WorldWideScience

Sample records for satellite derived rainfall

  1. Initialization with diabatic heating from satellite-derived rainfall

    Science.gov (United States)

    Ma, Leiming; Chan, Johnny; Davidson, Noel E.; Turk, Joe

    2007-07-01

    In this paper, a new technique is proposed to improve initialization of a tropical cyclone (TC) prediction model using diabatic heating profiles estimated from a combination of both infrared satellite cloud imagery and satellite-derived rainfall. The method is termed Rainfall-defined Diabatic Heating, RDH. To examine the RDH performance, initialization and forecast experiments are made with the Australia Bureau of Meteorology Research Centre (BMRC) Tropical Cyclone — Limited Area Prediction System (TC-LAPS) for the case of TC Chris, which made landfall on the west coast of Australia during 3-6 Feb 2002. RDH is performed in three steps: 1) based on previous observational and numerical studies, reference diabatic heating profiles are firstly classified into three kinds: convective, stratiform or composite types; 2) NRL (Naval Research Laboratory) 3-hourly gridded satellite rainfall estimates are categorized as one of the three types according to the rain rate; 3) within a nudging phase of 24 h, the model-generated heating at each grid point during the integration is replaced by the reference heating profiles on the basis of the satellite-observed cloud top temperature and rainfall type. The results of sensitivity experiments show that RDH has a positive impact on the model initialization of TC Chris. The heating profiles generated by the model within the observed rainfall area show agreement with that of reference heating. That is, maximum heating is located in the lower troposphere for convective rainfall, and in the upper troposphere for stratiform rainfall. In response to the replaced heating and its impact on the TC structure, the model initial condition and forecasts of the track and intensity are improved.

  2. Adequacy of satellite derived rainfall data for stream flow modeling

    Science.gov (United States)

    Artan, G.; Gadain, Hussein; Smith, Jody L.; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.

    2007-01-01

    Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

  3. Improvements of Satellite-Derived Cyclonic Rainfall over the North Atlantic.

    Science.gov (United States)

    Klepp, Christian-Philipp; Bakan, Stephan; Graßl, Hartmut

    2003-02-01

    Case studies of rainfall, derived from Special Sensor Microwave Imager (SSM/I) satellite data during the passage of individual cyclones over the North Atlantic, are presented to enhance the knowledge of rainfall processes associated with frontal systems. A multisatellite method is applied for complete coverage of the North Atlantic twice a day. Different SSM/I precipitation algorithms have been tested for individual cyclones and compared to the Global Precipitation Climatology Project (GPCP) datasets. An independent rainfall pattern and intensity validation method is presented using voluntary observing ship (VOS) datasets and Advanced Very High Resolution Radiometer (AVHRR) images.Intense cyclones occur frequently in the wintertime period, with cold fronts propagating far south over the North Atlantic. Following upstream, large cloud clusters are frequently embedded in the cellular structured cold air of the backside regions, which produce heavy convective rainfall events, especially in the region off Newfoundland around 50°N. These storms can be easily identified on AVHRR images. It transpired that only the SSM/I rainfall algorithm of Bauer and Schlüssel is sensitive enough to detect the rainfall patterns and intensities observed by VOS for those cyclone types over the North Atlantic. In contrast, the GPCP products do not recognize this backside rainfall, whereas the frontal rainfall conditions are well represented in all tested datasets. This is suggested from the results of an intensive intercomparison study with ship reports from the time period of the Fronts and Atlantic Storm Track Experiment (FASTEX) field campaign. For this purpose, a new technique has been developed to transfer ship report codes into rain-rate estimates. From the analysis of a complete life cycle of a cyclone, it follows that these mesoscale backside rainfall events contribute up to 25% to the total amount of rainfall in North Atlantic cyclones.

  4. Influence of satellite-derived rainfall patterns on plague occurrence in northeast Tanzania.

    Science.gov (United States)

    Debien, Annekatrien; Neerinckx, Simon; Kimaro, Didas; Gulinck, Hubert

    2010-12-13

    In the tropics, rainfall data are seldom accurately recorded, and are often discontinuous in time. In the scope of plague-research in northeast Tanzania, we adapted previous research to reconstruct rainfall patterns at a suitable resolution (1 km), based on time series of NDVI: more accurate satellite imagery was used, in the form of MODIS NDVI, and rainfall data were collected from the TRMM sensors instead of in situ data. First, we established a significant relationship between monthly rainfall and monthly composited MODIS NDVI. The established linear relationship was then used to reconstruct historic precipitation patterns over a mountainous area in northeastern Tanzania. We validated the resulting precipitation estimates with in situ rainfall time series of three meteorological stations located in the study area. Taking the region's topography into account, a correlation coefficient of 0.66 was obtained for two of the three meteorological stations. Our results suggest that the adapted strategy can be applied fruitfully to estimate rainfall variability and seasonality, despite the underestimation of overall rainfall rates. Based on this model, rainfall in previous years (1986) is modelled to obtain a dataset with which we can compare plague occurrence in the area. A positive correlation of 82% is obtained between high rainfall rates and plague incidence with a two month lag between rainfall and plague cases. We conclude that the obtained results are satisfactory in support of the human plague research in which this study is embedded, and that this approach can be applied in other studies with similar goals.

  5. Improvements of Satellite Derived Cyclonic Rainfall Over The North Atlantic and Implications Upon The Air-sea Interaction

    Science.gov (United States)

    Klepp, C.; Bakan, S.; Grassl, H.

    Case studies of rainfall, derived from Special Sensor Microwave/Imager (SSM/I) satellite data, during the passage of individual cyclones over the North Atlantic are presented to enhance the knowledge of rainfall processes asso ciated with frontal sys- tems. The Multi-Satellite-Technique (MST) is described to receive a complete cov- erage of the North Atlantic twice a day. Different SSM/I precipitation algorithms (Bauer and Schlüssel, Ferraro, Wentz) have been tested for individual cyclones and were compared to the Global Precipitation Climatology Project (GPCP) data sets and NWP model results (ECMWF, REMO). An independent rainfall pattern and -intensity vali dation method is presented using voluntary observing ship (VOS) data sets and AVHRR images. Intense storms occur very often in the wintertime period with cold fronts propagating far south over the North Atlantic. Large frontal conditions are mostly well represented in all tested data sets. Following upstream numerous showers are usually embedded in the cellular structures of the cold air on the backside of post frontal subsidences. Cold air clusters frequently occur in these backside regions which produce heavy convective rainfall events. Espe cially in the region off Newfoundland at 50o North, where very cold air within arctic cold air outbreaks is advected over the warm waters of the Gulfstream current, these heavily raining clusters often rapidly form into mesoscale storms. These small but intense cyclones up to 1500km in diame- ter are characterized by very heavy precipitation over the entire region and may occur every three days in wintertime. The storms can be easily identified on AVHRR im- ages. Only the SSM/I rainfall algorithm of Bauer and Schlüssel in combination with the presented MST is sensitive enough to detect the correct patterns and intensities of rainfall for those cyclone types over the North Atlantic, whereas the GPCP products fail in recognizing any rainfall at all. A SLP study figures

  6. Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model

    Science.gov (United States)

    Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.

    1990-01-01

    Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.

  7. Investigating the error budget of tropical rainfall accumulations derived from combined passive microwave and infrared satellite measurements

    Science.gov (United States)

    Roca, R.; Chambon, P.; jobard, I.; Viltard, N.

    2012-04-01

    Measuring rainfall requires a high density of observations, which, over the whole tropical elt, can only be provided from space. For several decades, the availability of satellite observations has greatly increased; thanks to newly implemented missions like the Megha-Tropiques mission and the forthcoming GPM constellation, measurements from space become available from a set of observing systems. In this work, we focus on rainfall error estimations at the 1 °/1-day accumulated scale, key scale of meteorological and hydrological studies. A novel methodology for quantitative precipitation estimation is introduced; its name is TAPEER (Tropical Amount of Precipitation with an Estimate of ERrors) and it aims to provide 1 °/1-day rain accumulations and associated errors over the whole Tropical belt. This approach is based on a combination of infrared imagery from a fleet of geostationary satellites and passive microwave derived rain rates from a constellation of low earth orbiting satellites. A three-stage disaggregation of error into sampling, algorithmic and calibration errors is performed; the magnitudes of the three terms are then estimated separately. A dedicated error model is used to evaluate sampling errors and a forward error propagation approach is used for an estimation of algorithmic and calibration errors. One of the main findings in this study is the large contribution of the sampling errors and the algorithmic errors of BRAIN on medium rain rates (2 mm h-1 to 10 mm h-1) in the total error budget.

  8. Improvements of Satellite-derived High Impact Weather Rainfall over Global Oceans and Implications for NWP models

    Science.gov (United States)

    Klepp, C.; Bakan, S.; Graßl, H.

    2003-04-01

    High impact weather precipitation fields of cyclone case studies over global ocean precipitation centers are presented using the technology of the HOAPS-II (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite data) data base. All case studies are compared to the Global Precipitation Climatology Project (GPCP) data set and to ECMWF numerical weather prediction output. A detailed in situ rainfall validation is presented using voluntary observing ships (VOS). Results show that only the HOAPS data base recognizes the development of frequently occurring mesoscale cyclones and gales over the North Atlantic and North Pacific ocean as observed by VOS data. In case of landfall these events cause high socio-economic impact to the society. GPCP and the ECMWF model are frequently missing these mesoscale storms. For example, the gale Lothar known as the `Christmas Storm', could have been nowcasted using the HOAPS data base. HOAPS probably allows to give high impact weather warning in the near future on a near real time basis.

  9. Satellite-rainfall estimation for identification of rainfall thresholds used for landslide/debris flow prediction

    Science.gov (United States)

    Maggioni, Viviana; Nikolopoulos, Efthymios I.; Marra, Francesco; Destro, Elisa; Borga, Marco

    2016-04-01

    satellite precipitation uncertainty is carried out using a stochastic satellite rainfall error model. Satellite precipitation ensembles derived from the error model are used to produce ensembles of rainfall thresholds. The use of rainfall threshold ensembles for probabilistic prediction of landsdlide/debris flow occurrence is evaluated.

  10. Sampling errors in rainfall estimates by multiple satellites

    Science.gov (United States)

    North, Gerald R.; Shen, Samuel S. P.; Upson, Robert

    1993-01-01

    This paper examines the sampling characteristics of combining data collected by several low-orbiting satellites attempting to estimate the space-time average of rain rates. The several satellites can have different orbital and swath-width parameters. The satellite overpasses are allowed to make partial coverage snapshots of the grid box with each overpass. Such partial visits are considered in an approximate way, letting each intersection area fraction of the grid box by a particular satellite swath be a random variable with mean and variance parameters computed from exact orbit calculations. The derivation procedure is based upon the spectral minimum mean-square error formalism introduced by North and Nakamoto. By using a simple parametric form for the spacetime spectral density, simple formulas are derived for a large number of examples, including the combination of the Tropical Rainfall Measuring Mission with an operational sun-synchronous orbiter. The approximations and results are discussed and directions for future research are summarized.

  11. Satellite rainfall retrieval by logistic regression

    Science.gov (United States)

    Chiu, Long S.

    1986-01-01

    The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.

  12. Satellite-based estimation of rainfall erosivity for Africa

    NARCIS (Netherlands)

    Vrieling, A.; Sterk, G.; Jong, S.M. de

    2010-01-01

    Rainfall erosivity is a measure for the erosive force of rainfall. Rainfall kinetic energy determines the erosivity and is in turn greatly dependent on rainfall intensity. Attempts for its large-scale mapping are rare. Most are based on interpolation of erosivity values derived from rain gauge data.

  13. Satellite-derived estimates of forest leaf area index in southwest Western Australia are not tightly coupled to interannual variations in rainfall: implications for groundwater decline in a drying climate.

    Science.gov (United States)

    Smettem, Keith R J; Waring, Richard H; Callow, John N; Wilson, Melissa; Mu, Qiaozhen

    2013-08-01

    There is increasing concern that widespread forest decline could occur in regions of the world where droughts are predicted to increase in frequency and severity as a result of climate change. The average annual leaf area index (LAI) is an indicator of canopy cover and the difference between the annual maximum and minimum LAI is an indicator of annual leaf turnover. In this study, we analyzed satellite-derived estimates of monthly LAI across forested coastal catchments of southwest Western Australia over a 12 year period (2000-2011) that included the driest year on record for the last 60 years. We observed that over the 12 year study period, the spatial pattern of average annual satellite-derived LAI values was linearly related to mean annual rainfall. However, interannual changes to LAI in response to changes in annual rainfall were far less than expected from the long-term LAI-rainfall trend. This buffered response was investigated using a physiological growth model and attributed to availability of deep soil moisture and/or groundwater storage. The maintenance of high LAIs may be linked to a long-term decline in areal average underground water storage and diminished summer flows, with an emerging trend toward more ephemeral flow regimes.

  14. Monitoring Niger River Floods from satellite Rainfall Estimates : overall skill and rainfall uncertainty propagation.

    Science.gov (United States)

    Gosset, Marielle; Casse, Claire; Peugeot, christophe; boone, aaron; pedinotti, vanessa

    2015-04-01

    Global measurement of rainfall offers new opportunity for hydrological monitoring, especially for some of the largest Tropical river where the rain gauge network is sparse and radar is not available. Member of the GPM constellation, the new French-Indian satellite Mission Megha-Tropiques (MT) dedicated to the water and energy budget in the tropical atmosphere contributes to a better monitoring of rainfall in the inter-tropical zone. As part of this mission, research is developed on the use of satellite rainfall products for hydrological research or operational application such as flood monitoring. A key issue for such applications is how to account for rainfall products biases and uncertainties, and how to propagate them into the end user models ? Another important question is how to choose the best space-time resolution for the rainfall forcing, given that both model performances and rain-product uncertainties are resolution dependent. This paper analyses the potential of satellite rainfall products combined with hydrological modeling to monitor the Niger river floods in the city of Niamey, Niger. A dramatic increase of these floods has been observed in the last decades. The study focuses on the 125000 km2 area in the vicinity of Niamey, where local runoff is responsible for the most extreme floods recorded in recent years. Several rainfall products are tested as forcing to the SURFEX-TRIP hydrological simulations. Differences in terms of rainfall amount, number of rainy days, spatial extension of the rainfall events and frequency distribution of the rain rates are found among the products. Their impacts on the simulated outflow is analyzed. The simulations based on the Real time estimates produce an excess in the discharge. For flood prediction, the problem can be overcome by a prior adjustment of the products - as done here with probability matching - or by analysing the simulated discharge in terms of percentile or anomaly. All tested products exhibit some

  15. 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.

  16. 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.

  17. Estimating Monthly Rainfall from Geostationary Satellite Imagery Over Amazonia, Brazil.

    Science.gov (United States)

    Cutrim, Elen Maria Camara

    The infrared regression and the grid-history satellite rainfall estimating techniques were utilized to estimate monthly rainfall in Amazonia during one month of the rainy season (March, 1980) and one month of the dry season (September, 1980). The estimates were based on 3-hourly SMS-II infrared and visible images. Three sets of coefficients for the grid history method (Marajo, Arabian Sea, and GATE) were used to estimate rainfall. The estimated rain was compared with gauge measurements over the region. The infrared regression technique overestimated by a factor of 1.5. The Marajo coefficients yielded the best estimate, especially for eastern Amazonia. In the wet month Marajo coefficients overestimated rain by 10% and in the dry month by 70%. The Arabian Sea coefficients overestimated rain and the GATE coefficients slightly underestimated rain for Amazonia. Two maps of monthly rainfall over Amazonia were constructed for March and September, 1980, combining the ground station and satellite inferred rainfall of the grid history method using the Marajo coefficients. The satellite observations and ground data were mutually compatible and were contourable on these final, composite maps. Monthly rainfall was found to be much more inhomogeneous than previously reported. In March there was a belt of high precipitation trending southwest, with higher values and sharpest gradients in the coastal area. The upper Amazon was also an area of high precipitation, both north and south of the equator. In Roraima rainfall decreased drastically to the north. In September, the area of highest precipitation was the northwestern part of Amazonas State (northern hemisphere). Rainfall elsewhere was very localized and in northeastern Amazonia varied from 0 to 150 mm. Even though the grid history method presented better results for estimating rainfall over Amazonia, the IR model could be utilized more efficiently and economically on an operational basis if the calibration were properly made

  18. 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

  19. Satellite radiance data assimilation for rainfall prediction in Java Region

    Science.gov (United States)

    Sagita, Novvria; Hidayati, Rini; Hidayat, Rahmat; Gustari, Indra

    2017-01-01

    This study examined the influence of satellite radiance data assimilation for predicting two days of heavy rainfall in the Java region. The first case occurred from 22 to 23 on January 2015 while the second case occurred from 1 to 2 on February 2015. The analysis examined before and after data assimilation in the two cases study. The Global Forecast System (GFS) data were used as initial condition which was assimilated with several data such as surface observation data, radiance data from AMSUA sensor, radiance data from HIRS sensor, and radiance data from MHS sensor. Weather Research and Forecasting Data Assimilation (WRFDA) is a tool which is used in this study for assimilating process with Three Dimensional Variation (3D-Var) method. The Quantitative Precipitation Forecast (QPF) skill was used to evaluate influence data assimilation for rainfall prediction. The result of the study obtained different rainfall prediction with different data assimilation. In general, the surface observation data assimilation has lower QPF skill than the satellite radiance data assimilation. Even thought radiance data assimilation has slightly contribution on rainfall prediction, but it gave better accuracy on rainfall prediction for two heavy rainfall cases.

  20. A satellite rainfall retrieval technique over northern Algeria based on the probability of rainfall intensities classification from MSG-SEVIRI

    Science.gov (United States)

    Lazri, Mourad; Ameur, Soltane

    2016-09-01

    In this paper, an algorithm based on the probability of rainfall intensities classification for rainfall estimation from Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) has been developed. The classification scheme uses various spectral parameters of SEVIRI that provide information about cloud top temperature and optical and microphysical cloud properties. The presented method is developed and trained for the north of Algeria. The calibration of the method is carried out using as a reference rain classification fields derived from radar for rainy season from November 2006 to March 2007. Rainfall rates are assigned to rain areas previously identified and classified according to the precipitation formation processes. The comparisons between satellite-derived precipitation estimates and validation data show that the developed scheme performs reasonably well. Indeed, the correlation coefficient presents a significant level (r:0.87). The values of POD, POFD and FAR are 80%, 13% and 25%, respectively. Also, for a rainfall estimation of about 614 mm, the RMSD, Bias, MAD and PD indicate 102.06(mm), 2.18(mm), 68.07(mm) and 12.58, respectively.

  1. U.S. rainfall satellite missions in flux

    Science.gov (United States)

    Zielinski, Sarah

    NASA's Tropical Rainfall Measuring Mission (TRMM) received a reprieve in September when the agency decided to continue the mission until at least fiscal year 2009 and possibly until 2012. Earlier agency plans had called for discontinuing TRMM this year while the satellite still had enough fuel for a controlled re-entry.Despite the TRMM reprieve, however, the U.S. National Oceanic and Atmospheric Administration (NOAA) is already preparing for TRMM's replacement, the Global Precipitation Measurement (GPM) mission.

  2. Application of seasonal rainfall forecasts and satellite rainfall observations to crop yield forecasting for Africa

    Science.gov (United States)

    Greatrex, H. L.; Grimes, D. I. F.; Wheeler, T. R.

    2009-04-01

    Rain-fed agriculture is of utmost importance in sub-Saharan Africa; the FAO estimates that over 90% of food consumed in the region is grown in rain-fed farming systems. As the climate in sub-Saharan Africa has a high interannual variability, this dependence on rainfall can leave communities extremely vulnerable to food shortages, especially when coupled with a lack of crop management options. The ability to make a regional forecast of crop yield on a timescale of months would be of enormous benefit; it would enable both governmental and non-governmental organisations to be alerted in advance to crop failure and could facilitate national and regional economic planning. Such a system would also enable individual communities to make more informed crop management decisions, increasing their resilience to climate variability and change. It should be noted that the majority of crops in the region are rainfall limited, therefore the ability to create a seasonal crop forecast depends on the ability to forecast rainfall at a monthly or seasonal timescale and to temporally downscale this to a daily time-series of rainfall. The aim of this project is to develop a regional-scale seasonal forecast for sub-Saharan crops, utilising the General Large Area Model for annual crops (GLAM). GLAM would initially be driven using both dynamical and statistical seasonal rainfall forecasts to provide an initial estimate of crop yield. The system would then be continuously updated throughout the season by replacing the seasonal rainfall forecast with daily weather observations. TAMSAT satellite rainfall estimates are used rather than rain-gauge data due to the scarcity of ground based observations. An important feature of the system is the use of the geo-statistical method of sequential simulation to create an ensemble of daily weather inputs from both the statistical seasonal rainfall forecasts and the satellite rainfall estimates. This allows a range of possible yield outputs to be

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

    Science.gov (United States)

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

    2009-04-01

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

  4. Rainfall estimation for real time flood monitoring using geostationary meteorological satellite data

    Science.gov (United States)

    Veerakachen, Watcharee; Raksapatcharawong, Mongkol

    2015-09-01

    Rainfall estimation by geostationary meteorological satellite data provides good spatial and temporal resolutions. This is advantageous for real time flood monitoring and warning systems. However, a rainfall estimation algorithm developed in one region needs to be adjusted for another climatic region. This work proposes computationally-efficient rainfall estimation algorithms based on an Infrared Threshold Rainfall (ITR) method calibrated with regional ground truth. Hourly rain gauge data collected from 70 stations around the Chao-Phraya river basin were used for calibration and validation of the algorithms. The algorithm inputs were derived from FY-2E satellite observations consisting of infrared and water vapor imagery. The results were compared with the Global Satellite Mapping of Precipitation (GSMaP) near real time product (GSMaP_NRT) using the probability of detection (POD), root mean square error (RMSE) and linear correlation coefficient (CC) as performance indices. Comparison with the GSMaP_NRT product for real time monitoring purpose shows that hourly rain estimates from the proposed algorithm with the error adjustment technique (ITR_EA) offers higher POD and approximately the same RMSE and CC with less data latency.

  5. An Experimental Global Monitoring System for Rainfall-triggered Landslides using Satellite Remote Sensing Information

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Huffman, George J.

    2006-01-01

    Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of extensive ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing an experimental real-time monitoring system to detect rainfall-triggered landslides is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.aov). First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a GIs weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide risks at areas with high susceptibility. A major outcome of this work is the availability of a first-time global assessment of landslide risk, which is only possible because of the utilization of global satellite remote sensing products. This experimental system can be updated continuously due to the availability of new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and risk mitigation activities across the world.

  6. Technical Report Series on Global Modeling and Data Assimilation. Volume 12; Comparison of Satellite Global Rainfall Algorithms

    Science.gov (United States)

    Suarez, Max J. (Editor); Chang, Alfred T. C.; Chiu, Long S.

    1997-01-01

    Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates.

  7. How Good Are Satellite Rainfall Products For Hydrologic Simulations Of A Small Watershed?

    Science.gov (United States)

    Zeweldi, D. A.; Gebremichael, M.; Downer, C. W.

    2009-12-01

    Despite recent advances in satellite rainfall technology, the use of satellite rainfall products for hydrological applications is very limited. Assessing the potential and utility of satellite rainfall products is crucially important to advance their utility. In this work, first we quantify the errors in satellite rainfall products. We considered different satellite rainfall algorithms; namely, CMORPH (~8km, 30-minute), PERSIANN-CCS (4km, hourly) and HydroEstimator (10 km, hourly). Second, we assess how these errors propagate to hydrologic model streamflow simulations. We used the fully-distributed hydrologic model known as GSSHA. Our study region is the Goodwin Creek experimental watershed (21 sq. km) in Mississippi, USA. Our results provide information on how good different satellite rainfall products are for hydrologic simulations of a small watershed.

  8. Assessment of satellite rainfall products over the Andean plateau

    Science.gov (United States)

    Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

    2016-01-01

    Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a

  9. Evaluation of satellite rainfall products through hydrologic simulation in a fully distributed hydrologic model

    Science.gov (United States)

    Bitew, Menberu M.; Gebremichael, Mekonnen

    2011-06-01

    The goal of this study is to evaluate the accuracy of four global high-resolution satellite rainfall products (CMORPH, TMPA 3B42RT, TMPA 3B42, and PERSIANN) through the hydrologic simulation of a 1656 km2 mountainous watershed in the fully distributed MIKE SHE hydrologic model. This study shows that there are significant biases in the satellite rainfall estimates and large variations in rainfall amounts, leading to large variations in hydrologic simulations. The rainfall algorithms that use primarily microwave data (CMORPH and TMPA 3B42RT) show consistent and better performance in streamflow simulation (bias in the order of -53% to -3%, Nash-Sutcliffe efficiency (NSE) from 0.34 to 0.65); the rainfall algorithm that uses primarily infrared data (PERSIANN) shows lower performance (bias from -82% to -3%, Nash-Sutcliffe efficiency from -0.39 to 0.43); and the rainfall algorithm that merges the satellite data with rain gage data (TMPA 3B42) shows inconsistencies and the lowest performance (bias from -86% to 0.43%, Nash-Sutcliffe efficiency from -0.50 to 0.27). A dilemma between calibrating the hydrologic model with rain gage data and calibrating it with the corresponding satellite rainfall data is presented. Calibrating the model with corresponding satellite rainfall data increases the performance of satellite streamflow simulation compared to the model calibrated with rain gage data, but decreases the performance of satellite evapotranspiration simulation.

  10. Evaluation of short-period rainfall estimates from Kalpana-1 satellite using MET software

    Indian Academy of Sciences (India)

    Soma Sen Roy; Subhendu Brata Saha; Hashmi Fatima; S K Roy Bhowmik; P K Kundu

    2012-10-01

    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 evaluates the 3-hourly precipitation estimates by this technique as well as the rainfall estimates by the GPI technique using data of the Kalpana-1 satellite, over the Indian region for the south-west monsoon season of 2010 to understand their relative strengths and weaknesses in estimating short period rainfall. The gridded 3 hourly accumulated TRMM satellite (3B42 V6 product or TMPA product) and surface raingauge data for stations over the Indian region for the same period is used as the standard measure of rainfall estimates. The Method for Object-based Diagnostic Evaluation (MODE) utility of the METv3.0 software, has been used for the evaluation purpose. The results show that the new IMSRA technique is closer to the TMPA rainfall estimate, in terms of areal spread, geometric shape and location of rainfall areas, as compared to the GPI technique. The overlap of matching rainfall areas with respect to TMPA rainfall patches is also higher for the IMSRA estimates as compared to the GPI values. However, both satellite rainfall estimates are observed to be generally higher compared to the TMPA measurements. However, the values for the highest 10% of the rainfall rates in any rainfall patch, is generally higher for rainfall measured by the IMSRA technique, as compared to the estimates by the GPI technique. This may partly be due to the capping maximum limit of 3 mm/hr for rainfall measured by the GPI technique limits the total 3-hour accumulation to 9 mm even during heavy rainfall episodes. This is not so with IMSRA technique, which has no such limiting value. However, this general overestimation of the rainfall amount, measured by both techniques

  11. Rainfall measurements from cellular networks microwave links : an alternative ground reference for satellite validation and hydrology in Africa .

    Science.gov (United States)

    Gosset, Marielle; cazenave, frederic; Zougmore, françois; Doumounia, Ali; kacou, Modeste

    2015-04-01

    In many part of the Tropics the ground based gauge networks are sparse, often degrading and accessing this data for monitoring rainfall or for validating satellite products is sometime difficult. Here, an alternative rainfall measuring technique is proposed and tested in West Africa. It is based on using commercial microwave links from cellular telephone networks to detect and quantify rainfall. Rainfall monitoring based on commercial terrestrial microwave links has been tested for the first time in Burkina Faso, in Sahel. The rainfall regime is characterized by intense rainfall intensities brought by mesoscale Convective systems (MCS), generated by deep organized convection. The region is subjected to drought as well as dramatic floods associated with the intense rainfall provided by a few MCSs. The hydrometeorological risk is increasing and need to be monitored. In collaboration with the national cellular phone operator, Telecel Faso, the attenuation on 29 km long microwave links operating at 7 GHz was monitored at 1s time rate for the monsoon season 2012. The time series of attenuation is transformed into rain rates and compared with rain gauge data. The method is successful in quantifying rainfall: 95% of the rainy days are detected. The correlation with the daily raingauge series is 0.8 and the season bias is 5%. The correlation at the 5 min time step within each event is also high. We will present the quantitative results, discuss the uncertainties and compare the time series and the 2D maps with those derived from a polarimetric radar. The results demonstrate the potential interest of exploiting national and regional wireless telecommunication networks to provide rainfall maps for various applications : urban hydrology, agro-hydrological risk monitoring, satellite validation and development of combined rainfall products. We will also present the outcome of the first international Rain Cell Africa workshop held in Ouagadougou early 2015.

  12. Evaluation of Satellite Rainfall Products over NASA's Iowa Flood Studies (IFloodS) Domain

    Science.gov (United States)

    ElSaadani, Mohamed; Quintero, Felipe; Krajewski, Witold F.; Goska, Radoslaw; Seo, Bongchul

    2014-05-01

    Iowa Flood Studies (IFloodS) is a NASA Global Precipitation Measurement (GPM) Mission to provide better understanding of the strengths and limitations of satellite products in the context of hydrologic applications. IFloodS took place in the central to north eastern part of Iowa in Midwestern United States during the months of April-June, 2013. Quantifying the physical characteristics, space/time variability and assessing satellite rainfall retrieval uncertainties at instantaneous to daily time scales are of the main objectives of IFloodS field experiment beside assessing hydrologic predictive skills as a function of space/time scales and discerning the relative roles of rainfall quantities in flood genesis. The errors of rainfall estimation of three satellite rainfall products (TRMM's TMPA 3B42 V7, CPC's CMORPH and CHRS at UCI's PERSIANN) have been characterized in space and time using NCEP Stage IV radar-rainfall product as a benchmark for comparison. The satellite rainfall products used in this study represent 3 hourly, quarter degree, rainfall accumulation. The benchmark rainfall accumulation has an hourly, four kilometers, resolutions in time and space respectively. We also investigate the adequacy of satellite rainfall products as inputs for hydrological modeling. To this end, these products were used as forcing for the Iowa Flood Center (IFC) hydrological model and produced discharge simulations in a high-resolution drainage network. The IFC hydrological model has been validated using radar rainfall product and thus, the hydrological outputs becomes the reference of comparison for the other rainfall products. We evaluated the hydrological performance of the rainfall products at different spatial scales, ranging from 2 to 14,000 square miles using stream discharge information from USGS gauges network. We discuss the adequacy of the rainfall products for flood forecasting at different spatial scales.

  13. A probabilistic approach for assessing landslide-triggering event rainfall in Papua New Guinea, using TRMM satellite precipitation estimates

    Science.gov (United States)

    Robbins, J. C.

    2016-10-01

    Large and numerous landslides can result in widespread impacts which are felt particularly strongly in the largely subsistence-orientated communities residing in the most landslide-prone areas of Papua New Guinea (PNG). Understanding the characteristics of rainfall preceding these landslide events is essential for the development of appropriate early warning systems and forecasting models. Relationships between rainfall and landslides are frequently complex and uncertainties tend to be amplified by inconsistent and incomplete landslide catalogues and sparse rainfall data availability. To address some of these uncertainties a modified Bayesian technique has been used, in conjunction with the multiple time frames method, to produce thresholds of landslide probability associated with rainfall events of specific magnitude and duration. Satellite-derived precipitation estimates have been used to derive representative rainfall accumulations and intensities over a range of different rainfall durations (5, 10, 15, 30, 45, 60, 75 and 90 days) for rainfall events which resulted in landslides and those which did not result in landslides. Of the two parameter combinations (accumulation-duration and intensity-duration) analysed, rainfall accumulation and duration provide the best scope for identifying probabilistic thresholds for use in landslide warning and forecasting in PNG. Analysis of historical events and rainfall characteristics indicates that high accumulation (>250 mm), shorter duration (75 days), high accumulation (>1200 mm) rainfall events are more likely to lead to moderate- to high-impact landslides. This analysis has produced the first proxy probability thresholds for landslides in PNG and their application within an early warning framework has been discussed.

  14. Evaluation of multi-satellite rainfall products over India during monsoon

    Science.gov (United States)

    Mitra, Ashis K.; Prakash, Satya; Pai, D. S.; Srivastava, A. K.

    2016-05-01

    Simulation and prediction of Indian monsoon rainfall at scales from days-to-season is a challenging task for numerical modelling community worldwide. Gridded estimates of daily rainfall data are required for both land and oceanic regions for model validation, process studies and in turn for model development. Due to recent developments in satellite meteorology, it has become possible to produce realistic near real-time gridded rainfall datasets at operational basis by combining satellite estimates with rain gauge values and other available in-situ observations. Microwave and space based radar based estimates of rainfall has revolutionised the preparation of rainfall datasets especially for tropics. However, a variety of multi-satellite products are available over Indian monsoon region from a variety of sources. Popular products like TRMM TMPA3B42 (RT and V7), GsMaP, CPC/RFE, GPCP and GPM are available to end users in various space/time scales for applications and model validation. In this study, we show the representation and skill of monsoon rainfall from a variety of multi-satellite products over the Indian region. The bias and skill of multi-satellite rainfall are evaluated against gauge based observations. It was found that the TRMM based TMPA was one of the best dataset for Indian monsoon region. Attempt is made to compare the latest GPM based data with other products. The GPM based rainfall product is seen to be superior compared to TRMM.

