only be applied during clear sky days. In order to derive seasonal evapotranspiration, one needs an interpolation method. Two combined interpolation/extrapolation methods based on the self preservation of evaporative fraction and the stress factor are compared to reconstruct seasonal evapotranspiration from instantaneous measurements acquired in clear sky conditions. Those measurements are taken from instantaneous latent heat flux from 11 datasets in Southern France and Morocco. Results show that both methods have comparable performances with a clear advantage for the evaporative fraction for datasets with several water stress events. Both interpolation algorithms tend to underestimate evapotranspiration due to the energy limiting conditions that prevail during cloudy days. Taking into account the diurnal variations of the evaporative fraction according to an empirical relationship derived from a previous study improved the performance of the extrapolation algorithm and therefore the retrieval of the seasonal evapotranspiration for all but one datasets.

Global analysis of approaches for deriving total water storage changes from GRACE satellites and implications for groundwater storage change estimation

Science.gov (United States)

Long, D.; Scanlon, B. R.; Longuevergne, L.; Chen, X.

2015-12-01

Increasing interest in use of GRACE satellites and a variety of new products to monitor changes in total water storage (TWS) underscores the need to assess the reliability of output from different products. The objective of this study was to assess skills and uncertainties of different approaches for processing GRACE data to restore signal losses caused by spatial filtering based on analysis of 1°×1° grid scale data and basin scale data in 60 river basins globally. Results indicate that scaling factors from six land surface models (LSMs), including four models from GLDAS-1 (Noah 2.7, Mosaic, VIC, and CLM 2.0), CLM 4.0, and WGHM, are similar over most humid, sub-humid, and high-latitude regions but can differ by up to 100% over arid and semi-arid basins and areas with intensive irrigation. Large differences in TWS anomalies from three processing approaches (scaling factor, additive, and multiplicative corrections) were found in arid and semi-arid regions, areas with intensive irrigation, and relatively small basins (e.g., ≤ 200,000 km2). Furthermore, TWS anomaly products from gridded data with CLM4.0 scaling factors and the additive correction approach more closely agree with WGHM output than the multiplicative correction approach. Estimation of groundwater storage changes using GRACE satellites requires caution in selecting an appropriate approach for restoring TWS changes. A priori ground-based data used in forward modeling can provide a powerful tool for explaining the distribution of signal gains or losses caused by low-pass filtering in specific regions of interest and should be very useful for more reliable estimation of groundwater storage changes using GRACE satellites.

Estimating the Mass of the Milky Way Using the Ensemble of Classical Satellite Galaxies

Science.gov (United States)

Patel, Ekta; Besla, Gurtina; Sohn, Sangmo Tony; Mandel, Kaisey

2018-06-01

High precision proper motions are currently available for approximately 20% of the Milky Way's known satellite galaxies. Often, the 6D phase space information of each satellite is used separately to constrain the mass of the MW. In this talk, I will discuss the Bayesian framework outlined in Patel et al. 2017b to make inferences of the MW's mass using satellite properties such as specific orbital angular momentum, rather than just position and velocity. By extending this framework from one satellite to a population of satellites, we can now form simultaneous MW mass estimates using the Illustris-Dark cosmological simulation that are unbiased by high speed satellites such as Leo I (Patel et al., submitted). Our resulting MW mass estimates reduce the current factor of two uncertainty in the mass range of the MW and show promising signs for improvement as upcoming ground- and space-based observatories obtain proper motions for additional MW satellite galaxies.

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,

The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

Science.gov (United States)

Kelly, R. E. J.; Saberi, N.; Li, Q.

2017-12-01

With moderate to high spatial resolution (observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides SWE estimates that are independent of real or near real

Solar Irradiance and Pan Evaporation Estimation from Meteorological Satellite Data

Directory of Open Access Journals (Sweden)

Ming-Ren Syu

2016-04-01

Full Text Available Knowledge about spatial and temporal variations in surface global solar radiation (GSR and evaporative water loss from the ground are important issues to many researches and applications. In this study empirical relationships suitable for Taiwan were established for GSR retrieval from geostationary satellite images using the Heliosat method for the period from 2011 - 2013. The derived GSR data has been used to generate consecutive maps of 10-day averaged pan evaporation (Epan as the basis to produce regional ET estimation using a strategy that does not require remote sensed land surface temperatures (LST. The retrieved daily GSR and the derived 10-day averaged Epan were validated against pyranometer and class-A pan measurements at selected Central Weather Bureau (CWB stations spread across various climatic regions in Taiwan. Compared with the CWB observed data the overall relative mean bias deviations (MBD% and root mean square differences (RMSD% in daily solar irradiance retrieval were about 5 and 15%, respectively. Seasonally, the largest MBD% and RMSD% of retrieved daily solar irradiance occur in spring (9.5 and 21.3% on average, while the least MBD% (-0.3% on average and RMSD% (9.7% on average occur in autumn and winter, respectively. For 10-day averaged Epan estimation, the mean MBD% and RMSD% for stations located in the coastal plain areas were 0.1 and 16.9%, respectively. However, in mountainous areas the mean MBD% and RMSD% increased to 30.2 and 34.5%, respectively. This overestimation was due mainly to the large differences in surrounding micro-environments between the mountainous and plain areas.

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.

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 ...

NMR-ON of 182Ta and 183Ta in Fe

International Nuclear Information System (INIS)

Allsop, A.L.; Chaplin, D.H.; Murray, D.W.; Stone, N.J.

1980-01-01

Nuclear magnetic resonance has been observed on radioactive 182 Ta and 183 Ta oriented at low temperature in an Fe host, by detection of the change in spatial anisotropy of γ-rays emitted during nuclear decay. By measuring the resonant frequencies of 183 Ta in four different applied magnetic fields the nuclear magnetic moment and hyperfine field have been deduced. These are: vertical stroke μ( 183 Ta;I = 7/2) = 2.28(3)μsub(N) and Bsub(h)sub(f)(TaFe at 0 K) = -67.2(1.3)T. The sin of the ground state of 182 Ta has been determined as I = 3 by comparing resonance results with those obtained in a thermal equilibrium nuclear orientation study. The ratio of the resonant frequencies observed for 182 Ta and 183 Ta at one applied field value yields a magnetic moment for the former of vertical stroke μ( 182 Ta;I = 3) vertical stroke = 2.91(3)μsub(N). The spin lattice relaxation time for 183 TaFe (0.12 at% Ta) at 18 mK in an applied field of 0.5 T has been found to be 40(10)s. (orig.)

Magnetic dipole moment estimation and compensation for an accurate attitude control in nano-satellite missions

Science.gov (United States)

Inamori, Takaya; Sako, Nobutada; Nakasuka, Shinichi

2011-06-01

Nano-satellites provide space access to broader range of satellite developers and attract interests as an application of the space developments. These days several new nano-satellite missions are proposed with sophisticated objectives such as remote-sensing and observation of astronomical objects. In these advanced missions, some nano-satellites must meet strict attitude requirements for obtaining scientific data or images. For LEO nano-satellite, a magnetic attitude disturbance dominates over other environmental disturbances as a result of small moment of inertia, and this effect should be cancelled for a precise attitude control. This research focuses on how to cancel the magnetic disturbance in orbit. This paper presents a unique method to estimate and compensate the residual magnetic moment, which interacts with the geomagnetic field and causes the magnetic disturbance. An extended Kalman filter is used to estimate the magnetic disturbance. For more practical considerations of the magnetic disturbance compensation, this method has been examined in the PRISM (Pico-satellite for Remote-sensing and Innovative Space Missions). This method will be also used for a nano-astrometry satellite mission. This paper concludes that use of the magnetic disturbance estimation and compensation are useful for nano-satellites missions which require a high accurate attitude control.

Satellite-based detection of global urban heat-island temperature influence

Science.gov (United States)

Gallo, K.P.; Adegoke, Jimmy O.; Owen, T.W.; Elvidge, C.D.

2002-01-01

This study utilizes a satellite-based methodology to assess the urban heat-island influence during warm season months for over 4400 stations included in the Global Historical Climatology Network of climate stations. The methodology includes local and regional satellite retrievals of an indicator of the presence green photosynthetically active vegetation at and around the stations. The difference in local and regional samples of the normalized difference vegetation index (NDVI) is used to estimate differences in mean air temperature. Stations classified as urban averaged 0.90??C (N. Hemisphere) and 0.92??C (S. Hemisphere) warmer than the surrounding environment on the basis of the NDVI-derived temperature estimates. Additionally, stations classified as rural averaged 0.19??C (N. Hemisphere) and 0.16??C (S. Hemisphere) warmer than the surrounding environment. The NDVI-derived temperature estimates were found to be in reasonable agreement with temperature differences observed between climate stations. The results suggest that satellite-derived data sets can be used to estimate the urban heat-island temperature influence on a global basis and that a more detailed analysis of rural stations and their surrounding environment may be necessary to assure that temperature trends derived from assumed rural environments are not influenced by changes in land use/land cover. Copyright 2002 by the American Geophysical Union.

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.

Estimating the spin axis orientation of the Echostar-2 box-wing geosynchronous satellite

Science.gov (United States)

Earl, Michael A.; Somers, Philip W.; Kabin, Konstantin; Bédard, Donald; Wade, Gregg A.

2018-04-01

For the first time, the spin axis orientation of an inactive box-wing geosynchronous satellite has been estimated from ground-based optical photometric observations of Echostar-2's specular reflections. Recent photometric light curves obtained of Echostar-2 over four years suggest that unusually bright and brief specular reflections were occurring twice within an observed spin period. These bright and brief specular reflections suggested two satellite surfaces with surface normals separated by approximately 180°. The geometry between the satellite, the Sun, and the observing location at the time of each of the brightest observed reflections, was used to estimate Echostar-2's equatorial spin axis orientation coordinates. When considering prograde and retrograde rotation, Echostar-2's spin axis orientation was estimated to have been located within 30° of either equatorial coordinate pole. Echostar-2's spin axis was observed to have moved approximately 180° in right ascension, within a time span of six months, suggesting a roughly one year spin axis precession period about the satellite's angular momentum vector.

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.

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.

Muscle Satellite Cell Protein Teneurin-4 Regulates Differentiation During Muscle Regeneration.

Science.gov (United States)

Ishii, Kana; Suzuki, Nobuharu; Mabuchi, Yo; Ito, Naoki; Kikura, Naomi; Fukada, So-Ichiro; Okano, Hideyuki; Takeda, Shin'ichi; Akazawa, Chihiro

2015-10-01

Satellite cells are maintained in an undifferentiated quiescent state, but during muscle regeneration they acquire an activated stage, and initiate to proliferate and differentiate as myoblasts. The transmembrane protein teneurin-4 (Ten-4) is specifically expressed in the quiescent satellite cells; however, its cellular and molecular functions remain unknown. We therefore aimed to elucidate the function of Ten-4 in muscle satellite cells. In the tibialis anterior (TA) muscle of Ten-4-deficient mice, the number and the size of myofibers, as well as the population of satellite cells, were reduced with/without induction of muscle regeneration. Furthermore, we found an accelerated activation of satellite cells in the regenerated Ten-4-deficient TA muscle. The cell culture analysis using primary satellite cells showed that Ten-4 suppressed the progression of myogenic differentiation. Together, our findings revealed that Ten-4 functions as a crucial player in maintaining the quiescence of muscle satellite cells. © 2015 The Authors STEM CELLS published by Wiley Periodicals, Inc. on behalf of AlphaMed Press.

Estimation of satellite position, clock and phase bias corrections

Science.gov (United States)

Henkel, Patrick; Psychas, Dimitrios; Günther, Christoph; Hugentobler, Urs

2018-05-01

Precise point positioning with integer ambiguity resolution requires precise knowledge of satellite position, clock and phase bias corrections. In this paper, a method for the estimation of these parameters with a global network of reference stations is presented. The method processes uncombined and undifferenced measurements of an arbitrary number of frequencies such that the obtained satellite position, clock and bias corrections can be used for any type of differenced and/or combined measurements. We perform a clustering of reference stations. The clustering enables a common satellite visibility within each cluster and an efficient fixing of the double difference ambiguities within each cluster. Additionally, the double difference ambiguities between the reference stations of different clusters are fixed. We use an integer decorrelation for ambiguity fixing in dense global networks. The performance of the proposed method is analysed with both simulated Galileo measurements on E1 and E5a and real GPS measurements of the IGS network. We defined 16 clusters and obtained satellite position, clock and phase bias corrections with a precision of better than 2 cm.