  15. The all-year rainfall region of South Africa: Satellite rainfall-estimate perspective

    CSIR Research Space (South Africa)

    Engelbrecht, CJ

    2012-09-01

    Full Text Available Climate predictability and variability studies over South Africa typically focus on the summer rainfall region and to a lesser extent on the winter rainfall region. The all-year rainfall region of South Africa, a narrow strip located along the Cape...

  16. 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

  17. A Multi-Scale Analysis of Namibian Rainfall: Comparing TRMM Satellite Data and Ground Observations

    Science.gov (United States)

    Lu, X.; Wang, L.; Pan, M.; Kaseke, K. F.

    2014-12-01

    Rainfall is critically important in dryland regions, as it is the major source of water for natural vegetation as well as agriculture and livestock production. However, the lack of ground observations has long been a major obstacle to the study of rainfall patterning in drylands. In this study, a continuous 6-year record of ground observations collected at Weltevrede Guest Farm Namibia was used to evaluate the Tropical Rainfall Measuring Mission (TRMM) 0.25-degree (~25 km) 3-hourly satellite rainfall estimates for the period of 2008-2013 for two locations. The agreement between ground and satellite rainfall data was generally good at annual scales but a large variation was observed at the hourly scale. A trend analysis was carried out using bias-corrected annual satellite data (1998-2013) to examine the long-term patterns in rainfall amount, intensity, frequency and seasonal variations. Our results suggest that satellite rainfall estimates offer reasonable performance at annual scale. The preliminary trend analyses showed significant changes in frequency, but not in intensity or total amount in one of the two locations during the rainy season (November - March), but not in the other, emphasizing the spatial variability of the dryland rainfall.

  18. 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

  19. Multi-satellite rainfall sampling error estimates – a comparative study

    Directory of Open Access Journals (Sweden)

    A. Loew

    2012-10-01

    Full Text Available This study focus is set on quantifying sampling related uncertainty in the satellite rainfall estimates. We conduct observing system simulation experiment to estimate sampling error for various constellations of Low-Earth orbiting and geostationary satellites. There are two types of microwave instruments currently available: cross track sounders and conical scanners. We evaluate the differences in sampling uncertainty for various satellite constellations that carry instruments of the common type as well as in combination with geostationary observations. A precise orbital model is used to simulate realistic satellite overpasses with orbital shifts taken into account. With this model we resampled rain gauge timeseries to simulate satellites rainfall estimates free of retrieval and calibration errors. We concentrate on two regions, Germany and Benin, areas with different precipitation regimes. Our results show that sampling uncertainty for all satellite constellations does not differ greatly depending on the area despite the differences in local precipitation patterns. Addition of 3 hourly geostationary observations provides equal performance improvement in Germany and Benin, reducing rainfall undersampling by 20–25% of the total rainfall amount. Authors do not find a significant difference in rainfall sampling between conical imager and cross-track sounders.

  20. Predicting global landslide spatiotemporal distribution: Integrating landslide susceptibility zoning techniques and real-time satellite rainfall estimates

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration thresholds and information related to land surface susceptibility. However, no system exists at either a national or a global scale to monitor or detect rainfall conditions that may trigger landslides due to the lack of sufficient ground-based observing network in many parts of the world. Recent advances in satellite remote sensing technology and increasing availability of high-resolution geospatial products around the globe have provided an unprecedented opportunity for such a study. In this paper, a framework for developing a preliminary real-time prediction system to identify where rainfall-triggered landslides will occur is proposed by combining two necessary components: surface landslide susceptibility and a real-time space-based rainfall analysis system (http://trmm.gsfc.nasa.govV First, a global landslide susceptibility map is derived from a combination of semi-static global surface characteristics (digital elevation topography, slope, soil types, soil texture, land cover classification, etc.) using a GIS weighted linear combination approach. Second, an adjusted empirical relationship between rainfall intensity-duration and landslide occurrence is used to assess landslide hazards at areas with high susceptibility. A major outcome of this work is the availability for the first time of a global assessment of landslide hazards, which is only possible because of the utilization of global satellite remote sensing products. This preliminary system can be updated continuously using the new satellite remote sensing products. This proposed system, if pursued through wide interdisciplinary efforts as recommended herein, bears the promise to grow many local landslide hazard analyses into a global decision-making support system for landslide disaster preparedness and mitigation activities across the world.

  1. Detailed Analysis of Indian Summer Monsoon Rainfall Processes with Modern/High-Quality Satellite Observations

    Science.gov (United States)

    Smith, Eric A.; Kuo, Kwo-Sen; Mehta, Amita V.; Yang, Song

    2007-01-01

    We examine, in detail, Indian Summer Monsoon rainfall processes using modernhigh quality satellite precipitation measurements. The focus here is on measurements derived from three NASA cloud and precipitation satellite missionslinstruments (TRMM/PR&TMI, AQUNAMSRE, and CLOUDSATICPR), and a fourth TRMM Project-generated multi-satellite precipitation measurement dataset (viz., TRMM standard algorithm 3b42) -- all from a period beginning in 1998 up to the present. It is emphasized that the 3b42 algorithm blends passive microwave (PMW) radiometer-based precipitation estimates from LEO satellites with infi-ared (IR) precipitation estimates from a world network of CEO satellites (representing -15% of the complete space-time coverage) All of these observations are first cross-calibrated to precipitation estimates taken from standard TRMM combined PR-TMI algorithm 2b31, and second adjusted at the large scale based on monthly-averaged rain-gage measurements. The blended approach takes advantage of direct estimates of precipitation from the PMW radiometerequipped LEO satellites -- but which suffer fi-om sampling limitations -- in combination with less accurate IR estimates from the optical-infrared imaging cameras on GEO satellites -- but which provide continuous diurnal sampling. The advantages of the current technologies are evident in the continuity and coverage properties inherent to the resultant precipitation datasets that have been an outgrowth of these stable measuring and retrieval technologies. There is a wealth of information contained in the current satellite measurements of precipitation regarding the salient precipitation properties of the Indian Summer Monsoon. Using different datasets obtained from the measuring systems noted above, we have analyzed the observations cast in the form of: (1) spatially distributed means and variances over the hierarchy of relevant time scales (hourly I diurnally, daily, monthly, seasonally I intra-seasonally, and inter

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

    Directory of Open Access Journals (Sweden)

    Greg Easson

    2007-12-01

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

  3. Applying satellite remote sensing technique in disastrous rainfall systems around Taiwan

    Science.gov (United States)

    Liu, Gin-Rong; Chen, Kwan-Ru; Kuo, Tsung-Hua; Liu, Chian-Yi; Lin, Tang-Huang; Chen, Liang-De

    2016-05-01

    Many people in Asia regions have been suffering from disastrous rainfalls year by year. The rainfall from typhoons or tropical cyclones (TCs) is one of their key water supply sources, but from another perspective such TCs may also bring forth unexpected heavy rainfall, thereby causing flash floods, mudslides or other disasters. So far we cannot stop or change a TC route or intensity via present techniques. Instead, however we could significantly mitigate the possible heavy casualties and economic losses if we can earlier know a TC's formation and can estimate its rainfall amount and distribution more accurate before its landfalling. In light of these problems, this short article presents methods to detect a TC's formation as earlier and to delineate its rainfall potential pattern more accurate in advance. For this first part, the satellite-retrieved air-sea parameters are obtained and used to estimate the thermal and dynamic energy fields and variation over open oceans to delineate the high-possibility typhoon occurring ocean areas and cloud clusters. For the second part, an improved tropical rainfall potential (TRaP) model is proposed with better assumptions then the original TRaP for TC rainfall band rotations, rainfall amount estimation, and topographic effect correction, to obtain more accurate TC rainfall distributions, especially for hilly and mountainous areas, such as Taiwan.

  4. Spatial distribution of the timing of rainfall extremes derived by remote sensing and raingauges data assimilation

    Science.gov (United States)

    Libertino, Andrea; Claps, Pierluigi; Sharma, Ashish; Lakshmi, Venkat

    2016-04-01

    Severe rainfall events are quite common in the coastal areas of the Mediterranean basin during autumn season, despite its generally mild climate. Very often meteorological conditions responsible for these kinds of events are quasi-stationary convective systems, characterized by very localized development, hard to detect with traditional rain gauge networks. In order to improve prediction and management capabilities, progress must be made in understanding the mechanism that govern the development of these kind of precipitation systems at the different scales. Rainfall product from the Tropical Rainfall Measuring Mission (TRMM) are commonly adopted in different branches of the environmental sciences due to the high spatio-temporal resolution and to the quasi-global nature of the data. Building upon the success of TRMM, NASA and JAXA deployed the GPM Core Observatory that, after just two years of activity, seems to allow for great improvement in the accuracy of rainfall products. We developed a methodology aimed at exploiting the timing information derived from high-resolution remote sensing products to analyze the characteristic of severe rainfall systems in the Mediterranean basin. The spatial analysis from satellite, combined with the historical information from the rain gauge network, allows us deepening the knowledge of the spatial extension of extreme rainfall phenomena. All those information, merged together in a hierarchical framework, lead to the definition of Intensity-Duration-Frequency curves "informed" on the nature of the events for each location of the domain, without the need to adopt classical interpolation techniques, unable to represent the complexity of the rainfall systems. The case study refers to a database of daily rainfall measurements extracted from the NOAA GHCN-Daily dataset, recorded during the 20th century by 700 rain gauges distributed in the Mediterranean basin. TRMM and GPM images are used to calibrate the event timing over the

  5. A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa

    Science.gov (United States)

    Maidment, Ross I.; Grimes, David; Black, Emily; Tarnavsky, Elena; Young, Matthew; Greatrex, Helen; Allan, Richard P.; Stein, Thorwald; Nkonde, Edson; Senkunda, Samuel; Alcántara, Edgar Misael Uribe

    2017-05-01

    Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets.

  6. Rainfall analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates: Evaluation of monsoon rainfall features

    Indian Academy of Sciences (India)

    S K Roy Bhowmik; Ananda K Das

    2007-06-01

    Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north–south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north–east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the grid resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.

  7. Urban-Induced Mechanisms for an Extreme Rainfall Event in Beijing China: A Satellite Perspective

    Directory of Open Access Journals (Sweden)

    Menglin S. Jin

    2015-03-01

    Full Text Available Using 1 km satellite remote sensing observations, this paper examines the clouds, aerosols, water vapor and surface skin temperature over Beijing to understand the possible urban system contributions to the extreme rainfall event on 21 July 2012 (i.e., 721 event. Remote sensing measurements, with the advantage of high spatial resolution and coverage, reveal three key urban-related mechanisms: (a the urban heat island effect (UHI resulted in strong surface convection and high level cloud cover over Beijing; (b urban aerosol amount peaked before the rainfall, which “seeded” the clouds and invigorated precipitation; and (c urban tall buildings provided additional lift for the air mass and provided heat at the underlying boundary to keep the rainfall system alive for a long duration precipitation (>10 hours. With the existing rainfall system moving from the northwest and abundant water vapor was transported from the southeast into Beijing, the urban canyon-lifting, aerosol, and UHI effects all enhanced this extreme rainfall event. This work proves that urban system is responsible, at least partly, for urban rainfall extremes and thus should be considered for urban extreme rainfall prediction in the future.

  8. Identification and Diagnosis of Rainfall Types over Southern West Africa Using Satellite and Rain Gauge Data

    Science.gov (United States)

    Maranan, Marlon; Fink, Andreas H.; Amekudzi, Leonard K.; Atiah, Winifred A.

    2017-04-01

    Rainfall over Southern West Africa (SWA) is mainly controlled by the West African Monsoon circulation. Not much is known, however, about the (thermo-)dynamic environmental conditions and storm dynamics of various regional rainfall systems that contribute to the total annual rainfall. This study exploits both satellite and rain gauge measurements to quantify the contribution and to examine the importance of different rainfall types in SWA. For the period of the Tropical Rainfall Measuring Mission (TRMM) 1998-2014, the rainfall types are identified by analyzing the 3-D reflectivity structure using scans of the TRMM Precipitation Radar (TRMM-PR). Since TRMM-PR scans only provide instantaneous snapshots, the rainfall events are then traced back and forward in time with observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) over the overlapping period of 2004-2014 to obtain information about their life cycle. The composition of the ensemble of the different rainfall types exhibits a substantial regional variability across SWA. Strong convection (Radar echo > 40 dBZ) generally makes a dominant contribution to the number of rainfall events and to the total rainfall amount. However, the influence of deeper (40 dBZ echo at altitudes > 10 km) and wider (Area of 40 dBZ echo > 1000 km2) systems on the total rainfall amount increases going farther northward into the continent. Additionally, the number of tracks of those systems features relative minima along the Ivorian and Ghanaian-Togolese coast, the latter reflecting the climatologically dry Dahomey Gap. In contrast, local warm rain from isolated shallow convection develops more often along the immediate coast line. Yet, their contribution to total rainfall remains negligible and is almost non-existent further north. Compared with high-resolution rain gauge data around Kumasi, Ghana, for the year 2016, it can be assumed that warm rain events show an even higher occurrence frequency. Likewise, their

  9. Systematic Evaluation of Satellite-Based Rainfall Products over the Brahmaputra Basin for Hydrological Applications

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    Sagar Ratna Bajracharya

    2015-01-01

    Full Text Available Estimation of the flow generated in the Brahmaputra river basin is important for establishing an effective flood prediction and warning services as well as for water resources assessment and management. But this is a data scarce region with few and unevenly distributed hydrometeorological stations. Five high-resolution satellite rainfall products (CPC RFE2.0, RFE2.0-Modified, CMORPH, GSMaP, and TRMM 3B42 were evaluated at different spatial and temporal resolutions (daily, dekadal, monthly, and seasonal with observed rain gauge data from 2004 to 2006 to determine their ability to fill the data gap and suitability for use in hydrological and water resources management applications. Grid-to-grid (G-G and catchment-to-catchment (C-C comparisons were performed using the verification methods developed by the International Precipitation Working Group (IPWG. Comparing different products, RFE2.0-Modified, TRMM 3B42, and CMORPH performed best; they all detected heavy, moderate, and low rainfall but still significantly underestimated magnitude of rainfall, particularly in orographically influenced areas. Overall, RFE2.0-Modified performed best showing a high correlation coefficient with observed data and low mean absolute error, root mean square error, and multiple bias and is reasonably good at detecting the occurrence of rainfall. TRMM 3B42 showed the second best performance. The study demonstrates that there is a potential use of satellite rainfall in a data scarce region.

  10. A space-time stochastic model of rainfall for satellite remote-sensing studies

    Science.gov (United States)

    Bell, Thomas L.

    1987-01-01

    A model of the spatial and temporal distribution of rainfall is described that produces random spatial rainfall patterns with these characteristics: (1) the model is defined on a grid with each grid point representing the average rain rate over the surrounding grid box, (2) rain occurs at any one grid point, on average, a specified percentage of the time and has a lognormal probability distribution, (3) spatial correlation of the rainfall can be arbitrarily prescribed, and (4) time stepping is carried out so that large-scale features persist longer than small-scale features. Rain is generated in the model from the portion of a correlated Gaussian random field that exceeds a threshold. The portion of the field above the threshold is rescaled to have a lognormal probability distribution. Sample output of the model designed to mimic radar observations of rainfall during the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE), is shown. The model is intended for use in evaluating sampling strategies for satellite remote-sensing of rainfall and for development of algorithms for converting radiant intensity received by an instrument from its field of view into rainfall amount.

  11. Incorporating Satellite Observations of `No Rain' in an Australian Daily Rainfall Analysis.

    Science.gov (United States)

    Ebert, Elizabeth E.; Weymouth, Gary T.

    1999-01-01

    Geostationary satellite observations can be used to distinguish potential rain-bearing clouds from nonraining areas, thereby providing surrogate observations of `no rain' over large areas. The advantages of including such observations are the provision of data in regions void of conventional rain gauges or radars, as well as the improved delineation of raining from nonraining areas in gridded rainfall analyses.This paper describes a threshold algorithm for delineating nonraining areas using the difference between the daily minimum infrared brightness temperature and the climatological minimum surface temperature. Using a fixed difference threshold of 13 K, the accuracy of `no rain' detection (defined as the percentage of no-rain diagnoses that was correct) was 98%. The average spatial coverage was 45%, capturing about half of the observed space-time frequency of no rain over Australia. By delineating cool, moderate, and warm threshold areas, the average spatial coverage was increased to 54% while maintaining the same level of accuracy.The satellite no-rain observations were sampled to a density consistent with the existing gauge network, then added to the real-time gauge observations and analyzed using the Bureau of Meteorology's operational three-pass Barnes objective rainfall analysis scheme. When verified against independent surface rainfall observations, the mean bias in the satellite-augmented analyses was roughly half of bias in the gauge-only analyses. The most noticeable impact of the additional satellite observations was a 66% reduction in the size of the data-void regions.

  12. Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products

    Directory of Open Access Journals (Sweden)

    Singaiah Chintalapudi

    2014-05-01

    Full Text Available In this study, seven precipitation products (rain gauges, NEXRAD MPE, PERSIANN 0.25 degree, PERSIANN CCS-3hr, PERSIANN CCS-1hr, TRMM 3B42V7, and CMORPH were used to force a physically-based distributed hydrologic model. The model was driven by these products to simulate the hydrologic response of a 1232 km2 watershed in the Guadalupe River basin, Texas. Storm events in 2007 were used to analyze the precipitation products. Comparison with rain gauge observations reveals that there were significant biases in the satellite rainfall products and large variations in the estimated amounts. The radar basin average precipitation compared very well with the rain gauge product while the gauge-adjusted TRMM 3B42V7 precipitation compared best with observed rainfall among all satellite precipitation products. The NEXRAD MPE simulated streamflows matched the observed ones the best yielding the highest Nash-Sutcliffe Efficiency correlation coefficient values for both the July and August 2007 events. Simulations driven by TRMM 3B42V7 matched the observed streamflow better than other satellite products for both events. The PERSIANN coarse resolution product yielded better runoff results than the higher resolution product. The study reveals that satellite rainfall products are viable alternatives when rain gauge or ground radar observations are sparse or non-existent.

  13. Constraining continuous rainfall simulations for derived design flood estimation

    Science.gov (United States)

    Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.

    2016-11-01

    Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.

  14. Using long-term daily satellite based rainfall data (1983-2015) to analyze spatio-temporal changes in the sahelian rainfall regime

    Science.gov (United States)

    Zhang, Wenmin; Brandt, Martin; Guichard, Francoise; Tian, Qingjiu; Fensholt, Rasmus

    2017-07-01

    The sahelian rainfall regime is characterized by a strong spatial as well as intra- and inter-annual variability. The satellite based African Rainfall Climatology Version 2 (ARC2) daily gridded rainfall estimates with a 0.1° × 0.1° spatial resolution provides the possibility for in-depth studies of seasonal changes over a 33-year period (1983-2015). Here we analyze rainfall regime variables that require daily observations: onset, cessation, and length of the wet season; seasonal rainfall amount; number of rainy days; intensity and frequency of rainfall events; number, length, and cumulative duration of dry spells. Rain gauge stations and MSWEP (Multi-Source Weighted-Ensemble Precipitation) data were used to evaluate the agreement of rainfall variables in both space and time, and trends were analyzed. Overall, ARC2 rainfall variables reliably show the spatio-temporal dynamics of seasonal rainfall over 33 years when compared to gauge and MSWEP data. However, a higher frequency of low rainfall events (spell characteristics). Most rainfall variables (both ARC2 and gauge data) show negative anomalies (except for onset of rainy season) from 1983 until the end of the 1990s, from which anomalies become mostly positive and inter-annual variability is higher. ARC2 data show a strong increase in seasonal rainfall, wet season length (caused by both earlier onset and a late end), number of rainy days, and high rainfall events (>20 mm day-1) for the western/central Sahel over the period of analysis, whereas the opposite trend characterizes the eastern part of the Sahel.

  15. Establishing a method of short-term rainfall forecasting based on GNSS-derived PWV and its application.

    Science.gov (United States)

    Yao, Yibin; Shan, Lulu; Zhao, Qingzhi

    2017-09-29

    Global Navigation Satellite System (GNSS) can effectively retrieve precipitable water vapor (PWV) with high precision and high-temporal resolution. GNSS-derived PWV can be used to reflect water vapor variation in the process of strong convection weather. By studying the relationship between time-varying PWV and rainfall, it can be found that PWV contents increase sharply before raining. Therefore, a short-term rainfall forecasting method is proposed based on GNSS-derived PWV. Then the method is validated using hourly GNSS-PWV data from Zhejiang Continuously Operating Reference Station (CORS) network of the period 1 September 2014 to 31 August 2015 and its corresponding hourly rainfall information. The results show that the forecasted correct rate can reach about 80%, while the false alarm rate is about 66%. Compared with results of the previous studies, the correct rate is improved by about 7%, and the false alarm rate is comparable. The method is also applied to other three actual rainfall events of different regions, different durations, and different types. The results show that the method has good applicability and high accuracy, which can be used for rainfall forecasting, and in the future study, it can be assimilated with traditional weather forecasting techniques to improve the forecasted accuracy.

  16. Japanese Global Precipitation Measurement (GPM) mission status and application of satellite-based global rainfall map

    Science.gov (United States)

    Kachi, Misako; Shimizu, Shuji; Kubota, Takuji; Yoshida, Naofumi; Oki, Riko; Kojima, Masahiro; Iguchi, Toshio; Nakamura, Kenji

    2010-05-01

    As accuracy of satellite precipitation estimates improves and observation frequency increases, application of those data to societal benefit areas, such as weather forecasts and flood predictions, is expected, in addition to research of precipitation climatology to analyze precipitation systems. There is, however, limitation on single satellite observation in coverage and frequency. Currently, the Global Precipitation Measurement (GPM) mission is scheduled under international collaboration to fulfill various user requirements that cannot be achieved by the single satellite, like the Tropical Rainfall Measurement Mission (TRMM). The GPM mission is an international mission to achieve high-accurate and high-frequent rainfall observation over a global area. GPM is composed of a TRMM-like non-sun-synchronous orbit satellite (GPM core satellite) and constellation of satellites carrying microwave radiometer instruments. The GPM core satellite carries the Dual-frequency Precipitation Radar (DPR), which is being developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT), and microwave radiometer provided by the National Aeronautics and Space Administration (NASA). Development of DPR instrument is in good progress for scheduled launch in 2013, and DPR Critical Design Review has completed in July - September 2009. Constellation satellites, which carry a microwave imager and/or sounder, are planned to be launched around 2013 by each partner agency for its own purpose, and will contribute to extending coverage and increasing frequency. JAXA's future mission, the Global Change Observation Mission (GCOM) - Water (GCOM-W) satellite will be one of constellation satellites. The first generation of GCOM-W satellite is scheduled to be launched in 2011, and it carries the Advanced Microwave Scanning Radiometer 2 (AMSR2), which is being developed based on the experience of the AMSR-E on EOS Aqua satellite

  17. Value of bias-corrected satellite rainfall products in SWAT simulations and comparison with other models in the Mara basin

    Science.gov (United States)

    Serrat-Capdevila, A.; Abitew, T. A.; Roy, T.; van Griensven, A.; Valdes, J. B.; Bauwens, W.

    2015-12-01

    Hydrometeorological monitoring networks are often limited for basins located in the developing world such as the transboundary Mara Basin. The advent of earth observing systems have brought satellite rainfall and evapotranspiration products, which can be used to force hydrological models in data scarce basins. The objective of this study is to develop improved hydrologic simulations using distributed satellite rainfall products (CMORPH and TMPA) with a bias-correction, and compare the performance with different input data and models. The bias correction approach for the satellite-products (CMORPH and TMPA) involves the use of a distributed reference dataset (CHIRPS) and historical ground gauge records. We have applied the bias-corrected satellite products to force the Soil and Water Assessment Tool (SWAT) model for the Mara Basin. Firstly, we calibrate the SWAT parameters related to ET simulation using ET from remote sensing. Then, the SWAT parameters that control surface processes are calibrated using the available limited flow. From the analysis, we noted that not only the bias-corrected satellite rainfall but also augmenting limited flow data with monthly remote sensing ET improves the model simulation skill and reduces the parameter uncertainty to some extent. We have planned to compare these results from a lumped model forced by the same input satellite rainfall. This will shed light on the potential of satellite rainfall and remote sensing ET along with in situ data for hydrological processes modeling and the inherent uncertainty in a data scarce basin.

  18. Sampling error study for rainfall estimate by satellite using a stochastic model

    Science.gov (United States)

    Shin, Kyung-Sup; North, Gerald R.

    1988-01-01

    In a parameter study of satellite orbits, sampling errors of area-time averaged rain rate due to temporal sampling by satellites were estimated. The sampling characteristics were studied by accounting for the varying visiting intervals and varying fractions of averaging area on each visit as a function of the latitude of the grid box for a range of satellite orbital parameters. The sampling errors were estimated by a simple model based on the first-order Markov process of the time series of area averaged rain rates. For a satellite of nominal Tropical Rainfall Measuring Mission (Thiele, 1987) carrying an ideal scanning microwave radiometer for precipitation measurements, it is found that sampling error would be about 8 to 12 pct of estimated monthly mean rates over a grid box of 5 X 5 degrees. It is suggested that an observation system based on a low inclination satellite combined with a sunsynchronous satellite simultaneously might be the best candidate for making precipitation measurements from space.

  19. Correcting Errors in Catchment-Scale Satellite Rainfall Accumulation Using Microwave Satellite Soil Moisture Products

    Science.gov (United States)

    Ryu, D.; Crow, W. T.

    2011-12-01

    Streamflow forecasting in the poorly gauged or ungauged catchments is very difficult mainly due to the absence of the input forcing data for forecasting models. This challenge poses a threat to human safety and industry in the areas where proper warning system is not provided. Currently, a number of studies are in progress to calibrate streamflow models without relying on ground observations as an effort to construct a streamflow forecasting systems in the ungauged catchments. Also, recent advances in satellite altimetry and innovative application of the optical has enabled mapping streamflow rate and flood extent in the remote areas. In addition, remotely sensed hydrological variables such as the real-time satellite precipitation data, microwave soil moisture retrievals, and surface thermal infrared observations have the great potential to be used as a direct input or signature information to run the forecasting models. In this work, we evaluate a real-time satellite precipitation product, TRMM 3B42RT, and correct errors of the product using the microwave satellite soil moisture products over 240 catchments in Australia. The error correction is made by analyzing the difference between output soil moisture of a simple model forced by the TRMM product and the satellite retrievals of soil moisture. The real-time satellite precipitation products before and after the error correction are compared with the daily gauge-interpolated precipitation data produced by the Australian Bureau of Meteorology. The error correction improves overall accuracy of the catchment-scale satellite precipitation, especially the root mean squared error (RMSE), correlation, and the false alarm ratio (FAR), however, only a marginal improvement is observed in the probability of detection (POD). It is shown that the efficiency of the error correction is affected by the surface vegetation density and the annual precipitation of the catchments.

  20. Satellite radiometric remote sensing of rainfall fields: multi-sensor retrieval techniques at geostationary scale

    Directory of Open Access Journals (Sweden)

    F. S. Marzano

    2005-01-01

    Full Text Available The Microwave Infrared Combined Rainfall Algorithm (MICRA consists in a statistical integration method using the satellite microwave-based rain-rate estimates, assumed to be accurate enough, to calibrate spaceborne infrared measurements on limited sub-regions and time windows. Rainfall retrieval is pursued at the space-time scale of typical geostationary observations, that is at a spatial resolution of few kilometers and a repetition period of few tens of minutes. The actual implementation is explained, although the basic concepts of MICRA are very general and the method is easy to be extended for considering innovative statistical techniques or measurements from additional space-borne platforms. In order to demonstrate the potentiality of MICRA, case studies over central Italy are also discussed. Finally, preliminary results of MICRA validation by ground based remote and in situ measurements are shown and a comparison with a Neural Network (NN based technique is briefly illustrated.

  1. Temporal and Spatial Assessment of Four Satellite Rainfall Estimates over French Guiana and North Brazil

    Directory of Open Access Journals (Sweden)

    Justine Ringard

    2015-12-01

    Full Text Available Satellite precipitation products are a means of estimating rainfall, particularly in areas that are sparsely equipped with rain gauges. The Guiana Shield is a region vulnerable to high water episodes. Flood risk is enhanced by the concentration of population living along the main rivers. A good understanding of the regional hydro-climatic regime, as well as an accurate estimation of precipitation is therefore of great importance. Unfortunately, there are very few rain gauges available in the region. The objective of the study is then to compare satellite rainfall estimation products in order to complement the information available in situ and to perform a regional analysis of four operational precipitation estimates, by partitioning the whole area under study into a homogeneous hydro-climatic region. In this study, four satellite products have been tested, TRMM TMPA (Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis V7 (Version 7 and RT (real time, CMORPH (Climate Prediction Center (CPC MORPHing technique and PERSIANN (Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network, for daily rain gauge data. Product performance is evaluated at daily and monthly scales based on various intensities and hydro-climatic regimes from 1 January 2001 to 30 December 2012 and using quantitative statistical criteria (coefficient correlation, bias, relative bias and root mean square error and quantitative error metrics (probability of detection for rainy days and for no-rain days and the false alarm ratio. Over the entire study period, all products underestimate precipitation. The results obtained in terms of the hydro-climate show that for areas with intense convective precipitation, TMPA V7 shows a better performance than other products, especially in the estimation of extreme precipitation events. In regions along the Amazon, the use of PERSIANN is better. Finally, in the driest areas, TMPA V7 and

  2. Rainfall interstation correlation functions derived for a class of generalized storm models

    NARCIS (Netherlands)

    Stol, P.T.

    1983-01-01

    The complete derivation and solution of the rainfall interstation correlation function is described. The report emphasizes the mathematical treatment and the way in which the analytical solution can be obtained by calculus

  3. Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

    Science.gov (United States)

    Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

    2016-04-01

    Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by

  4. Surface Emissivity Derived From Multispectral Satellite Data

    Science.gov (United States)

    Minnis, P.; Smith, W. L., Jr.; Young, D. F.

    1998-01-01

    Surface emissivity is critical for remote sensing of surface skin temperature and infrared cloud properties when the observed radiance is influenced by the surface radiation. It is also necessary to correctly compute the longwave flux from a surface at a given skin temperature. Surface emissivity is difficult to determine because skin temperature is an ill-defined parameter. The surface-emitted radiation may arise from a range of surface depths depending on many factors including soil moisture, vegetation, surface porosity, and heat capacity. Emissivity can be measured in the laboratory for pure surfaces. Transfer of laboratory measurements to actual Earth surfaces, however, is fraught with uncertainties because of their complex nature. This paper describes a new empirical approach for estimating surface skin temperature from a combination of brightness temperatures measured at different infrared wavelengths with satellite imagers. The method uses data from the new Geostationary Operational Environmental Satellite (GOES) imager to determine multispectral emissivities from the skin temperatures derived over the ARM Southern Great Plains domain.

  5. A multi-scale analysis of Namibian rainfall over the recent decade – comparing TMPA satellite estimates and ground observations

    Directory of Open Access Journals (Sweden)

    Xuefei Lu

    2016-12-01

    New hydrological insights for the region: The agreement between ground and satellite rainfall data was generally good at annual/monthly scales but large variations were observed at the daily scale. Results showed a spatial variability of rainfall trends across the rainfall gradient. We observed significant changes in frequency along with insignificant changes in intensity and no changes in total amount for the driest location, but no changes in any of the rainfall parameters were observed for the three wetter locations. The results also showed increased rainfall variability for the driest location. This study provided a useful approach of using TMPA data associated with trend analysis to extend the data record for ecohydrological studies for similar data scarce conditions. The results of this study will also help constrain IPCC predictions in this region.

  6. 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

  7. Synoptic Analysis of Heavy Rainfall and Flood Observed in Izmir on 20 May 2015 Using Radar and Satellite Images

    Science.gov (United States)

    Avsar, Ercument

    2016-07-01

    In this study, a meteorological analysis is conducted on the sudden and heavy rainfall that occurred in Izmir on May 20, 2015. The barotropic model that is observed in upper carts is shown in detail. We can access the data of and analyze the type, severity and amount of many meteorological parameters using the meteorological radars that form a remote sensing system. The one field that uses the radars most intensively is rainfall. Images from the satellite and radar systems are used in the meteorological analysis of the heavy rainfall that occurred in Izmir on 20 May 2015, and the development of the system that led to this rainfall is shown. In this study, data received from Bornova Automatic Meteorological Observation Station (OMGI), which is under the management of Meteorology General Directorate (MGM), Izmir 2. Regional Directorate; satellite images; Radar PPI (Plan Position Indicator) and Radar MAX (Maximum Display) images are evaluated. In addition, synoptic situation, outputs of numerical estimation models, indices calculated from Skew T Log-P diagram are shown. All these results are mapped and analyzed. At the end of these analyses, it is found that this sudden rainfall had developed according to the frontal system motion. A barotropic model occurred on the day of the rainfall over the Aegean Region. As a result of the rainfall that happened in Izmir at 12.00 UTC (Universal Coordinated Time), the May month rainfall record for the last 64 years is achieved with a rainfall amount of 67.7 mm per meter square. Keywords: Izmir, barotropic model, heavy rainfall, radar, synoptic analysis

  8. A space-time hybrid hourly rainfall model for derived flood frequency analysis

    Directory of Open Access Journals (Sweden)

    U. Haberlandt

    2008-12-01

    Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.

    First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in

  9. Application of satellite estimates of rainfall distribution to simulate the potential for malaria transmission in Africa

    Science.gov (United States)

    Yamana, T. K.; Eltahir, E. A.