Estimating Global Impervious Surface based on Social-economic Data and Satellite Observations

Science.gov (United States)

Zeng, Z.; Zhang, K.; Xue, X.; Hong, Y.

2016-12-01

Impervious surface areas around the globe are expanding and significantly altering the surface energy balance, hydrology cycle and ecosystem services. Many studies have underlined the importance of impervious surface, r from hydrological modeling to contaminant transport monitoring and urban development estimation. Therefore accurate estimation of the global impervious surface is important for both physical and social sciences. Given the limited coverage of high spatial resolution imagery and ground survey, using satellite remote sensing and geospatial data to estimate global impervious areas is a practical approach. Based on the previous work of area-weighted imperviousness for north branch of the Chicago River provided by HDR, this study developed a method to determine the percentage of impervious surface using latest global land cover categories from multi-source satellite observations, population density and gross domestic product (GDP) data. Percent impervious surface at 30-meter resolution were mapped. We found that 1.33% of the CONUS (105,814 km2) and 0.475% of the land surface (640,370km2) are impervious surfaces. To test the utility and practicality of the proposed method, National Land Cover Database (NLCD) 2011 percent developed imperviousness for the conterminous United States was used to evaluate our results. The average difference between the derived imperviousness from our method and the NLCD data across CONUS is 1.14%, while difference between our results and the NLCD data are within ±1% over 81.63% of the CONUS. The distribution of global impervious surface map indicates that impervious surfaces are primarily concentrated in China, India, Japan, USA and Europe where are highly populated and/or developed. This study proposes a straightforward way of mapping global imperviousness, which can provide useful information for hydrologic modeling and other applications.

Estimation of absorbed photosynthetically active radiation and vegetation net production efficiency using satellite data

International Nuclear Information System (INIS)

Hanan, N.P.; Prince, S.D.; Begue, A.

1995-01-01

The amount of photosynthetically active radiation (PAR) absorbed by green vegetation is an important determinant of photosynthesis and growth. Methods for the estimation of fractional absorption of PAR (iff PAR ) for areas greater than 1 km 2 using satellite data are discussed, and are applied to sites in the Sahel that have a sparse herb layer and tree cover of less than 5%. Using harvest measurements of seasonal net production, net production efficiencies are calculated. Variation in estimates of seasonal PAR absorption (APAR) caused by the atmospheric correction method and relationship between surface reflectances and iff PAR is considered. The use of maximum value composites of satellite NDVI to reduce the effect of the atmosphere is shown to produce inaccurate APAR estimates. In this data set, however, atmospheric correction using average optical depths was found to give good approximations of the fully corrected data. A simulation of canopy radiative transfer using the SAIL model was used to derive a relationship between canopy NDVI and iff PAR . Seasonal APAR estimates assuming a 1:1 relationship between iff PAR and NDVI overestimated the SAIL modeled results by up to 260%. The use of a modified 1:1 relationship, where iff PAR was assumed to be linearly related to NDVI scaled between minimum (soil) and maximum (infinite canopy) values, underestimated the SAIL modeled results by up to 35%. Estimated net production efficiencies (ϵ n , dry matter per unit APAR) fell in the range 0.12–1.61 g MJ −1 for above ground production, and in the range 0.16–1.88 g MJ −1 for total production. Sites with lower rainfall had reduced efficiencies, probably caused by physiological constraints on photosynthesis during dry conditions. (author)

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

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

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.

Fast Emission Estimates in China Constrained by Satellite Observations (Invited)

Science.gov (United States)

Mijling, B.; van der A, R.

2013-12-01

Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for an emerging economy such as China, where rapid economic growth changes emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. Constraining emissions from concentration measurements is, however, computationally challenging. Within the GlobEmission project of the European Space Agency (ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China, using the CHIMERE model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e.g. shipping emissions). The new emission estimates result in a better

179Ta and 180Ta structure by transfer reactions

International Nuclear Information System (INIS)

Warde, Elias.

1979-01-01

Transfer reactions (α,t); ( 3 He,d); (p,t) and (p,d) have been used to study the nuclear spectroscopy of 179 Ta and 180 Ta. In 179 Ta, 5/2 - and 9/2 - states of the 1/2(541) configuration have been identified. The core-quasiproton interaction has to be taken into account in order to explain the two-nucleon transfer intensities in the 181 Ta(p,t) 179 Ta reaction. A level scheme has been proposed for 180 Ta for the first time. Especially the ground state is identified with the (1 + ,1) level of the [7/2 + (404)sub(p), 9/2 + (624)sub(n)] configuration and spin (9 - ,9) of the configuration [9/2 - (514)sub(p), 9/2 + (624)sub(n)] has been assigned to the long-lived isomer. From the observed configurations in 180 Ta, the matrix elements of the effective residual interaction vsub(np) have been deduced and compared to theoretical predictions [fr

Satellite Estimation of Fractional Cover in Several California Specialty Crops

Science.gov (United States)

Johnson, L.; Cahn, M.; Rosevelt, C.; Guzman, A.; Lockhart, T.; Farrara, B.; Melton, F. S.

2016-12-01

Past research in California and elsewhere has revealed strong relationships between satellite NDVI, photosynthetically active vegetation fraction (Fc), and crop evapotranspiration (ETc). Estimation of ETc can support efficiency of irrigation practice, which enhances water security and may mitigate nitrate leaching. The U.C. Cooperative Extension previously developed the CropManage (CM) web application for evaluation of crop water requirement and irrigation scheduling for several high-value specialty crops. CM currently uses empirical equations to predict daily Fc as a function of crop type, planting date and expected harvest date. The Fc prediction is transformed to fraction of reference ET and combined with reference data from the California Irrigation Management Information System to estimate daily ETc. In the current study, atmospherically-corrected Landsat NDVI data were compared with in-situ Fc estimates on several crops in the Salinas Valley during 2011-2014. The satellite data were observed on day of ground collection or were linearly interpolated across no more than an 8-day revisit period. Results will be presented for lettuce, spinach, celery, broccoli, cauliflower, cabbage, peppers, and strawberry. An application programming interface (API) allows CM and other clients to automatically retrieve NDVI and associated data from NASA's Satellite Irrigation Management Support (SIMS) web service. The SIMS API allows for queries both by individual points or user-defined polygons, and provides data for individual days or annual timeseries. Updates to the CM web app will convert these NDVI data to Fc on a crop-specific basis. The satellite observations are expected to play a support role in Salinas Valley, and may eventually serve as a primary data source as CM is extended to crop systems or regions where Fc is less predictable.

Synthesis of Ni3Ta, Ni2Ta and NiTa by high-energy ball milling and subsequent heat treatment

International Nuclear Information System (INIS)

Benites, H.S.N.; Silva, B.P da; Ramos, A.S.; Silva, A.A.A.P.; Coelho, G.C.; Lima, B.B. de

2014-01-01

The tantalum has relevance for the development of multicomponent Ni-based superalloys which are hardened by solid solution and precipitation mechanisms. Master alloys are normally used in the production step in order to produce refractory metals and alloys. The present work reports on the synthesis of Ni_3Ta, Ni_2Ta and NiTa by high-energy ball milling and subsequent heat treatment. The elemental Ni-25Ta, Ni-33Ta and Ni-50Ta (at.-%) powder mixtures were ball milled under Ar atmosphere using stainless steel balls and vials, 300 rpm and a ball-to-powder weight ratio of 10:1. Following, the as-milled samples were uniaxially compacted and heat-treated at 1100 deg C for 4h under Ar atmosphere. The characterization of as-milled and heat-treated samples was conducted by means of X-ray diffraction, scanning electron microscopy, and energy dispersive spectrometry. A large amount of Ni_3Ta, Ni_2Ta and NiTa was formed in the mechanically alloyed heat-treated Ni-25Ta, Ni-33Ta and Ni-50Ta alloys. (author)

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.

Stoichiometry behavior of TaN, TaCN and TaC thin films produced by magnetron sputtering

International Nuclear Information System (INIS)

Vargas, M.; Castillo, H.A.; Restrepo-Parra, E.; De La Cruz, W.

2013-01-01

Thin films were synthesized in a magnetron sputtering system using a target of Ta with 99.99% purity and silicon substrates (1 1 1). The gases used for the film growth were (Ar + N 2 ), (Ar + CH 4 + N 2 ) and (Ar + CH 4 ) mixtures for TaN, TaCN and TaC, respectively. The substrate temperature increased from room temperature to 500 °C. The chemical composition and bonding configuration were examined using X-ray photoelectron spectroscopy (XPS), revealing Ta-N, Ta-C-N, Ta-C and C-C bonds. Moreover, the crystallographic structure was analyzed using X-ray diffraction (XRD), indicating the presence of (1 1 1) and (2 0 0) planes belonging to a face-centered cubic structure. The stoichiometry variation dependence on the CH 4 and N 2 flow was analyzed, and the influence of the substrate temperature on the coatings was investigated. Finally, scanning electron microscopy (SEM) was used to determine the evolution on the grain formation in the coatings as the substrate temperature increased.

Stoichiometry behavior of TaN, TaCN and TaC thin films produced by magnetron sputtering

Energy Technology Data Exchange (ETDEWEB)

Vargas, M. [Centro de Nanociencia y Nanotecnología, Universidad Nacional Autónoma de México, A.P. 2681, C.P. 22860, Ensenada, B.C. (Mexico); Castillo, H.A. [Centro de Enseñanza Técnica y Superior, CETYS Universidad, Campus Tijuana, Tijuana, B.C. (Mexico); Restrepo-Parra, E., E-mail: erestrepopa@unal.edu.co [Universidad Nacional de Colombia Sede Medellín Colombia, Facultad de Minas, Manizales (Colombia); De La Cruz, W. [Centro de Nanociencia y Nanotecnología, Universidad Nacional Autónoma de México, A.P. 2681, C.P. 22860, Ensenada, B.C. (Mexico)

2013-08-15

Thin films were synthesized in a magnetron sputtering system using a target of Ta with 99.99% purity and silicon substrates (1 1 1). The gases used for the film growth were (Ar + N{sub 2}), (Ar + CH{sub 4} + N{sub 2}) and (Ar + CH{sub 4}) mixtures for TaN, TaCN and TaC, respectively. The substrate temperature increased from room temperature to 500 °C. The chemical composition and bonding configuration were examined using X-ray photoelectron spectroscopy (XPS), revealing Ta-N, Ta-C-N, Ta-C and C-C bonds. Moreover, the crystallographic structure was analyzed using X-ray diffraction (XRD), indicating the presence of (1 1 1) and (2 0 0) planes belonging to a face-centered cubic structure. The stoichiometry variation dependence on the CH{sub 4} and N{sub 2} flow was analyzed, and the influence of the substrate temperature on the coatings was investigated. Finally, scanning electron microscopy (SEM) was used to determine the evolution on the grain formation in the coatings as the substrate temperature increased.

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

OpenAIRE

Carolien Toté; Domingos Patricio; Hendrik Boogaard; Raymond van der Wijngaart; Elena Tarnavsky; Chris Funk

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Cl...

Building Damage Estimation by Integration of Seismic Intensity Information and Satellite L-band SAR Imagery

Directory of Open Access Journals (Sweden)

Nobuoto Nojima

2010-09-01

Full Text Available For a quick and stable estimation of earthquake damaged buildings worldwide, using Phased Array type L-band Synthetic Aperture Radar (PALSAR loaded on the Advanced Land Observing Satellite (ALOS satellite, a model combining the usage of satellite synthetic aperture radar (SAR imagery and Japan Meteorological Agency (JMA-scale seismic intensity is proposed. In order to expand the existing C-band SAR based damage estimation model into L-band SAR, this paper rebuilds a likelihood function for severe damage ratio, on the basis of dataset from Japanese Earth Resource Satellite-1 (JERS-1/SAR (L-band SAR images observed during the 1995 Kobe earthquake and its detailed ground truth data. The model which integrates the fragility functions of building damage in terms of seismic intensity and the proposed likelihood function is then applied to PALSAR images taken over the areas affected by the 2007 earthquake in Pisco, Peru. The accuracy of the proposed damage estimation model is examined by comparing the results of the analyses with field investigations and/or interpretation of high-resolution satellite images.