    2009-12-01

    The Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS) is a mechanistic model developed to assess malaria risk in areas where the disease is water-limited. This model relies on precipitation inputs as its primary forcing. Until now, applications of the model have used ground-based precipitation observations. However, rain gauge networks in the areas most affected by malaria are often sparse. The increasing availability of satellite based rainfall estimates could greatly extend the range of the model. The minimum temporal resolution of precipitation data needed was determined to be one hour. The CPC Morphing technique (CMORPH ) distributed by NOAA fits this criteria, as it provides 30-minute estimates at 8km resolution. CMORPH data were compared to ground observations in four West African villages, and calibrated to reduce overestimation and false alarm biases. The calibrated CMORPH data were used to force HYDREMATS, resulting in outputs for mosquito populations, vectorial capacity and malaria transmission.

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

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye

    2016-10-01

    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 (+30 years), 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 evaluate their applicability for agricultural drought evaluation 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-based precipitation estimates. 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-based estimates. Nine statistics were used to evaluate the performance of satellite products to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to

  11. The impacts of assimilating satellite soil moisture into a rainfall-runoff model in a semi-arid catchment

    Science.gov (United States)

    Soil moisture plays a key role in runoff generation processes. As a result, the assimilation of soil moisture observations into rainfall-runoff models is increasingly being investigated. Given the scarcity of ground-based in situ measurements, satellite soil moisture observations offer a valuable da...

  12. Heavy rainfall prediction applying satellite-based cloud data assimilation over land

    Science.gov (United States)

    Seto, Rie; Koike, Toshio; Rasmy, Mohamed

    2016-08-01

    To optimize flood management, it is crucial to determine whether rain will fall within a river basin. This requires very fine precision in prediction of rainfall areas. Cloud data assimilation has great potential to improve the prediction of precipitation area because it can directly obtain information on locations of rain systems. Clouds can be observed globally by satellite-based microwave remote sensing. Microwave observation also includes information of latent heat and water vapor associated with cloud amount, which enables the assimilation of not only cloud itself but also the cloud-affected atmosphere. However, it is difficult to observe clouds over land using satellite microwave remote sensing, because their emissivity is much lower than that of the land surface. To overcome this challenge, we need appropriate representation of heterogeneous land emissivity. We developed a coupled atmosphere and land data assimilation system with the Weather Research and Forecasting Model (CALDAS-WRF), which can assimilate soil moisture, vertically integrated cloud water content over land, and heat and moisture within clouds simultaneously. We applied this system to heavy rain events in Japan. Results show that the system effectively assimilated cloud signals and produced very accurate cloud and precipitation distributions. The system also accurately formed a consistent atmospheric field around the cloud. Precipitation intensity was also substantially improved by appropriately representing the local atmospheric field. Furthermore, combination of the method and operationally analyzed dynamical and moisture fields improved prediction of precipitation duration. The results demonstrate the method's promise in dramatically improving predictions of heavy rain and consequent flooding.

  13. Flood and Landslide Applications of Near Real-time Satellite Rainfall Products

    Science.gov (United States)

    Hong, Yang; Adler, Robert F.; Negri, Andrew; Huffman, George J.

    2007-01-01

    Floods and associated landslides are one of the most widespread natural hazards on Earth, responsible for tens of thousands of deaths and billions of dollars in property damage every year. During 1993-2002, over 1000 of the more than 2,900 natural disasters reported were due to floods. These floods and associated landslides claimed over 90,000 lives, affected over 1.4 billion people and cost about $210 billion. The impact of these disasters is often felt most acutely in less developed regions. In many countries around the world, satellite-based precipitation estimation may be the best source of rainfall data due to lack of surface observing networks. Satellite observations can be of essential value in improving our understanding of the occurrence of hazardous events and possibly in lessening their impact on local economies and in reducing injuries, if they can be used to create reliable warning systems in cost-effective ways. This article addressed these opportunities and challenges by describing a combination of satellite-based real-time precipitation estimation with land surface characteristics as input, with empirical and numerical models to map potential of landslides and floods. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg. By careful integration of remote sensing and in-situ observations, and assimilation of these observations into hydrological and landslide/debris flow models with surface topographic information, prediction of useful

  14. Status and Future of a Real-time Global Flood Detection and Forecasting System Using Satellite Rainfall Information

    Science.gov (United States)

    Adler, R. F.; Wu, H.; Hong, Y.; Policelli, F.; Pierce, H.

    2011-12-01

    Over the last several years a Global Flood Monitoring System (GFMS) has been running in real-time to detect the occurrence of floods (see trmm.gsfc.nasa.gov and click on "Floods and Landslides"). The system uses 3-hr resolution composite rainfall analyses (TRMM Multi-satellite Precipitation Analysis [TMPA]) as input into a hydrological model that calculates water depth at each grid (at 0.25 degree latitude-longitude) over the tropics and mid-latitudes. These calculations can provide information useful to national and international agencies in understanding the location, intensity, timeline and impact on populations of these significant hazard events. The status of these flood calculations will be shown by case study examples and a statistical comparison against a global flood event database. The validation study indicates that results improve with longer duration (> 3 days) floods and that the statistics are impacted by the presence of dams, which are not accounted for in the model calculations. Limitations in the flood calculations that are related to the satellite rainfall estimates include space and time resolution limitations and underestimation of shallow orographic and monsoon system rainfall. The current quality of these flood estimations is at the level of being useful, but there is a potential for significant improvement, mainly through improved and more timely satellite precipitation information and improvement in the hydrological models being used. NASA's Global Precipitation Measurement (GPM) program should lead to better precipitation analyses utilizing space-time interpolations that maintain accurate intensity distributions along with methods to disaggregate the rain information research should lead to improved rain estimation for shallow, orographic rainfall systems and some types of monsoon rainfall, a current problem area for satellite rainfall. Higher resolution flood models with accurate routing and regional calibration, and the use of satellite

  15. Mapping the world's tropical cyclone rainfall contribution over land using TRMM satellite data: precipitation budget and extreme rainfall

    Science.gov (United States)

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

    2012-12-01

    A study was performed to characterize over-land precipitation associated with tropical cyclones (TCs) for basins around the world gathered in the International Best Track Archive for Climate Stewardship (IBTrACS). From 1998 to 2010, rainfall data from TRMM 3B42, showed that TCs accounted for 8-, 11-, 7-, 10-, and 12-% of the annual over-land precipitation for North America, East Asia, Northern Indian Ocean, Australia, and South-West Indian Ocean respectively, and that TC-contribution decreased importantly within the first 150-km from the coast. At the local scale, TCs contributed on average to more than 40% and up to 77% of the annual precipitation budget over very different climatic areas with arid or tropical characteristics. The East Asia domain presented the higher and most constant TC-rain (170±23%-mm/yr) normalized over the area impacted, while the Southwest Indian domain presented the highest variability (130±48%-mm/yr), and the North American domain displayed the lowest average TC-rain (77±27%-mm/yr) despite a higher TC-activity. The maximum monthly TC-contribution (11-15%) was found later in the TC-season and was a conjunction between the peak of TC-activity, TC-rainfall, and the domain annual antagonism between dry and wet regimes if any. Furthermore, TC-days that accounted globally for 2±0.5% of all precipitation events for all basins, represented between 11-30% of rainfall extremes (>101.6mm/day). Locally, TC-rainfall was linked with the majority (>70%) or the quasi-totality (≈100%) of extreme rainfall. Finally, because of their importance in terms of rainfall amount, the contribution of tropical cyclones is provided for a selection of fifty urban areas experiencing cyclonic activity. Cases studies conducted at the regional scale will focus on the link between TC-activity, water resources, and hydrohazards such as floods and droughts.

  16. Propagation of Rainfall Products uncertainties in hydrological applications : Studies in the framework of the Megha-Tropiques Satellite Mission

    Science.gov (United States)

    Gosset, M.; Roca, R.

    2012-04-01

    The use of satellite based rainfall in research or operational Hydrological application is becoming more and more frequent. This is specially true in the Tropics where ground based gages (or radar) network are generally scarce and generally degrading. The new French-Indian satellite Mission Megha-Tropiques (MT) dedicated to the water and energy budget in the tropical atmosphere will contribute to a better monitoring of rainfall in the inter-tropical zone. As part of this mission, research is developed on the use of MT rainfall products for hydrological research or operational application such as flood monitoring. A key issue for such applications is how to account for rainfall products biases and uncertainties, and how to propagate them in the end user models ? Another important question is how to chose the best space-time resolution for the rainfall forcing, given that both model performances and rain-product uncertainties are resolution dependent. This talk will present on going investigations and perspectives on this subject, with examples from the Megha_tropiques Ground validation sites. Several sensitivity studies have been carried out in the Oueme Basin in Benin, West Africa, one the instrumented basin that will be used for MT products direct and hydrological validation.

  17. An evaluation and regional error modeling methodology for near-real-time satellite rainfall data over Australia

    Science.gov (United States)

    Pipunic, Robert C.; Ryu, Dongryeol; Costelloe, Justin F.; Su, Chun-Hsu

    2015-10-01

    In providing uniform spatial coverage, satellite-based rainfall estimates can potentially benefit hydrological modeling, particularly for flood prediction. Maximizing the value of information from such data requires knowledge of its error. The most recent Tropical Rainfall Measuring Mission (TRMM) 3B42RT (TRMM-RT) satellite product version 7 (v7) was used for examining evaluation procedures against in situ gauge data across mainland Australia at a daily time step, over a 9 year period. This provides insights into estimating uncertainty and informing quantitative error model development, with methodologies relevant to the recently operational Global Precipitation Measurement mission that builds upon the TRMM legacy. Important error characteristics highlighted for daily aggregated TRMM-RT v7 include increasing (negative) bias and error variance with increasing daily gauge totals and more reliability at detecting larger gauge totals with a probability of detection of data have increasing (positive) bias and error variance with increasing TRMM-RT estimates. Difference errors binned within 10 mm/d increments of TRMM-RT v7 estimates highlighted negatively skewed error distributions for all bins, suitably approximated by the generalized extreme value distribution. An error model based on this distribution enables bias correction and definition of quantitative uncertainty bounds, which are expected to be valuable for hydrological modeling and/or merging with other rainfall products. These error characteristics are also an important benchmark for assessing if/how future satellite rainfall products have improved.

  18. Validation and Inter-comparison of Satellite Rainfall Products over East Africa's Complex Topography

    Science.gov (United States)

    Dinku, T.; Ceccato, P.; Grover-Kopec, E.; Connor, S. J.; Ropelewski, C. F.

    2006-05-01

    A relatively dense station network of about 140 stations over the highlands of Ethiopia is used to perform an extensive validation and inter-comparison of different semi-operational satellite rainfall products. The validation region is located over 5oN to 13oN, and 35oE to 40oE. It has a very complex topography with alternating valleys and mountain ranges that varies between a point at below sea level and a highest peak of about 4620 meters. The gauge data are obtained from the National Meteorological Services Agency of Ethiopia. The data used in the current research covers the period 1990 to 2004. Though the gage data has already gone through routine quality control by NMSA, it has been subjected to further quality control. The validation and inter-comparison exercise is performed for three groups of products. The first group has low spatial (2.5o) and temporal (monthly) resolutions. These include Global Precipitation Climatology (GPCP) estimates, NOAA-CPC (Climate Prediction Center) Merged Analysis (CMAP), and the Tropical Rainfall Measuring Mission (TRMM) combined "TRMM and Other Sources" product (3B43). The later product has higher spatial resolution (0.25o), but has been remapped to 2.5o in order to compare it with the other products. The second group consists of products with high spatial (0.1o to 1o) and temporal (three-hourly to daily) resolutions. These products include NOAA-CPC African Rainfall Estimation Algorithm (CPC-RFE), GPCP One- Degree-Daily, and TRMM combined "TRMM and Other Satellites" product (3B42). These products are aggregated to a common one-degree and 10-daily total for comparison. The 10-day aggregation period is selected because it is the aggregation used in many operational early warning activities. The third category consists of a relatively new product (available starting from December 2002) from NOAA-CPC named CPC Morphing Technique (CMORPH). CMORPH is available at three-hourly temporal resolution and 0.25o spatial resolution, and it

  19. Effect of Bias Correction of Satellite-Rainfall Estimates on Runoff Simulations at the Source of the Upper Blue Nile

    Directory of Open Access Journals (Sweden)

    Emad Habib

    2014-07-01

    Full Text Available Results of numerous evaluation studies indicated that satellite-rainfall products are contaminated with significant systematic and random errors. Therefore, such products may require refinement and correction before being used for hydrologic applications. In the present study, we explore a rainfall-runoff modeling application using the Climate Prediction Center-MORPHing (CMORPH satellite rainfall product. The study area is the Gilgel Abbay catchment situated at the source basin of the Upper Blue Nile basin in Ethiopia, Eastern Africa. Rain gauge networks in such area are typically sparse. We examine different bias correction schemes applied locally to the CMORPH product. These schemes vary in the degree to which spatial and temporal variability in the CMORPH bias fields are accounted for. Three schemes are tested: space and time-invariant, time-variant and spatially invariant, and space and time variant. Bias-corrected CMORPH products were used to calibrate and drive the Hydrologiska Byråns Vattenbalansavdelning (HBV rainfall-runoff model. Applying the space and time-fixed bias correction scheme resulted in slight improvement of the CMORPH-driven runoff simulations, but in some instances caused deterioration. Accounting for temporal variation in the bias reduced the rainfall bias by up to 50%. Additional improvements were observed when both the spatial and temporal variability in the bias was accounted for. The rainfall bias was found to have a pronounced effect on model calibration. The calibrated model parameters changed significantly when using rainfall input from gauges alone, uncorrected, and bias-corrected CMORPH estimates. Changes of up to 81% were obtained for model parameters controlling the stream flow volume.

  20. Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

    Science.gov (United States)

    Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

    2016-05-01

    Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

  1. Validation and Analysis of Microwave-Derived Rainfall Over the Tropics

    Science.gov (United States)

    1993-01-01

    Intraseasonal Oscillations In addition to the biennial signals identified by Meehl (1987), Lau and col- laborators (Peng 1987; Shen 1987) expound on...temporally integrated, over a 50 x 50 area for a minimum of one month, to create clima - tological rainfall composites. Validation of the ESMR-derived

  2. Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

    KAUST Repository

    Viswanadhapalli, Yesubabu

    2015-08-20

    The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011, the city was deluged with more than double the annual rainfall amount caused by convective storms. We used a high resolution, two-way nested domain WRF model to simulate the two rainfall episodes. Simulations include control runs initialized with National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) data and 3-Dimensional Variational (3DVAR) data assimilation experiments conducted by assimilating NCEP prepbufr and radiance observations. Observations from Automated Weather Stations (AWS), synoptic charts, radar reflectivity and satellite pictures from the Presidency of Meteorology and Environment (PME), Jeddah, Saudi Arabia are used to assess the forecasting results. To evaluate the impact of the different assimilated observational datasets on the simulation of the major flooding event of 2009, we conducted 3DVAR experiments assimilating individual sources and a combination of all data sets. Results suggest that while the control run had a tendency to predict the storm earlier than observed, the assimilation of profile observations greatly improved the model\\'s thermodynamic structure and lead to better representation of simulated rainfall both in timing and amount. The experiment with assimilation of all available observations compared best with observed rainfall in terms of timing of the storm and rainfall distribution, demonstrating the importance of assimilating different types of observations. Retrospective experiments with and without data assimilation, for three different model lead times (48, 72 and 96-h), were performed to examine the skill of WRF model to predict the heavy rainfall events. Quantitative rainfall analysis of these simulations suggests that 48-h lead time runs with

  3. Network-derived inhomogeneity in monthly rainfall analyses over western Tasmania

    Science.gov (United States)

    Fawcett, Robert; Trewin, Blair; Barnes-Keoghan, Ian

    2010-08-01

    Monthly rainfall in the wetter western half of Tasmania was relatively poorly observed in the early to middle parts of the 20th century, and this causes a marked inhomogeneity in the operational gridded monthly rainfall analyses generated by the Australian Bureau of Meteorology up until the end of 2009. These monthly rainfall analyses were generated for the period 1900 to 2009 in two forms; a national analysis at 0.25° latitude-longitude resolution, and a southeastern Australia regional analysis at 0.1° resolution. For any given month, they used all the monthly data from the standard Bureau rainfall gauge network available in the Australian Data Archive for Meteorology. Since this network has changed markedly since Federation (1901), there is obvious scope for network-derived inhomogeneities in the analyses. In this study, we show that the topography-resolving techniques of the new Australian Water Availability Project analyses, adopted as the official operational analyses from the start of 2010, substantially diminish those inhomogeneities, while using largely the same observation network. One result is an improved characterisation of recent rainfall declines across Tasmania. The new analyses are available at two resolutions, 0.25° and 0.05°.

  4. Network-derived inhomogeneity in monthly rainfall analyses over western Tasmania

    Energy Technology Data Exchange (ETDEWEB)

    Fawcett, Robert; Trewin, Blair [National Climate Centre, Australian Bureau of Meteorology, Docklands, Victoria 3008 (Australia); Barnes-Keoghan, Ian, E-mail: r.fawcett@bom.gov.a, E-mail: b.trewin@bom.gov.a, E-mail: i.barnes-keoghan@bom.gov.a [Tasmanian Regional Office, Australian Bureau of Meteorology, Hobart, Tasmania 3000 (Australia)

    2010-08-15

    Monthly rainfall in the wetter western half of Tasmania was relatively poorly observed in the early to middle parts of the 20th century, and this causes a marked inhomogeneity in the operational gridded monthly rainfall analyses generated by the Australian Bureau of Meteorology up until the end of 2009. These monthly rainfall analyses were generated for the period 1900 to 2009 in two forms; a national analysis at 0.25{sup 0} latitude-longitude resolution, and a southeastern Australia regional analysis at 0.1{sup 0} resolution. For any given month, they used all the monthly data from the standard Bureau rainfall gauge network available in the Australian Data Archive for Meteorology. Since this network has changed markedly since Federation (1901), there is obvious scope for network-derived inhomogeneities in the analyses. In this study, we show that the topography-resolving techniques of the new Australian Water Availability Project analyses, adopted as the official operational analyses from the start of 2010, substantially diminish those inhomogeneities, while using largely the same observation network. One result is an improved characterisation of recent rainfall declines across Tasmania. The new analyses are available at two resolutions, 0.25{sup 0} and 0.05{sup 0}.

  5. Potential of commercial microwave link network derived rainfall for river runoff simulations

    Science.gov (United States)

    Smiatek, Gerhard; Keis, Felix; Chwala, Christian; Fersch, Benjamin; Kunstmann, Harald

    2017-03-01

    Commercial microwave link networks allow for the quantification of path integrated precipitation because the attenuation by hydrometeors correlates with rainfall between transmitter and receiver stations. The networks, operated and maintained by cellphone companies, thereby provide completely new and country wide precipitation measurements. As the density of traditional precipitation station networks worldwide is significantly decreasing, microwave link derived precipitation estimates receive increasing attention not only by hydrologists but also by meteorological and hydrological services. We investigate the potential of microwave derived precipitation estimates for streamflow prediction and water balance analyses, exemplarily shown for an orographically complex region in the German Alps (River Ammer). We investigate the additional value of link derived rainfall estimations combined with station observations compared to station and weather radar derived values. Our river runoff simulation system employs a distributed hydrological model at 100 × 100 m grid resolution. We analyze the potential of microwave link derived precipitation estimates for two episodes of 30 days with typically moderate river flow and an episode of extreme flooding. The simulation results indicate the potential of this novel precipitation monitoring method: a significant improvement in hydrograph reproduction has been achieved in the extreme flooding period that was characterized by a large number of local strong precipitation events. The present rainfall monitoring gauges alone were not able to correctly capture these events.

  6. Comparison of random forests and support vector machine for real-time radar-derived rainfall forecasting

    Science.gov (United States)

    Yu, Pao-Shan; Yang, Tao-Chang; Chen, Szu-Yin; Kuo, Chen-Min; Tseng, Hung-Wei

    2017-09-01

    This study aims to compare two machine learning techniques, random forests (RF) and support vector machine (SVM), for real-time radar-derived rainfall forecasting. The real-time radar-derived rainfall forecasting models use the present grid-based radar-derived rainfall as the output variable and use antecedent grid-based radar-derived rainfall, grid position (longitude and latitude) and elevation as the input variables to forecast 1- to 3-h ahead rainfalls for all grids in a catchment. Grid-based radar-derived rainfalls of six typhoon events during 2012-2015 in three reservoir catchments of Taiwan are collected for model training and verifying. Two kinds of forecasting models are constructed and compared, which are single-mode forecasting model (SMFM) and multiple-mode forecasting model (MMFM) based on RF and SVM. The SMFM uses the same model for 1- to 3-h ahead rainfall forecasting; the MMFM uses three different models for 1- to 3-h ahead forecasting. According to forecasting performances, it reveals that the SMFMs give better performances than MMFMs and both SVM-based and RF-based SMFMs show satisfactory performances for 1-h ahead forecasting. However, for 2- and 3-h ahead forecasting, it is found that the RF-based SMFM underestimates the observed radar-derived rainfalls in most cases and the SVM-based SMFM can give better performances than RF-based SMFM.

  7. A wavelet-based non-linear autoregressive with exogenous inputs (WNARX) dynamic neural network model for real-time flood forecasting using satellite-based rainfall products

    Science.gov (United States)

    Nanda, Trushnamayee; Sahoo, Bhabagrahi; Beria, Harsh; Chatterjee, Chandranath

    2016-08-01

    Although flood forecasting and warning system is a very important non-structural measure in flood-prone river basins, poor raingauge network as well as unavailability of rainfall data in real-time could hinder its accuracy at different lead times. Conversely, since the real-time satellite-based rainfall products are now becoming available for the data-scarce regions, their integration with the data-driven models could be effectively used for real-time flood forecasting. To address these issues in operational streamflow forecasting, a new data-driven model, namely, the wavelet-based non-linear autoregressive with exogenous inputs (WNARX) is proposed and evaluated in comparison with four other data-driven models, viz., the linear autoregressive moving average with exogenous inputs (ARMAX), static artificial neural network (ANN), wavelet-based ANN (WANN), and dynamic nonlinear autoregressive with exogenous inputs (NARX) models. First, the quality of input rainfall products of Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA), viz., TRMM and TRMM-real-time (RT) rainfall products is assessed through statistical evaluation. The results reveal that the satellite rainfall products moderately correlate with the observed rainfall, with the gauge-adjusted TRMM product outperforming the real-time TRMM-RT product. The TRMM rainfall product better captures the ground observations up to 95 percentile range (30.11 mm/day), although the hit rate decreases for high rainfall intensity. The effect of antecedent rainfall (AR) and climate forecast system reanalysis (CFSR) temperature product on the catchment response is tested in all the developed models. The results reveal that, during real-time flow simulation, the satellite-based rainfall products generally perform worse than the gauge-based rainfall. Moreover, as compared to the existing models, the flow forecasting by the WNARX model is way better than the other four models studied herein with the

  8. Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Mahanadi River basin

    Science.gov (United States)

    Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath

    2016-04-01

    Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling

  9. Assimilation of microwave, infrared, and radio occultation satellite observations with a weather research and forecasting model for heavy rainfall forecasting

    Science.gov (United States)

    Boonyuen, Pakornpop; Wu, Falin; Phunthirawuth, Parwapath; Zhao, Yan

    2016-10-01

    In this research, satellite observation data were assimilated into Weather Research and Forecasting Model (WRF) by using Three-dimensional Variational Data Assimilation System (3DVAR) to analyze its impacts on heavy rainfall forecasts. The weather case for this research was during 13-18 September 2015. Tropical cyclone VAMCO, forming in South China Sea near with Vietnam, moved on west direction to the Northeast of Thailand. After passed through Vietnam, the tropical cyclone was become to depression and there was heavy rainfall throughout the area of Thailand. Observation data, used in this research, included microwave radiance observations from the Advanced Microwave Sounding Unit-A (AMSU-A), infrared radiance observations from Infrared Atmospheric Sounding Interferometer (IASI), and GPS radio occultation (RO) from the COSMIC and CHAMP missions. The experiments were designed in five cases, namely, 1) without data assimilation (CTRL); 2) with only RO data (RO); 3) with only AMSU-A data (AMSUA); 4) with only IASI data (IASI); and 5) with all of RO, AMSU-A and IASI data assimilation (ALL). Then all experiment results would be compared with both NCEP FNL (Final) Operational Global Analysis and the observation data from Thai Meteorological Department weather stations. The experiments result demonstrated that with microwave (AMSU-A), infrared (IASI) and GPS radio occultation (RO) data assimilation can produce the positive impact on analyses and forecast. All of satellite data assimilations have corresponding positive effects in term of temperature and humidity forecasting, and the GPS-RO assimilation produces the best of temperature and humidity forecast biases. The satellite data assimilation has a good impact on temperature and humidity in lower troposphere and vertical distribution that very helpful for heavy rainfall forecast improvement.

  10. A Global Poverty Map Derived from Satellite Data

    Energy Technology Data Exchange (ETDEWEB)

    Elvidge, Christopher D. [NOAA National Geophysical Data Center,; Sutton, Paul S. [University of Denver; Ghosh, Tilottama [University of Denver; Tuttle, Benjamin T. [NOAA National Geophysical Data Center,; Baugh, Kimberly E. [NOAA National Geophysical Data Center,; Bhaduri, Budhendra L [ORNL; Bright, Eddie A [ORNL

    2009-01-01

    A global poverty map has been produced at 30 arc sec resolution using a poverty index calculated by dividing population count (LandScan2004) by the brightness of satellite observed lighting (DMSP nighttimelights). Inputs to the LandScan product include satellite-derived landcover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have been calibrated using national level poverty data from the World Development Indicators (WDI) 2006 edition. The total estimate of the numbers of individuals living in poverty is 2.2billion, slightly under the WDI estimate of 2.6 billion. We have demonstrated a new class of poverty map that should improve over time through the inclusion of new reference data for calibration of poverty estimates and as improvements are made in the satellite observation of human activities related to economic activity and technology access.

  11. A global poverty map derived from satellite data

    Science.gov (United States)

    Elvidge, Christopher D.; Sutton, Paul C.; Ghosh, Tilottama; Tuttle, Benjamin T.; Baugh, Kimberly E.; Bhaduri, Budhendra; Bright, Edward

    2009-08-01

    A global poverty map has been produced at 30 arcsec resolution using a poverty index calculated by dividing population count (LandScan 2004) by the brightness of satellite observed lighting (DMSP nighttime lights). Inputs to the LandScan product include satellite-derived land cover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have been calibrated using national level poverty data from the World Development Indicators (WDI) 2006 edition. The total estimate of the numbers of individuals living in poverty is 2.2 billion, slightly under the WDI estimate of 2.6 billion. We have demonstrated a new class of poverty map that should improve over time through the inclusion of new reference data for calibration of poverty estimates and as improvements are made in the satellite observation of human activities related to economic activity and technology access.

  12. Rainfall-derived growing season characteristics for agricultural impact assessments in South Africa

    Science.gov (United States)

    Ambrosino, Chiara; Chandler, Richard E.; Todd, Martin C.

    2014-02-01

    Precipitation variability imposes significant pressure in areas where agricultural practice is dominated by smallholder farmers who are dependent on subsistence farming. Advances in the understanding of this variability, in both time and space, have an important role to play in increasing the resilience of agricultural systems. The need is particularly pressing in regions of the world such as the African continent, which is already affected by multiple stresses including poverty and economic and political instability. In this paper, we explore the use of generalised linear models (GLMs) for this purpose, via a case study from north-east South Africa. A GLM is used to link the local rainfall variability to large-scale climate drivers identified from previous subcontinental-scale analyses, and the ability of the resulting model to simulate precipitation features that are relevant in agricultural applications is evaluated. We focus in particular on a set of growing season indices, proposed for the investigation of intraseasonal characteristics relevant for maize production in the region. Seven indices were computed from spatially averaged daily rainfall series from nine stations in the study area. As a first attempt to use GLMs for this type of application, the results are encouraging and suggest that the models are able to reproduce a range of agriculture-relevant indices. However, further research into spatial correlation structure is recommended to improve the multisite generation of the rainfall-derived characteristics.

  13. Satellite-derived methane emissions from inundation in Bangladesh

    Science.gov (United States)

    Peters, C. N.; Bennartz, R.; Hornberger, G. M.

    2017-05-01

    The uncertainty in methane (CH4) source strength of rice fields and wetlands is particularly high in South Asia CH4 budgets. We used satellite observations of CH4 column mixing ratios from Atmospheric Infrared Sounder (AIRS), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and Greenhouse Gases Observing Satellite (GOSAT) to estimate the contribution of Bangladesh emissions to atmospheric CH4 concentrations. Using satellite-derived inundation area as a proxy for source area, we developed a simple inverse advection model that estimates average annual CH4 surface fluxes to be 4, 9, and 19 mg CH4 m-2 h-1 in AIRS, SCIAMACHY, and GOSAT, respectively. Despite this variability, our flux estimates varied over a significantly narrower range than reported values for CH4 surface fluxes from a survey of 32 studies reporting ground-based observations between 0 and 260 mg CH4 m-2 h-1. Upscaling our satellite-derived surface flux estimates, we estimated total annual CH4 emissions for Bangladesh to be 1.3 ± 3.2, 1.8 ± 2.0, 3.1 ± 1.6 Tg yr-1, depending on the satellite. Our estimates of total emissions are in line with the median of total emission values for Bangladesh reported in earlier studies.

  14. Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data

    Science.gov (United States)

    López, Oliver; Houborg, Rasmus; McCabe, Matthew Francis

    2017-01-01

    Advances in space-based observations have provided the capacity to develop regional- to global-scale estimates of evaporation, offering insights into this key component of the hydrological cycle. However, the evaluation of large-scale evaporation retrievals is not a straightforward task. While a number of studies have intercompared a range of these evaporation products by examining the variance amongst them, or by comparison of pixel-scale retrievals against ground-based observations, there is a need to explore more appropriate techniques to comprehensively evaluate remote-sensing-based estimates. One possible approach is to establish the level of product agreement between related hydrological components: for instance, how well do evaporation patterns and response match with precipitation or water storage changes? To assess the suitability of this consistency-based approach for evaluating evaporation products, we focused our investigation on four globally distributed basins in arid and semi-arid environments, comprising the Colorado River basin, Niger River basin, Aral Sea basin, and Lake Eyre basin. In an effort to assess retrieval quality, three satellite-based global evaporation products based on different methodologies and input data, including CSIRO-PML, the MODIS Global Evapotranspiration product (MOD16), and Global Land Evaporation: the Amsterdam Methodology (GLEAM), were evaluated against rainfall data from the Global Precipitation Climatology Project (GPCP) along with Gravity Recovery and Climate Experiment (GRACE) water storage anomalies. To ensure a fair comparison, we evaluated consistency using a degree correlation approach after transforming both evaporation and precipitation data into spherical harmonics. Overall we found no persistent hydrological consistency in these dryland environments. Indeed, the degree correlation showed oscillating values between periods of low and high water storage changes, with a phase difference of about 2-3 months

  15. Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

    Science.gov (United States)

    Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

    2015-04-01

    Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

  16. Using satellite imagery to assess the influence of urban development on the impacts of extreme rainfall

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin; Madsen, Henrik;

    We investigate the applicability of medium resolution Landsat satellite imagery for mapping temporal changes in urban land cover for direct use in urban flood models. The overarching aim is to provide accurate and cost- and resource-efficient quantification of temporal changes in risk towards...... the impacts of pluvial flooding. Initial results show that satellite imagery may have considerable potential in this respect....

  17. Impact of AWiFS derived land use land cover on simulation of heavy rainfall

    Science.gov (United States)

    Karri, Srinivasarao; Gharai, Biswadip; Sai Krishna, S. V. S.; Rao, P. V. N.

    2016-05-01

    Land use/land cover (LU/LC) changes are considered to be one of the most important factors affecting regional climate and are thus an area of public concern. The land surface plays a crucial role in boundary layer evolution and precipitation patterns thereby establishing the need for LU/LC inputs as a critical part of modeling systems. Inaccurate LU/LC information often leads to very large errors in surface energy fluxes thus leading to errors in boundary layer state. We have investigated an incident of heavy rainfall during August 2015 over West Bengal, India using Weather Research and Forecast (WRF) model by incorporating different LU/LC datasets, IRS P6 Advanced Wide Field Sensor (AWiFS) LU/LC data for 2012-13 and the default Moderate Resolution Imaging Spectro-radiometer (MODIS) derived USGS LU/LC data for 2001. In the present study, we have made a comparative assessment between AWiFS derived LU/LC and USGS LU/LC by incorporating these datasets as one of the lower boundary conditions over Indian region in WRF model version 3.5.1 to simulate, at 10km resolution, a heavy rainfall event associated with landfall of a cyclonic system over West Bengal. The results of the study suggested influence of LU/LC in occurrence of heavy rainfall with WRF model using AWiFS LU/LC showing more realistic simulation as AWiFS LU/LC is more up-to-date and features recent changes in LU/LC over India.

  18. Cross-validation Methodology between Ground and GPM Satellite-based Radar Rainfall Product over Dallas-Fort Worth (DFW) Metroplex

    Science.gov (United States)

    Chen, H.; Chandrasekar, V.; Biswas, S.