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

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

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.

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

International Nuclear Information System (INIS)

Boresjoe Bronge, Laine

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given

Satellite remote sensing for estimating leaf area index, FPAR and primary production. A literature review

Energy Technology Data Exchange (ETDEWEB)

Boresjoe Bronge, Laine [SwedPower AB, Stockholm (Sweden)

2004-03-01

Land vegetation is a critical component of several biogeochemical cycles that have become the focus of concerted international research effort. Most ecosystem productivity models, carbon budget models, and global models of climate, hydrology and biogeochemistry require vegetation parameters to calculate land surface photosynthesis, evapotranspiration and net primary production. Therefore, accurate estimates of vegetation parameters are increasingly important in the carbon cycle, the energy balance and in environmental impact assessment studies. The possibility of quantitatively estimating vegetation parameters of importance in this context using satellite data has been explored by numerous papers dealing with the subject. This report gives a summary of the present status and applicability of satellite remote sensing for estimating vegetation productivity by using vegetation index for calculating leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR). Some possible approaches for use of satellite data for estimating LAI, FPAR and net primary production (NPP) on a local scale are suggested. Recommendations for continued work in the Forsmark and Oskarshamn investigation areas, where vegetation data and NDVI-images based on satellite data have been produced, are also given.

Bayesian estimation of animal movement from archival and satellite tags.

Directory of Open Access Journals (Sweden)

Michael D Sumner

Full Text Available The reliable estimation of animal location, and its associated error is fundamental to animal ecology. There are many existing techniques for handling location error, but these are often ad hoc or are used in isolation from each other. In this study we present a Bayesian framework for determining location that uses all the data available, is flexible to all tagging techniques, and provides location estimates with built-in measures of uncertainty. Bayesian methods allow the contributions of multiple data sources to be decomposed into manageable components. We illustrate with two examples for two different location methods: satellite tracking and light level geo-location. We show that many of the problems with uncertainty involved are reduced and quantified by our approach. This approach can use any available information, such as existing knowledge of the animal's potential range, light levels or direct location estimates, auxiliary data, and movement models. The approach provides a substantial contribution to the handling uncertainty in archival tag and satellite tracking data using readily available tools.

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.

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.

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...

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 (r_e 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 r_e 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 r_e 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

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.

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.

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

A neutron scattering study of the quasi-one-dimensional conductor (TaSe{sub 4}){sub 2}I

Energy Technology Data Exchange (ETDEWEB)

Lorenzo, J.E.; Currat, R. [Institut Laue-Langevin, BP 156, 38042 Grenoble Cedex 9 (France); Monceau, P. [Centre de Recherches sur les Tres Basses Temperatures, associe a l' Universite Joseph Fourier, CNRS, BP 166, 38042 Grenoble Cedex 9 (France); Hennion, B. [Laboratoire Leon Brillouin, Centre d' Etudes de Saclay, 91191 Gif-sur-Yvette Cedex (France); Berger, H.; Levy, F. [Institut de Physique Appliquee, Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne (Switzerland)

1998-06-15

The Peierls phase transition in the quasi-one-dimensional conductor (TaSe{sub 4}){sub 2}I is investigated by means of elastic and inelastic neutron scattering. The effective critical exponent {beta}, extracted from the temperature dependence of the integrated intensity from the CDW satellite reflections, is anomalously low, suggesting that the phase transition may be of first order. The intensity distribution among symmetry-related satellite reflections indicates a domain structure with slowly fluctuating domain populations. Correlation lengths associated with the diverging 'central peak' are determined and are found to be nearly isotropic, at variance with results obtained on other quasi-one-dimensional compounds, such as platinum chains (KCP) or blue bronze, K{sub 0.3}MoO{sub 3}. Doping with 1.2% Nb has a severe effect on the modulated state. The low-temperature satellites are replaced by a diffuse scattering distribution elongated along c*. The absence of a phonon soft mode and the presence of a diverging central peak at the phase transition is interpreted within the framework of strong electron-phonon coupling. Finally, we propose a Ginzburg-Landau phenomenological model, where the interplay between the electronically coupled optical-like order parameter (Ta-atom tetramerization along the chain axis) and the elastic deformations lies at the origin of the phase transition in (TaSe{sub 4}){sub 2}I. (author)

"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.

Does quality control matter? Surface urban heat island intensity variations estimated by satellite-derived land surface temperature products

Science.gov (United States)

Lai, Jiameng; Zhan, Wenfeng; Huang, Fan; Quan, Jinling; Hu, Leiqiu; Gao, Lun; Ju, Weimin

2018-05-01

The temporally regular and spatially comprehensive monitoring of surface urban heat islands (SUHIs) have been extremely difficult, until the advent of satellite-based land surface temperature (LST) products. However, these LST products have relatively higher errors compared to in situ measurements. This has resulted in comparatively inaccurate estimations of SUHI indicators and, consequently, may have distorted interpretations of SUHIs. Although reports have shown that LST qualities are important for SUHI interpretations, systematic investigations of the response of SUHI indicators to LST qualities across cities with dissimilar bioclimates are rare. To address this issue, we chose eighty-six major cities across mainland China and analyzed SUHI intensity (SUHII) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The LST-based SUHII differences due to inclusion or exclusion of MODIS quality control (QC) flags (i.e., ΔSUHII) were evaluated. Our major findings included, but are not limited to, the following four aspects: (1) SUHIIs can be significantly impacted by MODIS QC flags, and the associated QC-induced ΔSUHIIs generally accounted for 24.3% (29.9%) of the total SUHII value during the day (night); (2) the ΔSUHIIs differed between seasons, with considerable differences between transitional (spring and autumn) and extreme (summer and winter) seasons; (3) significant discrepancies also appeared among cities located in northern and southern regions, with northern cities often possessing higher annual mean ΔSUHIIs. The internal variations of ΔSUHIIs within individual cities also showed high heterogeneity, with ΔSUHII variations that generally exceeded 5.0 K (3.0 K) in northern (southern) cities; (4) ΔSUHIIs were negatively related to SUHIIs and cloud cover percentages (mostly in transitional seasons). No significant relationship was found in the extreme seasons. Our findings highlight the need to be extremely cautious when using LST

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...

Satellite Estimation of Daily Land Surface Water Vapor Pressure Deficit from AMSR- E

Science.gov (United States)

Jones, L. A.; Kimball, J. S.; McDonald, K. C.; Chan, S. K.; Njoku, E. G.; Oechel, W. C.

2007-12-01

Vapor pressure deficit (VPD) is a key variable for monitoring land surface water and energy exchanges, and estimating plant water stress. Multi-frequency day/night brightness temperatures from the Advanced Microwave Scanning Radiometer on EOS Aqua (AMSR-E) were used to estimate daily minimum and average near surface (2 m) air temperatures across a North American boreal-Arctic transect. A simple method for determining daily mean VPD (Pa) from AMSR-E air temperature retrievals was developed and validated against observations across a regional network of eight study sites ranging from boreal grassland and forest to arctic tundra. The method assumes that the dew point and minimum daily air temperatures tend to equilibrate in areas with low night time temperatures and relatively moist conditions. This assumption was tested by comparing the VPD algorithm results derived from site daily temperature observations against results derived from AMSR-E retrieved temperatures alone. An error analysis was conducted to determine the amount of error introduced in VPD estimates given known levels of error in satellite retrieved temperatures. Results indicate that the assumption generally holds for the high latitude study sites except for arid locations in mid-summer. VPD estimates using the method with AMSR-E retrieved temperatures compare favorably with site observations. The method can be applied to land surface temperature retrievals from any sensor with day and night surface or near-surface thermal measurements and shows potential for inferring near-surface wetness conditions where dense vegetation may hinder surface soil moisture retrievals from low-frequency microwave sensors. This work was carried out at The University of Montana, at San Diego State University, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

TaEDS1 genes positively regulate resistance to powdery mildew in wheat.

Science.gov (United States)

Chen, Guiping; Wei, Bo; Li, Guoliang; Gong, Caiyan; Fan, Renchun; Zhang, Xiangqi

2018-04-01

Three EDS1 genes were cloned from common wheat and were demonstrated to positively regulate resistance to powdery mildew in wheat. The EDS1 proteins play important roles in plant basal resistance and TIR-NB-LRR protein-triggered resistance in dicots. Until now, there have been very few studies on EDS1 in monocots, and none in wheat. Here, we report on three common wheat orthologous genes of EDS1 family (TaEDS1-5A, 5B and 5D) and their function in powdery mildew resistance. Comparisons of these genes with their orthologs in diploid ancestors revealed that EDS1 is a conserved gene family in Triticeae. The cDNA sequence similarity among the three TaEDS1 genes was greater than 96.5%, and they shared sequence similarities of more than 99.6% with the respective orthologs from diploid ancestors. The phylogenetic analysis revealed that the EDS1 family originated prior to the differentiation of monocots and dicots, and EDS1 members have since undergone clear structural differentiation. The transcriptional levels of TaEDS1 genes in the leaves were obviously higher than those of the other organs, and they were induced by Blumeria graminis f. sp. tritici (Bgt) infection and salicylic acid (SA) treatment. The BSMV-VIGS experiments indicated that knock-down the transcriptional levels of the TaEDS1 genes in a powdery mildew-resistant variety of common wheat compromised resistance. Contrarily, transient overexpression of TaEDS1 genes in a susceptible common wheat variety significantly reduced the haustorium index and attenuated the growth of Bgt. Furthermore, the expression of TaEDS1 genes in the Arabidopsis mutant eds1-1 complemented its susceptible phenotype to powdery mildew. The above evidences strongly suggest that TaEDS1 acts as a positive regulator and confers resistance against powdery mildew in common wheat.

The Role of Satellite Imagery to Improve Pastureland Estimates in South America

Science.gov (United States)

Graesser, J.

2015-12-01

Agriculture has changed substantially across the globe over the past half century. While much work has been done to improve spatial-temporal estimates of agricultural changes, we still know more about the extent of row-crop agriculture than livestock-grazed land. The gap between cropland and pastureland estimates exists largely because it is challenging to characterize natural versus grazed grasslands from a remote sensing perspective. However, the impasse of pastureland estimates is set to break, with an increasing number of spaceborne sensors and freely available satellite data. The Landsat satellite archive in particular provides researchers with immense amounts of data to improve pastureland information. Here we focus on South America, where pastureland expansion has been scrutinized for the past few decades. We explore the challenges of estimating pastureland using temporal Landsat imagery and focus on key agricultural countries, regions, and ecosystems. We focus on the suggested shift of pastureland from the Argentine Pampas to northern Argentina, and the mixing of small-scale and large-scale ranching in eastern Paraguay and how it could impact the Chaco forest to the west. Further, the Beni Savannahs of northern Bolivia and the Colombian Llanos—both grassland and savannah regions historically used for livestock grazing—have been hinted at as future areas for cropland expansion. There are certainly environmental concerns with pastureland expansion into forests; but what are the environmental implications when well-managed pasture systems are converted to intensive soybean or palm oil plantation? Tropical, grazed grasslands are important habitats for biodiversity, and pasturelands can mitigate soil erosion when well managed. Thus, we must improve estimates of grazed land before we can make informed policy and conservation decisions. This talk presents insights into pastureland estimates in South America and discusses the feasibility to improve current

Estimation of evaporation rates over the Arabian Sea from Satellite data

Digital Repository Service at National Institute of Oceanography (India)

Rao, M.V.; RameshBabu, V.; Rao, L.V.G.; Sastry, J.S.

Utilizing both the SAMIR brightness temperatures of Bhaskara 2 and GOSSTCOMP charts of NOAA satellite series, the evaporation rates over the Arabian Sea for June 1982 are estimated through the bulk aerodynamic method. The spatial distribution...

Method of quantitative x-ray diffractometric analysis of Ta-Ta2C system

International Nuclear Information System (INIS)

Gavrish, A.A.; Glazunov, M.P.; Korolev, Yu.M.; Spitsyn, V.I.; Fedoseev, G.K.

1976-01-01

The syste86 Ta-Ta 2 C has beemonsidered because of specific features of diffraction patterns of the components, namely, overlapping of the most intensive reflexes of both phases. The method of standard binary system has been used for quantitative analysis. Because of overlapping of the intensive reflexes dsub(1/01)=2.36(Ta 2 C) and dsub(110)=2.33(Ta), the other, most intensive, reflexes have been used for quantitative determination of Ta 2 C and Ta: dsub(103)=1.404 A for tantalum subcarbide and dsub(211)=1.35A for tantalum. Besides, the TaTa 2 C phases have been determined quantitatively with the use of another pair of reflexes: dsub(102)=1.82 A for Ta 2 C and dsub(200)=1.65 A for tantalum. The agreement between the results obtained while performing the quantitative phase analysis is good. To increase reliability and accuracy of the quantitative determination of Ta and Ta 2 C, it is expedient to carry out the analysis with the use of two above-mentioned pairs of reflexes located in different regions of the diffraction spectrum. Thus, the procedure of quantitative analysis of Ta and Ta 2 C in different ratios has been developed taking into account the specific features of the diffraction patterns of these components as well as the ability of Ta 2 C to texture in the process of preparation

An Online Tilt Estimation and Compensation Algorithm for a Small Satellite Camera

Science.gov (United States)

Lee, Da-Hyun; Hwang, Jai-hyuk

2018-04-01

In the case of a satellite camera designed to execute an Earth observation mission, even after a pre-launch precision alignment process has been carried out, misalignment will occur due to external factors during the launch and in the operating environment. In particular, for high-resolution satellite cameras, which require submicron accuracy for alignment between optical components, misalignment is a major cause of image quality degradation. To compensate for this, most high-resolution satellite cameras undergo a precise realignment process called refocusing before and during the operation process. However, conventional Earth observation satellites only execute refocusing upon de-space. Thus, in this paper, an online tilt estimation and compensation algorithm that can be utilized after de-space correction is executed. Although the sensitivity of the optical performance degradation due to the misalignment is highest in de-space, the MTF can be additionally increased by correcting tilt after refocusing. The algorithm proposed in this research can be used to estimate the amount of tilt that occurs by taking star images, and it can also be used to carry out automatic tilt corrections by employing a compensation mechanism that gives angular motion to the secondary mirror. Crucially, this algorithm is developed using an online processing system so that it can operate without communication with the ground.

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.

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.

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

Directory of Open Access Journals (Sweden)

K. Aalstad

2018-01-01

Full Text Available With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD at the 1 km scale by assimilating fractional snow-covered area (fSCA satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation ensemble smoother with multiple data assimilation (ES-MDA scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e. and 0.13, respectively. The ES-MDA either

Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites

Science.gov (United States)

Aalstad, Kristoffer; Westermann, Sebastian; Vikhamar Schuler, Thomas; Boike, Julia; Bertino, Laurent

2018-01-01

With its high albedo, low thermal conductivity and large water storing capacity, snow strongly modulates the surface energy and water balance, which makes it a critical factor in mid- to high-latitude and mountain environments. However, estimating the snow water equivalent (SWE) is challenging in remote-sensing applications already at medium spatial resolutions of 1 km. We present an ensemble-based data assimilation framework that estimates the peak subgrid SWE distribution (SSD) at the 1 km scale by assimilating fractional snow-covered area (fSCA) satellite retrievals in a simple snow model forced by downscaled reanalysis data. The basic idea is to relate the timing of the snow cover depletion (accessible from satellite products) to the peak SSD. Peak subgrid SWE is assumed to be lognormally distributed, which can be translated to a modeled time series of fSCA through the snow model. Assimilation of satellite-derived fSCA facilitates the estimation of the peak SSD, while taking into account uncertainties in both the model and the assimilated data sets. As an extension to previous studies, our method makes use of the novel (to snow data assimilation) ensemble smoother with multiple data assimilation (ES-MDA) scheme combined with analytical Gaussian anamorphosis to assimilate time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-2 fSCA retrievals. The scheme is applied to Arctic sites near Ny-Ålesund (79° N, Svalbard, Norway) where field measurements of fSCA and SWE distributions are available. The method is able to successfully recover accurate estimates of peak SSD on most of the occasions considered. Through the ES-MDA assimilation, the root-mean-square error (RMSE) for the fSCA, peak mean SWE and peak subgrid coefficient of variation is improved by around 75, 60 and 20 %, respectively, when compared to the prior, yielding RMSEs of 0.01, 0.09 m water equivalent (w.e.) and 0.13, respectively. The ES-MDA either outperforms or at least

A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

Science.gov (United States)

Zorzetto, E.; Marani, M.

2017-12-01

The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

Merging Satellite Precipitation Products for Improved Streamflow Simulations

Science.gov (United States)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical

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...

Effect of Ta content on martensitic transformation behavior of RuTa ultrahigh temperature shape memory alloys

International Nuclear Information System (INIS)

He Zhirong; Zhou Jingen; Furuya, Y.

2003-01-01

Effects of Ta content on martensitic transformation (MT) behavior of Ru 100-x Ta x (x=46-54 at.%) alloys have been investigated by differential scanning calorimetry, dilatometry, X-ray diffraction and optical microscopy. Ta content significantly affects the MT behavior of RuTa alloys. The one-stage reservible MT occurs in Ta-poor RuTa alloys with Ta content less than 49 at.%. The two-stage reservible MT takes place in near-equiatomic RuTa alloys. No reservible MT is observed in Ta-rich alloys with Ta content more then 52 at.% Ta. The MT temperatures and hysteresis of RuTa alloys decrease with increasing Ta content. The aged and thermal cycled processes are nearly no effect on the MT behavior of these alloys. The deforming way of RuTa alloys is twinning. The Ru 50 Ta 50 alloy is of the most excellent MT behavior among these RuTa alloys

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

NARCIS (Netherlands)

Tote, C.; Patricio, D.; Boogaard, H.L.; Wijngaart, van der R.; Tarnavsky, E.; Funk, C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and

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.

Estimation of Daily Air Temperature Based on MODIS Land Surface Temperature Products over the Corn Belt in the US

Directory of Open Access Journals (Sweden)

Linglin Zeng

2015-01-01

Full Text Available Air temperature (Ta is a key input in a wide range of agroclimatic applications. Moderate Resolution Imaging Spectroradiometer (MODIS Ts (Land Surface Temperature (LST products are widely used to estimate daily Ta. However, only daytime LST (Ts-day or nighttime LST (Ts-night data have been used to estimate Tmax/Tmin (daily maximum or minimum air temperature, respectively. The relationship between Tmax and Ts-night, and the one between Tmin and Ts-day has not been studied. In this study, both the ability of Ts-night data to estimate Tmax and the ability of Ts-day data to estimate Tmin were tested and studied in the Corn Belt during the growing season (May–September from 2008 to 2012, using MODIS daily LST products from both Terra and Aqua. The results show that using Ts-night for estimating Tmax could result in a higher accuracy than using Ts-day for a similar estimate. Combining Ts-day and Ts-night, the estimation of Tmax was improved by 0.19–1.85, 0.37–1.12 and 0.26–0.93 °C for crops, deciduous forest and developed areas, respectively, when compared with using only Ts-day or Ts-night data. The main factors influencing the Ta estimation errors spatially and temporally were analyzed and discussed, such as satellite overpassing time, air masses, irrigation, etc.

Estimation of CO2 emissions from fossil fuel burning by using satellite measurements of co-emitted gases: a new method and its application to the European region

Science.gov (United States)

Berezin, Evgeny V.; Konovalov, Igor B.; Ciais, Philippe; Broquet, Gregoire

2014-05-01

Accurate estimates of emissions of carbon dioxide (CO2), which is a major greenhouse gas, are requisite for understanding of the thermal balance of the atmosphere and for predicting climate change. International and regional CO2 emission inventories are usually compiled by following the 'bottom-up' approach on the basis of available statistical information about fossil fuel consumption. Such information may be rather uncertain, leading to uncertainties in the emission estimates. One of the possible ways to understand and reduce this uncertainty is to use satellite measurements in the framework of the inverse modeling approach; however, information on CO2 emissions, which is currently provided by direct satellite measurements of CO2, remains very limited. The main goal of this study is to develop a CO2 emission estimation method based on using satellite measurements of co-emitted species, such as NOx (represented by NO2 in the satellite measurements) and CO. Due to a short lifetime of NOx and relatively low background concentration of CO, the observed column amounts of NO2 and CO are typically higher over regions with strong emission sources than over remote regions. Therefore, satellite measurements of these species can provide useful information on the spatial distribution and temporal evolution of major emission sources. The method's basic idea (which is similar to the ideas already exploited in the earlier studies [1, 2]) is to combine this information with available estimates of emission factors for all of the species considered. The method assumes optimization of the total CO2 emissions from the two major aggregated sectors of economy. CO2 emission estimates derived from independent satellite measurements of the different species are combined in a probabilistic way by taking into account their uncertainties. The CHIMERE chemistry transport model is used to simulate the relationship between NOx (CO) emissions and NO2 (CO) columns from the OMI (IASI

Improving satellite-based post-fire evapotranspiration estimates in semi-arid regions

Science.gov (United States)

Poon, P.; Kinoshita, A. M.

2017-12-01

Climate change and anthropogenic factors contribute to the increased frequency, duration, and size of wildfires, which can alter ecosystem and hydrological processes. The loss of vegetation canopy and ground cover reduces interception and alters evapotranspiration (ET) dynamics in riparian areas, which can impact rainfall-runoff partitioning. Previous research evaluated the spatial and temporal trends of ET based on burn severity and observed an annual decrease of 120 mm on average for three years after fire. Building upon these results, this research focuses on the Coyote Fire in San Diego, California (USA), which burned a total of 76 km2 in 2003 to calibrate and improve satellite-based ET estimates in semi-arid regions affected by wildfire. The current work utilizes satellite-based products and techniques such as the Google Earth Engine Application programming interface (API). Various ET models (ie. Operational Simplified Surface Energy Balance Model (SSEBop)) are compared to the latent heat flux from two AmeriFlux eddy covariance towers, Sky Oaks Young (US-SO3), and Old Stand (US-SO2), from 2000 - 2015. The Old Stand tower has a low burn severity and the Young Stand tower has a moderate to high burn severity. Both towers are used to validate spatial ET estimates. Furthermore, variables and indices, such as Enhanced Vegetation Index (EVI), Normalized Difference Moisture Index (NDMI), and the Normalized Burn Ratio (NBR) are utilized to evaluate satellite-based ET through a multivariate statistical analysis at both sites. This point-scale study will able to improve ET estimates in spatially diverse regions. Results from this research will contribute to the development of a post-wildfire ET model for semi-arid regions. Accurate estimates of post-fire ET will provide a better representation of vegetation and hydrologic recovery, which can be used to improve hydrologic models and predictions.

Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium).

Science.gov (United States)

di Diodato, A.; de Leonibus, L.; Zauli, F.; Biron, D.; Melfi, D.