    2015-12-01

    Over the past two decades, a large number of rainfall products have been developed based on satellite, radar, and/or rain gauge observations. However, to produce optimal rainfall estimation for a given region is still challenging due to the space time variability of rainfall at many scales and the spatial and temporal sampling difference of different rainfall instruments. In order to produce high-resolution rainfall products for urban flash flood applications and improve the weather sensing capability in urban environment, the center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in collaboration with National Weather Service (NWS) and North Central Texas Council of Governments (NCTCOG), has developed an urban radar remote sensing network in DFW Metroplex. DFW is the largest inland metropolitan area in the U.S., that experiences a wide range of natural weather hazards such as flash flood and hailstorms. The DFW urban remote sensing network, centered by the deployment of eight dual-polarization X-band radars and a NWS WSR-88DP radar, is expected to provide impacts-based warning and forecasts for benefit of the public safety and economy. High-resolution quantitative precipitation estimation (QPE) is one of the major goals of the development of this urban test bed. In addition to ground radar-based rainfall estimation, satellite-based rainfall products for this area are also of interest for this study. Typical example is the rainfall rate product produced by the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) Core Observatory satellite. Therefore, cross-comparison between ground and space-based rainfall estimation is critical to building an optimal regional rainfall system, which can take advantages of the sampling differences of different sensors. This paper presents the real-time high-resolution QPE system developed for DFW urban radar network, which is based upon the combination of S-band WSR-88DP and X

  19. Satellite-Derived Extinction at A Desert Site

    Science.gov (United States)

    Walker, P. L.; Blomshield, F. S.

    2002-12-01

    We have been conducting research aimed at enabling determination of desert optical environments from meteorological and satellite observations. To this end we have been making Rotating Shadowband Radiometer measurements, collecting aerosol size distributions, visibility and meteorological data continuously for the past 2 years in the Indian Wells Valley of the Mojave Desert of California. These data present an opportunity to validate satellite retrieval of atmospheric optical depth. Specifically, MISR-derived optical depths are compared to those derived from Shadowband measurements. A crude measure of extinction can be made by dividing the optical depth by the height of the mixing layer. The validity of this procedure is determined by comparison with extinction directly measured by nephelometers and calculated from measured aerosol size distributions.

  20. A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations

    Directory of Open Access Journals (Sweden)

    Markus Enenkel

    2016-04-01

    Full Text Available Governments, aid organizations and researchers are struggling with the complexity of detecting and monitoring drought events, which leads to weaknesses regarding the translation of early warnings into action. Embedded in an advanced decision-support framework for Doctors without Borders (Médecins sans Frontières, this study focuses on identifying the added-value of combining different satellite-derived datasets for drought monitoring and forecasting in Ethiopia. The core of the study is the improvement of an existing drought index via methodical adaptations and the integration of various satellite-derived datasets. The resulting Enhanced Combined Drought Index (ECDI links four input datasets (rainfall, soil moisture, land surface temperature and vegetation status. The respective weight of each input dataset is calculated for every grid point at a spatial resolution of 0.25 degrees (roughly 28 kilometers. In the case of data gaps in one input dataset, the weights are automatically redistributed to other available variables. Ranking the years 1992 to 2014 according to the ECDI-based warning levels allows for the identification of all large-scale drought events in Ethiopia. Our results also indicate a good match between the ECDI-based drought warning levels and reported drought impacts for both the start and the end of the season.

  1. Transitioning from CRD to CDRD in Bayesian retrieval of rainfall from satellite passive microwave measurements: Part 3 - Identification of optimal meteorological tags

    Science.gov (United States)

    Smith, E. A.; Leung, H. W.-Y.; Elsner, J. B.; Mehta, A. V.; Tripoli, G. J.; Casella, D.; Dietrich, S.; Mugnai, A.; Panegrossi, G.; Sanò, P.

    2013-05-01

    In the first two parts of this study we have presented a performance analysis of our new Cloud Dynamics and Radiation Database (CDRD) satellite precipitation retrieval algorithm on various convective and stratiform rainfall case studies verified with precision radar ground truth data, and an exposition of the algorithm's detailed design in conjunction with a proof-of-concept analysis vis-à-vis its theoretical underpinnings. In this third part of the study, we present the underlying analysis used to identify what we refer to as the optimal metrological and geophysical tags, which are the optimally effective atmospheric and geographic parameters that are used to refine the selection of candidate microphysical profiles used for the Bayesian retrieval. These tags enable extending beyond the conventional Cloud Radiation Database (CRD) algorithm by invoking meteorological-geophysical guidance, drawn from a simulated database, which affect and are in congruence with the observed precipitation states. This is guidance beyond the restrictive control provided by only simulated radiative transfer equation (RTE) model-derived database brightness temperature (TB) vector proximity information in seeking to relate physically consistent precipitation profile solutions to individual satellite-observed TB vectors. The first two parts of the study have rigorously demonstrated that the optimal tags effectively mitigate against solution ambiguity, where use of only a CRD framework (TB guidance only) leads to pervasive non-uniqueness problems in finding rainfall solutions. Alternatively, a CDRD framework (TB + tag guidance) mitigates against non-uniqueness problems through improved constraints. It remains to show how these optimal tags are identified. By use of three statistical analysis procedures applied to a database from 120 North American atmospheric simulations of precipitating storms (independent of the 60 simulations for the European-Mediterranean basin region used in the Parts

  2. Study on the association of green house gas (CO2) with monsoon rainfall using AIRS and TRMM satellite observations

    Science.gov (United States)

    Singh, R. B.; Janmaijaya, M.; Dhaka, S. K.; Kumar, V.

    Monsoon water cycle is the lifeline to over 60 per cent of the world's population. Throughout history, the monsoon-related calamities of droughts and floods have determined the life pattern of people. The association of Green House Gases (GHGs) particularly Carbon dioxide (CO2) with monsoon has been greatly debated amongst the scientific community in the past. The effect of CO2 on the monsoon rainfall over the Indian-Indonesian region (8-30°N, 65°-100°E) is being investigated using satellite data. The correlation coefficient (Rxy) between CO2 and monsoon is analysed. The Rxy is not significantly positive over a greater part of the study region, except a few regions. The inter-annual anomalies of CO2 is identified for playing a secondary role to influencing monsoon while other phenomenon like ENSO might be exerting a much greater influence.

  3. Near-real-time global rainfall map using multi-satellite data by JAXA and its validation

    Science.gov (United States)

    Kubota, T.; Kachi, M.; Oki, R.; Ushio, T.; Shige, S.; Aonashi, K.; Okamoto, K.

    2010-12-01

    Japan Aerospace Exploration Agency (JAXA) has developed and operated near-real-time data processing system with passive microwave radiometer (PMW) data (i.e., TRMM TMI, Aqua AMSR-E, and DMSP SSM/I and SSMIS) and GEO IR data and distributed rainfall products via the Internet (http://sharaku.eorc.jaxa.jp/GSMaP/). Core algorithms of the system are based on the algorithm developed under the Global Satellite Mapping of Precipitation (GSMaP) project. Horizontal resolution of GSMaP_NRT is 0.1-degree latitude/longitude grid and temporal resolution is 1 hour. The datasets are provided in near real time (about four hours after observation). The PMW-IR blended products of the GSMaP are the GSMaP_NRT for the near-real-time purpose and the GSMaP_MVK. The GSMaP_MVK estimates are achieved by the temporal interpolation of PMW retrievals using a PMW-IR blended algorithm composed of a morphed technique (Joyce et al., 2004) and a Kalman filter (Ushio et al., 2009) using IR information. For computation of the PMW retrievals, estimates from the PMW imagers are retrieved by a TRMM/PR-consistent advanced microwave radiometer algorithm by the GSMaP Project (Aonashi and Liu 2000; Kubota et al. 2007; Aonashi et al. 2009). The retrievals from the SSMIS instruments on the DMSP F16 and F17 have been merged in the GSMaP_NRT since June 2010. Rainfall estimates from the NOAA AMSU-B are not used in the GSMaP_NRT now (Aug. 2010), but they will be merged in near future. In the current plan, we will use the retrievals from the GSMaP_AMSU algorithm (Shige et al., 2009) over ocean and the NOAA Microwave Surface and Precipitation Products System (Zhao and Weng 2002; Ferraro et al. 2005) over land and coast. Kubota et al. (2009) analyzed satellite estimates in terms of data sources and surface types around Japan with reference to a ground-radar dataset calibrated by rain gauges provided by the Japan Meteorological Agency from January through December 2004. They demonstrated effective performance by the

  4. Estimating Ground-Level Particulate Matter (PM) Concentration using Satellite-derived Aerosol Optical Depth (AOD)

    Science.gov (United States)

    Park, Seohui; Im, Jungho

    2017-04-01

    Atmospheric aerosols are strongly associated with adverse human health effects. In particular, particulate matter less than 10 micrometers and 2.5 micrometers (i.e., PM10 and PM2.5, respectively) can cause cardiovascular and lung diseases such as asthma and chronic obstructive pulmonary disease (COPD). Air quality including PM has typically been monitored using station-based in-situ measurements over the world. However, in situ measurements do not provide spatial continuity over large areas. An alternative approach is to use satellite remote sensing as it provides data over vast areas at high temporal resolution. The literature shows that PM concentrations are related with Aerosol Optical Depth (AOD) that is derived from satellite observations, but it is still difficult to identify PM concentrations directly from AOD. Some studies used statistical approaches for estimating PM concentrations from AOD while some others combined numerical models and satellite-derived AOD. In this study, satellite-derived products were used to estimate ground PM concentrations based on machine learning over South Korea. Satellite-derived products include AOD from Geostationary Ocean Color Imager (GOCI), precipitation from Tropical Rainfall Measuring Mission (TRMM), soil moisture from AMSR-2, elevation from Shuttle Radar Topography Mission (SRTM), and land cover, land surface temperature and normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS). PM concentrations data were collected from 318 stations. A statistical ordinary least squares (OLS) approach was also tested and compared with the machine learning approach (i.e., random forest). PM concentration was estimated during spring season (from March to May) in 2015 that typically shows high concentration of PM. The randomly selected 80% of data were used for model calibration and the remaining 20% were used for validation. The developed models were further tested for prediction of PM

  5. Rainfall effects on Ku-band satellite link design in rainy tropical climate

    Science.gov (United States)

    Mandeep, J. S.; Hassan, S. I. S.; Tanaka, K.

    2008-03-01

    The performance of rain attenuation models in equatorial zones is still a debated issue due to the lack of measurements reported from these areas. Therefore,Therefore the rainfall path attenuation at 12.255 GHz measured at Universiti Sains Malaysia (USM) for three years is presented. It shows that the power law function of rain attenuation with ground rain rate deviates at very high rain rate. A comparison is made between the measured cumulative distributions and current prediction models, in order to determine which model gives the best prediction for this location.

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

    Directory of Open Access Journals (Sweden)

    T. Cohen Liechti

    2011-08-01

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

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

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

    In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating by nearly 1.5 times the rainfall. The statistics of TRMM and FEWS estimates show quite similar results.

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

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

    Science.gov (United States)

    Shariatinajafabadi, Mitra; Wang, Tiejun; Skidmore, Andrew K; Toxopeus, Albertus G; Kölzsch, Andrea; Nolet, Bart A; Exo, Klaus-Michael; Griffin, Larry; Stahl, Julia; Cabot, David

    2014-01-01

    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.

  8. 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.

  9. Hydrologic Simulations Driven by Satellite Rainfall to Study the Hydroelectric Development Impacts on River Flow

    Directory of Open Access Journals (Sweden)

    Tuan B. Le

    2014-11-01

    Full Text Available This study assesses the impact of hydroelectric dams on the discharge and total suspended solids (TSS concentration in the Huong River basin in Vietnam. The analysis is based on hydrologic and sediment transport simulations by the Soil and Water Assessment Tool (SWAT model driven by the Tropical Rainfall Measuring Mission (TRMM 3B42V6 rainfall data, from January 2003 through December 2010. An upstream sub-basin not affected by the hydroelectric dams was used for model calibration. The calibration results indicate good agreement between simulated and observed daily data (0.67 Nash-Sutcliffe efficiency, 0.82 Pearson correlation coefficient. The calibrated model for discharge and TSS simulation is then applied on another major sub-basin and then the whole Huong River basin. The simulation results indicate that dam operation in 2010 decreased downstream discharge during the rainy season by about 35% and augmented it during the dry season by about 226%. The downstream TSS concentration has decreased due to the dam operation but the total sediment loading increased during the dry season and decreased during the rainy season. On average, the dam construction and operation affected the pattern of discharge more than that of the sediment loading. Results indicate that SWAT, driven by remotely sensed inputs, can reasonably simulate discharge and water quality in ungauged or poorly gauged river basins and can be very useful for water resources assessment and climate change impact studies in such basins.

  10. Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

    Science.gov (United States)

    Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

    2013-01-01

    The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case

  11. Consistency analysis of the water cycle from recently derived satellite products

    Science.gov (United States)

    Berbery, E. H.; Hain, C.; Anderson, M. C.; Zhan, X.; Liu, J.; Ferraro, R. R.; Adler, R. F.; Wu, H.

    2015-12-01

    NOAA's National Environmental Satellite, Data, and Information Service (NESDIS) develops environmental data from satellites and other sources that is a critical resource for the management of energy, water, and food supplies. Variables related to the water cycle are routinely computed from satellite remote sensing from several space agencies, and the products are used at NOAA in operational or experimental modes. This study seeks to investigate to what extent there is consistency among the diverse products, and how they represent the water cycle at different scales. Remote sensing of land surface temperature and radiation is used to estimate surface energy fluxes by means of the Atmosphere Land Exchange Inverse (ALEXI) model. An Evaporative Stress Index representing anomalies in the ratio of actual-to-potential is a reliable indicator of drought also obtained from the ALEXI model. Observations from all currently available microwave satellite sensors are processed and merged to obtain the best possible estimates of soil moisture. The Global Soil Moisture Operational Product System (SMOPS) may also ingest brightness temperature observations applying a single channel algorithm to retrieve soil moisture. All satellite retrievals in SMOPS are merged into a soil moisture product that includes proxies of the errors. The Global Precipitation Climatology Project (GPCP) monthly precipitation data set (a current NOAA CDR project) uses satellite precipitation data sets over ocean and satellite plus gauge-based analyses over land. For operational needs, NESDIS's Hydro-Estimator (H-E) uses infrared data from GOES to estimate higher temporal resolution (sub-daily) rainfall rates. Streamflow at all the river mouths is estimated by the Dominant river tracing-Routing Integrated with VIC Environment model using precipitation input and other forcing data. Evapotranspiration, soil moisture, precipitation, streamflow and groundwater are derived at different resolutions, time scales and

  12. Physically, Fully-Distributed Hydrologic Simulations Driven by GPM Satellite Rainfall over an Urbanizing Arid Catchment in Saudi Arabia

    Directory of Open Access Journals (Sweden)

    Hatim O. Sharif

    2017-02-01

    Full Text Available A physically-based, distributed-parameter hydrologic model was used to simulate a recent flood event in the city of Hafr Al Batin, Saudi Arabia to gain a better understanding of the runoff generation and spatial distribution of flooding. The city is located in a very arid catchment. Flooding of the city is influenced by the presence of three major tributaries that join the main channel in and around the heavily urbanized area. The Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG rainfall product was used due to lack of detailed ground observations. To overcome the heavy computational demand, the catchment was divided into three sub-catchments with a variable model grid resolution. The model was run on three subcatchments separately, without losing hydrologic connectivity among the sub-catchments. Uncalibrated and calibrated satellite products were used producing different estimates of the predicted runoff. The runoff simulations demonstrated that 85% of the flooding was generated in the urbanized portion of the catchments for the simulated flood. Additional model simulations were performed to understand the roles of the unique channel network in the city flooding. The simulations provided insights into the best options for flood mitigation efforts. The variable model grid size approach allowed using physically-based, distributed models—such as the Gridded Surface Subsurface Hydrologic Analysis (GSSHA model used in this study—on large basins that include urban centers that need to be modeled at very high resolutions.

  13. Global Flood Response Using Satellite Rainfall Information Coupled with Land Surface and Routing Models

    Science.gov (United States)

    Adler, R. F.; Wu, H.

    2016-12-01

    The Global Flood Monitoring System (GFMS) (http://flood.umd.edu) has been developed and used in recent years to provide real-time flood detection, streamflow estimates and inundation calculations for most of the globe. The GFMS is driven by satellite-based precipitation, with the accuracy of the flood estimates being primarily dependent on the accuracy of the precipitation analyses and the land surface and routing models used. The routing calculations are done at both 12 km and 1 km resolution. Users of GFMS results include international and national flood response organizations. The devastating floods in October 2015 in South Carolina are analyzed indicating that the GFMS estimated streamflow is accurate and useful indicating significant flooding in the upstream basins. Further downstream the GFMS streamflow underestimates due to the presence of dams which are not accounted for in GFMS. Other examples are given for Yemen and Somalia and for Sri Lanka and southern India. A forecast flood event associated with a typhoon hitting Taiwan is also examined. One-kilometer resolution inundation mapping from GFMS holds the promise of highly useful information for flood disaster response. The algorithm is briefly described and examples are shown for recent cases where inundation estimates available from optical and Synthetic Aperture Radar (SAR) satellite sensors are available. For a case of significant flooding in Texas in May and June along the Brazos River the GFMS calculated streamflow compares favorably with the observed. Available Landsat-based (May 28) and MODIS-based (June 2) inundation analyses from U. of Colorado shows generally good agreement with the GFMS inundation calculation in most of the area where skies were clear and the optical techniques could be applied. The GFMS provides very useful disaster response information on a timely basis. However, there is still significant room for improvement, including improved precipitation information from NASA's Global

  14. Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

    Science.gov (United States)

    Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

    2002-01-01

    The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

  15. NOx emission trends in megacities derived from satellite measurements

    Science.gov (United States)

    Konovalov, Igor; Beekmann, Matthias; Richter, Andreas

    2010-05-01

    The effects of air pollutant emissions on both local air quality in megacities and composition of the atmosphere on regional and global scales are currently an important issue of atmospheric researches. In order to properly evaluate these effects, atmospheric models should be provided with accurate information on emissions of major air pollutants. However, such information is frequently very uncertain, as it is documented in literature. The quantification of emissions and related effects is an especially difficult task in the case of developing countries. Recently, it has been demonstrated that satellite measurements of nitrogen dioxide (NO2) can be used as a source of independent information on NOx emissions. In particular, the satellite measurements were used in our earlier studies to improve spatial allocation of NOx emissions, to estimate multi-annual changes of NOx emissions on regional scales and to validate data of traditional emission inventories (see Ref. 1, 2). The goals of the present study are (1) developing an efficient method for estimation of NOx emissions trend in megacity regions by using satellite measurements and an inverse modeling technique and (2) obtaining independent estimates of NOx emission trends in several megacities in Europe and the Middle East in the period from 1996 to 2008. The study is based on the synergetic use of the data for tropospheric NO2 column amounts derived from the long-term GOME and SCIAMACHY measurements and simulations performed by the CHIMERE chemistry transport model. We performed the analysis involving methods of different complexity ranging from estimation of linear trends in the tropospheric NO2 columns retrieved from satellite measurements to evaluation of nonlinear trends in NOx emission estimates obtained with the inverse modeling approach, which, in the given case, involves only very simple and transparent formulations. The most challenging part of the study is the nonlinear trend estimation, which is

  16. Relating watershed nutrient loads to satellite derived estuarine water quality

    Science.gov (United States)

    Lehrter, J. C.; Le, C.

    2015-12-01

    Nutrient enhanced phytoplankton production is a cause of degraded estuarine water quality. Yet, relationships between watershed nutrient loads and the spatial and temporal scales of phytoplankton blooms and subsequent water quality impairments remain unquantified for most systems. This is partially due to a lack of observations. In many systems, satellite remote sensing of water quality variables may be used to supplement limited field observations and improve understanding of linkages to nutrients. Here, we present the results from a field and satellite ocean color study that quantitatively links nutrients to variations in estuarine water quality endpoints. The study was conducted in Pensacola Bay, Florida, an estuary in the northern Gulf of Mexico that is impacted by watershed nutrients. We developed new empirical band ratio algorithms to retrieve phytoplankton biomass as chlorophyll a (chla), colored dissolved organic matter (CDOM), and suspended particulate matter (SPM) from the MEdium Resolution Imaging Spectrometer (MERIS). MERIS had suitable spatial resolution (300-m) for the scale of Pensacola Bay (area = 370 km2, mean depth = 3.4 m) and a spectral band centered at wavelength 709 nm that was used to minimize the effect of organic matter on chla retrieval. The algorithms were applied to daily MERIS remote sensing reflectance (level 2) data acquired from 2003 to 2011 to calculate nine-year time-series of mean monthly chla, CDOM, and SPM concentrations. The MERIS derived time-series were then analyzed for statistical relations with time-series of mean monthly river discharge and river loads of nitrogen, phosphorus, dissolved organic carbon, and SPM. Regression analyses revealed significant relationships between river loads and MERIS water quality variables. The simple regression models provide quantitative predictions about how much chla, CDOM, and SPM concentrations in Pensacola Bay will increase with increased river loading, which is necessary information

  17. A New Method for Radar Rainfall Estimation Using Merged Radar and Gauge Derived Fields

    Science.gov (United States)

    Hasan, M. M.; Sharma, A.; Johnson, F.; Mariethoz, G.; Seed, A.

    2014-12-01

    Accurate estimation of rainfall is critical for any hydrological analysis. The advantage of radar rainfall measurements is their ability to cover large areas. However, the uncertainties in the parameters of the power law, that links reflectivity to rainfall intensity, have to date precluded the widespread use of radars for quantitative rainfall estimates for hydrological studies. There is therefore considerable interest in methods that can combine the strengths of radar and gauge measurements by merging the two data sources. In this work, we propose two new developments to advance this area of research. The first contribution is a non-parametric radar rainfall estimation method (NPZR) which is based on kernel density estimation. Instead of using a traditional Z-R relationship, the NPZR accounts for the uncertainty in the relationship between reflectivity and rainfall intensity. More importantly, this uncertainty can vary for different values of reflectivity. The NPZR method reduces the Mean Square Error (MSE) of the estimated rainfall by 16 % compared to a traditionally fitted Z-R relation. Rainfall estimates are improved at 90% of the gauge locations when the method is applied to the densely gauged Sydney Terrey Hills radar region. A copula based spatial interpolation method (SIR) is used to estimate rainfall from gauge observations at the radar pixel locations. The gauge-based SIR estimates have low uncertainty in areas with good gauge density, whilst the NPZR method provides more reliable rainfall estimates than the SIR method, particularly in the areas of low gauge density. The second contribution of the work is to merge the radar rainfall field with spatially interpolated gauge rainfall estimates. The two rainfall fields are combined using a temporally and spatially varying weighting scheme that can account for the strengths of each method. The weight for each time period at each location is calculated based on the expected estimation error of each method

  18. Satellite-derived emissions inventories and detection of missing sources

    Science.gov (United States)

    McLinden, C. A.; Fioletov, V.; Shephard, M.; Krotkov, N. A.; Li, C.; Joiner, J.

    2016-12-01

    Our understanding of the impacts of air pollution on health and the environment, and our ability to predict future levels, is limited by our knowledge of its sources. Here, a global inventory of SO2 emissions, derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite and independent of conventional emissions databases, is presented. Our OMI-based inventory is found to be generally consistent with these conventional inventories. However, since we are also able to detect emission sources (in addition to quantifying their emissions), many SO2 sources were identified that are evidently missing from bottom-up inventories, including nearly 40 large anthropogenic sources pointing to significant discrepancies in some regions such as the Middle-East. The methodology, inventory highlights, and applications to other pollutants (NO2 from OMI and NH3 from the Cross-track Infrared Sounder) will be discussed.

  19. Rainfall estimation using raingages and radar — A Bayesian approach: 1. Derivation of estimators

    Science.gov (United States)

    Seo, D.-J.; Smith, J. A.

    1991-03-01

    Procedures for estimating rainfall from radar and raingage observations are constructed in a Bayesian framework. Given that the number of raingage measurements is typically very small, mean and variance of gage rainfall are treated as uncertain parameters. Under the assumption that log gage rainfall and log radar rainfall are jointly multivariate normal, the estimation problem is equivalent to lognormal co-kriging with uncertain mean and variance of the gage rainfall field. The posterior distribution is obtained under the assumption that the prior for the mean and inverse of the variance of log gage rainfall is normal-gamma 2. Estimate and estimation variance do not have closed-form expressions, but can be easily evaluated by numerically integrating two single integrals. To reduce computational burden associated with evaluating sufficient statistics for the likelihood function, an approximate form of parameter updating is given. Also, as a further approximation, the parameters are updated using raingage measurements only, yielding closed-form expressions for estimate and estimation variance in the Gaussian domain. With a reduction in the number of radar rainfall data in constructing covariance matrices, computational requirements for the estimation procedures are not significantly greater than those for simple co-kriging. Given their generality, the estimation procedures constructed in this work are considered to be applicable in various estimation problems involving an undersampled main variable and a densely sampled auxiliary variable.

  20. Propagation of Satelite Rainfall Products uncertainties in hydrological applications : Examples in West-Africa in the framework of the Megha-Tropiques Satellite Mission

    Science.gov (United States)

    Casse, C.; Gosset, M.; Peugeot, C.; Boone, A.; Pedinotti, V.

    2013-12-01

    The use of satellite based rainfall in research or operational Hydrological application is becoming more and more frequent. This is specially true in the Tropics where ground based gauge (or radar) network are generally scarce and often degrading. Member of the GPM constellation, the new French-Indian satellite Mission Megha-Tropiques (MT) dedicated to the water and energy budget in the tropical atmosphere contributes to a better monitoring of rainfall in the inter-tropical zone. As part of this mission, research is developed on the use of MT rainfall products for hydrological research or operational application such as flood monitoring. A key issue for such applications is how to account for rainfall products biases and uncertainties, and how to propagate them in the end user models ? Another important question is how to choose the best space-time resolution for the rainfall forcing, given that both model performances and rain-product uncertainties are resolution dependent. This talk will present on going investigations and perspectives on this subject, with examples from the Megha_tropiques Ground validation sites in West Africa. The CNRM model Surfex-ISBA/TRIP has been set up to simulate the hydrological behavior of the Niger River. This modeling set up is being used to study the predictability of Niger Floods events in the city of Niamey and the performances of satellite rainfall products as forcing for such predictions. One of the interesting feature of the Niger outflow in Niamey is its double peak : a first peak attributed to 'local' rainfall falling in small to medium size basins situated in the region of Niamey, and a second peak linked to the rainfall falling in the upper par of the river, and slowly propagating through the river towards Niamey. The performances of rainfall products are found to differ between the wetter/upper part of the basin, and the local/sahelian areas. Both academic tests with artificially biased or 'perturbed' rainfield and actual

  1. A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland

    Science.gov (United States)

    Panziera, Luca; Gabella, Marco; Zanini, Stefano; Hering, Alessandro; Germann, Urs; Berne, Alexis

    2016-06-01

    This paper presents a regional extreme rainfall analysis based on 10 years of radar data for the 159 regions adopted for official natural hazard warnings in Switzerland. Moreover, a nowcasting tool aimed at issuing heavy precipitation regional alerts is introduced. The two topics are closely related, since the extreme rainfall analysis provides the thresholds used by the nowcasting system for the alerts. Warm and cold seasons' monthly maxima of several statistical quantities describing regional rainfall are fitted to a generalized extreme value distribution in order to derive the precipitation amounts corresponding to sub-annual return periods for durations of 1, 3, 6, 12, 24 and 48 h. It is shown that regional return levels exhibit a large spatial variability in Switzerland, and that their spatial distribution strongly depends on the duration of the aggregation period: for accumulations of 3 h and shorter, the largest return levels are found over the northerly alpine slopes, whereas for longer durations the southern Alps exhibit the largest values. The inner alpine chain shows the lowest values, in agreement with previous rainfall climatologies. The nowcasting system presented here is aimed to issue heavy rainfall alerts for a large variety of end users, who are interested in different precipitation characteristics and regions, such as, for example, small urban areas, remote alpine catchments or administrative districts. The alerts are issued not only if the rainfall measured in the immediate past or forecast in the near future exceeds some predefined thresholds but also as soon as the sum of past and forecast precipitation is larger than threshold values. This precipitation total, in fact, has primary importance in applications for which antecedent rainfall is as important as predicted one, such as urban floods early warning systems. The rainfall fields, the statistical quantity representing regional rainfall and the frequency of alerts issued in case of

  2. Optimizing Satellite-Based Precipitation Estimation for Nowcasting of Rainfall and Flash Flood Events over the South African Domain

    OpenAIRE

    Estelle de Coning

    2013-01-01

    The South African Weather Service is mandated to issue warnings of hazardous weather events, including those related to heavy precipitation, in order to safeguard life and property. Flooding and flash flood events are common in South Africa. Frequent updates and real-time availability of precipitation data are crucial to support hydrometeorological warning services. Satellite rainfall estimation provides a very important data source for flash flood guidance systems as well as nowcasting of pr...

  3. How useful are Green-Ampt parameters derived from small rainfall simulation plots for modelling runoff at different plot lengths?

    Science.gov (United States)

    Langhans, Christoph; Engels, Lien; Tegenbos, Lize; Govers, Gerard; Diels, Jan

    2010-05-01

    Rainfall simulation on small field plots is an invaluable method to derive effective field parameters for infiltration models such as Green-Ampt. Plot scales of ca. 1m² integrate much of the micro-scale variability and processes, which ring-infiltrometers or soil core measurements cannot capture. However, these parameters have to be used with caution on larger scales, because processes such as run-on infiltration can be considerable. The Green-Ampt parameters suction across the wetting front (psi) and effective hydraulic conductivity (Ke) were estimated from rainfall simulations on two ridged fields in Togo, West Africa. Additionally, rainfall events were recorded, and on plots of 1m width and lengths of 1, 4 and 16m, total runoff volume and sediment concentration were measured. The storm runoff hydrographs of the plots were modelled with Chu's Green-Ampt variable rainfall intensity infiltration model, using the field-average parameters derived from the simulations. Potential effects of runoff lag time were assumed negligible. Calculated total runoff volumes were compared to measured runoff volumes. For the 1m plots, runoff was underestimated, as patches of seal in the furrows produced runoff already at rainfall intensities much lower than the average infiltration capacity. For the longer plots, no run-on infiltration or other scale dependent processes were assumed, so the relative error due to scale effects was proportional to the average difference or runoff depth. In contrast to the 1m plots, runoff was overestimated by a factor of 1.2 and 2 for the 4m and 16m plots, respectively. It appears that the application of the Green-Ampt effective hydraulic conductivity derived from rainfall simulations faces two main problems, which are their dependence on one single rainfall intensity and scale-effects by run-on infiltration. Errors necessarily propagate into the scale dependency of erosion and sediment transport, as these processes are directly dependent on runoff

  4. Exploring the relationship between malaria, rainfall intermittency, and spatial variation in rainfall seasonality

    Science.gov (United States)

    Merkord, C. L.; Wimberly, M. C.; Henebry, G. M.; Senay, G. B.

    2014-12-01

    Malaria is a major public health problem throughout tropical regions of the world. Successful prevention and treatment of malaria requires an understanding of the environmental factors that affect the life cycle of both the malaria pathogens, protozoan parasites, and its vectors, anopheline mosquitos. Because the egg, larval, and pupal stages of mosquito development occur in aquatic habitats, information about the spatial and temporal distribution of rainfall is critical for modeling malaria risk. Potential sources of hydrological data include satellite-derived rainfall estimates (TRMM and GPM), evapotranspiration derived from a simplified surface energy balance, and estimates of soil moisture and fractional water cover from passive microwave imagery. Previous studies have found links between malaria cases and total monthly or weekly rainfall in areas where both are highly seasonal. However it is far from clear that monthly or weekly summaries are the best metrics to use to explain malaria outbreaks. It is possible that particular temporal or spatial patterns of rainfall result in better mosquito habitat and thus higher malaria risk. We used malaria case data from the Amhara region of Ethiopia and satellite-derived rainfall estimates to explore the relationship between malaria outbreaks and rainfall with the goal of identifying the most useful rainfall metrics for modeling malaria occurrence. First, we explored spatial variation in the seasonal patterns of both rainfall and malaria cases in Amhara. Second, we assessed the relative importance of different metrics of rainfall intermittency, including alternation of wet and dry spells, the strength of intensity fluctuations, and spatial variability in these measures, in determining the length and severity of malaria outbreaks. We also explored the sensitivity of our results to the choice of method for describing rainfall intermittency and the spatial and temporal scale at which metrics were calculated. Results

  5. Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

    Science.gov (United States)

    Zambrano-Bigiarini, Mauricio; Nauditt, Alexandra; Birkel, Christian; Verbist, Koen; Ribbe, Lars

    2017-03-01

    Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SREs) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods.This study attempts to exhaustively evaluate - for the first time - the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-Adj, MSWEPv1.1, and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25° grid if necessary). The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities.Results revealed that most SRE products performed better for the humid South (36.4-43.7° S) and Central Chile (32.18-36.4° S), in particular at low- and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (autumn and winter; MAM-JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no-rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere

  6. Utilization of Precipitation and Moisture Products Derived from Satellites to Support NOAA Operational Precipitation Forecasts

    Science.gov (United States)

    Ferraro, R.; Zhao, L.; Kuligowski, R. J.; Kusselson, S.; Ma, L.; Kidder, S. Q.; Forsythe, J. M.; Jones, A. S.; Ebert, E. E.; Valenti, E.