2009-04-01

Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium). Cap. Attilio DI DIODATO(*), T.Col. Luigi DE LEONIBUS(*), T.Col Francesco ZAULI(*), Cap. Daniele BIRON(*), Ten. Davide Melfi(*) Satellite Application Facilities (SAFs) are specialised development and processing centres of the EUMETSAT Distributed Ground Segment. SAFs process level 1b data from meteorological satellites (geostationary and polar ones) in conjunction with all other relevant sources of data and appropriate models to generate services and level 2 products. Each SAF is a consortium of EUMETSAT European partners lead by a host institute responsible for the management of the complete SAF project. The Meteorological Service of Italian Air Force is the host Institute for the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). HSAF has the commitment to develop and to provide, operationally after 2010, products regarding precipitation, soil moisture and snow. HSAF is going to provide information on error structure of its products and validation of the products via their impacts into Hydrological models. To that purpose it has been structured a specific subgroups. Accumulated precipitation is computed by temporal integration of the instantaneous rain rate achieved by the blended LEO/MW and GEO/IR precipitation rate products generated by Rapid Update method available every 15 minutes. The algorithm provides four outputs, consisting in accumulated precipitation in 3, 6, 12 and 24 hours, delivered every 3 hours at the synoptic hours. These outputs are our precipitation background fields. Satellite estimates can cover most of the globe, however, they suffer from errors due to lack of a direct relationship between observation parameters and precipitation, the poor sampling and algorithm imperfections. For this reason the 3 hours accumulated precipitation is

A new approach to estimate ice dynamic rates using satellite observations in East Antarctica

Directory of Open Access Journals (Sweden)

B. Kallenberg

2017-05-01

Full Text Available Mass balance changes of the Antarctic ice sheet are of significant interest due to its sensitivity to climatic changes and its contribution to changes in global sea level. While regional climate models successfully estimate mass input due to snowfall, it remains difficult to estimate the amount of mass loss due to ice dynamic processes. It has often been assumed that changes in ice dynamic rates only need to be considered when assessing long-term ice sheet mass balance; however, 2 decades of satellite altimetry observations reveal that the Antarctic ice sheet changes unexpectedly and much more dynamically than previously expected. Despite available estimates on ice dynamic rates obtained from radar altimetry, information about ice sheet changes due to changes in the ice dynamics are still limited, especially in East Antarctica. Without understanding ice dynamic rates, it is not possible to properly assess changes in ice sheet mass balance and surface elevation or to develop ice sheet models. In this study we investigate the possibility of estimating ice sheet changes due to ice dynamic rates by removing modelled rates of surface mass balance, firn compaction, and bedrock uplift from satellite altimetry and gravity observations. With similar rates of ice discharge acquired from two different satellite missions we show that it is possible to obtain an approximation of the rate of change due to ice dynamics by combining altimetry and gravity observations. Thus, surface elevation changes due to surface mass balance, firn compaction, and ice dynamic rates can be modelled and correlated with observed elevation changes from satellite altimetry.

Estimating tropical vertical motion profile shapes from satellite observations

Science.gov (United States)

Back, L. E.; Handlos, Z.

2013-12-01

The vertical structure of tropical deep convection strongly influences interactions with larger scale circulations and climate. This research focuses on investigating this vertical structure and its relationship with mesoscale tropical weather states. We test the hypothesis that vertical motion shape varies in association with weather state type. We estimate mean state vertical motion profile shapes for six tropical weather states defined using cloud top pressure and optical depth properties from the International Satellite Cloud Climatology Project. The relationship between vertical motion and the dry static energy budget are utilized to set up a regression analysis that empirically determines two modes of variability in vertical motion from reanalysis data. We use these empirically determined modes, this relationship and surface convergence to estimate vertical motion profile shape from observations of satellite retrievals of rainfall and surface convergence. We find that vertical motion profile shapes vary systematically between different tropical weather states. The "isolated systems" regime exhibits a more ''bottom-heavy'' profile shape compared to the convective/thick cirrus and vigorous deep convective regimes, with maximum upward vertical motion occurring in the lower troposphere rather than the middle to upper troposphere. The variability we observe with our method does not coincide with that expected based on conventional ideas about how stratiform rain fraction and vertical motion are related.

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.

Estimation of global soil respiration by accounting for land-use changes derived from remote sensing data.

Science.gov (United States)

Adachi, Minaco; Ito, Akihiko; Yonemura, Seiichiro; Takeuchi, Wataru

2017-09-15

Soil respiration is one of the largest carbon fluxes from terrestrial ecosystems. Estimating global soil respiration is difficult because of its high spatiotemporal variability and sensitivity to land-use change. Satellite monitoring provides useful data for estimating the global carbon budget, but few studies have estimated global soil respiration using satellite data. We provide preliminary insights into the estimation of global soil respiration in 2001 and 2009 using empirically derived soil temperature equations for 17 ecosystems obtained by field studies, as well as MODIS climate data and land-use maps at a 4-km resolution. The daytime surface temperature from winter to early summer based on the MODIS data tended to be higher than the field-observed soil temperatures in subarctic and temperate ecosystems. The estimated global soil respiration was 94.8 and 93.8 Pg C yr -1 in 2001 and 2009, respectively. However, the MODIS land-use maps had insufficient spatial resolution to evaluate the effect of land-use change on soil respiration. The spatial variation of soil respiration (Q 10 ) values was higher but its spatial variation was lower in high-latitude areas than in other areas. However, Q 10 in tropical areas was more variable and was not accurately estimated (the values were >7.5 or soil respiration in tropical ecosystems. To solve these problems, it will be necessary to validate our results using a combination of remote sensing data at higher spatial resolution and field observations for many different ecosystems, and it will be necessary to account for the effects of more soil factors in the predictive equations. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms

Directory of Open Access Journals (Sweden)

Patrick Marina

2017-01-01

Full Text Available On-site measurements from rain gauge provide important information for the design, construction, and operation of water resources engineering projects, groundwater potentials, and the water supply and irrigation systems. A dense gauging network is needed to accurately characterize the variation of rainfall over a region, unfitting for conditions with limited networks, such as in Sarawak, Malaysia. Hence, satellite-based algorithm estimates are introduced as an innovative solution to these challenges. With accessibility to dataset retrievals from public domain websites, it has become a useful source to measure rainfall for a wider coverage area at finer temporal resolution. This paper aims to investigate the rainfall estimates prepared by Tropical Rainfall Measuring Mission (TRMM to explain whether it is suitable to represent the distribution of extreme rainfall in Sungai Sarawak Basin. Based on the findings, more uniform correlations for the investigated storms can be observed for low to medium altitude (>40 MASL. It is found for the investigated events of Jan 05-11, 2009: the normalized root mean square error (NRMSE = 36.7 %; and good correlation (CC = 0.9. These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.

Superconducting state in (W, Ta)5SiB2

Science.gov (United States)

Fukuma, M.; Kawashima, K.; Akimitsu, J.

We characterize the superconducting state in a boro-silicide (W, Ta)5SiB2, with Tc of 6.5 K by means of magnetization, electrical resistivity, and specific heat measurements. As x increased, the transition temperature Tc abruptly enhances from 5.8 to 6.5 K. The magnetization versus magnetic field (M-H) curve indicated that (W, Ta)5SiB2 was a conventional type-II superconductor. The estimated lower critical field Hc1(0) and upper critical field Hc2(T) are about 121 Oe and 14.7 kOe, respectively. The penetration depth λ(0) and coherence length ξ(0) are calculated to be approximately 369 and 14.9 nm, respectively, using Ginzburg-Landau (GL) equations. Specific heat data shows the superconductivity in W4.5Ta0.5SiB2 belongs to a week-coupling BCS superconductor. Finally, we discuss the increasing of Tc in of (W, Ta)5SiB2 system.

Distributed Extended Kalman Filter for Position, Velocity, Time, Estimation in Satellite Navigation Receivers

Directory of Open Access Journals (Sweden)

O. Jakubov

2013-09-01

Full Text Available Common techniques for position-velocity-time estimation in satellite navigation, iterative least squares and the extended Kalman filter, involve matrix operations. The matrix inversion and inclusion of a matrix library pose requirements on a computational power and operating platform of the navigation processor. In this paper, we introduce a novel distributed algorithm suitable for implementation in simple parallel processing units each for a tracked satellite. Such a unit performs only scalar sum, subtraction, multiplication, and division. The algorithm can be efficiently implemented in hardware logic. Given the fast position-velocity-time estimator, frequent estimates can foster dynamic performance of a vector tracking receiver. The algorithm has been designed from a factor graph representing the extended Kalman filter by splitting vector nodes into scalar ones resulting in a cyclic graph with few iterations needed. Monte Carlo simulations have been conducted to investigate convergence and accuracy. Simulation case studies for a vector tracking architecture and experimental measurements with a real-time software receiver developed at CTU in Prague were conducted. The algorithm offers compromises in stability, accuracy, and complexity depending on the number of iterations. In scenarios with a large number of tracked satellites, it can outperform the traditional methods at low complexity.

Impaired macrophage and satellite cell infiltration occurs in a muscle-specific fashion following injury in diabetic skeletal muscle.

Directory of Open Access Journals (Sweden)

Matthew P Krause

Full Text Available Systemic elevations in PAI-1 suppress the fibrinolytic pathway leading to poor collagen remodelling and delayed regeneration of tibialis anterior (TA muscles in type-1 diabetic Akita mice. However, how impaired collagen remodelling was specifically attenuating regeneration in Akita mice remained unknown. Furthermore, given intrinsic differences between muscle groups, it was unclear if the reparative responses between muscle groups were different.Here we reveal that diabetic Akita muscles display differential regenerative responses with the TA and gastrocnemius muscles exhibiting reduced regenerating myofiber area compared to wild-type mice, while soleus muscles displayed no difference between animal groups following injury. Collagen levels in TA and gastrocnemius, but not soleus, were significantly increased post-injury versus controls. At 5 days post-injury, when degenerating/necrotic regions were present in both animal groups, Akita TA and gastrocnemius muscles displayed reduced macrophage and satellite cell infiltration and poor myofiber formation. By 10 days post-injury, necrotic regions were absent in wild-type TA but persisted in Akita TA. In contrast, Akita soleus exhibited no impairment in any of these measures compared to wild-type soleus. In an effort to define how impaired collagen turnover was attenuating regeneration in Akita TA, a PAI-1 inhibitor (PAI-039 was orally administered to Akita mice following cardiotoxin injury. PAI-039 administration promoted macrophage and satellite cell infiltration into necrotic areas of the TA and gastrocnemius. Importantly, soleus muscles exhibit the highest inducible expression of MMP-9 following injury, providing a mechanism for normative collagen degradation and injury recovery in this muscle despite systemically elevated PAI-1.Our findings suggest the mechanism underlying how impaired collagen remodelling in type-1 diabetes results in delayed regeneration is an impairment in macrophage

Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

Science.gov (United States)

Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

2016-12-01

Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

Energy Technology Data Exchange (ETDEWEB)

Stenz, Ronald; Dong, Xiquan; Xi, Baike; Feng, Zhe; Kuligowski, Robert J.

2016-02-01

To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systems (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions (Stenz et al. 2014). A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. The performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.

Geothermal Heat Flux Underneath Ice Sheets Estimated From Magnetic Satellite Data

DEFF Research Database (Denmark)

Fox Maule, Cathrine; Purucker, M.E.; Olsen, Nils

The geothermal heat flux is an important factor in the dynamics of ice sheets, and it is one of the important parameters in the thermal budgets of subglacial lakes. We have used satellite magnetic data to estimate the geothermal heat flux underneath the ice sheets in Antarctica and Greenland...

Estimating the top altitude of optically thick ice clouds from thermal infrared satellite observations using CALIPSO data

Science.gov (United States)

Minnis, Patrick; Yost, Chris R.; Sun-Mack, Sunny; Chen, Yan

2008-06-01

The difference between cloud-top altitude Z top and infrared effective radiating height Z eff for optically thick ice clouds is examined using April 2007 data taken by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and the Moderate-Resolution Imaging Spectroradiometer (MODIS). For even days, the difference ΔZ between CALIPSO Z top and MODIS Z eff is 1.58 +/- 1.26 km. The linear fit between Z top and Z eff , applied to odd-day data, yields a difference of 0.03 +/- 1.21 km and can be used to estimate Z top from any infrared-based Z eff for thick ice clouds. Random errors appear to be due primarily to variations in cloud ice-water content (IWC). Radiative transfer calculations show that ΔZ corresponds to an optical depth of ~1, which based on observed ice-particle sizes yields an average cloud-top IWC of ~0.015 gm-3, a value consistent with in situ measurements. The analysis indicates potential for deriving cloud-top IWC using dual-satellite data.

Solar resources estimation combining digital terrain models and satellite images techniques

Energy Technology Data Exchange (ETDEWEB)

Bosch, J.L.; Batlles, F.J. [Universidad de Almeria, Departamento de Fisica Aplicada, Ctra. Sacramento s/n, 04120-Almeria (Spain); Zarzalejo, L.F. [CIEMAT, Departamento de Energia, Madrid (Spain); Lopez, G. [EPS-Universidad de Huelva, Departamento de Ingenieria Electrica y Termica, Huelva (Spain)

2010-12-15

One of the most important steps to make use of any renewable energy is to perform an accurate estimation of the resource that has to be exploited. In the designing process of both active and passive solar energy systems, radiation data is required for the site, with proper spatial resolution. Generally, a radiometric stations network is used in this evaluation, but when they are too dispersed or not available for the study area, satellite images can be utilized as indirect solar radiation measurements. Although satellite images cover wide areas with a good acquisition frequency they usually have a poor spatial resolution limited by the size of the image pixel, and irradiation must be interpolated to evaluate solar irradiation at a sub-pixel scale. When pixels are located in flat and homogeneous areas, correlation of solar irradiation is relatively high, and classic interpolation can provide a good estimation. However, in complex topography zones, data interpolation is not adequate and the use of Digital Terrain Model (DTM) information can be helpful. In this work, daily solar irradiation is estimated for a wide mountainous area using a combination of Meteosat satellite images and a DTM, with the advantage of avoiding the necessity of ground measurements. This methodology utilizes a modified Heliosat-2 model, and applies for all sky conditions; it also introduces a horizon calculation of the DTM points and accounts for the effect of snow covers. Model performance has been evaluated against data measured in 12 radiometric stations, with results in terms of the Root Mean Square Error (RMSE) of 10%, and a Mean Bias Error (MBE) of +2%, both expressed as a percentage of the mean value measured. (author)

A simple and efficient algorithm to estimate daily global solar radiation from geostationary satellite data

International Nuclear Information System (INIS)

Lu, Ning; Qin, Jun; Yang, Kun; Sun, Jiulin

2011-01-01

Surface global solar radiation (GSR) is the primary renewable energy in nature. Geostationary satellite data are used to map GSR in many inversion algorithms in which ground GSR measurements merely serve to validate the satellite retrievals. In this study, a simple algorithm with artificial neural network (ANN) modeling is proposed to explore the non-linear physical relationship between ground daily GSR measurements and Multi-functional Transport Satellite (MTSAT) all-channel observations in an effort to fully exploit information contained in both data sets. Singular value decomposition is implemented to extract the principal signals from satellite data and a novel method is applied to enhance ANN performance at high altitude. A three-layer feed-forward ANN model is trained with one year of daily GSR measurements at ten ground sites. This trained ANN is then used to map continuous daily GSR for two years, and its performance is validated at all 83 ground sites in China. The evaluation result demonstrates that this algorithm can quickly and efficiently build the ANN model that estimates daily GSR from geostationary satellite data with good accuracy in both space and time. -- Highlights: → A simple and efficient algorithm to estimate GSR from geostationary satellite data. → ANN model fully exploits both the information from satellite and ground measurements. → Good performance of the ANN model is comparable to that of the classical models. → Surface elevation and infrared information enhance GSR inversion.

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.

Validation of the CHIRPS Satellite Rainfall Estimates over Eastern of Africa

Science.gov (United States)

Dinku, T.; Funk, C. C.; Tadesse, T.; Ceccato, P.

2017-12-01

Long and temporally consistent rainfall time series are essential in climate analyses and applications. Rainfall data from station observations are inadequate over many parts of the world due to sparse or non-existent observation networks, or limited reporting of gauge observations. As a result, satellite rainfall estimates have been used as an alternative or as a supplement to station observations. However, many satellite-based rainfall products with long time series suffer from coarse spatial and temporal resolutions and inhomogeneities caused by variations in satellite inputs. There are some satellite rainfall products with reasonably consistent time series, but they are often limited to specific geographic areas. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and quasi-global coverage. In this study, CHIRP and CHIRPS were evaluated over East Africa at daily, dekadal (10-day) and monthly time scales. The evaluation was done by comparing the satellite products with rain gauge data from about 1200 stations. The is unprecedented number of validation stations for this region covering. The results provide a unique region-wide understanding of how satellite products perform over different climatic/geographic (low lands, mountainous regions, and coastal) regions. The CHIRP and CHIRPS products were also compared with two similar satellite rainfall products: the African Rainfall Climatology version 2 (ARC2) and the latest release of the Tropical Applications of Meteorology using Satellite data (TAMSAT). The results show that both CHIRP and CHIRPS products are significantly better than ARC2 with higher skill and low or no bias. These products were also found to be slightly better than the latest version of the TAMSAT product. A comparison was also done between the latest release of the TAMSAT product

Investigation of TaC–TaB2 ceramic composites

Indian Academy of Sciences (India)

ture and the mechanical properties of the composites were investigated. The results .... 300 nm. Jingangzuan in the TaC/TaB2 composites SPS for 10 min at different temperatures are .... [1] Liu L, Yea F, Hea X and Zhoua Y 2011 Mater. Chem.

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.

Role of Ta-spacer layer on tuning the tilt angle magnetic anisotropy of L1{sub 1}-CoPt/Ta/NiFe exchange springs

Energy Technology Data Exchange (ETDEWEB)

Saravanan, P., E-mail: psdrdo@gmail.com [Defence Metallurgical Research Laboratory, Hyderabad 500058 (India); Talapatra, A.; Mohanty, J. [Department of Physics, Indian Institute of Technology Hyderabad, Hyderabad 502285 (India); Hsu, Jen-Hwa, E-mail: jhhsu@phys.ntu.edu.tw [Department of Physics, National Taiwan University, Taipei 106, Taiwan (China); Kamat, S.V. [Defence Metallurgical Research Laboratory, Hyderabad 500058 (India)

2017-06-15

Highlights: • Role of Ta-spacer layer in L1{sub 1}-CoPt(10 nm)/Ta//NiFe(4 nm) trilayers was investigated. • Domain size increased at the expense of magnetic phase contrast with increasing t{sub Ta}. • Tilt angle magnetization increased from 43° to 77° upon increasing t{sub Ta} (0–2.5 nm). • Micromagnetic studies confirmed the existence of tilted magnetic anisotropy. • Ta-spacer is effective in preserving competing anisotropies of CoPt and NiFe-layers. - Abstract: L1{sub 1}-CoPt/Ta/NiFe trilayers are chosen as model films for probing the role of spacer layer on tuning the tilt angle magnetization (θ{sub M}) in such exchange springs. For this purpose, a non-magnetic layer (Ta) with varying thickness (t{sub Ta}) from 0 to 2.5 nm was inserted between 10-nm thick CoPt film exhibiting strong perpendicular magnetic anisotropy (PMA) and 4-nm thick NiFe film having in-plane magnetic anisotropy (IMA). With the insertion of Ta-spacer, the magnetic hysteresis loops become more and more tilted as t{sub Ta} increases. Upon increasing the t{sub Ta} from 0 to 2.5 nm, the estimated SQR{sub ⊥} (=M{sub r⊥}/M{sub s⊥}) from the M–H loops is found to decrease moderately; while the θ{sub M} increases significantly from 43° to 77°. MFM images revealed maze-like domain patterns and the domain size tends to increase at the expense of magnetic phase contrast with increasing t{sub Ta}. Micro-magnetic simulation of tilt in the anisotropy axis with respect to the bare CoPt-layer showed a trend similar to that of those observed with the M–H loops obtained by VSM measurements. The results of present study suggest that the insertion of Ta-spacer is not only beneficial in terms of preserving the competing anisotropies such as PMA and IMA of CoPt and NiFe-layers respectively through weakened exchange coupling; but also, act as an appropriate means for realizing tunable tilted magnetic anisotropy in the L1{sub 1}-CoPt/NiFe exchange springs.

Essential climatic variables estimation with satellite imagery

Science.gov (United States)

Kolotii, A.; Kussul, N.; Shelestov, A.; Lavreniuk, M. S.

2016-12-01

According to Sendai Framework for Disaster Risk Reduction 2015 - 2030 Leaf Area Index (LAI) is considered as one of essential climatic variables. This variable represents the amount of leaf material in ecosystems and controls the links between biosphere and atmosphere through various processes and enables monitoring and quantitative assessment of vegetation state. LAI has added value for such important global resources monitoring tasks as drought mapping and crop yield forecasting with use of data from different sources [1-2]. Remote sensing data from space can be used to estimate such biophysical parameter at regional and national scale. High temporal satellite imagery is usually required to capture main parameters of crop growth [3]. Sentinel-2 mission launched in 2015 be ESA is a source of high spatial and temporal resolution satellite imagery for mapping biophysical parameters. Products created with use of automated Sen2-Agri system deployed during Sen2-Agri country level demonstration project for Ukraine will be compared with our independent results of biophysical parameters mapping. References Shelestov, A., Kolotii, A., Camacho, F., Skakun, S., Kussul, O., Lavreniuk, M., & Kostetsky, O. (2015, July). Mapping of biophysical parameters based on high resolution EO imagery for JECAM test site in Ukraine. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1733-1736 Kolotii, A., Kussul, N., Shelestov, A., Skakun, S., Yailymov, B., Basarab, R., ... & Ostapenko, V. (2015). Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 39-44. Kussul, N., Lemoine, G., Gallego, F. J., Skakun, S. V., Lavreniuk, M., & Shelestov, A. Y. Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 (6), 2500-2508.

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.

75 FR 43556 - TA-W-73,381, MT Rail Link, Inc., Missoula, MT; TA-W-73,381A, Billings, MT; TA-W-73,381B, Laurel...

Science.gov (United States)

2010-07-26

... DEPARTMENT OF LABOR Employment and Training Administration TA-W-73,381, MT Rail Link, Inc., Missoula, MT; TA-W-73,381A, Billings, MT; TA-W-73,381B, Laurel, MT; TA-W-73,381C, Livingston, MT; TA-W-73... Helena, Montana. The amended notice applicable to TA-W-73,381 is hereby issued as follows: All workers of...

Global High Resolution Sea Surface Flux Parameters From Multiple Satellites

Science.gov (United States)

Zhang, H.; Reynolds, R. W.; Shi, L.; Bates, J. J.

2007-05-01

Advances in understanding the coupled air-sea system and modeling of the ocean and atmosphere demand increasingly higher resolution data, such as air-sea fluxes of up to 3 hourly and every 50 km. These observational requirements can only be met by utilizing multiple satellite observations. Generation of such high resolution products from multiple-satellite and in-situ observations on an operational basis has been started at the U.S. National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center. Here we describe a few products that are directly related to the computation of turbulent air-sea fluxes. Sea surface wind speed has been observed from in-situ instruments and multiple satellites, with long-term observations ranging from one satellite in the mid 1987 to six or more satellites since mid 2002. A blended product with a global 0.25° grid and four snapshots per day has been produced for July 1987 to present, using a near Gaussian 3-D (x, y, t) interpolation to minimize aliases. Wind direction has been observed from fewer satellites, thus for the blended high resolution vector winds and wind stresses, the directions are taken from the NCEP Re-analysis 2 (operationally run near real time) for climate consistency. The widely used Reynolds Optimum Interpolation SST analysis has been improved with higher resolutions (daily and 0.25°). The improvements use both infrared and microwave satellite data that are bias-corrected by in- situ observations for the period 1985 to present. The new versions provide very significant improvements in terms of resolving ocean features such as the meandering of the Gulf Stream, the Aghulas Current, the equatorial jets and other fronts. The Ta and Qa retrievals are based on measurements from the AMSU sounder onboard the NOAA satellites. Ta retrieval uses AMSU-A data, while Qa retrieval uses both AMSU-A and AMSU-B observations. The retrieval algorithms are developed using the neural network approach. Training

Errors of Mean Dynamic Topography and Geostrophic Current Estimates in China's Marginal Seas from GOCE and Satellite Altimetry

DEFF Research Database (Denmark)

Jin, Shuanggen; Feng, Guiping; Andersen, Ole Baltazar

2014-01-01

and geostrophic current estimates from satellite gravimetry and altimetry are investigated and evaluated in China's marginal seas. The cumulative error in MDT from GOCE is reduced from 22.75 to 9.89 cm when compared to the Gravity Recovery and Climate Experiment (GRACE) gravity field model ITG-Grace2010 results......The Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) and satellite altimetry can provide very detailed and accurate estimates of the mean dynamic topography (MDT) and geostrophic currents in China's marginal seas, such as, the newest high-resolution GOCE gravity field model GO......-CONS-GCF-2-TIM-R4 and the new Centre National d'Etudes Spatiales mean sea surface model MSS_CNES_CLS_11 from satellite altimetry. However, errors and uncertainties of MDT and geostrophic current estimates from satellite observations are not generally quantified. In this paper, errors and uncertainties of MDT...