    2012-12-01

    NOAA/NESDIS operates a constellation of polar and geostationary orbiting satellites to support weather forecasts and to monitor the climate. Additionally, NOAA utilizes satellite assets from other U.S. agencies like NASA and the Department of Defense, as well as those from other nations with similar weather and climate responsibilities (i.e., EUMETSAT and JMA). Over the past two decades, through joint efforts between U.S. and international government researchers, academic partners, and private sector corporations, a series of "value added" products have been developed to better serve the needs of weather forecasters and to exploit the full potential of precipitation and moisture products generated from these satellites. In this presentation, we will focus on two of these products - Ensemble Tropical Rainfall Potential (eTRaP) and Blended Total Precipitable Water (bTPW) - and provide examples on how they contribute to hydrometeorological forecasts. In terms of passive microwave satellite products, TPW perhaps is most widely used to support real-time forecasting applications, as it accurately depicts tropospheric water vapor and its movement. In particular, it has proven to be extremely useful in determining the location, timing, and duration of "atmospheric rivers" which contribute to and sustain flooding events. A multi-sensor approach has been developed and implemented at NESDIS in which passive microwave estimates from multiple satellites and sensors are merged to create a seamless, bTPW product that is more efficient for forecasters to use. Additionally, this product is being enhanced for utilization for television weather forecasters. Examples will be shown to illustrate the roll of atmospheric rivers and contribution to flooding events, and how the bTPW product was used to improve the forecast of these events. Heavy rains associated with land falling tropical cyclones (TC) frequently trigger floods that cause millions of dollars of damage and tremendous loss

  7. Online Assessment of Satellite-Derived Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Ostrenga, D.; Teng, W.; Kempler, S.

    2012-01-01

    Precipitation is difficult to measure and predict. Each year droughts and floods cause severe property damages and human casualties around the world. Accurate measurement and forecast are important for mitigation and preparedness efforts. Significant progress has been made over the past decade in satellite precipitation product development. In particular, products' spatial and temporal resolutions as well as timely availability have been improved by blended techniques. Their resulting products are widely used in various research and applications. However biases and uncertainties are common among precipitation products and an obstacle exists in quickly gaining knowledge of product quality, biases and behavior at a local or regional scale, namely user defined areas or points of interest. Current online inter-comparison and validation services have not addressed this issue adequately. To address this issue, we have developed a prototype to inter-compare satellite derived daily products in the TRMM Online Visualization and Analysis System (TOVAS). Despite its limited functionality and datasets, users can use this tool to generate customized plots within the United States for 2005. In addition, users can download customized data for further analysis, e.g. comparing their gauge data. To meet increasing demands, we plan to increase the temporal coverage and expanded the spatial coverage from the United States to the globe. More products have been added as well. In this poster, we present two new tools: Inter-comparison of 3B42RT and 3B42 Inter-comparison of V6 and V7 TRMM L-3 monthly products The future plans include integrating IPWG (International Precipitation Working Group) Validation Algorithms/statistics, allowing users to generate customized plots and data. In addition, we will expand the current daily products to monthly and their climatology products. Whenever the TRMM science team changes their product version number, users would like to know the differences by

  8. Bombardment History of the Galilean Satellites and Derived Ages

    Science.gov (United States)

    Neukum, G.; Wagner, R.; Wolf, U.; Head, J. W., III; Pappalardo, R.; Chapman, C. R.; Merline, W.; Belton, M. S.

    1997-07-01

    During the first seven Galileo flybys, high resolution imagery of the three Galilean moons, Europa, Ganymede and Callisto have been obtained. The new imaging data allow to measure crater diameters as small as ~ 100 m. In combination with Voyager data, size-frequency distribution characteristics in the size range of ~ 100 m to ~ 100 km have been determined. Crater distributions show steep slopes (cumulative index about -3) at smaller diameters on each satellite and are shallower at larger diameters, similar to what is seen on the Moon and the asteroids Gaspra and Ida. % % At D = 1 km, crater densities differ by about a factor of 10 between % average dark terrain of Galileo Regio and youngest bright resurfaced areas % on Ganymede. % Crater densities on the most heavily cratered regions on both Ganymede and Callisto are fairly comparable. On Europa, crater densities have turned out to be about a factor of 10 lower than on the youngest bright terrain in the Uruk Sulcus region of Ganymede. The similarity to crater size-frequency distributions found in the inner solar system suggests a similar origin of the projectiles, probably mainly stemming from the asteroid belt, and the impact rate on the Galilean satellites may have had a lunar-like decay with time. Under this assumption, absolute ages may be derived making use of the idea of the ''marker horizon'', i. e. formation of the youngest basins, such as Gilgamesh on Ganymede, about 3.8 b.y. ago. Thus, the most densely cratered dark terrains on both Ganymede and Callisto have likely ages of 4.1 - 4.3 b.y. Basins such as Neith (on Ganymede) or Adlinda (on Callisto) yield likely ages of about 3.9 b.y. Some areas on Europa may be as old as 3 - 3.3 b.y. Other scenarios based on values proposed for the present-day comet impact rate in the Jovian system with non-lunar-like flux time dependences are conceivable and would result in generally younger ages, possibly as young as 10 m.y. These young ages and impact rates for Europa

  9. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    Science.gov (United States)

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde

    2016-04-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. We present a rainfall retrieval algorithm, which is employed to obtain rainfall maps from microwave links in a cellular communication network. We compare these rainfall maps to gauge-adjusted radar rainfall maps. The microwave link data set, as well as the developed code, a package in the open source scripting language "R", are freely available at GitHub (https://github.com/overeem11/RAINLINK). The purpose of this presentation is to promote rainfall mapping utilizing microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  10. Variability in rainfall at monitoring stations and derivation of a long-term rainfall intensity record in the Grand Canyon Region, Arizona, USA

    Science.gov (United States)

    Caster, Joshua; Sankey, Joel B.

    2016-04-11

    In this study, we examine rainfall datasets of varying temporal length, resolution, and spatial distribution to characterize rainfall depth, intensity, and seasonality for monitoring stations along the Colorado River within Marble and Grand Canyons. We identify maximum separation distances between stations at which rainfall measurements might be most useful for inferring rainfall characteristics at other locations. We demonstrate a method for applying relations between daily rainfall depth and intensity, from short-term high-resolution data to lower-resolution longer-term data, to synthesize a long-term record of daily rainfall intensity from 1950–2012. We consider the implications of our spatio-temporal characterization of rainfall for understanding local landscape change in sedimentary deposits and archaeological sites, and for better characterizing past and present rainfall and its potential role in overland flow erosion within the canyons. We find that rainfall measured at stations within the river corridor is spatially correlated at separation distances of tens of kilometers, and is not correlated at the large elevation differences that separate stations along the Colorado River from stations above the canyon rim. These results provide guidance for reasonable separation distances at which rainfall measurements at stations within the Grand Canyon region might be used to infer rainfall at other nearby locations along the river. Like other rugged landscapes, spatial variability between rainfall measured at monitoring stations appears to be influenced by canyon and rim physiography and elevation, with preliminary results suggesting the highest elevation landform in the region, the Kaibab Plateau, may function as an important orographic influence. Stations at specific locations within the canyons and along the river, such as in southern (lower) Marble Canyon and eastern (upper) Grand Canyon, appear to have strong potential to receive high-intensity rainfall that

  11. Deriving atmospheric visibility from satellite retrieved aerosol optical depth

    Science.gov (United States)

    Riffler, M.; Schneider, Ch.; Popp, Ch.; Wunderle, S.

    2009-04-01

    Atmospheric visibility is a measure that reflects different physical and chemical properties of the atmosphere. In general, poor visibility conditions come along with risks for transportation (e.g. road traffic, aviation) and can negatively impact human health since visibility impairment often implies the presence of atmospheric pollution. Ambient pollutants, particulate matter, and few gaseous species decrease the perceptibility of distant objects. Common estimations of this parameter are usually based on human observations or devices that measure the transmittance of light from an artificial light source over a short distance. Such measurements are mainly performed at airports and some meteorological stations. A major disadvantage of these observations is the gap between the measurements, leaving large areas without any information. As aerosols are one of the most important factors influencing atmospheric visibility in the visible range, the knowledge of their spatial distribution can be used to infer visibility with the so called Koschmieder equation, which relates visibility and atmospheric extinction. In this study, we evaluate the applicability of satellite aerosol optical depth (AOD) products from the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) to infer atmospheric visibility on large spatial scale. First results applying AOD values scaled with the planetary boundary layer height are promising. For the comparison we use a full automated and objective procedure for the estimation of atmospheric visibility with the help of a digital panorama camera serving as ground truth. To further investigate the relation between the vertical measure of AOD and the horizontal visibility data from the Aerosol Robotic Network (AERONET) site Laegeren (Switzerland), where the digital camera is mounted, are included as well. Finally, the derived visibility maps are compared with synoptical observations in central

  12. Assessment of small-scale variability of rainfall and multi-satellite precipitation estimates using measurements from a dense rain gauge network in Southeast India

    Science.gov (United States)

    Sunilkumar, K.; Narayana Rao, T.; Satheeshkumar, S.

    2016-05-01

    This paper describes the establishment of a dense rain gauge network and small-scale variability in rain events (both in space and time) over a complex hilly terrain in Southeast India. Three years of high-resolution gauge measurements are used to validate 3-hourly rainfall and sub-daily variations of four widely used multi-satellite precipitation estimates (MPEs). The network, established as part of the Megha-Tropiques validation program, consists of 36 rain gauges arranged in a near-square grid area of 50 km × 50 km with an intergauge distance of 6-12 km. Morphological features of rainfall in two principal rainy seasons (southwest monsoon, SWM, and northeast monsoon, NEM) show marked differences. The NEM rainfall exhibits significant spatial variability and most of the rainfall is associated with large-scale/long-lived systems (during wet spells), whereas the contribution from small-scale/short-lived systems is considerable during the SWM. Rain events with longer duration and copious rainfall are seen mostly in the western quadrants (a quadrant is 1/4 of the study region) in the SWM and northern quadrants in the NEM, indicating complex spatial variability within the study region. The diurnal cycle also exhibits large spatial and seasonal variability with larger diurnal amplitudes at all the gauge locations (except for 1) during the SWM and smaller and insignificant diurnal amplitudes at many gauge locations during the NEM. On average, the diurnal amplitudes are a factor of 2 larger in the SWM than in the NEM. The 24 h harmonic explains about 70 % of total variance in the SWM and only ˜ 30 % in the NEM. During the SWM, the rainfall peak is observed between 20:00 and 02:00 IST (Indian Standard Time) and is attributed to the propagating systems from the west coast during active monsoon spells. Correlograms with different temporal integrations of rainfall data (1, 3, 12, 24 h) show an increase in the spatial correlation with temporal integration, but the

  13. An ice core derived 1013-year catchment-scale annual rainfall reconstruction in subtropical eastern Australia

    Science.gov (United States)

    Tozer, Carly R.; Vance, Tessa R.; Roberts, Jason L.; Kiem, Anthony S.; Curran, Mark A. J.; Moy, Andrew D.

    2016-05-01

    Paleoclimate research indicates that the Australian instrumental climate record (˜ 100 years) does not cover the full range of hydroclimatic variability that is possible. To better understand the implications of this on catchment-scale water resources management, a 1013-year (1000-2012 common era (CE)) annual rainfall reconstruction was produced for the Williams River catchment in coastal eastern Australia. No high-resolution paleoclimate proxies are located in the region and so a teleconnection between summer sea salt deposition recorded in ice cores from East Antarctica and rainfall variability in eastern Australia was exploited to reconstruct the catchment-scale rainfall record. The reconstruction shows that significantly longer and more frequent wet and dry periods were experienced in the preinstrumental compared to the instrumental period. This suggests that existing drought and flood risk assessments underestimate the true risks due to the reliance on data and statistics obtained from only the instrumental record. This raises questions about the robustness of existing water security and flood protection measures and has serious implications for water resources management, infrastructure design and catchment planning. The method used in this proof of concept study is transferable and enables similar insights into the true risk of flood/drought to be gained for other paleoclimate proxy poor regions for which suitable remote teleconnected proxies exist. This will lead to improved understanding and ability to deal with the impacts of multi-decadal to centennial hydroclimatic variability.

  14. An ice core derived 1013-year catchment scale annual rainfall reconstruction in subtropical eastern Australia

    Science.gov (United States)

    Tozer, C. R.; Vance, T. R.; Roberts, J.; Kiem, A. S.; Curran, M. A. J.; Moy, A. D.

    2015-12-01

    Paleoclimate research indicates that the instrumental climate record (~100 years in Australia) does not cover the full range of hydroclimatic variability possible. To better understand the implications of this for catchment-scale water resources management, an annual rainfall reconstruction is produced for the Williams River catchment in coastal eastern Australia. No high resolution palaeoclimate proxies are located in the region and so a teleconnection between summer sea salt deposition recorded in ice cores from East Antarctica and rainfall variability in eastern Australia was exploited to reconstruct 1013 years of rainfall (AD 1000-2012). The reconstruction shows that significantly longer and more frequent wet and dry periods were experienced in the preinstrumental compared to the instrumental period. This suggests that existing drought and flood risk assessments underestimate the true risks due to the reliance on data and statistics obtained from only the instrumental record. This raises questions about the robustness of existing water security and flood protection measures and has serious implications for water resources management, infrastructure design, and catchment planning. The method used in this proof of concept study is transferable and enables similar insights into the true risk of flood/drought to be gained for other locations that are teleconnected to East Antarctica. This will lead to improved understanding and ability to deal with the impacts of multidecadal to centennial hydroclimatic variability.

  15. NOAA/NESDIS Satellite Derived Surface Oil Analysis Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NESDIS Experimental Marine Pollution Surveillance Report (EMPSR) and the Daily Composite product are new products of the NOAA Satellite Analysis Branch and...

  16. 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...

  17. Using satellite data to study the relationship between rainfall and diarrheal diseases in a Southwestern Amazon basin.

    Science.gov (United States)

    Fonseca, Paula Andrea Morelli; Hacon, Sandra de Souza; Reis, Vera Lúcia; Costa, Duarte; Brown, Irving Foster

    2016-03-01

    The North region is the second region in Brazil with the highest incidence rate of diarrheal diseases in children under 5 years old. The aim of this study was to investigate the relationship between rainfall and water level during the rainy season principally with the incidence rate of this disease in a southwestern Amazon basin. Rainfall estimates and the water level were correlated and both of them were correlated with the diarrheal incidence rate. For the Alto Acre region, 2 to 3 days' time-lag is the best interval to observe the impact of the rainfall in the water level (R = 0.35). In the Lower Acre region this time-lag increased (4 days) with a reduction in the correlation value was found. The correlation between rainfall and diarrheal disease was better in the Lower Acre region (Acrelândia, R = 0.7) and rainfall upstream of the city. Between water level and diarrheal disease, the best results were found for the Brasiléia gauging station (Brasiléia, R = 0.3; Epitaciolândia, R = 0.5). This study's results may support planning and financial resources allocation to prioritize actions for local Civil Defense and health care services before, during and after the rainy season.

  18. 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 around Timor-Leste from WorldView-2 satellite imagery. Habitat classes include different combinations of...

  19. On the use of satellite-derived CH

    NARCIS (Netherlands)

    Pandey, S.; Houweling, S.; Krol, M.; Aben, I.; Röckmann, T.

    2015-01-01

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

  20. Monitoring Surface Climate With its Emissivity Derived From Satellite Measurements

    Science.gov (United States)

    Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

    2012-01-01

    Satellite thermal infrared (IR) spectral emissivity data have been shown to be significant for atmospheric research and monitoring the Earth fs environment. Long-term and large-scale observations needed for global monitoring and research can be supplied by satellite-based remote sensing. Presented here is the global surface IR emissivity data retrieved from the last 5 years of Infrared Atmospheric Sounding Interferometer (IASI) measurements observed from the MetOp-A satellite. Monthly mean surface properties (i.e., skin temperature T(sub s) and emissivity spectra epsilon(sub v) with a spatial resolution of 0.5x0.5-degrees latitude-longitude are produced to monitor seasonal and inter-annual variations. We demonstrate that surface epsilon(sub v) and T(sub s) retrieved with IASI measurements can be used to assist in monitoring surface weather and surface climate change. Surface epsilon(sub v) together with T(sub s) from current and future operational satellites can be utilized as a means of long-term and large-scale monitoring of Earth 's surface weather environment and associated changes.

  1. 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 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 crop yields and

  2. Evaluating large scale orthophotos derived from high resolution satellite imagery

    Science.gov (United States)

    Ioannou, Maria Teresa; Georgopoulos, Andreas

    2013-08-01

    For the purposes of a research project, for the compilation of the archaeological and environmental digital map of the island of Antiparos, the production of updated large scale orthophotos was required. Hence suitable stereoscopic high resolution satellite imagery was acquired. Two Geoeye-1 stereopairs were enough to cover this small island of the Cyclades complex in the central Aegean. For the orientation of the two stereopairs numerous ground control points were determined using GPS observations. Some of them would also serve as check points. The images were processed using commercial stereophotogrammetric software suitable to process satellite stereoscopic imagery. The results of the orientations are evaluated and the digital terrain model was produced using automated and manual procedures. The DTM was checked both internally and externally with comparison to other available DTMs. In this paper the procedures for producing the desired orthophotography are critically presented and the final result is compared and evaluated for its accuracy, completeness and efficiency. The final product is also compared against the orthophotography produced by Ktimatologio S.A. using aerial images in 2007. The orthophotography produced has been evaluated metrically using the available check points, while qualitative evaluation has also been performed. The results are presented and a critical approach for the usability of satellite imagery for the production of large scale orthophotos is attempted.

  3. Linking Satellite-Derived Fire Counts to Satellite-Derived Weather Data in Fire Prediction Models to Forecast Extreme Fires in Siberia

    Science.gov (United States)

    Westberg, D. J.; Soja, A. J.; Stackhouse, P. W.

    2009-12-01

    Fire is the dominant disturbance that precipitates ecosystem change in boreal regions, and fire is largely under the control of weather and climate. Fire frequency, fire severity, area burned and fire season length are predicted to increase in boreal regions under climate change scenarios. Therefore to predict fire weather and ecosystem change, we must understand the factors that influence fire regimes and at what scale these are viable. The Canadian Fire Weather Index (FWI), developed by the Canadian Forestry Service, is used for this comparison, and it is calculated using local noon surface-level air temperature, relative humidity, wind speed, and daily (noon-noon) rainfall. The FWI assesses daily forest fire burning potential. Large-scale FWI are calculated at the NASA Langley Research Center (LaRC) using NASA Goddard Earth Observing System version 4 (GEOS-4) large-scale reanalysis and NASA Global Precipitation Climatology Project (GPCP) data. The GEOS-4 reanalysis weather data are 3-hourly interpolated to 1-hourly data at a 1ox1o resolution and the GPCP precipitation data are also at 1ox1o resolution. In previous work focusing on the fire season in Siberia in 1999 and 2002, we have shown the combination of GEOS-4 weather data and Global Precipitation Climatology Project (GPCP) precipitation data compares well to ground-based weather data when used as inputs for FWI calculation. The density and accuracy of Siberian surface station data can be limited, which leads to results that are not representative of the spatial reality. GEOS-4/GPCP-dervied FWI can serve to spatially enhance current and historic FWI, because these data are spatially and temporally consistency. The surface station and model reanalysis derived fire weather indices compared well spatially, temporally and quantitatively, and increased fire activity compares well with increasing FWI ratings. To continue our previous work, we statistically compare satellite-derived fire counts to FWI categories at

  4. Characteristics of equatorial electrojet derived from Swarm satellites

    Science.gov (United States)

    Thomas, Neethal; Vichare, Geeta; Sinha, A. K.

    2017-03-01

    The vector magnetic field measurements from three satellite constellation, Swarm mission (Alpha 'Swarm-A', Bravo 'Swarm-B', and Charlie 'Swarm-C') during the quiet days (daily ∑Kp ⩽ 10) of the years 2014-2015 are used to study the characteristic features of equatorial electrojet (EEJ). A program is developed to identify the EEJ signature in the X (northward) component of the magnetic field recorded by the satellite. An empirical model is fitted into the observed EEJ signatures separately for both the hemispheres, to obtain the parameters of electrojet current such as peak current density, total eastward current, the width of EEJ, position of the electrojet axis, etc. The magnetic field signatures of EEJ at different altitudes are then estimated. Swarm B and C are orbiting at different heights (separation ∼50 km) and during the month of April 2014, both the satellites were moving almost simultaneously over nearby longitudes. Therefore, we used those satellite passes to validate the methodology used in the present study. The magnetic field estimates at the location of Swarm-C obtained using the observations of Swarm B are compared with the actual observations of Swarm-C. A good correlation between the actual and the computed values (correlation coefficient = 0.98) authenticates the method of analysis. The altitudinal variation of the amplitude and the width of the EEJ signatures are also depicted. The ratio of the total eastward flowing forward to westward return currents is found to vary between 0.1 and 1.0. The forward and return current values in the northern hemisphere are found to be ∼0.5 to 2 times of those in the southern hemisphere, thereby indicating the hemispheric asymmetry. The latitudinal extents of the forward and return currents are found to have longitudinal dependence similar to that of the amplitude and the width of EEJ showing four peak structures. Local time dependence of EEJ parameters has also been investigated. In general, the results

  5. Improvement in airsea flux estimates derived from satellite observations

    OpenAIRE

    Bentamy, Abderrahim; Grodsky, Semyon A.; Katsaros, Kristina; Mestas-nunez, Alberto M.; Blanke, Bruno; Desbiolles, Fabien

    2013-01-01

    A new method is developed to estimate daily turbulent airsea fluxes over the global ocean on a 0.25 degrees grid. The required surface wind speed (w(10)) and specific air humidity (q(10)) at 10m height are both estimated from remotely sensed measurements. w(10) is obtained from the SeaWinds scatterometer on board the QuikSCAT satellite. A new empirical model relating brightness temperatures (T-b) from the Special Sensor Microwave Imager (SSM/I) and q(10) is developed. It is an extension of th...

  6. 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.

    , there is a need for satellite-based estimations. One potential solution is to use sea surface height anomalies (SSHAs) from altimeter observations. However, any estimation derived from satellite measurements requires extensive regional validation...

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

    Directory of Open Access Journals (Sweden)

    Anima Biswal

    2014-09-01

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

  8. Utilizing Satellite-derived Precipitation Products in Hydrometeorological Applications

    Science.gov (United States)

    Liu, Z.; Ostrenga, D.; Teng, W. L.; Kempler, S. J.; Huffman, G. J.

    2012-12-01

    Each year droughts and floods happen around the world and can cause severe property damages and human casualties. Accurate measurement and forecast are important for preparedness and mitigation efforts. Through multi-satellite blended techniques, significant progress has been made over the past decade in satellite-based precipitation product development, such as, products' spatial and temporal resolutions as well as timely availability. These new products are widely used in various research and applications. In particular, the TRMM Multi-satellite Precipitation Analysis (TMPA) products archived and distributed by the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) provide 3-hourly, daily and monthly near-global (50° N - 50° S) precipitation datasets for research and applications. Two versions of TMPA products are available, research (3B42, 3B43, rain gauge adjusted) and near-real-time (3B42RT). At GES DISC, we have developed precipitation data services to support hydrometeorological applications in order to maximize the TRMM mission's societal benefits. In this presentation, we will present examples of utilizing TMPA precipitation products in hydrometeorological applications including: 1) monitoring global floods and droughts; 2) providing data services to support the USDA Crop Explorer; 3) support hurricane monitoring activities and research; and 4) retrospective analog year analyses to improve USDA's world agricultural supply and demand estimates. We will also present precipitation data services that can be used to support hydrometeorological applications including: 1) User friendly TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/); 2) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at GES DISC; 3) Simple Subset Wizard (http://disc.sci.gsfc.nasa.gov/SSW/ ) for data subsetting and format conversion; 4) Data

  9. Intercomparison of satellite-derived cloud analyses for the Arctic Ocean in spring and summer

    Science.gov (United States)

    Mcguffie, K.; Barry, R. G.; Schweiger, A.; Newell, J.; Robinson, D. A.

    1988-01-01

    Several methods of deriving Arctic cloud information, primarily from satellite imagery, have been intercompared. The comparisons help in establishing what cloud information is most readily determined in polar regions from satellite data analysis. The analyses for spring-summer conditions show broad agreement, but subjective errors affecting some geographical areas and cloud types are apparent. The results suggest that visible and thermal infrared data may be insufficient for adequate cloud mapping over some Arctic surfaces.

  10. Satellite-derived mineral mapping and monitoring of weathering, deposition and erosion

    Science.gov (United States)

    Cudahy, Thomas; Caccetta, Mike; Thomas, Matilda; Hewson, Robert; Abrams, Michael; Kato, Masatane; Kashimura, Osamu; Ninomiya, Yoshiki; Yamaguchi, Yasushi; Collings, Simon; Laukamp, Carsten; Ong, Cindy; Lau, Ian; Rodger, Andrew; Chia, Joanne; Warren, Peter; Woodcock, Robert; Fraser, Ryan; Rankine, Terry; Vote, Josh; de Caritat, Patrice; English, Pauline; Meyer, Dave; Doescher, Chris; Fu, Bihong; Shi, Pilong; Mitchell, Ross

    2016-01-01

    The Earth’s surface comprises minerals diagnostic of weathering, deposition and erosion. The first continental-scale mineral maps generated from an imaging satellite with spectral bands designed to measure clays, quartz and other minerals were released in 2012 for Australia. Here we show how these satellite mineral maps improve our understanding of weathering, erosional and depositional processes in the context of changing weather, climate and tectonics. The clay composition map shows how kaolinite has developed over tectonically stable continental crust in response to deep weathering during northwardly migrating tropical conditions from 45 to 10 Ma. The same clay composition map, in combination with one sensitive to water content, enables the discrimination of illite from montmorillonite clays that typically develop in large depositional environments over thin (sinking) continental crust such as the Lake Eyre Basin. Cutting across these clay patterns are sandy deserts that developed <10 Ma and are well mapped using another satellite product sensitive to the particle size of silicate minerals. This product can also be used to measure temporal gains/losses of surface clay caused by periodic wind erosion (dust) and rainfall inundation (flood) events. The accuracy and information content of these satellite mineral maps are validated using published data. PMID:27025192

  11. Satellite-derived mineral mapping and monitoring of weathering, deposition and erosion.

    Science.gov (United States)

    Cudahy, Thomas; Caccetta, Mike; Thomas, Matilda; Hewson, Robert; Abrams, Michael; Kato, Masatane; Kashimura, Osamu; Ninomiya, Yoshiki; Yamaguchi, Yasushi; Collings, Simon; Laukamp, Carsten; Ong, Cindy; Lau, Ian; Rodger, Andrew; Chia, Joanne; Warren, Peter; Woodcock, Robert; Fraser, Ryan; Rankine, Terry; Vote, Josh; de Caritat, Patrice; English, Pauline; Meyer, Dave; Doescher, Chris; Fu, Bihong; Shi, Pilong; Mitchell, Ross

    2016-03-30

    The Earth's surface comprises minerals diagnostic of weathering, deposition and erosion. The first continental-scale mineral maps generated from an imaging satellite with spectral bands designed to measure clays, quartz and other minerals were released in 2012 for Australia. Here we show how these satellite mineral maps improve our understanding of weathering, erosional and depositional processes in the context of changing weather, climate and tectonics. The clay composition map shows how kaolinite has developed over tectonically stable continental crust in response to deep weathering during northwardly migrating tropical conditions from 45 to 10 Ma. The same clay composition map, in combination with one sensitive to water content, enables the discrimination of illite from montmorillonite clays that typically develop in large depositional environments over thin (sinking) continental crust such as the Lake Eyre Basin. Cutting across these clay patterns are sandy deserts that developed <10 Ma and are well mapped using another satellite product sensitive to the particle size of silicate minerals. This product can also be used to measure temporal gains/losses of surface clay caused by periodic wind erosion (dust) and rainfall inundation (flood) events. The accuracy and information content of these satellite mineral maps are validated using published data.

  12. Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets

    Science.gov (United States)

    Pedinotti, V.; Boone, A.; Decharme, B.; Crétaux, J. F.; Mognard, N.; Panthou, G.; Papa, F.; Tanimoun, B. A.

    2012-06-01

    During the 1970s and 1980s, West Africa has faced extreme climate variations with extended drought conditions. Of particular importance is the Niger basin, since it traverses a large part of the Sahel and is thus a critical source of water for an ever-increasing local population in this semi arid region. However, the understanding of the hydrological processes over this basin is currently limited by the lack of spatially distributed surface water and discharge measurements. The purpose of this study is to evaluate the ability of the ISBA-TRIP continental hydrologic system to represent key processes related to the hydrological cycle of the Niger basin. ISBA-TRIP is currently used within a coupled global climate model, so that the scheme must represent the first order processes which are critical for representing the water cycle while retaining a limited number of parameters and a simple representation of the physics. To this end, the scheme uses first-order approximations to account explicitly for the surface river routing, the floodplain dynamics, and the water storage using a deep aquifer reservoir. In the current study, simulations are done at a 0.5 by 0.5° spatial resolution over the 2002-2007 period (in order to take advantage of the recent satellite record and data from the African Monsoon Multidisciplinary Analyses project, AMMA). Four configurations of the model are compared to evaluate the separate impacts of the flooding scheme and the aquifer on the water cycle. Moreover, the model is forced by two different rainfall datasets to consider the sensitivity of the model to rainfall input uncertainties. The model is evaluated using in situ discharge measurements as well as satellite derived flood extent, total continental water storage changes and river height changes. The basic analysis of in situ discharges confirms the impact of the inner delta area, known as a significant flooded area, on the discharge, characterized by a strong reduction of the

  13. Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets

    Directory of Open Access Journals (Sweden)

    V. Pedinotti

    2012-06-01

    Full Text Available During the 1970s and 1980s, West Africa has faced extreme climate variations with extended drought conditions. Of particular importance is the Niger basin, since it traverses a large part of the Sahel and is thus a critical source of water for an ever-increasing local population in this semi arid region. However, the understanding of the hydrological processes over this basin is currently limited by the lack of spatially distributed surface water and discharge measurements. The purpose of this study is to evaluate the ability of the ISBA-TRIP continental hydrologic system to represent key processes related to the hydrological cycle of the Niger basin. ISBA-TRIP is currently used within a coupled global climate model, so that the scheme must represent the first order processes which are critical for representing the water cycle while retaining a limited number of parameters and a simple representation of the physics. To this end, the scheme uses first-order approximations to account explicitly for the surface river routing, the floodplain dynamics, and the water storage using a deep aquifer reservoir. In the current study, simulations are done at a 0.5 by 0.5° spatial resolution over the 2002–2007 period (in order to take advantage of the recent satellite record and data from the African Monsoon Multidisciplinary Analyses project, AMMA. Four configurations of the model are compared to evaluate the separate impacts of the flooding scheme and the aquifer on the water cycle. Moreover, the model is forced by two different rainfall datasets to consider the sensitivity of the model to rainfall input uncertainties. The model is evaluated using in situ discharge measurements as well as satellite derived flood extent, total continental water storage changes and river height changes. The basic analysis of in situ discharges confirms the impact of the inner delta area, known as a significant flooded area, on the discharge, characterized by a strong

  14. Temporal Trends in Satellite-Derived Erythemal UVB and Implications for Ambient Sun Exposure Assessment

    Directory of Open Access Journals (Sweden)

    Marvin Langston

    2017-02-01

    Full Text Available Ultraviolet radiation (UVR has been associated with various health outcomes, including skin cancers, vitamin D insufficiency, and multiple sclerosis. Measurement of UVR has been difficult, traditionally relying on subject recall. We investigated trends in satellite-derived UVB from 1978 to 2014 within the continental United States (US to inform UVR exposure assessment and determine the potential magnitude of misclassification bias created by ignoring these trends. Monthly UVB data remotely sensed from various NASA satellites were used to investigate changes over time in the United States using linear regression with a harmonic function. Linear regression models for local geographic areas were used to make inferences across the entire study area using a global field significance test. Temporal trends were investigated across all years and separately for each satellite type due to documented differences in UVB estimation. UVB increased from 1978 to 2014 in 48% of local tests. The largest UVB increase was found in Western Nevada (0.145 kJ/m2 per five-year increment, a total 30-year increase of 0.87 kJ/m2. This largest change only represented 17% of total ambient exposure for an average January and 2% of an average July in Western Nevada. The observed trends represent cumulative UVB changes of less than a month, which are not relevant when attempting to estimate human exposure. The observation of small trends should be interpreted with caution due to measurement of satellite parameter inputs (ozone and climatological factors that may impact derived satellite UVR nearly 20% compared to ground level sources. If the observed trends hold, satellite-derived UVB data may reasonably estimate ambient UVB exposures even for outcomes with long latency phases that predate the satellite record.

  15. a Diagnostic Approach to Obtaining Planetary Boundary Layer Winds Using Satellite-Derived Thermal Data

    Science.gov (United States)

    Belt, Carol Lynn

    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 (0921 GMT 19 April 1979) 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. Horizontal moisture divergence, moisture advection, velocity divergence and relative vorticity are computed at 300 m AGL using satellite-derived winds and moisture data. Results show excellent agreement with corresponding RAOB-derived values. Areas of horizontal moisture convergence, velocity convergence, and positive vorticity are nearly coincident and align in regions which later develop intense convection. Vertical motion at 1600 m AGL is computed using stepwise integration of the satellite winds through the PBL. Values and patterns are similar to those obtained using the RAOB-derived winds. Regions of maximum upward motion correspond with areas of greatest moisture convergence and the convection that later develops.

  16. Disaggregating radar-derived rainfall measurements in East Azarbaijan, Iran, using a spatial random-cascade model

    Science.gov (United States)

    Fouladi Osgouei, Hojjatollah; Zarghami, Mahdi; Ashouri, Hamed

    2016-04-01

    The availability of spatial, high-resolution rainfall data is one of the most essential needs in the study of water resources. These data are extremely valuable in providing flood awareness for dense urban and industrial areas. The first part of this paper applies an optimization-based method to the calibration of radar data based on ground rainfall gauges. Then, the climatological Z-R relationship for the Sahand radar, located in the East Azarbaijan province of Iran, with the help of three adjacent rainfall stations, is obtained. The new climatological Z-R relationship with a power-law form shows acceptable statistical performance, making it suitable for radar-rainfall estimation by the Sahand radar outputs. The second part of the study develops a new heterogeneous random-cascade model for spatially disaggregating the rainfall data resulting from the power-law model. This model is applied to the radar-rainfall image data to disaggregate rainfall data with coverage area of 512 × 512 km2 to a resolution of 32 × 32 km2. Results show that the proposed model has a good ability to disaggregate rainfall data, which may lead to improvement in precipitation forecasting, and ultimately better water-resources management in this arid region, including Urmia Lake.