Simple Air Temperature Estimation Method from MODIS Satellite Images on a Regional Scale Método Simple de Estimación de Temperatura del Aire a Escala Regional, a Partir de Imágenes Satelitales MODIS

Directory of Open Access Journals (Sweden)

Fabiola Flores P

2010-09-01

Full Text Available Agricultural studies on a regional scale about water balance and evapotranspiration estimation, among others, require estimating air temperature (Ta spatial variation since the generally low density of weather stations does not allow obtaining such data for a specific area. The aim of this study was to estimate air temperature through atmospheric profiles provided by the Moderate Resolution Imaging Spectroradiometer (MODIS sensor on a regional level. One of the present-day methodologies estimates Ta through vertical temperature profiles, which is why modifications to this methodology were proposed for zoning, surface elevation, and pressure/altitude ratios. By applying this new methodology, better Ta estimates were obtained by replacing the MODIS sensor surface elevation with those of the Shuttle Radar Topography Mission (SRTM. Finally, it was possible to estimate Ta spatial variation only from remotely sensed data in various geomorphological areas.Para estudios relacionados con la agricultura a escala regional, como balance hídrico y estimación de evapotranspiración entre otros, es importante estimar la variación espacial de la temperatura del aire (Ta, ya que la baja densidad de estaciones meteorológicas no permite obtener dichos datos para una zona determinada. El objetivo de este trabajo fue estimar Ta a partir de perfiles atmosféricos proporcionados por el sensor de imágenes espectroradiométricas de resolución moderada (MODIS a nivel regional. Una de las metodologías actuales estima la Ta a partir de perfiles verticales de temperatura, por lo que se plantearon modificaciones a dicha metodología en la zonificación, superficie de elevación y relación presión-altitud. Al aplicar esta nueva metodología, las mejores estimaciones de Ta se consiguieron al reemplazar la superficie de elevación del sensor MODIS por la misión topográfica de plataforma radar (SRTM. Finalmente, fue posible estimar la variación espacial de Ta

Point Cloud Based Relative Pose Estimation of a Satellite in Close Range

Directory of Open Access Journals (Sweden)

Lujiang Liu

2016-06-01

Full Text Available Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This paper aims to estimate the pose of a target satellite in close range on the basis of its known model by using point cloud data generated by a flash LIDAR sensor. A novel model based pose estimation method is proposed; it includes a fast and reliable pose initial acquisition method based on global optimal searching by processing the dense point cloud data directly, and a pose tracking method based on Iterative Closest Point algorithm. Also, a simulation system is presented in this paper in order to evaluate the performance of the sensor and generate simulated sensor point cloud data. It also provides truth pose of the test target so that the pose estimation error can be quantified. To investigate the effectiveness of the proposed approach and achievable pose accuracy, numerical simulation experiments are performed; results demonstrate algorithm capability of operating with point cloud directly and large pose variations. Also, a field testing experiment is conducted and results show that the proposed method is effective.

Leveraging Machine Learning to Estimate Soil Salinity through Satellite-Based Remote Sensing

Science.gov (United States)

Welle, P.; Ravanbakhsh, S.; Póczos, B.; Mauter, M.

2016-12-01

Human-induced salinization of agricultural soils is a growing problem which now affects an estimated 76 million hectares and causes billions of dollars of lost agricultural revenues annually. While there are indications that soil salinization is increasing in extent, current assessments of global salinity levels are outdated and rely heavily on expert opinion due to the prohibitive cost of a worldwide sampling campaign. A more practical alternative to field sampling may be earth observation through remote sensing, which takes advantage of the distinct spectral signature of salts in order to estimate soil conductivity. Recent efforts to map salinity using remote sensing have been met with limited success due to tractability issues of managing the computational load associated with large amounts of satellite data. In this study, we use Google Earth Engine to create composite satellite soil datasets, which combine data from multiple sources and sensors. These composite datasets contain pixel-level surface reflectance values for dates in which the algorithm is most confident that the surface contains bare soil. We leverage the detailed soil maps created and updated by the United States Geological Survey as label data and apply machine learning regression techniques such as Gaussian processes to learn a smooth mapping from surface reflection to noisy estimates of salinity. We also explore a semi-supervised approach using deep generative convolutional networks to leverage the abundance of unlabeled satellite images in producing better estimates for salinity values where we have relatively fewer measurements across the globe. The general method results in two significant contributions: (1) an algorithm that can be used to predict levels of soil salinity in regions without detailed soil maps and (2) a general framework that serves as an example for how remote sensing can be paired with extensive label data to generate methods for prediction of physical phenomenon.

Use of satellite data to estimate radiation and evaporation for northwest Mexico

International Nuclear Information System (INIS)

Stewart, J.B.; Watts, C.J.; Rodriguez, J.C.; Bruin, H.A.R. de; Berg, A.R. van den; Garatuza-Payán, J.

1999-01-01

Incoming solar radiation was estimated from visible band data obtained by the GOES satellite over northwest Mexico. Comparisons against ground-based measurements of incoming solar radiation showed good agreement, particularly in months with low cloud cover. The data from an automatic weather station installed within the Yaqui Valley Irrigation Scheme was used to estimate potential evaporation from a formula based on incoming solar radiation and climatological values of temperature. The success of this formula was assessed by comparison against potential evaporation estimated using the Penman and Penman–Monteith formulae and measurements of net radiation. (author)

Satellite air temperature estimation for monitoring the canopy layer heat island of Milan

DEFF Research Database (Denmark)

Pichierri, Manuele; Bonafoni, Stefania; Biondi, Riccardo

2012-01-01

across the city center from June to September confirming that, in Milan, urban heating is not an occasional phenomenon. Furthermore, this study shows the utility of space missions to monitor the metropolis heat islands if they are able to provide nighttime observations when CLHI peaks are generally......In this work, satellite maps of the urban heat island of Milan are produced using satellite-based infrared sensor data. For this aim, we developed suitable algorithms employing satellite brightness temperatures for the direct air temperature estimation 2 m above the surface (canopy layer), showing...... 2007 and 2010 were processed. Analysis of the canopy layer heat island (CLHI) maps during summer months reveals an average heat island effect of 3–4K during nighttime (with some peaks around 5K) and a weak CLHI intensity during daytime. In addition, the satellite maps reveal a well defined island shape...

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

Signal Conditioning for the Kalman Filter: Application to Satellite Attitude Estimation with Magnetometer and Sun Sensors.

Science.gov (United States)

Esteban, Segundo; Girón-Sierra, Jose M; Polo, Óscar R; Angulo, Manuel

2016-10-31

Most satellites use an on-board attitude estimation system, based on available sensors. In the case of low-cost satellites, which are of increasing interest, it is usual to use magnetometers and Sun sensors. A Kalman filter is commonly recommended for the estimation, to simultaneously exploit the information from sensors and from a mathematical model of the satellite motion. It would be also convenient to adhere to a quaternion representation. This article focuses on some problems linked to this context. The state of the system should be represented in observable form. Singularities due to alignment of measured vectors cause estimation problems. Accommodation of the Kalman filter originates convergence difficulties. The article includes a new proposal that solves these problems, not needing changes in the Kalman filter algorithm. In addition, the article includes assessment of different errors, initialization values for the Kalman filter; and considers the influence of the magnetic dipole moment perturbation, showing how to handle it as part of the Kalman filter framework.

Signal Conditioning for the Kalman Filter: Application to Satellite Attitude Estimation with Magnetometer and Sun Sensors

Directory of Open Access Journals (Sweden)

Segundo Esteban

2016-10-01

Full Text Available Most satellites use an on-board attitude estimation system, based on available sensors. In the case of low-cost satellites, which are of increasing interest, it is usual to use magnetometers and Sun sensors. A Kalman filter is commonly recommended for the estimation, to simultaneously exploit the information from sensors and from a mathematical model of the satellite motion. It would be also convenient to adhere to a quaternion representation. This article focuses on some problems linked to this context. The state of the system should be represented in observable form. Singularities due to alignment of measured vectors cause estimation problems. Accommodation of the Kalman filter originates convergence difficulties. The article includes a new proposal that solves these problems, not needing changes in the Kalman filter algorithm. In addition, the article includes assessment of different errors, initialization values for the Kalman filter; and considers the influence of the magnetic dipole moment perturbation, showing how to handle it as part of the Kalman filter framework.

Generalized Jackknife Estimators of Weighted Average Derivatives

DEFF Research Database (Denmark)

Cattaneo, Matias D.; Crump, Richard K.; Jansson, Michael

With the aim of improving the quality of asymptotic distributional approximations for nonlinear functionals of nonparametric estimators, this paper revisits the large-sample properties of an important member of that class, namely a kernel-based weighted average derivative estimator. Asymptotic...

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

Estimating Dynamical Systems: Derivative Estimation Hints from Sir Ronald A. Fisher

Science.gov (United States)

Deboeck, Pascal R.

2010-01-01

The fitting of dynamical systems to psychological data offers the promise of addressing new and innovative questions about how people change over time. One method of fitting dynamical systems is to estimate the derivatives of a time series and then examine the relationships between derivatives using a differential equation model. One common…

Piezoelectric properties of nonstoichiometric Sr1-xBi2+2x/3Ta2O9 ceramics

International Nuclear Information System (INIS)

Jain, Rajni; Chauhan, Arun Kumar Singh; Gupta, Vinay; Sreenivas, K.

2005-01-01

The effect of poling on the structural, dielectric, and piezoelectric properties has been investigated for sol-gel-derived strontium bismuth tantalate (SBT) [Sr 1-x Bi 2+2x/3 Ta 2 O 9 ] ceramics with x=0.0,0.15,0.30,0.45. The dielectric and ferroelectric properties are found to improve with increase in x up to 0.3. Beyond x>0.3 the properties are found to degrade due to the limited solid solubility and the presence of a mixed phase of bismuth tantalate (BiTaO 4 ) is detected with x=0.45. Poling treatment reduces the dielectric dispersion and dielectric loss in the frequency range (0.1-100 kHz). The resonance and antiresonance frequencies increase with increase in x (x=0-0.30), and the corresponding minimum impedance decreases. The measured coupling coefficients (k p ) are small (0.0967-0.1) for x=0-0.30, and the electromechanical quality factor (Q m =915) is a maximum for the Sr 0.7 Bi 2.2 Ta 2 O 9 composition (x=0.30). The estimated piezoelectric charge coefficient (d 31 ) and piezoelectric voltage coefficient (g 31 ) are 5.2 pC/N and 5.8x10 -3 V m/N, respectively. The positive values of d 31 and g 31 and the low dielectric permittivity of SBT yield a high value for the hydrostatic coefficients, despite the low charge coefficient of d 33 =24 pC/N. The maximum values of charge coefficient (d h =34 pC/N) and voltage coefficient (g h =39x10 -3 V m/N) are obtained for Sr 0.7 Bi 2.2 Ta 2 O 9 composition, and the estimated hydrostatic figure of merit (d h g h x10 -15 =1215 m 2 /N) is high

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.

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Science.gov (United States)

M.D. Nelson; R.E. McRoberts; G.R. Holden; M.E. Bauer

2009-01-01

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We...

Fast emission estimates in China and South Africa constrained by satellite observations

Science.gov (United States)

Mijling, Bas; van der A, Ronald

2013-04-01

Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for emerging economies such as China and South Africa, where rapid economic growth change emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. However, constraining emissions from observations of concentrations is computationally challenging. Within the GlobEmission project (part of the Data User Element programme of ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China and South Africa, using the CHIMERE chemical transport model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e

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.

A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data

International Nuclear Information System (INIS)

Elvidge, Ch. D.; Erwin, E. H.; Ziskin, D.; Baugh, K. E.; Tuttle, B. T.; Ghosh, T.; Tuttle, B. T.; Ghosh, T.; Pack, D. W.; Zhizhin, M.