  17. Disaggregating radar-derived rainfall measurements in East Azarbaijan, Iran, using a spatial random-cascade model

    Science.gov (United States)

    Fouladi Osgouei, Hojjatollah; Zarghami, Mahdi; Ashouri, Hamed

    2017-07-01

    The availability of spatial, high-resolution rainfall data is one of the most essential needs in the study of water resources. These data are extremely valuable in providing flood awareness for dense urban and industrial areas. The first part of this paper applies an optimization-based method to the calibration of radar data based on ground rainfall gauges. Then, the climatological Z-R relationship for the Sahand radar, located in the East Azarbaijan province of Iran, with the help of three adjacent rainfall stations, is obtained. The new climatological Z-R relationship with a power-law form shows acceptable statistical performance, making it suitable for radar-rainfall estimation by the Sahand radar outputs. The second part of the study develops a new heterogeneous random-cascade model for spatially disaggregating the rainfall data resulting from the power-law model. This model is applied to the radar-rainfall image data to disaggregate rainfall data with coverage area of 512 × 512 km2 to a resolution of 32 × 32 km2. Results show that the proposed model has a good ability to disaggregate rainfall data, which may lead to improvement in precipitation forecasting, and ultimately better water-resources management in this arid region, including Urmia Lake.

  18. Will the aerosol derived from the OCM satellite sensor be representative of the aerosol over Goa?

    Digital Repository Service at National Institute of Oceanography (India)

    Talaulikar, M.; Suresh, T.; Rodrigues, A.; Desa, E.; Chauhan, P.

    is within a tolerable limit considering the error in the instrument, measurement and satellite-derived values. Seasonal variations are also observed of the variations of the aerosol data at noon from those in the morning and evening. Variations of data...

  19. Using satellite-based evapotranspiration estimates to improve the structure of a simple conceptual rainfall-runoff model

    Science.gov (United States)

    Roy, Tirthankar; Gupta, Hoshin V.; Serrat-Capdevila, Aleix; Valdes, Juan B.

    2017-02-01

    Daily, quasi-global (50° N-S and 180° W-E), satellite-based estimates of actual evapotranspiration at 0.25° spatial resolution have recently become available, generated by the Global Land Evaporation Amsterdam Model (GLEAM). We investigate the use of these data to improve the performance of a simple lumped catchment-scale hydrologic model driven by satellite-based precipitation estimates to generate streamflow simulations for a poorly gauged basin in Africa. In one approach, we use GLEAM to constrain the evapotranspiration estimates generated by the model, thereby modifying daily water balance and improving model performance. In an alternative approach, we instead change the structure of the model to improve its ability to simulate actual evapotranspiration (as estimated by GLEAM). Finally, we test whether the GLEAM product is able to further improve the performance of the structurally modified model. Results indicate that while both approaches can provide improved simulations of streamflow, the second approach also improves the simulation of actual evapotranspiration significantly, which substantiates the importance of making diagnostic structural improvements to hydrologic models whenever possible.

  20. The contribution of tropical cyclones to rainfall in Mexico

    Science.gov (United States)

    Agustín Breña-Naranjo, J.; Pedrozo-Acuña, Adrián; Pozos-Estrada, Oscar; Jiménez-López, Salma A.; López-López, Marco R.

    Investigating the contribution of tropical cyclones to the terrestrial water cycle can help quantify the benefits and hazards caused by the rainfall generated from this type of hydro-meteorological event. Rainfall induced by tropical cyclones can enhance both flood risk and groundwater recharge, and it is therefore important to characterise its minimum, mean and maximum contributions to a region or country's water balance. This work evaluates the rainfall contribution of tropical depressions, storms and hurricanes across Mexico from 1998 to 2013 using the satellite-derived precipitation dataset TMPA 3B42. Additionally, the sensitivity of rainfall to other datasets was assessed: the national rain gauge observation network, real-time satellite rainfall and a merged product that combines rain gauges with non-calibrated space-borne rainfall measurements. The lower Baja California peninsula had the highest contribution from cyclonic rainfall in relative terms (∼40% of its total annual rainfall), whereas the contributions in the rest of the country showed a low-to-medium dependence on tropical cyclones, with mean values ranging from 0% to 20%. In quantitative terms, southern regions of Mexico can receive more than 2400 mm of cyclonic rainfall during years with significant TC activity. Moreover, (a) the number of tropical cyclones impacting Mexico has been significantly increasing since 1998, but cyclonic contributions in relative and quantitative terms have not been increasing, and (b) wind speed and rainfall intensity during cyclones are not highly correlated. Future work should evaluate the impacts of such contributions on surface and groundwater hydrological processes and connect the knowledge gaps between the magnitude of tropical cyclones, flood hazards, and economic losses.

  1. Air-sea Fluxes Derived From Satellite Data: Achievements and Perspectives

    Science.gov (United States)

    Schulz, J.; Andersson, A.; Bakan, S.; Fennig, K.; Klepp, C. P.; Klocke, D.

    2007-05-01

    Time series of satellite data, suitable for retrieval of water cycle components over the ocean, approach lengths that make them attractive to be used for the analysis of inter-annual variability and trends. Additionally, they can serve as an evaluation tool for model based atmospheric reanalyses and climate models. Based on the example of the satellite-derived Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data set (HOAPS-3) the presentation will contain some comparisons to ERA40 and control runs of the ECHAM5 climate model to elucidate the current status of similarities and differences between models and observations. The HOAPS-3 data set utilized the NOAA pathfinder sea surface temperature data set and several retrieval schemes for basic variables as near-surface humidity and wind speed applicable to the series of SSM/I instruments. The data set covers a time span from 1987-2005. Satellite based data sets are constructed from a series of instruments flying on successive platforms, e.g. SSM/I on the DMSP series and AVHRR on the NOAA series. To use those data for establishing time series suitable for trend detection a very careful correction of individual instrument and satellite platform errors has to be performed. Examples for those errors are orbit decay of the satellite that changes zenith angles over time and diurnal drift of the satellite platform aliasing in the diurnal cycle. Despite the high quality of some of those corrections a inter- sensor homogenization to a reference platform is unavoidable. The presentation will give a short review on used techniques and their advantages and disadvantages. Finally, the presentation will discuss the idea to use infrared sounding data from the IASI instrument on the MetOp satellite to improve current near-surface humidity and temperature retrievals and ways to include error information to the data sets.

  2. Calibration of commercial microwave link derived- rainfall and its relevance to flash flood occurrence in the Dead Sea area

    Science.gov (United States)

    Eshel, Adam; Alpert, Pinhas; Raich, Roi; Laronne, Jonathan; Merz, Ralf; Geyer, Stefan; Corsmeier, Ulrich

    2016-04-01

    Flash floods are a common phenomenon in arid and semi-arid areas such as the Dead Sea. These floods are generated due to a combination of short lasting, yet intense rainfall and typical low infiltration rates. The rare flow events in ephemeral rivers have significant importance in the replenishment of groundwater via transmission losses and in sustaining the vivid ecology of drylands. In some cases, flash floods cause severe damage to infrastructure as well as to private property, constituting a threat to human life. The temporal variation of rainfall intensity is the main driver generating the majority of flash floods in the Judean Desert, hence its monitoring is crucial in this area as in other remote arid areas worldwide. Cellular communication towers are profusely located. Commercial Microwave Links (CML) attenuation data obtained by cellular companies can be used for environmental monitoring. Rain is one of the most effective meteorological phenomena to attenuate a CML signal which, unlike radar backscatter, relates to near-surface conditions and is, therefore, suitable for surface hydrology. A 16 km CML crosses the Wadi Ze'elim drainage basin (~250 square kilometers), at the outlet of which the discharge is calculated using the Manning formula. The hydrometric data include accurate longitudinal and cross sectional measurements, water level and importantly mean water surface velocity when present during a flash flood. The latter is first-ever obtained in desert flash floods by portable, radar-based surface velocimetry. Acquisition of water velocity data is essential to avoid assuming a constant roughness coefficient, thereby more accurately calculating water discharge. Calibrating the CML-rain intensity, derived from the International Telecommunication Union (ITU)'s power law, is necessary to correlate the surface hydrologic response to the link. Our calibration approach is as follows: all the Israel Meteorological Service C-band radar cells over the CML

  3. Satellite Derived Volcanic Ash Product Inter-Comparison in Support to SCOPE-Nowcasting

    Science.gov (United States)

    Siddans, Richard; Thomas, Gareth; Pavolonis, Mike; Bojinski, Stephan

    2016-04-01

    In support of aeronautical meteorological services, WMO organized a satellite-based volcanic ash retrieval algorithm inter-comparison activity, to improve the consistency of quantitative volcanic ash products from satellites, under the Sustained, Coordinated Processing of Environmental Satellite Data for Nowcasting (SCOPEe Nowcasting) initiative (http:/ jwww.wmo.int/pagesjprogjsatjscopee nowcasting_en.php). The aims of the intercomparison were as follows: 1. Select cases (Sarychev Peak 2009, Eyjafyallajökull 2010, Grimsvötn 2011, Puyehue-Cordón Caulle 2011, Kirishimayama 2011, Kelut 2014), and quantify the differences between satellite-derived volcanic ash cloud properties derived from different techniques and sensors; 2. Establish a basic validation protocol for satellite-derived volcanic ash cloud properties; 3. Document the strengths and weaknesses of different remote sensing approaches as a function of satellite sensor; 4. Standardize the units and quality flags associated with volcanic cloud geophysical parameters; 5. Provide recommendations to Volcanic Ash Advisory Centers (VAACs) and other users on how to best to utilize quantitative satellite products in operations; 6. Create a "road map" for future volcanic ash related scientific developments and inter-comparison/validation activities that can also be applied to SO2 clouds and emergent volcanic clouds. Volcanic ash satellite remote sensing experts from operational and research organizations were encouraged to participate in the inter-comparison activity, to establish the plans for the inter-comparison and to submit data sets. RAL was contracted by EUMETSAT to perform a systematic inter-comparison of all submitted datasets and results were reported at the WMO International Volcanic Ash Inter-comparison Meeting to held on 29 June - 2 July 2015 in Madison, WI, USA (http:/ /cimss.ssec.wisc.edujmeetings/vol_ash14). 26 different data sets were submitted, from a range of passive imagers and spectrometers and

  4. Variational assimilation of satellite cloud water/ice path and microphysics scheme sensitivity to the assimilation of a rainfall case

    Science.gov (United States)

    Chen, Yaodeng; Zhang, Ruizhi; Meng, Deming; Min, Jinzhong; Zhang, Lina

    2016-10-01

    Hydrometeor variables (cloud water and cloud ice mixing ratios) are added into the WRF three-dimensional variational assimilation system as additional control variables to directly analyze hydrometeors by assimilating cloud observations. In addition, the background error covariance matrix of hydrometeors is modeled through a control variable transform, and its characteristics discussed in detail. A suite of experiments using four microphysics schemes (LIN, SBU-YLIN, WDM6 and WSM6) are performed with and without assimilating satellite cloud liquid/ice water path. We find analysis of hydrometeors with cloud assimilation to be significantly improved, and the increment and distribution of hydrometeors are consistent with the characteristics of background error covariance. Diagnostic results suggest that the forecast with cloud assimilation represents a significant improvement, especially the ability to forecast precipitation in the first seven hours. It is also found that the largest improvement occurs in the experiment using the WDM6 scheme, since the assimilated cloud information can sustain for longer in this scheme. The least improvement, meanwhile, appears in the experiment using the SBU-YLIN scheme.

  5. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    Science.gov (United States)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.

  6. Satellite derived precipitation and freshwater flux variability and its dependence on the North Atlantic Oscillation

    Science.gov (United States)

    Andersson, Axel; Bakan, Stephan; Graßl, Hartmut

    2010-08-01

    The variability of satellite retrieved precipitation and freshwater flux from the `Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data' (HOAPS) is assessed with special emphasis on the `North Atlantic Oscillation' (NAO). To cover also land areas, a novel combination of the satellite derived precipitation climatology with the rain gauge based `Full Data Reanalysis Product Version 4', of the `Global Precipitation Climatology Centre' (GPCC) is used. This yields unique high-resolution, quasi-global precipitation fields compiled from two independent data sources. Over the ocean, the response of the freshwater balance and the related parameters to the NAO is investigated for the first time by using a purely satellite based data set. A strong dependence of precipitation patterns to the state of the NAO is found. On synoptic scale this is in accordance with earlier findings by other satellite based and reanalysis products. Furthermore, the consistency of the combined HOAPS-3/GPCC data set allows also detailed regional analyses of precipitation patterns. The response of HOAPS-3 freshwater flux to the NAO is dominated by precipitation at mid and high latitudes, while for the subtropical regions the feedback of the evaporation is stronger.

  7. 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.

  8. Satellite derived integrated water vapor and rain intensity patterns - Indicators of rapid cyclogenesis

    Science.gov (United States)

    Mcmurdie, Lynn; Katsaros, Kristina

    1992-01-01

    We examine integrated water vapor fields and rain intensity patterns derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) for several rapidly deepening and non-rapidly deepening midlatitude cyclones in the North Atlantic. Our goal is to identify features in the satellite data unique to the rapidly deepening cases, and to explore how these data can potentially be used in the analysis and forecasting of these events.

  9. Satellite derived integrated water vapor and rain intensity patterns: Indicators of rapid cyclogenesis

    Science.gov (United States)

    Mcmurdie, Lynn; Katsaros, Kristina

    1992-01-01

    We examine integrated water vapor fields and rain intensity patterns derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) for several rapidly deepening and non-rapidly deepening midlatitude cyclones in the North Atlantic. Our goal is to identify features in the satellite data unique to the rapidly deepening cases, and to explore how these data can potentially be used in the analysis and forecasting of these events.

  10. Comparison of advanced Arctic Ocean model sea ice fields to satellite derived measurements

    OpenAIRE

    Dimitriou, David S.

    1998-01-01

    Approved for public release; distribution is unlimited Numerical models have proven integral to the study of climate dynamics. Sea ice models are critical to the improvement of general circulation models used to study the global climate. The object of this study is to evaluate a high resolution ice-ocean coupled model by comparing it to derived measurements from SMMR and SSM/I satellite observations. Utilized for this study was the NASA Goddard Space Flight (GSFC) Sea Ice Concentration Dat...

  11. Comparison of rainfall based SPI drought indices with SMDI and ETDI indices derived from a soil water budget model

    Science.gov (United States)

    Houcine, A.; Bargaoui, Z.

    2012-04-01

    Modelling soil water budget is a key issue for assessing drought awareness indices based on soil moisture estimation. The aim of the study is to compare drought indices based on rainfall time series to those based on soil water content time series and evapotranspiration time series. To this end, a vertically averaged water budget over the root zone is implemented to assist the estimation of evapotranspiration flux. A daily time step is adopted to run the water budget model for a lumped watershed of 250 km2 under arid climate where recorded meteorological and hydrological data are available for a ten year period. The water balance including 7 parameters is computed including evapotranspiration, runoff and leakage. Soil properties related parameters are derived according to pedo transfer functions while two remaining parameters are considered as data driven and are subject to calibration. The model is calibrated using daily hydro meteorological data (solar radiation, air temperature, air humidity, mean areal rainfall) as well as daily runoff records and also average annual (or regional) evapotranspiration. The latter is estimated using an empirical sub-model. A set of acceptable solutions is identified according to the values of the Nash coefficients for annual and decadal runoffs as well as the relative bias for average annual evapotranspiration. Using these acceptable solutions several drought indices are computed: SPI (standard precipitation index), SMDI (soil moisture deficit index) and ETDI (evapotranspiration deficit index). While SPI indicators are based only on monthly precipitation time series, SMDI are based on weekly mean soil water content as computed by the hydrological model. On the other hand ETDI indices are based on weekly mean potential and actual evapotranspirations as estimated by the meteorological and hydrological models. For SPI evaluation various time scales are considered from one to twelve months (SPI1, SPI3, SPI6, SPI9 and SPI12). For all

  12. A southern Africa harmonic spline core field model derived from CHAMP satellite data

    Science.gov (United States)

    Nahayo, E.; Kotzé, P. B.; McCreadie, H.

    2015-02-01

    The monitoring of the Earth's magnetic field time variation requires a continuous recording of geomagnetic data with a good spatial coverage over the area of study. In southern Africa, ground recording stations are limited and the use of satellite data is needed for the studies where high spatial resolution data is required. We show the fast time variation of the geomagnetic field in the southern Africa region by deriving an harmonic spline model from CHAMP satellite measurements recorded between 2001 and 2010. The derived core field model, the Southern Africa Regional Model (SARM), is compared with the global model GRIMM-2 and the ground based data recorded at Hermanus magnetic observatory (HER) in South Africa and Tsumeb magnetic observatory (TSU) in Namibia where the focus is mainly on the long term variation of the geomagnetic field. The results of this study suggest that the regional model derived from the satellite data alone can be used to study the small scale features of the time variation of the geomagnetic field where ground data is not available. In addition, these results also support the earlier findings of the occurrence of a 2007 magnetic jerk and rapid secular variation fluctuations of 2003 and 2004 in the region.

  13. Spatial Correlation of Satellite-Derived PM2.5 with Hospital Admissions for Respiratory Diseases

    Directory of Open Access Journals (Sweden)

    Ching-Ju Liu

    2016-11-01

    Full Text Available Respiratory diseases, particularly allergic rhinitis, are spatially and temporally correlated with the ground PM2.5 level. A study of the correlation between the two factors should therefore account for spatiotemporal variations. Satellite observation has the advantage of wide spatial coverage over pin-point style ground-based in situ monitoring stations. Therefore, the current study used both ground measurement and satellite data sets to investigate the spatial and temporal correlation of satellite-derived PM2.5 with respiratory diseases. This study used 4-year satellite data and PM2.5 levels of the period at eight stations in Taiwan to obtain the spatial and temporal relationship between aerosol optical depth (AOD and PM2.5. The AOD-PM2.5 model was further examined using the cross-validation (CV technique and was found to have high reliability compared with similar models. The model was used to obtain satellite-derived PM2.5 levels and to analyze the hospital admissions for allergic rhinitis in 2008. The results suggest that adults (18–65 years and children (3–18 years are the most vulnerable groups to the effect of PM2.5 compared with infants and elderly people. This result may be because the two affected age groups spend longer time outdoors. This result may also be attributed to the long-range PM2.5 transport from upper stream locations and the atmospheric circulation patterns, which are significant in spring and fall. The results of the current study suggest that additional environmental factors that might be associated with respiratory diseases should be considered in future studies.

  14. Method for seasonal precipitation reconstruction derived from snow and rainfall archives in Qing Dynasty:A case study in Shijiazhuang

    Institute of Scientific and Technical Information of China (English)

    ZHENG Jingyun; HAO Zhixin; GE Quansheng

    2004-01-01

    Two methods to reconstruct seasonal precipitation are developed in terms of the soil surface water balance and field infiltration experiment by artificial rainfall. Seasonal and annual precipitation for the period of 1736~1910 are reconstructed from snow and rainfall archives in the Qing Dynasty through both methods. The seasonal precipitation series from 1736 to 2000 is also established. The results show that the time series of seasonal precipitation obtained from both methods are statistically significant and consistent, implying that the seasonal precipitation can be reconstructed accurately from snow and rainfall archives in the Qing Dynasty by the above two methods, and thus the Chinese precipitation data in a large area would be extended to the early 18th century from 20th century (instrumental observation period).

  15. Are there urban signatures in the tropospheric ozone column products derived from satellite measurements?

    Directory of Open Access Journals (Sweden)

    J. Kar

    2010-06-01

    Full Text Available In view of the proposed geostationary satellite missions to monitor air quality from space, it is important to first assess the capability of the current suite of satellite instruments to provide information on the urban scale pollution. We explore the possibility of detecting urban signatures in the tropospheric column ozone data derived from Total Ozone Mapping Spectrometer (TOMS/Solar Backscattered Ultraviolet (SBUV and Ozone Monitoring Instrument (OMI/Microwave Limb Sounder (MLS satellite data. We find that distinct isolated plumes of tropospheric ozone near several large and polluted cities around the world may be detected in these data sets. The ozone plumes generally correspond with the tropospheric column NO2 plumes around these cities as observed by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY instrument. Similar plumes are also seen in tropospheric mean ozone mixing ratio distribution after accounting for the surface and tropopause pressure variations. The total column ozone retrievals indicate fairly significant sensitivity to the lower troposphere over the polluted land areas, which might help explain these detections. These results indicate that ultraviolet (UV measurements may, in principle, be able to capture the urban signatures and may have implications for future missions using geostationary satellites.

  16. Resolving orographic rainfall on the Indian west coast

    Digital Repository Service at National Institute of Oceanography (India)

    Suprit, K.; Shankar, D.

    consequence of the small scale of these west-coast rivers. This need for estimating the freshwater discharge into the seas around India led Shankar et al. (2004) to assemble a framework for estimating river discharge. The framework was based on Terrestrial... at various spatial and temporal scales. Some of these data sets are based on rain-gauge measurements and some on satellite estimates; some of them use model- derived reanalysis data. We tested three available rainfall data sets to see if these rainfall data...

  17. Application of satellite derived information for disaster risk reduction: vulnerability assessment for southwest coast of Pakistan

    Science.gov (United States)

    Rafiq, Lubna; Blaschke, Thomas; Zeil, Peter

    2010-10-01

    The SW-coast of Pakistan is vulnerable to natural disasters, such as cyclones and tsunamis. Lack of spatially referenced information is a major hinder for proper disaster risk management programs in Pakistan, but satellite remote sensing being reliable, fast and spatially referenced information can be used as an important component in various natural disaster risk reduction activities. This study aimed to investigate vulnerability of coastal communities to cyclone and tsunamis based on satellite derived information. It is observed that SPOT-5 is relevant source on threatened features with respect to certain vulnerabilities like road, settlements, infrastructure and used in preparation of hazard zonation and vulnerability maps. Landsat ETM found very useful in demarcation of flood inundated areas. The GIS integrated evaluation of LANDSAT and ASTER GDEM helps identify low lying areas most susceptible to flooding and inundation by cyclone surges and tsunamis. The GIS integrated evaluation of SPOT, LANDSAT and ASTER GDEM data helps identify areas and infrastructure most vulnerable to cyclone surges and tsunami. Additionally, analysis of the vulnerability of critical infrastructures (schools, hospitals) within hazard zones provides indicators for the degree of spatial exposure to disaster. Satellite derived information in conjunction with detailed surveys of hazard prone areas can provide comprehensive vulnerability and risk analysis.

  18. Trends and Bioclimatic Assessment of Extreme Indices: Emerging Insights for Rainfall Derivative Crop Microinsurance in Central-West Nigeria

    Science.gov (United States)

    Awolala, D. O.

    2015-12-01

    Scientific predictions have forecasted increasing economic losses by which farming households will be forced to consider new adaptation pathways to close the food gap and be income secure. Pro-poor adaptation planning decisions therefore must rely on location-specific details from systematic assessment of extreme climate indices to provide template for most suitable financial adaptation instruments. This paper examined critical loss point to water stress in maize production and risk-averse behaviour to extreme local climate in Central West Nigeria. Trends of extreme indices and bio-climatic assessment based on RClimDex for numerical weather predictions were carried out using a 3-decade time series daily observational climate data of the sub-humid region. The study reveals that the flowering and seed formation stage was identified as the most critical loss point when seed formation is a function of per unit soil water available for uptake. The sub-humid has a bi-modal rainfall pattern but faces longer dry spell with a fast disappearing mild climate measured by budyko evaporation of 80.1%. Radiation index of dryness of 1.394 confirms the region is rapidly becoming drier at an evaporation rate of 949 mm/year and rainfall deficit of 366 mm/year. Net primary production from rainfall is fast declining by 1634 g(DM)/m2/year. These conditions influenced by monthly rainfall uncertainties are associated with losses of standing crops because farmers are uncertain of rainfall probability distribution especially during most important vegetative stage. In a simulated warmer climate, an absolute dryness of months was observed compared with 4 dry months in a normal climate which explains triggers of food deficits and income losses. Positive coefficients of tropical nights (TR20), warm nights (TN90P) and warm days (TX90P), and the negative coefficient of cold days (TX10P) with time are significant at P<0.05. The increasing gradient of warm spell indicator (WSDI), the decreasing

  19. Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

    Science.gov (United States)

    Hall, Dorothy K.; Box, Jason E.; Casey, Kimberly A.; Hook, Simon J.; Shuman, Christopher A.; Steffen, Konrad

    2008-01-01

    The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

  20. Utilization of web-based stationary rainfall data for near-real-time derivation of spatial landslide susceptibility

    Science.gov (United States)

    Canli, Ekrem; Glade, Thomas; Loigge, Bernd

    2016-04-01

    Scarcity of high-quality meteorological data is often referred to as one of the main constraints for performing real-time landslide forecasting. Meteorological data may be expensive or not up-to-date any more soon after it is acquired. However, the internet is a great source of freely available, high quality real-time weather data from different sources. Web scraping has emerged into a highly valuable technique for utilizing information from public websites. Hereby, web scraping is the process of automatically gathering data from the internet, extracting these data according to required needs, storing the selected data and using those self-generated databases for further analysis. This technique is of great value, in particular for weather data that is released regularly in short intervals to the public, but may be applicable to any other type of continuously released data. By applying these techniques, research institutions in developing countries may be able to generate their own free data without the need of purchasing expensive, ready-made weather data. However, some weather data providers already offer application programming interfaces (API) that facilitate access to real-time weather data, but those usually have to be purchased. Here we present an approach for integrating web-based rainfall data from different sources into an automated workflow. This workflow ranges from the query of near-real-time data to spatially interpolating those rain gauge measurements into a continuous rainfall raster. Subsequently, this raster is handed over into a dynamic, physical-based landslide model for generating hourly distributed landslide susceptibility maps on a regional scale. Future work involves the establishment or regional intensity-duration rainfall thresholds that are continuously evaluated against the distributed rainfall patterns based on real-time rainfall data.

  1. Calibration and evaluation of a flood forecasting system: Utility of numerical weather prediction model, data assimilation and satellite-based rainfall

    Science.gov (United States)

    Yucel, I.; Onen, A.; Yilmaz, K. K.; Gochis, D. J.

    2015-04-01

    A fully-distributed, multi-physics, multi-scale hydrologic and hydraulic modeling system, WRF-Hydro, is used to assess the potential for skillful flood forecasting based on precipitation inputs derived from the Weather Research and Forecasting (WRF) model and the EUMETSAT Multi-sensor Precipitation Estimates (MPEs). Similar to past studies it was found that WRF model precipitation forecast errors related to model initial conditions are reduced when the three dimensional atmospheric data assimilation (3DVAR) scheme in the WRF model simulations is used. A comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow is then made. The ten rainfall-runoff events that occurred in the Black Sea Region were used for testing and evaluation. With the availability of streamflow data across rainfall-runoff events, the calibration is only performed on the Bartin sub-basin using two events and the calibrated parameters are then transferred to other neighboring three ungauged sub-basins in the study area. The rest of the events from all sub-basins are then used to evaluate the performance of the WRF-Hydro system with the calibrated parameters. Following model calibration, the WRF-Hydro system was capable of skillfully reproducing observed flood hydrographs in terms of the volume of the runoff produced and the overall shape of the hydrograph. Streamflow simulation skill was significantly improved for those WRF model simulations where storm precipitation was accurately depicted with respect to timing, location and amount. Accurate streamflow simulations were more evident in WRF model simulations where the 3DVAR scheme was used compared to when it was not used. Because of substantial dry bias feature of MPE, as compared with surface rain gauges, streamflow derived using this precipitation product is in general very poor. Overall, root mean squared errors for runoff were reduced by

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

  7. An evaluation of the MSG-based operational rainfall product H05 based on a comparison with the raingauges network in Italy

    Science.gov (United States)

    Campo, Lorenzo

    2016-04-01

    The interest for the monitoring and nowcasting/forecasting the rainfall on large areas is nowadays well established all around the world. The applications span from agriculture purposes to flood and drought monitoring forecasts, with particular interest in flash floods and relatively short but intense events that can cause consistent damages to urban settlements, industrial facilities and agricultural production. While the main and most reliable tool for the rainfall monitoring remains the raingauge, with opportune networks and operational data transmission chains, the extreme spatial variability of the rainfall fields shows all the limits of such instruments. Different alternatives exist, such as meteorological radar and satellite-derived rainfall, that allows a monitoring on medium-large areas with the production of continuous and instantaneous maps at high temporal frequencies. However, these alternatives present different problems on the reliability of the data, both on the rainfall intensity and on the actual presence of rainfall. In this work, the data time series of the Italian raingauges network are employed for an evaluation of the operational satellite rainfall product H05, produced by the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF), and based on MSG (Meteosat Second Generation) satellite platform. The analysis is constituted by a series of synthetic indexes that compare the rainfall field produced by satellite with the actual point observations obtained by the ground sensors network. The analysis was conducted on the whole Italian territory, in the period 2009-2013.

  8. Can satellite-derived water surface changes be used to calibrate a hydrodynamic model?

    Science.gov (United States)

    Revilla-Romero, Beatriz; Beck, Hylke; Salamon, Peter; Burek, Peter; de Roo, Ad; Thielen, Jutta

    2015-04-01

    The limited availability of recent ground observational data is one of the main challenges for validation of hydrodynamic models. This is especially relevant for real-time global applications such as flood forecasting models. In this study, we aim to use remotely-sensed data from the Global Flood Detection System (GFDS) as a proxy of river discharge time series and test its value through calibration of the hydrological model LISFLOOD. This was carried out for the time period 1998-2010 at 40 sites in Africa, Europe, North America and South America by calibrating the parameters that control the flow routing and groundwater processes. We compared the performance of the calibrated simulated discharge time series that used satellite-derived data with the ground discharge time series. Furthermore, we compared it with the independent calibrated run that used ground data and also, to the non-calibrated simulated discharge time series. The non-calibrated set up used a set of parameters which values were predefined by expert-knowledge. This is currently being used by the LISFLOOD set up model embedded in the pre-operational Global Flood Awareness System (GloFAS). The results of this study showed that the satellite surface water changes from the Global Flood Detection System can be used as a proxy of river discharge data, through the demonstration of its added value for model calibration and validation. Using satellite-derived data, the skill scores obtained by the calibrated simulated model discharge improved when comparing to non-calibrated simulated time series. Calibration, post-processing and data assimilation strategies of satellite data as a proxy for streamflow data within the global hydrological model are outlined and discussed.

  9. Satellite-derived sea surface height and sea surface wind data fusion for spilled oil tracking

    Science.gov (United States)

    Kozai, Katsutoshi

    2003-12-01

    An attempt is made to estimate the trajectory of the spilled oil from the sunken tanker Nakhodka occurred on January 2, 1997 in the Japan Sea by fusing two microwave sensor data, namely ERS-2 altimeter and ADEOS/NSCAT scatterometer data. In this study 'fusion' is defined as the method of more reliable prediction for the trajectory of spilled oil than before. Geostrophic current vectors are derived from ERS-2 altimeter and wind-induced drift vectors are derived from ADEOS/NSCAT scatterometer data These two different satellite-derived vectors are 'fused' together in the surface current model to estimate and evaluate the trajectory of spilled oil from the sunken tanker Nakhodka. The distribution of component of spill vector is mostly accounted for by the distribution of geostrophic velocity component during the study period with some discrepancies during March, 1997.

  10. Patterns of Precipitation and Convection Occurrence over the Mediterranean Basin Derived from a Decade of Microwave Satellite Observations

    Directory of Open Access Journals (Sweden)

    Bahjat Alhammoud

    2014-05-01

    lower than those derived from AMSU-B. These results are potentially valuable to evaluate the rainfall parameterization in weather and climate models and to constrain ocean models.

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

    Science.gov (United States)

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

    2010-01-01

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

  12. Rainfall generation

    Science.gov (United States)

    Sharma, Ashish; Mehrotra, Raj

    This chapter presents an overview of methods for stochastic generation of rainfall at annual to subdaily time scales, at single- to multiple-point locations, and in a changing climatic regime. Stochastic rainfall generators are used to provide inputs for risk assessment of natural or engineering systems that can undergo failure under sustained (high or low) extremes. As a result, generation of rainfall has evolved to provide options that adequately represent such conditions, leading to sequences that exhibit low-frequency variability of a nature similar to the observed rainfall. The chapter consists of three key sections: the first two outlining approaches for rainfall generation using endogenous predictor variables and the third highlighting approaches for generation using exogenous predictors often simulated to represent future climatic conditions. The first section presents approaches for generation of annual and seasonal rainfall and daily rainfall, both at single-point locations and multiple sites, with an emphasis on alternatives that ensure appropriate representation of low-frequency variability in the generated rainfall sequences. The second section highlights advancements in the subdaily rainfall generation procedures including commonly used approaches for daily to subdaily rainfall generation. The final section (generation using exogenous predictors) presents a range of alternatives for stochastic downscaling of rainfall for climate change impact assessments of natural and engineering systems. We conclude the chapter by outlining some of the key challenges that remain to be addressed, especially in generation under climate change conditions, with an emphasis on the importance of incorporating uncertainty present in both measurements and models, in the rainfall sequences that are generated.

  13. Model-simulated and Satellite-derived Leaf Area Index (LAI) Comparisons Across Multiple Spatial Scales

    Science.gov (United States)

    Iiames, J. S., Jr.; Cooter, E. J.

    2016-12-01

    Leaf Area Index (LAI) is an important parameter in assessing vegetation structure for characterizing forest canopies over large areas at broad spatial scales using satellite remote sensing data. However, satellite-derived LAI products can be limited by obstructed atmospheric conditions yielding sub-optimal values, or complete non-returns. The United States Environmental Protection Agency's Exposure Methods and Measurements and Computational Exposure Divisions are investigating the viability of supplemental modelled LAI inputs into satellite-derived data streams to support various regional and local scale air quality models for retrospective and future climate assessments. In this present study, one-year (2002) of plot level stand characteristics at four study sites located in Virginia and North Carolina (USA) are used to calibrate species-specific plant parameters in a semi-empirical biogeochemical model. The Environmental Policy Integrated Climate (EPIC) model was designed primarily for managed agricultural field crop ecosystems, but also includes managed woody species that span both xeric and mesic sites (e.g., mesquite, pine, oak, etc.). LAI was simulated using EPIC at a 4 km2 and 12 km2 grid coincident with the regional Community Multiscale Air Quality Model (CMAQ) grid. LAI comparisons were made between model-simulated and MODIS-derived LAI. Field/satellite-upscaled LAI was also compared to the corresponding MODIS LAI value. Preliminary results show field/satellite-upscaled LAI (1 km2) was 1.5 to 3 times smaller than that with the corresponding 1 km2 MODIS LAI for all four sites across all dates, with the largest discrepancies occurring at leaf-out and leaf senescence periods. Simulated LAI/MODIS LAI comparison results will be presented at the conference. Disclaimer: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S. Environmental Protection Agency funded and conducted the research described in this paper. Although

  14. 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

  15. Intercomparison of planetary-scale diagnostics derived from separate satellite and radiosonde time-mean temperature fields

    Science.gov (United States)

    Miles, T.; Chapman, W. A.

    1984-01-01

    The planetary-scale components of the extratropical Northern Hemisphere troposphere-stratosphere 1973-74 winter circulation are diagnosed using separate time-mean temperature fields based on radiosonde and satellite observations. Meridional cross-sections of zonal wind together with, for zonal wavenumbers 1, 2 and 3, the streamfunction amplitude, phase and Eliassen-Palm flux are displayed, with the relative accuracy of the satellite-derived diagnostics assessed through comparison with the 'ground-truth' radiosonde information. The satellite and radiosonde diagnostics compare most favourably in terms of zonal wind speed and shear, direction of wave propagation and meridional wave structure - all of which are closely related to the differential properties of the atmospheric temperature field. The intensity of the satellite-derived patterns of tropospheric wave propagation is underestimated due to the effects of spatial smoothing and residual cloud contamination present in the satellite radiance measurements.

  16. Spatial disaggregation of satellite-derived irradiance using a high-resolution digital elevation model

    Energy Technology Data Exchange (ETDEWEB)

    Ruiz-Arias, Jose A.; Tovar-Pescador, Joaquin [Department of Physics, University of Jaen (Spain); Cebecauer, Tomas [European Commission, Joint Research Centre, Ispra (Italy); GeoModel s.r.o., Bratislava (Slovakia); Institute of Geography, Slovak Academy of Sciences, Bratislava (Slovakia); Suri, Marcel [European Commission, Joint Research Centre, Ispra (Italy); GeoModel s.r.o., Bratislava (Slovakia)

    2010-09-15

    Downscaling of the Meteosat-derived solar radiation ({proportional_to}5 km grid resolution) is based on decomposing the global irradiance and correcting the systematic bias of its components using the elevation and horizon shadowing that are derived from the SRTM-3 digital elevation model (3 arc sec resolution). The procedure first applies the elevation correction based on the difference between coarse and high spatial resolution. Global irradiance is split into direct, diffuse circumsolar and diffuse isotropic components using statistical models, and then corrections due to terrain shading and sky-view fraction are applied. The effect of reflected irradiance is analysed only in the theoretical section. The method was applied in the eastern Andalusia, Spain, and the validation was carried out for 22 days on April, July and December 2006 comparing 15-min estimates of the satellite-derived solar irradiance and observations from nine ground stations. Overall, the corrections of the satellite estimates in the studied region strongly reduced the mean bias of the estimates for clear and cloudy days from roughly 2.3% to 0.4%. (author)

  17. Preliminary survey on site-adaptation techniques for satellite-derived and reanalysis solar radiation datasets

    Energy Technology Data Exchange (ETDEWEB)

    Polo, J.; Wilbert, S.; Ruiz-Arias, J. A.; Meyer, R.; Gueymard, C.; Súri, M.; Martín, L.; Mieslinger, T.; Blanc, P.; Grant, I.; Boland, J.; Ineichen, P.; Remund, J.; Escobar, R.; Troccoli, A.; Sengupta, M.; Nielsen, K. P.; Renne, D.; Geuder, N.; Cebecauer, T.

    2016-07-01

    At any site, the bankability of a projected solar power plant largely depends on the accuracy and general quality of the solar radiation data generated during the solar resource assessment phase. The term 'site adaptation' has recently started to be used in the framework of solar energy projects to refer to the improvement that can be achieved in satellite-derived solar irradiance and model data when short-term local ground measurements are used to correct systematic errors and bias in the original dataset. This contribution presents a preliminary survey of different possible techniques that can improve long-term satellite-derived and model-derived solar radiation data through the use of short-term on-site ground measurements. The possible approaches that are reported here may be applied in different ways, depending on the origin and characteristics of the uncertainties in the modeled data. This work, which is the first step of a forthcoming in-depth assessment of methodologies for site adaptation, has been done within the framework of the International Energy Agency Solar Heating and Cooling Programme Task 46 'Solar Resource Assessment and Forecasting.'

  18. 4-D Cloud Water Content Fields Derived from Operational Satellite Data

    Science.gov (United States)

    Smith, William L., Jr.; Minnis, Patrick

    2010-01-01

    In order to improve operational safety and efficiency, the transportation industry, including aviation, has an urgent need for accurate diagnoses and predictions of clouds and associated weather conditions. Adverse weather accounts for 70% of all air traffic delays within the U.S. National Airspace System. The Federal Aviation Administration has determined that as much as two thirds of weather-related delays are potentially avoidable with better weather information and roughly 20% of all aviation accidents are weather related. Thus, it is recognized that an important factor in meeting the goals of the Next Generation Transportation System (NexGen) vision is the improved integration of weather information. The concept of a 4-D weather cube is being developed to address that need by integrating observed and forecasted weather information into a shared 4-D database, providing an integrated and nationally consistent weather picture for a variety of users and to support operational decision support systems. Weather analyses and forecasts derived using Numerical Weather Prediction (NWP) models are a critical tool that forecasters rely on for guidance and also an important element in current and future decision support systems. For example, the Rapid Update Cycle (RUC) and the recently implemented Rapid Refresh (RR) Weather Research and Forecast (WRF) models provide high frequency forecasts and are key elements of the FAA Aviation Weather Research Program. Because clouds play a crucial role in the dynamics and thermodynamics of the atmosphere, they must be adequately accounted for in NWP models. The RUC, for example, cycles at full resolution five cloud microphysical species (cloud water, cloud ice, rain, snow, and graupel) and has the capability of updating these fields from observations. In order to improve the models initial state and subsequent forecasts, cloud top altitude (or temperature, T(sub c)) derived from operational satellite data, surface observations of

  19. High resolution satellite derived erodibility factors for WRF/Chem windblown dust simulations in Argentina

    Science.gov (United States)

    Cremades, Pablo Gabriel; Fernandez, Rafael Pedro; Allend, David; Mulena, Celeste; Puliafito, Salvador Enrique

    2017-04-01

    A proper representation of dust sources is critical to accurately predict atmospheric particle concentrations in regional windblown dust simulations. The Weather Research and Forecasting model with Chemistry (WRF/Chem) includes a topographic-based erodibility map originally conceived for global scale modeling, which fails to identify the geographical location of dust sources in many regions of Argentina. Therefore, this study aims at developing a method to obtain a high-resolution erodibility map suitable for regional or local scale modeling using WRF/Chem. We present two independent approaches based on global methods to estimate soil erodibility using satellite retrievals, i.e. topography from the Shuttle Radar Topography Mission (SRTM) and surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). Simulation results of a severe Zonda wind episode in the arid central-west Argentina serve as bases for the analysis of these methods. Simulated dust concentration at surface level is compared with particulate matter measurements at one site in Mendoza city. In addition, we use satellite aerosol optical depth (AOD) retrievals to investigate model performance in reproducing spatial distribution of dust emissions. The erodibility map based on surface reflectance from MODIS improves the representation of small scale features, and increases the overall dust aerosol loading with respect to the standard map included by default. Simulated concentrations are in good agreement with measurements as well as satellite derived dust spatial distribution.

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

    Science.gov (United States)

    Olsen, Nils; Finlay, Christopher C.; Kotsiaros, Stavros; Tøffner-Clausen, Lars

    2016-07-01

    More than 2 years of magnetic field data taken by the three-satellite constellation mission Swarm are used to derive a model of Earth's magnetic field and its time variation. This model is called SIFMplus. In addition to the magnetic field observations provided by each of the three Swarm satellites, explicit advantage is taken of the constellation aspect of Swarm by including East-West magnetic intensity and vector field gradient information from the lower satellite pair. Along-track differences of the magnetic intensity as well as of the vector components provide further information concerning the North-South gradient. The SIFMplus model provides a description of the static lithospheric field that is very similar to models determined from CHAMP data, up to at least spherical harmonic degree n=75. Also the core field part of SIFMplus, with a quadratic time dependence for n ≤ 6 and a linear time dependence for n=7-15, demonstrates the possibility to determine high-quality field models from only 2 years of Swarm data, thanks to the unique constellation aspect of Swarm. To account for the magnetic signature caused by ionospheric electric currents at polar latitudes we co-estimate, together with the model of the core, lithospheric and large-scale magnetospheric fields, a magnetic potential that depends on quasi-dipole latitude and magnetic local time.

  1. Evaluation of a physically-based snow model with infrared and microwave satellite-derived estimates

    Science.gov (United States)

    Wang, L.

    2013-05-01

    Snow (with high albedo, as well as low roughness and thermal conductivity) has significant influence on the land-atmosphere interactions in the cold climate and regions of high elevation. The spatial and temporal variability of the snow distribution on a basin scale greatly determines the timing and magnitude of spring snowmelt runoff. For improved water resources management, a physically-based distributed snow model has been developed and applied to the upper Yellow River Basin to provide the outputs of snow variables as well as streamflows from 2001 to 2005. Remotely-sensed infrared information from MODIS satellites has been used to evaluate the model's outputs of spatially-distributed snow cover extent (SCE) and land surface temperature (LST); while the simulated snow depth (SD) and snow water equivalent (SWE) have been compared with the microwave information from SSM/I and AMSR-E satellites. In general, the simulated streamflows (including spring snowmelt) agree fairly well with the gauge-based observations; while the modeled snow variables show acceptable accuracies through comparing to various satellite-derived estimates from infrared or microwave information.;

  2. Trends in stratospheric ozone derived from merged SAGE II and Odin-OSIRIS satellite observations

    Directory of Open Access Journals (Sweden)

    A. E. Bourassa

    2014-03-01

    Full Text Available Stratospheric ozone profile measurements from the Stratospheric Aerosol and Gas Experiment (SAGE II satellite instrument (1984–2005 are combined with those from the Optical Spectrograph and InfraRed Imager System (OSIRIS instrument on the Odin satellite (2001–Present to quantify interannual variability and decadal trends in stratospheric ozone between 60° S and 60° N. These data are merged into a multi-instrument, long-term stratospheric ozone record (1984–present by analyzing the measurements during the overlap period of 2002–2005 when both satellite instruments were operational. The variability in the deseasonalized time series is fit using multiple linear regression with predictor basis functions including the quasi-biennial oscillation, El Niño-Southern Oscillation index, solar activity proxy, and the pressure at the tropical tropopause, in addition to two linear trends (one before and one after 1997, from which the decadal trends in ozone are derived. From 1984–1997, there are statistically significant negative trends of 5–10% per decade throughout the stratosphere between approximately 30–50 km. From 1997–present, a statistically significant recovery of 3–8% per decade has taken place throughout most of the stratosphere with the notable exception between 40° S–40° N below approximately 22 km where the negative trend continues. The recovery is not significant between 25–35 km altitude when accounting for a conservative estimate of instrument drift.

  3. Surface radiation at sea validation of satellite-derived data with shipboard measurements

    Directory of Open Access Journals (Sweden)

    Hein Dieter Behr

    2009-03-01

    Full Text Available Quality-controlled and validated radiation products are the basis for their ability to serve the climate and solar energy community. Satellite-derived radiation fluxes are well preferred for this task as they cover the whole research area in time and space. In order to monitor the accuracy of these data, validation with well maintained and calibrated ground based measurements is necessary. Over sea, however, long-term accurate reference data sets from calibrated instruments recording radiation are scarce. Therefore data from research vessels operating at sea are used to perform a reasonable validation. A prerequisite is that the instruments on board are maintained as well as land borne stations. This paper focuses on the comparison of radiation data recorded on board of the German Research Vessel "Meteor" during her 13 months cruise across the Mediterranean and the Black Sea with CM-SAF products using NOAA- and MSG-data (August 2006-August 2007: surface incoming short-wave radiation (SIS and surface downward long-wave radiation (SDL. Measuring radiation fluxes at sea causes inevitable errors, e.g.shadowing of fields of view of the radiometers by parts of the ship. These ship-inherent difficulties are discussed at first. A comparison of pairs of ship-recorded and satellite-derived mean fluxes for the complete measuring period delivers a good agreement: the mean bias deviation (MBD for SIS daily means is −7.6 W/m2 with a median bias of −4 W/m2 and consistently the MBD for monthly means is −7.3 W/m2, for SDL daily means the MBD is 8.1 and 6 W/m2 median bias respectively. The MBD for monthly means is 8.2 W/m2. The variances of the daily means (ship and satellite have the same annual courses for both fluxes. No significant dependence of the bias on the total cloud cover recorded according to WMO (1969 has been found. The results of the comparison between ship-based observations and satellite retrieved surface radiation reveal the good accuracy

  4. Calibration of the Distributed Hydrological Model mHM using Satellite derived Land Surface Temperature

    Science.gov (United States)

    Zink, M.; Samaniego, L. E.; Cuntz, M.

    2012-12-01

    A combined investigation of the water and energy balance in hydrologic models can lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on information of few points within a catchment. This procedure does not take into account any spatio-temporal variability of fluxes or state variables. Satellite data are a useful source of information to account for this spatial distributions. The objective of this study is to calibrate the distributed hydrological model mHM with satellite derived Land Surface Temperature (LST) fields provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). LST is preferred to other satellite products such as soil moisture or evapotranspiration due to its higher precision. LST is obtained by solving the energy balance by assuming that the soil heat flux and the storage term are negligible on a daily time step. The evapotranspiration is determined by closing the water balance in mHM. The net radiation is calculated by using the incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is used to determine the aerodynamic resistance among other parameters. The optimization is performed within the time period 2008-2010 using three objective functions that consider 1) only discharge, 2) only LST, and 3) a combination of both. The proposed method is applied to seven major German river basins: Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The annual coefficient of correlation between LSA-SAF incoming shortwave radiation and 28 meteorological stations operated by the German Weather Service (DWD) is 0.94 (RMSE = 29 W m-2) in 2009. LSA-SAF incoming longwave radiation could be further evaluated at two eddy covariance stations with a very similar

  5. Tree cover in sub-Saharan Africa: rainfall and fire constrain forest and savanna as alternative stable states

    CSIR Research Space (South Africa)

    Staver, AC

    2011-01-01

    Full Text Available adding fire improved model fit. 3 Terms Fire improved fit? scale Model R2 N GC V term F/t df p F df p 500m tree cover ~ MAR 0.50 0 2252 1 232. 4 MAR 2434 9.2 4 <0.00 1 225. 5 8.8 8 <0.00 1 tree cover ~ MAR * fire 0... METHODS 10 We analyzed patterns of tree cover with respect to rainfall and fire frequency using 11 satellite data. We derived fire frequency and tree cover from MODIS satellite reflectance 12 data at 500m resolution. We derived rainfall from...

  6. Seasonal variability of cloud optical depth over northwestern China derived from CERES/MODIS satellite measurements

    Institute of Scientific and Technical Information of China (English)

    Yonghang Chen; Hongtao Bai; Jianping Huang; Hua Zhang; Jinming Ge; Xiaodan Guan; Xiaoqin Mao

    2008-01-01

    The seasonal variability of cloud optical depth over northwestern China derived from Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint (SSF) Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Edition 1B data from July 2002 to June 2004 is presented. The regions of interest are those with Asia monsoon influence, the Tianshan and Qilian Mountains, and the Taklimakan Desert. The results show that the instantaneous measurements presented here are much higher than the previous results derived from International Satellite Cloud Climatology Project (ISCCP) D2 monthly mean data. Generally the measurements of cloud optical depth are the highest in summer and the lowest in winter, however, Taklimakan Desert has the lowest measurements in autumn. The regional variation is quite significant over northwestern China.

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

    Directory of Open Access Journals (Sweden)

    W. Tang

    2014-09-01

    Full Text Available 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 (VCD is further reduced by increasing modeled NOx lifetime and adding an artificial amount of NO2 in the upper troposphere. The sector-based DKF inversion tends to scale down area and non-road 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 inverted 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 and increases the model correlation with ground measurement in O3 simulations and makes O3 more sensitive to NOx emissions in the O3 non-attainment areas.

  8. Earth's gravity field modelling based on satellite accelerations derived from onboard GPS phase measurements

    Science.gov (United States)

    Guo, X.; Ditmar, P.; Zhao, Q.; Klees, R.; Farahani, H. H.

    2017-09-01

    GPS data collected by satellite gravity missions can be used for extracting the long-wavelength part of the Earth's gravity field. We propose a new data processing method which makes use of the `average acceleration' approach to gravity field modelling. In this method, satellite accelerations are directly derived from GPS carrier phase measurements with an epoch-differenced scheme. As a result, no ambiguity solutions are needed and the systematic errors that do not change much from epoch to epoch are largely eliminated. The GPS data collected by the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite mission are used to demonstrate the added value of the proposed method. An analysis of the residual accelerations shows that accelerations derived in this way are more precise, with noise being reduced by about 20 and 5% at the cross-track component and the other two components, respectively, as compared to those based on kinematic orbits. The accelerations obtained in this way allow the recovery of the gravity field to a slightly higher maximum degree compared to the solution based on kinematic orbits. Furthermore, the gravity field solution has an overall better performance. Errors in spherical harmonic coefficients are smaller, especially at low degrees. The cumulative geoid height error is reduced by about 15 and 5% up to degree 50 and 150, respectively. An analysis in the spatial domain shows that large errors along the geomagnetic equator, which are caused by a high electron density coupled with large short-term variations, are substantially reduced. Finally, the new method allows for a better observation of mass transport signals. In particular, sufficiently realistic signatures of regional mass anomalies in North America and south-west Africa are obtained.

  9. Earth's gravity field modelling based on satellite accelerations derived from onboard GPS phase measurements

    Science.gov (United States)

    Guo, X.; Ditmar, P.; Zhao, Q.; Klees, R.; Farahani, H. H.

    2017-02-01

    GPS data collected by satellite gravity missions can be used for extracting the long-wavelength part of the Earth's gravity field. We propose a new data processing method which makes use of the `average acceleration' approach to gravity field modelling. In this method, satellite accelerations are directly derived from GPS carrier phase measurements with an epoch-differenced scheme. As a result, no ambiguity solutions are needed and the systematic errors that do not change much from epoch to epoch are largely eliminated. The GPS data collected by the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite mission are used to demonstrate the added value of the proposed method. An analysis of the residual accelerations shows that accelerations derived in this way are more precise, with noise being reduced by about 20 and 5% at the cross-track component and the other two components, respectively, as compared to those based on kinematic orbits. The accelerations obtained in this way allow the recovery of the gravity field to a slightly higher maximum degree compared to the solution based on kinematic orbits. Furthermore, the gravity field solution has an overall better performance. Errors in spherical harmonic coefficients are smaller, especially at low degrees. The cumulative geoid height error is reduced by about 15 and 5% up to degree 50 and 150, respectively. An analysis in the spatial domain shows that large errors along the geomagnetic equator, which are caused by a high electron density coupled with large short-term variations, are substantially reduced. Finally, the new method allows for a better observation of mass transport signals. In particular, sufficiently realistic signatures of regional mass anomalies in North America and south-west Africa are obtained.

  10. GHRSST Level 2P Global Subskin Sea Surface Temperature from TRMM Microwave Imager (TMI) onboard Tropical Rainfall Measurement Mission (TRMM) satellite (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GDS2 Version -The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is a well calibrated passive microwave radiometer, similar to the Special Sensor...

  11. CHAOS-a model of the Earth's magnetic field derived from CHAMP, Orsted, and SAC-C magnetic satellite data

    DEFF Research Database (Denmark)

    Olsen, Nils; Luhr, H.; Sabaka, T.J.;

    2006-01-01

    We have derived a model of the near-Earth magnetic field (up to spherical harmonic degree n= 50 for the static field, and up to n = 18 for the first time derivative) using more than 6.5 yr of high-precision geomagnetic measurements from the three satellites Orsted, CHAMP and SAC-C taken between...

  12. Contribution of MODIS Derived Snow Cover Satellite Data into Artificial Neural Network for Streamflow Estimation

    Science.gov (United States)

    Uysal, Gokcen; Arda Sorman, Ali; Sensoy, Aynur

    2014-05-01

    Contribution of snowmelt and correspondingly snow observations are highly important in mountainous basins for modelers who deal with conceptual, physical or soft computing models in terms of effective water resources management. Long term archived continuous data are needed for appropriate training and testing of data driven approaches like artificial neural networks (ANN). Data is scarce at the upper elevations due to the difficulty of installing sufficient automated SNOTEL stations; thus in literatures many attempts are made on the rainfall dominated basins for streamflow estimation studies. On the other hand, optical satellites can easily detect snow because of its high reflectance property. MODIS (Moderate Resolution Imaging Spectroradiometer) satellite that has two platforms (Terra and Aqua) provides daily and 8-daily snow images for different time periods since 2000, therefore snow cover data (SCA) may be useful as an input layer for ANN applications. In this study, a multi-layer perceptron (MLP) model is trained and tested with precipitation, temperature, radiation, previous day discharges as well as MODIS daily SCA data. The weights and biases are optimized with fastest and robust Levenberg-Marquardt backpropagation algorithm. MODIS snow cover images are removed from cloud coverage using certain filtering techniques. The Upper Euphrates River Basin in eastern part of Turkey (10 250 km2) is selected as the application area since it is fed by snowmelt approximately 2/3 of total annual volume during spring and early summer. Several input models and ANN structures are investigated to see the effect of the contributions using 10 years of data (2001-2010) for training and validation. The accuracy of the streamflow estimations is checked with statistical criteria (coefficient of determination, Nash-Sutcliffe model efficiency, root mean square error, mean absolute error) and the results seem to improve when SCA data is introduced. Furthermore, a forecast study is

  13. Evaluation of methods to derive green-up dates based on daily NDVI satellite observations

    Science.gov (United States)

    Doktor, Daniel

    2010-05-01

    Bridging the gap between satellite derived green-up dates and in situ phenological observations has been the purpose of many studies over the last decades. Despite substantial advancements in satellite technology and data quality checks there is as yet no universally accepted method for extracting phenological metrics based on satellite derived vegetation indices. Dependent on the respective method derived green-up dates can vary up to serveral weeks using identical data sets. Consequently, it is difficult to compare various studies and to accurately determine an increased vegetation length due to changing temperature patterns as observed by ground phenological networks. Here, I compared how the characteristic NDVI increase over temperate deciduous forests in Germany in spring relates to respective budburst events observed on the ground. MODIS Terra daily surface reflectances with a 250 m resolution (2000-2008) were gathered to compute daily NDVI values. As ground truth, observations of the extensive phenological network of the German Weather Service were used. About 1500 observations per year and species (Beech, Oak and Birch) were available evenly distributed all over Germany. Two filtering methods were tested to reduce the noisy raw data. The first method only keeps NDVI values which are classified as ‚ideal global quality' and applies on those a temporal moving window where values are removed which differ more than 20% of the mean. The second method uses an adaptation of the BISE (Best Index Slope Extraction) algorithm. Subsequently, three functions were fitted to the selected observations: a simple linear interpolation, a sigmoidal function and a double logistic sigmoidal function allowing to approximate two temporally separated green-up signals. The green-up date was then determined at halfway between minimum and maximum (linear interpolation) or at the inflexion point of the sigmoidal curve. A number of global threshold values (NDVI 0.4,0.5,0.6) and

  14. Impact of Atmospheric Attenuations Time Resolutions in Solar Radiation Derived from Satellite Imagery

    Science.gov (United States)

    Cony, Marco; Liria, Juan; Weisenberg, Ralf; Serrano, Enrique

    2014-05-01

    Accurate knowledge of solar irradiance components at the earth surface is of highly interest in many scientific and technology branches concerning meteorology, climate, agriculture and solar energy applications. In the specific case of solar energy systems the solar resource analysis with accuracy is a first step in every project since it is a required data for design, power output estimations, systems simulations and risk assessments. Solar radiation measurement availability is increasing both in spatial density and in historical archiving. However, it is still quite limited and most of the situations cannot make use of a long term ground database of high quality since solar irradiance is not generally measured where users need data. Satellite-derived solar radiation estimations are a powerful and valuable tool for solar resource assessment studies that have achieved a relatively high maturity due to years of developments and improvements. However, several sources of uncertainty are still present in satellite-derived methods. In particular, the strong influence of atmospheric attenuation information as input to the method is one of the main topics of improvement. Since solar radiation attenuation by atmospheric aerosols, and water vapor in a second place, is, after clouds, the second most important factor determining solar radiation, and particularly direct normal irradiance, the accurate knowledge of aerosol optical depth and water vapor content is relevant in the final output of satellite-derived methods. This present work, two different datasets we are used for extract atmospheric attenuation information. On the one hand the monthly mean values of the Linke turbidity factor from Meteotest database, which are twelve unique values of the Linke turbidity worldwide with a spatial resolution of 1/12º. On the other hand, daily values of AOD (Aerosol Optical Depth) at 550 nm, Angstrom alpha exponent and water vapor column were taken from a gridded database that

  15. Utilization of satellite-derived estimates of meteorological and land surface characteristics in the Land Surface Model for vast agricultural region territory

    Science.gov (United States)

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

    2015-04-01

    data from named radiometers. All technologies have been adapted to the study area. Verification of the AVHRR- and MODIS-derived LST estimates has been performed through comparison with ground-measured temperatures and analogous estimates obtained from remaining sensors. The reliability of SEVIRI-derived LST estimates has been verified by comparison with similar synchronous SEVIRI-derived estimates produced in LSA SAF (Land Surface Analysis Satellite Applications Facility, Lisbon, Portugal). Correctness of LAI estimates has been confirmed by comparing time behavior of satellite- and ground-based LAI during vegetation season. Satellite-derived estimates of precipitation have been built using the Multi Threshold Method (MTM) developed for automatic pixel-by-pixel classification of AVHRR and SEVIRI data. The method is intended for the cloud detection and identification of its types, estimation of the maximum liquid water content and water content of the cloud layer, allocation of precipitation zones and determination of instantaneous maximum intensities of precipitation in the pixel range around the clock throughout the year independently of the land surface type. Measurement data from five AVHRR channels or from eleven SEVIRI channels as well as their differences have been used in the MTM as predictors. To validate the methodology, ground-based observation data on daily precipitation sums at agricultural meteorological stations of the study region have been used. The probability of correct precipitation zone detection from satellite data is at least 70% (80-85% in some cases) when compared with ground-based observations. In the frame of this approach the transition from the rainfall intensity estimation to the calculation of their daily values has been accomplished. In the study the AVHRR- and SEVIRI-derived daily, monthly and annual sums of precipitation for the region of interest have been calculated. The daily and monthly sums have been found to be in good agreement

  16. Validation of Satellite-Derived Land Surface Temperature Products - Methods and Good Practice

    Science.gov (United States)

    Guillevic, P. C.; Hulley, G. C.; Hook, S. J.; Biard, J.; Ghent, D.

    2014-12-01

    Land Surface Temperature (LST) is a key variable for surface water and energy budget calculations that can be obtained globally and operationally from satellite observations. LST is used for many applications, including weather forecasting, short-term climate prediction, extreme weather monitoring, and irrigation and water resource management. In order to maximize the usefulness of LST for research and studies it is necessary to know the uncertainty in the LST measurement. Multiple validation methods and activities are necessary to assess LST compliance with the quality specifications of operational users. This work presents four different validation methods that have been widely used to determine the uncertainties in LST products derived from satellite measurements. 1) The temperature based validation method involves comparisons with ground-based measurements of LST. The method is strongly limited by the number and quality of available field stations. 2) Scene-based comparisons involve comparing a new satellite LST product with a heritage LST product. This method is not an absolute validation and satellite LST inter-comparisons alone do not provide an independent validation measurement. 3) The radiance-based validation method does not require ground-based measurements and is usually used for large scale validation effort or for LST products with coarser spatial resolution (> 1km). 4) Time series comparisons are used to detect problems that can occur during the instrument's life, e.g. calibration drift, or unrealistic outliers due to cloud coverage. This study enumerates the sources of errors associated with each method. The four different approaches are complementary and provide different levels of information about the quality of the retrieved LST. The challenges in retrieving the LST from satellite measurements are discussed using results obtained for MODIS and VIIRS. This work contributes to the objective of the Land Product Validation (LPV) sub-group of the

  17. Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics

    Science.gov (United States)

    Ji, Lei; Brown, Jesslyn F.

    2017-10-01

    The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, -14, -16, -17, -18, and -19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989-1994) and NOAA-14 (1995-2000) missions. The growing-season median SZA values (44°-60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°-40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1-20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the influence of orbital drift

  18. Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics

    Science.gov (United States)

    Ji, Lei; Brown, Jesslyn

    2017-01-01

    The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, −14, −16, −17, −18, and −19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989–1994) and NOAA-14 (1995–2000) missions. The growing-season median SZA values (44°–60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°–40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1–20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the

  19. 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

  20. Estimating Uncertainties in Bio-Optical Products Derived from Satellite Ocean Color Imagery Using an Ensemble Approach

    Science.gov (United States)

    2011-01-01

    We propose a methodology to quantify errors and produce uncertainty maps for satellite-derived ocean color bio -optical products using ensemble...retrievals of bio -optical properties from satellite ocean color imagery are related to a variety of factors, including sensor calibration, atmospheric...correction, and the bio -optical inversion algorithms. Errors propagate, amplify, and intertwine along the processing path, so it is important to

  1. Satellite-derived determination of PM10 concentration and of the associated risk on public health

    Science.gov (United States)

    Sarigiannis, Dimosthenis; Sifakis, Nicolaos I.; Soulakellis, Nikos; Tombrou, Maria; Schaefer, Klaus P.

    2004-02-01

    Recent studies worldwide have revealed the relation between urban air pollution, particularly fine aerosols, and human health. The current state of the art in air quality assessment, monitoring and management comprises analytical measurements and atmospheric transport modeling. Earth observation from satellites provides an additional information layer through the calculation of synoptic air pollution indicators, such as atmospheric turbidity. Fusion of these data sources with ancillary data, including classification of population vulnerability to the adverse health effects of fine particulate and, especially, PM10 pollution, in the ambient air, integrates them into an optimally managed environmental information processing tool. Several algorithms pertaining to urban air pollution assessment using HSR satellite imagery have been developed and applied to urban sites in Europe such as Athens, Greece, the Po valley in Northern Italy, and Munich, Germany. Implementing these computational procedures on moderate spatial resolution (MSR) satellite data and coupling the result with the output of HSR data processing provides comprehensive and dynamic information on the spatial distribution of PM10 concentration. The result of EO data processing is corrected to account for the relative importance of the signal due to anthropogenic fine particles, concentrated in the lower troposphere. Fusing the corrected maps of PM10 concentration with data on vulnerable population distribution and implementation of epidemiology-derived exposure-response relationships results in the calculation of indices of the public health risk from PM10 concentration in the ambient air. Results from the pilot application of this technique for integrated environmental and health assessment in the urban environment are given.

  2. Quantifying winter wheat residue biomass with a spectral angle index derived from China Environmental Satellite data

    Science.gov (United States)

    Zhang, Miao; Wu, Bingfang; Meng, Jihua

    2014-10-01

    Quantification of crop residue biomass on cultivated lands is essential for studies of carbon cycling of agroecosystems, soil-atmospheric carbon exchange and Earth systems modeling. Previous studies focus on estimating crop residue cover (CRC) while limited research exists on quantifying crop residue biomass. This study takes advantage of the high temporal resolution of the China Environmental Satellite (HJ-1) data and utilizes the band configuration features of HJ-1B data to establish spectral angle indices to estimate crop residue biomass. Angles formed at the NIRIRS vertex by the three vertices at R, NIRIRS, and SWIR (ANIRIRS) of HJ-1B can effectively indicate winter wheat residue biomass. A coefficient of determination (R2) of 0.811 was obtained between measured winter wheat residue biomass and ANIRIRS derived from simulated HJ-1B reflectance data. The ability of ANIRIRS for quantifying winter wheat residue biomass using HJ-1B satellite data was also validated and evaluated. Results indicate that ANIRIRS performed well in estimating winter wheat residue biomass with different residue treatments; the root mean square error (RMSE) between measured and estimated residue biomass was 0.038 kg/m2. ANIRIRS is a potential method for quantifying winter wheat residue biomass at a large scale due to wide swath width (350 km) and four-day revisit rate of the HJ-1 satellite. While ANIRIRS can adequately estimate winter wheat residue biomass at different residue moisture conditions, the feasibility of ANIRIRS for winter wheat residue biomass estimation at different fractional coverage of green vegetation and different environmental conditions (soil type, soil moisture content, and crop residue type) needs to be further explored.