2009-01-01

We have produced annual estimates of national and global gas flaring and gas flaring efficiency from 1994 through 2008 using low light imaging data acquired by the Defense Meteorological Satellite Program (DMSP). Gas flaring is a widely used practice for the disposal of associated gas in oil production and processing facilities where there is insufficient infrastructure for utilization of the gas (primarily methane). Improved utilization of the gas is key to reducing global carbon emissions to the atmosphere. The DMSP estimates of flared gas volume are based on a calibration developed with a pooled set of reported national gas flaring volumes and data from individual flares. Flaring efficiency was calculated as the volume of flared gas per barrel of crude oil produced. Global gas flaring has remained largely stable over the past fifteen years, in the range of 140 to 170 billion cubic meters (BCM). Global flaring efficiency was in the seven to eight cubic meters per barrel from 1994 to 2005 and declined to 5.6 m 3 per barrel by 2008. The 2008 gas flaring estimate of 139 BCM represents 21% of the natural gas consumption of the USA with a potential retail market value of 68 billions USD. The 2008 flaring added more than 278 million metric tons of carbon dioxide equivalent (CO 2e ) into the atmosphere. The DMSP estimated gas flaring volumes indicate that global gas flaring has declined by 19% since 2005, led by gas flaring reductions in Russia and Nigeria, the two countries with the highest gas flaring levels. The flaring efficiency of both Russia and Nigeria improved from 2005 to 2008, suggesting that the reductions in gas flaring are likely the result of either improved utilization of the gas, reinjection, or direct venting of gas into the atmosphere, although the effect of uncertainties in the satellite data cannot be ruled out. It is anticipated that the capability to estimate gas flaring volumes based on satellite data will spur improved utilization of gas that

Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data.

Science.gov (United States)

Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen

2013-02-01

The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T(a)) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T(a) estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T(a) based on MODIS land surface temperature (LST) data. The verification results of maximum T(a), minimum T(a), GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale.

Fault estimation of satellite reaction wheels using covariance based adaptive unscented Kalman filter

Science.gov (United States)

Rahimi, Afshin; Kumar, Krishna Dev; Alighanbari, Hekmat

2017-05-01

Reaction wheels, as one of the most commonly used actuators in satellite attitude control systems, are prone to malfunction which could lead to catastrophic failures. Such malfunctions can be detected and addressed in time if proper analytical redundancy algorithms such as parameter estimation and control reconfiguration are employed. Major challenges in parameter estimation include speed and accuracy of the employed algorithm. This paper presents a new approach for improving parameter estimation with adaptive unscented Kalman filter. The enhancement in tracking speed of unscented Kalman filter is achieved by systematically adapting the covariance matrix to the faulty estimates using innovation and residual sequences combined with an adaptive fault annunciation scheme. The proposed approach provides the filter with the advantage of tracking sudden changes in the system non-measurable parameters accurately. Results showed successful detection of reaction wheel malfunctions without requiring a priori knowledge about system performance in the presence of abrupt, transient, intermittent, and incipient faults. Furthermore, the proposed approach resulted in superior filter performance with less mean squared errors for residuals compared to generic and adaptive unscented Kalman filters, and thus, it can be a promising method for the development of fail-safe satellites.

High-pressure phases of Weyl semimetals NbP, NbAs, TaP, and TaAs

Science.gov (United States)

Guo, ZhaoPeng; Lu, PengChao; Chen, Tong; Wu, JueFei; Sun, Jian; Xing, DingYu

2018-03-01

In this study, we used the crystal structure search method and first-principles calculations to systematically explore the highpressure phase diagrams of the TaAs family (NbP, NbAs, TaP, and TaAs). Our calculation results show that NbAs and TaAs have similar phase diagrams, the same structural phase transition sequence I41 md→ P6¯ m2→ P21/ c→ Pm3¯ m, and slightly different transition pressures. The phase transition sequence of NbP and TaP differs somewhat from that of NbAs and TaAs, in which new structures emerge, such as the Cmcm structure in NbP and the Pmmn structure in TaP. Interestingly, we found that in the electronic structure of the high-pressure phase P6¯ m2-NbAs, there are coexistingWeyl points and triple degenerate points, similar to those found in high-pressure P6¯ m2-TaAs.

Electron radiation defects in TaCsub(1-x) and TiCsub(0.97)

International Nuclear Information System (INIS)

Morillo, J.; Novion, C.H. de; Dural, J.

1981-08-01

The electrical resistivity changes of TaCsub(0.99) and TaCsub(0.80) have been measured at 21 K during irradiation with electrons of incident energies ranging from 2.5 to 0.25 MeV: a non-zero production rate is observed, even at the lowest energies. The recovery of defects was followed up to 400 K for TaCsub(0.99) and TiCsub(0.97) irradiated with 2.25 MeV electrons and up to 160 K for TaCsub(0.80) irradiated with 0.75 MeV electrons. The results are compared to fast neutron radiation damage data. For TiCsub(0.97) and TaCsub(0.99), the contributions of the different defects to the production rates and recovery spectra are tentatively separated, and a rough estimate of Frenkel pair resistivities is given

Oxidative addition of diphenyl disulfide across a Ta=Ta bond. Preparation and characterization of [TaCl3(Me2S)]2(μ-SPh)2

International Nuclear Information System (INIS)

Campbell, G.C.; Canich, J.A.M; Cotton, F.A.; Duraj, S.A.; Haw, J.F.

1986-01-01

The tantalum complex (SMe 2 )Cl 2 Ta(μ-Cl) 2 (μ-SMe 2 )TaCl 2 (SMe 2 ), possessing a sigma 2 π 2 Ta=Ta double bond, reacts readily with PhSSPh to give (SMe 2 )Cl 3 Ta(μ-SPh) 2 TaCl 2 (SMe 2 ). In this reaction, the starting material loses the bridging SMe 2 ligand and two chloride bridges are broken while only two new SPh bridges are formed in the final product. This oxidative-addition reaction of the S-S single bond to the Ta=Ta double bond converts the face-sharing bioctahedron structure of the starting compound to an edge-sharing bioctahedron structure in the final dimer, with concomitant change of the oxidation state of tantalum from III to IV. The product is the first example of a d 1 -d 1 ditantalum thiolate-bridged dimer. Important structural data for (SMe 2 )Cl 3 Ta(μ-SPh) 2 TaCl 3 (SMe 2 ), which has an inversion center, are determined. The new compound crystallizes in the monoclinic space group C2/c with a = 17.934 (5) A, b = 12.445 (4) A, c = 11.705 (4) A, β = 92.50 (3) 0 , V = 2610 (2) A 3 , and Z = 4. Solid-state 13 C NMR spectroscopy with cross polarization and magic-angle spinning (CP/MAS) at 28 and -103 0 C provides evidence that this compound is diamagnetic. 12 references, 3 figures, 4 tables

Web TA Production (WebTA)

Data.gov (United States)

US Agency for International Development — WebTA is a web-based time and attendance system that supports USAID payroll administration functions, and is designed to capture hours worked, leave used and...

Density of salt melts containing KF, KCl, K2TaF7 and Ta2O5

International Nuclear Information System (INIS)

Agulyanskij, A.I.; Stangrit, P.T.; Konstantinov, V.I.

1978-01-01

The results of density measurements by hydrostatic weighing are given for molten K 2 TaF 7 - KF, K 2 TaF 7 -KCL, K 2 TaF 7 - KF - KCl and K 2 TaF 7 - KF - KCl - Ta 2 O 5 mixtures depending on their temperature and composition. The density of the last two systems was measured at compositions close to those of commercial electrolytes. The obtained specific volume - composition dependencies show that no interaction is taking place in the mixtures studied. It is, therefore, believed that, in the K 2 TaF 7 - KF melt, tantalum is mainly present as a complex TaF 7 2- ion, and, in the K 2 TaF 7 - KCl mlt, a certain amount of TaF 6 - ions may be formed along with TaF 7 2-

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.

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

Fission-fragment mass distribution and estimation of the cluster emission probability in the γ + 232Th and 181Ta reactions

International Nuclear Information System (INIS)

Karamyan, S.A.; Adam, J.; Belov, A.G.; Chaloun, P.; Norseev, Yu.V.; Stegajlov, V.I.

1997-01-01

Fission-fragment mass distribution has been measured by the cumulative yields of radionuclides detected in the 232 Th(γ,f)-reaction at the Bremsstrahlung endpoint energies of 12 and 24 MeV. The yield upper limits have been estimated for the light nuclei 24 Na, 28 Mg, 38 S etc. at the Th and Ta targets exposure to the 24 MeV Bremsstrahlung. The results are discussed in terms of the multimodal fission phenomena and cluster emission >from a deformed fissioning system or from a compound nucleus

Inconing solar radiation estimates at terrestrial surface using meteorological satellite

International Nuclear Information System (INIS)

Arai, N.; Almeida, F.C. de.

1982-11-01

By using the digital images of the visible channel of the GOES-5 meteorological satellite, and a simple radiative transfer model of the earth's atmosphere, the incoming solar radiation reaching ground is estimated. A model incorporating the effects of Rayleigh scattering and water vapor absorption, the latter parameterized using the surface dew point temperature value, is used. Comparisons with pyranometer observations, and parameterization versus radiosonde water vapor absorption calculation are presented. (Author) [pt

Estimations of natural variability between satellite measurements of trace species concentrations

Science.gov (United States)

Sheese, P.; Walker, K. A.; Boone, C. D.; Degenstein, D. A.; Kolonjari, F.; Plummer, D. A.; von Clarmann, T.

2017-12-01

In order to validate satellite measurements of atmospheric states, it is necessary to understand the range of random and systematic errors inherent in the measurements. On occasions where the measurements do not agree within those errors, a common "go-to" explanation is that the unexplained difference can be chalked up to "natural variability". However, the expected natural variability is often left ambiguous and rarely quantified. This study will look to quantify the expected natural variability of both O3 and NO2 between two satellite instruments: ACE-FTS (Atmospheric Chemistry Experiment - Fourier Transform Spectrometer) and OSIRIS (Optical Spectrograph and Infrared Imaging System). By sampling the CMAM30 (30-year specified dynamics simulation of the Canadian Middle Atmosphere Model) climate chemistry model throughout the upper troposphere and stratosphere at times and geolocations of coincident ACE-FTS and OSIRIS measurements at varying coincidence criteria, height-dependent expected values of O3 and NO2 variability will be estimated and reported on. The results could also be used to better optimize the coincidence criteria used in satellite measurement validation studies.

78 FR 28627 - TA-W-80,340; TA-W-80,340A; TA-W-80,340B

Science.gov (United States)

2013-05-15

...] Bush Industries, Inc., Mason Drive Facility, Including On-Site Leased Workers From Morris Security...., Mason Drive Facility, Jamestown, New York (TA-W-80,340) and Bush Industries, Inc., Allen Street Facility... applicable to TA-W-80,340 is hereby issued as follows: All workers of Bush Industries, Inc., Mason Drive...

Estimating crop net primary production using inventory data and MODIS-derived parameters

Energy Technology Data Exchange (ETDEWEB)

Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.

2013-06-03

National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

Science.gov (United States)

Winesett, Thomas; Magi, Brian; Cecil, Daniel

2015-01-01

present in the cloud and electric charge separation occurs. These ice particles efficiently scatter the microwave radiation at the 85 and 37 GHz frequencies, thus leading to large brightness temperature depressions. Lightning flash rate is related to the total amount of ice passing through the convective updraft regions of thunderstorms. Confirmation of this relationship using TRMM LIS and TMI data, however, remains constrained to TRMM observational limits of the tropics and subtropics. Satellites from the Defense Meteorology Satellite Program (DMSP) have global coverage and are equipped with passive microwave imagers that, like TMI, observe brightness temperatures at 85 and 37 GHz. Unlike the TRMM satellite, however, DMSP satellites do not have a lightning sensor, and the DMSP microwave data has never been used to derive global lightning. In this presentation, a relationship between DMSP Special Sensor Microwave Imager (SSMI) data and ground-based cloud-to-ground (CG) lightning data from NLDN is investigated to derive a spatially complete time history of CG lightning for the USA study area. This relationship is analogous to the established using TRMM LIS and TMI data. NLDN has the most spatially and temporally complete CG lightning data for the USA, and therefore provides the best opportunity to find geospatially coincident observations with SSMI sensors. The strongest thunderstorms generally have minimum 85 GHz Polarized Corrected brightness Temperatures (PCT) less than 150 K. Archived radar data was used to resolve the spatial extent of the individual storms. NLDN data for that storm spatial extent defined by radar data was used to calculate the CG flash rate for the storm. Similar to results using TRMM sensors, a linear model best explained the relationship between storm-specific CG flash rates and minimum 85 GHz PCT. However, the results in this study apply only to CG lightning. To extend the results to weaker storms, the probability of CG lightning (instead of the

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...