  3. The contribution of satellite SAR-derived displacement measurements in landslide risk management practices

    Science.gov (United States)

    Raspini, Federico; Bardi, Federica; Bianchini, Silvia; Ciampalini, Andrea; Del Ventisette, Chiara; Farina, Paolo; Ferrigno, Federica; Solari, Lorenzo; Casagli, Nicola

    2017-04-01

    Landslides are common phenomena that occur worldwide and are a main cause of loss of life and damage to property. The hazards associated with landslides are a challenging concern in many countries, including Italy. With 13% of the territory prone to landslides, Italy is one of the European countries with the highest landslide hazard, and on a worldwide scale, it is second only to Japan among the technologically advanced countries. Over the last 15 years, an increasing number of applications have aimed to demonstrate the applicability of images captured by space-borne Synthetic Aperture Radar (SAR) sensors in slope instability investigations. InSAR (SAR Interferometry) is currently one of the most exploited techniques for the assessment of ground displacements, and it is becoming a consolidated tool for Civil Protection institutions in addressing landslide risk. We present a subset of the results obtained in Italy within the framework of SAR-based programmes and applications intended to test the potential application of C- and X-band satellite interferometry during different Civil Protection activities (namely, prevention, prevision, emergency response and post-emergency phases) performed to manage landslide risk. In all phases, different benefits can be derived from the use of SAR-based measurements, which were demonstrated to be effective in the field of landslide analysis. Analysis of satellite-SAR data is demonstrated to play a major role in the investigation of landslide-related events at different stages, including detection, mapping, monitoring, characterization and prediction. Interferometric approaches are widely consolidated for analysis of slow-moving slope deformations in a variety of environments, and exploitation of the amplitude data in SAR images is a somewhat natural complement for rapid-moving landslides. In addition, we discuss the limitations that still exist and must be overcome in the coming years to manage the transition of satellite SAR

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

    Directory of Open Access Journals (Sweden)

    Johannes Stoffels

    2015-06-01

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

  5. 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

    2015-03-01

    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. 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. 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. 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. © The Author 2015. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  6. The HOAPS-II climatology - Release II of the satellite-derived freshwater flux climatology

    Science.gov (United States)

    Fennig, K.; Klepp, C.; Bakan, S.; Schulz, J.; Graßl, H.

    2003-04-01

    HOAPS-II (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) is the improved global climatology of sea surface parameters and surface energy and freshwater fluxes derived from satellite radiances for the time period July 1987 until the recent dates. Data from polar orbiting radiometers, all available Special Sensor Microwave/Imager (SSM/I) radiometers and the Advanced Very High Resolution Radiometer (AVHRR), have been used to get global fields of surface meteorological and oceanographic parameters but also latent heat flux, evaporation, precipitation and net freshwater flux as well as the wind speed, water vapor- and total water content over ice free ocean areas for various averaging periods and grid sizes including scan orientated data in the NetCDF data format. All retrieval methods have been validated with in situ data on a global scale with a focus on precipitation validation. The new release of the data base is freely available to the community. Additionally, applications of the HOAPS-II data base will demonstrate its ability to detect ground validated High Impact Weather over global oceans that the Global Precipitation Climatology Project (GPCP) climatology and the ECMWF model is frequently missing. Nowcasting of model-unpredicted storms is a high potential application of this new data base.

  7. Insolation data for solar energy conversion derived from satellite measurements of earth radiance

    Science.gov (United States)

    Thekaekara, M. P.

    1976-01-01

    Detailed knowledge of the irradiance of the sun at ground locations is essential for the design and evaluation of solar energy conversion systems. The primary source of such data is the global network of weather stations. Such stations are often too far apart and for most locations the data available are only daily total irradiance or monthly averages. Solar energy conversion programs require insolation data with considerably higher geographical and temporal resolution. Meteorological satellites gather routinely extensive data on the energy reflected and scattered into space by the earth-atmosphere system. A program has been initiated to use such data for deriving ground insolation for energy conversion. Some of the preliminary results of this program will be discussed.

  8. Bathymetry Prediction in Shallow Water by the Satellite Altimetry-Derived Gravity Anomalies

    Science.gov (United States)

    Kim, Kwang Bae; Yun, Hong Sik

    2017-04-01

    The satellite altimetry-derived free-air gravity anomalies (SAFAGAs) are correlated with undulations of crustal density variations under the seafloor. In this study, shipborne bathymetry from the Korea Rural Community Corporation (KRC) and the SAFAGAs from Scripps Institution of Oceanography were combined to predict bathymetry in shallow water. Density contrast of 5.0 g/cm3 estimated by the check points method of the gravity-geologic method (GGM) between seawater and the seafloor topographic mass was applied to predict bathymetry in shallow water areas outside of the Saemangeum Seawall located on the southwest coast of the Korean peninsula. Bathymetry predicted by the GGM was compared with depth measurements on the shipborne locations to analyze the bathymetry accuracy. The root mean square error (RMSE) of the differences of bathymetry between GGM and KRC on the KRC shipborne tracks in shallow water around the Saemangeum Seawall is 0.55 m. The topographic effects in off-tracks extracted from SAFAGAs in the GGM can be effectively utilized to predict bathymetry by combining with shipborne depth data in shallow water where shipborne depth data are limited. In addition, bathymetry and the SAFAGAs have a linear correlation in the 20 160 km wavelength. The coherency analysis was performed by computing the cross-spectral coherence between satellite altimetry derived bathymetry and the SAFAGAs. Acknowledgement This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2016R1A6A3A11931032).

  9. Assessment of spatially distributed values of Kc using vegetation indices derived from medium resolution satellite data

    Science.gov (United States)

    Greco, M.; Simoniello, T.; Lanfredi, M.; Russo, A. L.

    2010-09-01

    In the last years, the theme of suitable assessment of irrigation water supply has been raised relevant interest for both general principles of sustainable development and optimization of water resources techniques and management. About 99% of the water used in agriculture is lost by crops as evapotranspiration (ET). Thus, it becomes crucial to drive direct or indirect measurement in order to perform a suitable evaluation of water loss by evapotranspiration (i.e. actual evapotranspiration) as well as crop water status and its effect on the production. The main methods used to measure evapotranspiration are available only at field scale (Bowen ratio, eddy correlation system, soil water balance) confined to a small pilot area, generally due to expense and logistical constraints. This led over the last 50 years to the development of a large number of empirical methods to estimate evapotranspiration through different climatic and meteorological variables as well as combining models, based on aerodynamic theory and energy balance, taking into account both canopy properties and meteorological conditions. Among these, the Penman-Monteith equation seems to give the best results providing a robust and consistent method world wide accepted. Such conventional methods only provide accurate evapotranspiration assessment for a homogeneous region nearby the meteorological gauge station and cannot be extrapolated to other different sites; whereas remote sensing techniques allow for filling up such a gap. Some of these satellite techniques are based on the use of thermal band signals as inputs for energy balance equations. Another common approach is mainly based on the FAO method for estimating crop evapotranspiration, in which evapotranspiration data are multiplied by crop coefficients, Kc, derived from satellite multispectral vegetation indices obtained. The rationale behind such a link considers that Kc and vegetation indices are sensitive to both leaf area index and fractional

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

    DEFF Research Database (Denmark)

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

    2002-01-01

    for the use of gravity data especially, when computing geoid models in coastal regions. The presence of reliable marine gravity data for independent control offers an opportunity to study procedures for the merging of airborne and satellite data around Greenland. Two different merging techniques, both based...... on collocation, are investigated in this paper. Collocation offers a way of combining the individual airborne gravity observation with either the residual geoid observations derived from satellite altimetry or with gravity derived from these data using the inverse Stokes method implemented by Fast Fourier...

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

    Science.gov (United States)

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

    2015-04-01

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

  12. 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.

  13. Vulnerability Assessment of Rainfall-Induced Debris Flow

    Science.gov (United States)

    Lu, G. Y.; Wong, D. W.; Chiu, L. S.

    2006-05-01

    Debris flow is a common hazard triggered by large amount of rainfall over mountainous areas. A debris flow event results from a complex interaction between rainfall and topographical properties of watersheds. Heavy rainfall facilitates this process by increasing pore water pressure, seepage force and reducing effective stress of soils (normal stress carried by soil particles at the points of contact). Since debris flow events are closely related to topography and rainfall, the goal of this research is to assess debris flow vulnerability related to these two factors. Objectives of this research are to: (1) examine new spatial interpolation techniques to estimate high spatial rainfall data relevant to debris flows. (2) develop topographical factors using Geography Information System (GIS) and remote sensing (RS) approaches and (3) combine the estimated rainfall and topographical factors to assess the vulnerability of debris flow. We examined three spatial interpolation techniques: adaptive inversed distance weight (AIDW), simple kriging and spatial disaggregation using wind induced-topographic effect that incorporates gauge measurements, satellite remote sensing data (TRMM). The topographical factors are derived from high resolution digital elevation model (DEM), and adopt fuzzy-based topographical models proposed by Tseng (2004). Estimated rainfall and topographical factors are processed by self-organizing maps (SOM) to provide vulnerability assessment. To demonstrate our technique, rainfall data collected by 39 rain gauges in the central part of Taiwan during the passage of Typhoon Tori-Ji around July 29, 2001 were used. Results indicate that the proposed spatial interpolation methods outperform existing methods (i.e. kriging, inverse distance weight, and co-kriging methods). The vulnerability assessment of 187 debris flows watersheds in the study area will be presented. Keyword: Debris flow, spatial interpolation, adaptive inverse distance weight, TRMM, self

  14. Comparative Study of Ground Measured, Satellite-Derived, and Estimated Global Solar Radiation Data in Nigeria

    Directory of Open Access Journals (Sweden)

    Boluwaji M. Olomiyesan

    2016-01-01

    Full Text Available In this study, the performance of three global solar radiation models and the accuracy of global solar radiation data derived from three sources were compared. Twenty-two years (1984–2005 of surface meteorological data consisting of monthly mean daily sunshine duration, minimum and maximum temperatures, and global solar radiation collected from the Nigerian Meteorological (NIMET Agency, Oshodi, Lagos, and the National Aeronautics Space Agency (NASA for three locations in North-Western region of Nigeria were used. A new model incorporating Garcia model into Angstrom-Prescott model was proposed for estimating global radiation in Nigeria. The performances of the models used were determined by using mean bias error (MBE, mean percentage error (MPE, root mean square error (RMSE, and coefficient of determination (R2. Based on the statistical error indices, the proposed model was found to have the best accuracy with the least RMSE values (0.376 for Sokoto, 0.463 for Kaduna, and 0.449 for Kano and highest coefficient of determination, R2 values of 0.922, 0.938, and 0.961 for Sokoto, Kano, and Kaduna, respectively. Also, the comparative study result indicates that the estimated global radiation from the proposed model has a better error range and fits the ground measured data better than the satellite-derived data.

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

    Directory of Open Access Journals (Sweden)

    Ming-An Lee

    2005-01-01

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

  16. Uncertainty analysis of the optical satellite data-derived snow products

    Science.gov (United States)

    Salminen, Miia; Pulliainen, Jouni; Metsämäki, Sari; Luojus, Kari; Böttcher, Kristin; Hannula, Henna-Reetta

    2014-05-01

    -observations in various measurement conditions. These important error contributors in FSC retrieval with SCAmod are the variabilities in snow reflectance, forest transmissivity, forest reflectance (of an opaque canopy) and snow-free ground reflectance for different land cover classes. Based on the obtained results, it is possible to calculate the statistical error layers for different global FSC products and analyze the performance of the snow monitoring technique in various circumstances. This is highly relevant for the utilization of the CDRs for climate research purposes. We present the results and demonstrate the possibilities in global snow monitoring. Further work will clarify the behavior of the systematic errors by exploiting different ground truth reference datasets available. Optical satellite data-derived information on FSC can be also used in combination with SWE estimates from passive microwave sensors, in order to provide combined information on global snow extent and snow mass with confidence limits. This is furthermore demonstrated here. The presented results are obtained within the ESA DUE GlobSnow project.

  17. Zero initial partial derivatives of satellite orbits with respect to force parameters violate the physics of motion of celestial bodies

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Satellite orbits have been routinely used to produce models of the Earth’s gravity field. In connection with such productions, the partial derivatives of a satellite orbit with respect to the force parameters to be determined, namely, the unknown harmonic coefficients of the gravitational model, have been first computed by setting the initial values of partial derivatives to zero. In this note, we first design some simple mathematical examples to show that setting the initial values of partial derivatives to zero is generally erroneous mathematically. We then prove that it is prohibited physically. In other words, set-ting the initial values of partial derivatives to zero violates the physics of motion of celestial bodies.

  18. Zero initial partial derivatives of satellite orbits with respect to force parameters violate the physics of motion of celestial bodies

    Institute of Scientific and Technical Information of China (English)

    XU PeiLiang

    2009-01-01

    Satellite orbits have been routinely used to produce models of the Earth's gravity field. In connection with such productions, the partial derivatives of a satellite orbit with respect to the force parameters to be determined, namely, the unknown harmonic coefficients of the gravitational model, have been first computed by setting the initial values of partial derivatives to zero. In this note, we first design some simple mathematical examples to show that setting the initial values of partial derivatives to zero is generally erroneous mathematically. We then prove that it is prohibited physically. In other words, set-ting the initial values of partial derivatives to zero violates the physics of motion of celestial bodies.

  19. Steady state estimation of soil organic carbon using satellite-derived canopy leaf area index

    Science.gov (United States)

    Fang, Yilin; Liu, Chongxuan; Huang, Maoyi; Li, Hongyi; Leung, L. Ruby

    2014-12-01

    Estimation of soil organic carbon (SOC) stock using models typically requires long term spin-up of the carbon-nitrogen (CN) models, which has become a bottleneck for global modeling. We report a new numerical approach to estimate global SOC stock that can alleviate long spin-up. The approach uses satellite-based canopy leaf area index (LAI) and takes advantage of a reaction-based biogeochemical module—Next Generation BioGeoChemical Module (NGBGC) that was recently developed and incorporated in version 4 of the Community Land Model (CLM4). Although NGBGC uses the same CN mechanisms as in CLM4CN, it can be easily configured to run prognostic or steady state simulations. The new approach was applied at point and global scales and compared with SOC derived from spin-up by running NGBGC in the prognostic mode, and SOC from the Harmonized World Soil Database (HWSD). The steady state solution is comparable to the spin-up value when the satellite LAI is close to that from the spin-up solution, and largely captured the global variability of the HWSD SOC across the different dominant plant functional types (PFTs). The correlation between the simulated and HWSD SOC was, however, weak at both point and global scales, suggesting the needs for improving the biogeochemical processes described in CLM4 and updating HWSD. Besides SOC, the steady state solution also includes all other state variables simulated by a spin-up run, which makes the tested approach a promising tool to efficiently estimate global SOC distribution and evaluate and compare multiple aspects simulated by different CN mechanisms in the model.

  20. Spatial heterogeneity of satellite derived land surface parameters and energy flux densities for LITFASS-area

    Directory of Open Access Journals (Sweden)

    A. Tittebrand

    2009-03-01

    Full Text Available Based on satellite data in different temporal and spatial resolution, the current use of frequency distribution functions (PDF for surface parameters and energy fluxes is one of the most promising ways to describe subgrid heterogeneity of a landscape. Objective of this study is to find typical distribution patterns of parameters (albedo, NDVI for the determination of the actual latent heat flux (L.E determined from highly resolved satellite data within pixel on coarser scale.

    Landsat ETM+, Terra MODIS and NOAA-AVHRR surface temperature and spectral reflectance were used to infer further surface parameters and radiant- and energy flux densities for LITFASS-area, a 20×20 km2 heterogeneous area in Eastern Germany, mainly characterised by the land use types forest, crop, grass and water. Based on the Penman-Monteith-approach L.E, as key quantity of the hydrological cycle, is determined for each sensor in the accordant spatial resolution with an improved parametrisation. However, using three sensors, significant discrepancies between the inferred parameters can cause flux distinctions resultant from differences of the sensor filter response functions or atmospheric correction methods. The approximation of MODIS- and AVHRR- derived surface parameters to the reference parameters of ETM (via regression lines and histogram stretching, respectively, further the use of accurate land use classifications (CORINE and a new Landsat-classification, and a consistent parametrisation for the three sensors were realized to obtain a uniform base for investigations of the spatial variability.

    The analyses for 4 scenes in 2002 and 2003 showed that for forest clear distribution-patterns for NDVI and albedo are found. Grass and crop distributions show higher variability and differ significantly to each other in NDVI but only marginal in albedo. Regarding NDVI-distribution functions NDVI was found to be the key variable for L.E-determination.

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

    DEFF Research Database (Denmark)

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

    2002-01-01

    The National Survey and Cadastre - Denmark (KMS) has for several years produced gravity anomaly maps over the oceans derived from satellite altimetry. During the last four years, KMS has also conducted airborne gravity surveys along the coast of Greenland dedicated to complement the existing onsh...

  2. "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.

  3. Analysis of satellite-derived Arctic tropospheric BrO columns in conjunction with aircraft measurements during ARCTAS and ARCPAC

    Directory of Open Access Journals (Sweden)

    S. Choi

    2011-09-01

    Full Text Available We derive estimates of tropospheric BrO column amounts during two Arctic field campaigns in 2008 using information from the satellite UV nadir sensors Ozone Monitoring Instrument (OMI and the second Global Ozone Monitoring Experiment (GOME-2 as well as estimates of stratospheric BrO columns from a model simulation. The sensitivity of the satellite-derived tropospheric BrO columns to various parameters is investigated using a radiative transfer model. We conduct a comprehensive analysis of satellite-derived tropospheric BrO columns including a detailed comparison with aircraft in-situ observations of BrO and related species obtained during the field campaigns. In contrast to prior expectation, tropospheric BrO, when present, existed over a broad range of altitudes. Our results show reasonable agreement between tropospheric BrO columns derived from the satellite observations and columns found using aircraft in-situ BrO. After accounting for the stratospheric contribution to total BrO column, several events of rapid BrO activation due to surface processes in the Arctic are apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low pressure systems, strong surface winds, and high planetary boundary layer heights are associated with the observed tropospheric BrO activation events.

  4. Remote sensing of rainfall for debris-flow hazard assessment

    Science.gov (United States)

    Wieczorek, G.F.; Coe, J.A.; Godt, J.W.; ,

    2003-01-01

    Recent advances in remote sensing of rainfall provide more detailed temporal and spatial data on rainfall distribution. Four case studies of abundant debris flows over relatively small areas triggered during intense rainstorms are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. Three examples with rainfall estimates from National Weather Service Doppler radar and one example with rainfall estimates from infrared imagery from a National Oceanic and Atmospheric Administration satellite are compared with ground-based measurements of rainfall and with landslide distribution. The advantages and limitations of using remote sensing of rainfall for landslide hazard analysis are discussed. ?? 2003 Millpress,.

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

    Directory of Open Access Journals (Sweden)

    S. Kotsuki

    2015-01-01

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

  6. A Satellite-Derived Upper-Tropospheric Water Vapor Transport Index for Climate Studies

    Science.gov (United States)

    Jedlovec, Gray J.; Lerner, Jeffrey A.; Atkinson, Robert J.

    1998-01-01

    A new approach is presented to quantify upper-level moisture transport from geostationary satellite data. Daily time sequences of Geostationary Operational Environmental Satellite GOES-7 water vapor imagery were used to produce estimates of winds and water vapor mixing ratio in the cloud-free region of the upper troposphere sensed by the 6.7- microns water vapor channel. The winds and mixing ratio values were gridded and then combined to produce a parameter called the water vapor transport index (WVTI), which represents the magnitude of the two-dimensional transport of water vapor in the upper troposphere. Daily grids of WVTI, meridional moisture transport, mixing ratio, pressure, and other associated parameters were averaged to produce monthly fields for June, July, and August (JJA) of 1987 and 1988 over the Americas and surrounding oceanic regions, The WVTI was used to compare upper-tropospheric moisture transport between the summers of 1987 and 1988, contrasting the latter part of the 1986/87 El Nino event and the La Nina period of 1988. A similar product derived from the National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) 40-Year Reanalysis Project was used to help to validate the index. Although the goal of this research was to describe the formulation and utility of the WVTI, considerable insight was obtained into the interannual variability of upper-level water vapor transport. Both datasets showed large upper-level water vapor transport associated with synoptic features over the Americas and with outflow from tropical convective systems. Minimal transport occurred over tropical and subtropical high pressure regions where winds were light. Index values from NCEP-NCAR were 2-3 times larger than that determined from GOES. This difference resulted from large zonal wind differences and an apparent overestimate of upper-tropospheric moisture in the reanalysis model. A comparison of the satellite-derived monthly

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

    Directory of Open Access Journals (Sweden)

    N. Peter Benny

    2015-01-01

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

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

    Science.gov (United States)

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

    2013-10-01

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

  9. Aerus-GEO: newly available satellite-derived aerosol optical depth product over Europe and Africa

    Science.gov (United States)

    Carrer, D.; Roujean, J. L.; Ceamanos, X.; Six, B.; Suman, S.

    2015-12-01

    The major difficulty in detecting the aerosol signal from visible and near-infrared remote sensing observations is to reach the proper separation of the components related to the atmosphere and the surface. A method is proposed to circumvent this issue by exploiting the directional and temporal dimensions of the satellite signal through the use of a semi-empirical kernel-driven model for the surface/atmosphere coupled system. This algorithm was implemented by the ICARE Data Center (http://www.icare.univ-lille1.fr), which operationally disseminates a daily AOD product at 670 nm over the MSG disk since 2014. The proposed method referred to as AERUS-GEO (Aerosol and surface albEdo Retrieval Using a directional Splitting method - application to GEO data) is applied to three spectral bands (0.6 mm, 0.8 mm, and 1.6 mm) of MSG (Meteosat Second Generation) observations, which scan Europe, Africa, and the Eastern part of South America every 15 minutes. The daily AOD estimates at 0.63μm has been extensively validated. In contrast, the Angstrom coefficient is still going through validation and we will show the differences between the MSG derived Angstrom exponent with that of CAMS (Copernicus Atmosphere Monitoring Service) near-real time aerosol product. The impact of aerosol type on the aerosol radiative forcing will be presented as a part of future development plan.

  10. Mapping the mass distribution of Earth's mantle using satellite-derived gravity gradients

    Science.gov (United States)

    Panet, Isabelle; Pajot-Métivier, Gwendoline; Greff-Lefftz, Marianne; Métivier, Laurent; Diament, Michel; Mandea, Mioara

    2014-02-01

    The dynamics of Earth's mantle are not well known. Deciphering mantle flow patterns requires an understanding of the global distribution of mantle density. Seismic tomography has been used to derive mantle density distributions, but converting seismic velocities into densities is not straightforward. Here we show that data from the GOCE (Gravity field and steady-state Ocean Circulation Explorer) mission can be used to probe our planet's deep mass structure. We construct global anomaly maps of the Earth's gravitational gradients at satellite altitude and use a sensitivity analysis to show that these gravitational gradients image the geometry of mantle mass down to mid-mantle depths. Our maps highlight north-south-elongated gravity gradient anomalies over Asia and America that follow a belt of ancient subduction boundaries, as well as gravity gradient anomalies over the central Pacific Ocean and south of Africa that coincide with the locations of deep mantle plumes. We interpret these anomalies as sinking tectonic plates and convective instabilities between 1,000 and 2,500km depth, consistent with seismic tomography results. Along the former Tethyan Margin, our data also identify an east-west-oriented mass anomaly likely in the upper mantle. We suggest that by combining gravity gradients with seismic and geodynamic data, an integrated dynamic model for Earth can be achieved.

  11. The relationship between satellite-derived indices and species diversity across African savanna ecosystems

    Science.gov (United States)

    Mapfumo, Ratidzo B.; Murwira, Amon; Masocha, Mhosisi; Andriani, R.

    2016-10-01

    The ability to use remotely sensed diversity is important for the management of ecosystems at large spatial extents. However, to achieve this, there is still need to develop robust methods and approaches that enable large-scale mapping of species diversity. In this study, we tested the relationship between species diversity measured in situ with the Normalized Difference Vegetation Index (NDVI) and the Coefficient of Variation in the NDVI (CVNDVI) derived from high and medium spatial resolution satellite data at dry, wet and coastal savanna woodlands. We further tested the effect of logging on NDVI along the transects and between transects as disturbance may be a mechanism driving the patterns observed. Overall, the results of this study suggest that high tree species diversity is associated with low and high NDVI and at intermediate levels is associated with low tree species diversity and NDVI. High tree species diversity is associated with high CVNDVI and vice versa and at intermediate levels is associated with high tree species diversity and CVNDVI.

  12. Spatial and Temporal Variability of Satellite-Derived Cloud and Surface Characteristics During FIRE-ACE

    Science.gov (United States)

    Maslanik, J. A.; Key, J.; Fowler, C. W.; Nguyen, T.; Wang, X.a

    2000-01-01

    Advanced very high resolution radiometer (AVHRR) products calculated for the western Arctic for April-July 1998 are used to investigate spatial, temporal, and regional patterns and variability in energy budget parameters associated with ocean- ice-atmosphere interactions over the Arctic Ocean during the Surface Heat Budget of the Arctic Ocean (SHEBA) project and the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment - Arctic Cloud Experiment (FIRE-ACE). The AVHRR-derived parameters include cloud fraction, clear-sky and all-sky skin temperature and broadband albedo, upwelling and downwelling shortwave and longwave radiation, cloud top pressure and temperature, and cloud optical depth. The remotely sensed products generally agree well with field observations at the SHEBA site, which in turn is shown to be representative of a surrounding region comparable in size to a climate-model grid cell. Time series of products for other locations in the western Arctic illustrate the magnitude of spatial variability during the study period and provide spatial and temporal detail useful for studying regional processes. The data illustrate the progression of reduction in cloud cover, albedo decrease, and the considerable heating of the open ocean associated with the anomalous decrease in sea ice cover in the eastern Beaufort Sea that began in late spring. Above-freezing temperatures are also recorded within the ice pack, suggesting warming of the open water areas within the ice cover.

  13. Statistical Characteristics of Mesoscale Eddies in the North Pacific Derived from Satellite Altimetry

    Directory of Open Access Journals (Sweden)

    Yu-Hsin Cheng

    2014-06-01

    Full Text Available The sea level anomaly data derived from satellite altimetry are analyzed to investigate statistical characteristics of mesoscale eddies in the North Pacific. Eddies are detected by a free-threshold eddy identification algorithm. The results show that the distributions of size, amplitude, propagation speed, and eddy kinetic energy of eddy follow the Rayleigh distribution. The most active regions of eddies are the Kuroshio Extension region, the Subtropical Counter Current zone, and the Northeastern Tropical Pacific region. By contrast, eddies are seldom observed around the center of the eastern part of the North Pacific Subarctic Gyre. The propagation speed and kinetic energy of cyclonic and anticyclonic eddies are almost the same, but anticyclonic eddies possess greater lifespans, sizes, and amplitudes than those of cyclonic eddies. Most eddies in the North Pacific propagate westward except in the Oyashio region. Around the northeastern tropical Pacific and the California currents, cyclonic and anticyclonic eddies propagate westward with slightly equatorward (197° average azimuth relative to east and poleward (165° deflection, respectively. This implies that the background current may play an important role in formation of the eddy pathway patterns.

  14. Improvement in the geopotential derived from satellite and surface data (GEM 7 and 8)

    Science.gov (United States)

    Wagner, C. A.; Lerch, F. J.; Brownd, J. E.; Richardson, J. A.

    1976-01-01

    A refinement was obtained in the earth's gravitational field using satellite and surface data. In addition to a more complete treatment of data previously employed on 27 satellites, the new satellite solution (Goddard Earth Model 7) includes 64,000 laser measurements taken on 7 satellites during the international satellite geodesy experiment (ISAGEX) program. The GEM 7, containing 400 harmonic terms, is complete through degree and order 16. The companion solution GEM 8 combines the same satellite data as in GEM 7 with surface gravimetry over 39% of the earth. The GEM 8 is complete to degree and order 25. Extensive tests on data independent of the solution show that the undulation of the geoidal surface computed by GEM 7 has an accuracy of about 3m (rms). The overall accuracy of the geoid estimated by GEM 8 is estimated to be about 4-1/4m (rms), an improvement of almost 1m over previous solutions.

  15. Analysis of Satellite-Derived Arctic Tropospheric BrO Columns in Conjunction with Aircraft Measurements During ARCTAS and ARCPAC

    Science.gov (United States)

    Choi, S.; Wang, Y.; Salawitch, R. J.; Canty, T.; Joiner, J.; Zeng, T.; Kurosu, T. P.; Chance, K.; Richter, A.; Huey, L. G.; hide

    2012-01-01

    We derive tropospheric column BrO during the ARCTAS and ARCPAC field campaigns in spring 2008 using retrievals of total column BrO from the satellite UV nadir sensors OMI and GOME-2 using a radiative transfer model and stratospheric column BrO from a photochemical simulation. We conduct a comprehensive comparison of satellite-derived tropospheric BrO column to aircraft in-situ observations ofBrO and related species. The aircraft profiles reveal that tropospheric BrO, when present during April 2008, was distributed over a broad range of altitudes rather than being confined to the planetary boundary layer (PBL). Perturbations to the total column resulting from tropospheric BrO are the same magnitude as perturbations due to longitudinal variations in the stratospheric component, so proper accounting of the stratospheric signal is essential for accurate determination of satellite-derived tropospheric BrO. We find reasonably good agreement between satellite-derived tropospheric BrO and columns found using aircraft in-situ BrO profiles, particularly when satellite radiances were obtained over bright surfaces (albedo> 0.7), for solar zenith angle BrO due to surface processes (the bromine explosion) is apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low surface pressure, strong wind, and high PBL height are associated with an observed BrO activation event, supporting the notion of bromine activation by high winds over snow.

  16. Analysis of satellite-derived Arctic tropospheric BrO columns in conjunction with aircraft measurements during ARCTAS and ARCPAC

    Directory of Open Access Journals (Sweden)

    S. Choi

    2012-02-01

    Full Text Available We derive tropospheric column BrO during the ARCTAS and ARCPAC field campaigns in spring 2008 using retrievals of total column BrO from the satellite UV nadir sensors OMI and GOME-2 using a radiative transfer model and stratospheric column BrO from a photochemical simulation. We conduct a comprehensive comparison of satellite-derived tropospheric BrO column to aircraft in-situ observations of BrO and related species. The aircraft profiles reveal that tropospheric BrO, when present during April 2008, was distributed over a broad range of altitudes rather than being confined to the planetary boundary layer (PBL. Perturbations to the total column resulting from tropospheric BrO are the same magnitude as perturbations due to longitudinal variations in the stratospheric component, so proper accounting of the stratospheric signal is essential for accurate determination of satellite-derived tropospheric BrO. We find reasonably good agreement between satellite-derived tropospheric BrO and columns found using aircraft in-situ BrO profiles, particularly when satellite radiances were obtained over bright surfaces (albedo >0.7, for solar zenith angle <80° and clear sky conditions. The rapid activation of BrO due to surface processes (the bromine explosion is apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low surface pressure, strong wind, and high PBL height are associated with an observed BrO activation event, supporting the notion of bromine activation by high winds over snow.

  17. Data Filtering and Assimilation of Satellite Derived Aerosol Optical Depth Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Satellite observations of the Earth often contain excessive noise and extensive data voids. Aerosol measurements, for instance, are obscured and contaminated by...

  18. Data Filtering and Assimilation of Satellite Derived Aerosol Optical Depth Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Satellite observations of the Earth often contain excessive noise and extensive data voids. Aerosol measurements, for instance, are obscured and contaminated by...

  19. Benefits Derived From Laser Ranging Measurements for Orbit Determination of the GPS Satellite Orbit

    Science.gov (United States)

    Welch, Bryan W.

    2007-01-01

    While navigation systems for the determination of the orbit of the Global Position System (GPS) have proven to be very effective, the current research is examining methods to lower the error in the GPS satellite ephemerides below their current level. Two GPS satellites that are currently in orbit carry retro-reflectors onboard. One notion to reduce the error in the satellite ephemerides is to utilize the retro-reflectors via laser ranging measurements taken from multiple Earth ground stations. Analysis has been performed to determine the level of reduction in the semi-major axis covariance of the GPS satellites, when laser ranging measurements are supplemented to the radiometric station keeping, which the satellites undergo. Six ground tracking systems are studied to estimate the performance of the satellite. The first system is the baseline current system approach which provides pseudo-range and integrated Doppler measurements from six ground stations. The remaining five ground tracking systems utilize all measurements from the current system and laser ranging measurements from the additional ground stations utilized within those systems. Station locations for the additional ground sites were taken from a listing of laser ranging ground stations from the International Laser Ranging Service. Results show reductions in state covariance estimates when utilizing laser ranging measurements to solve for the satellite s position component of the state vector. Results also show dependency on the number of ground stations providing laser ranging measurements, orientation of the satellite to the ground stations, and the initial covariance of the satellite's state vector.

  20. Validating long-term satellite-derived disturbance products: the case of burned areas

    Science.gov (United States)

    Boschetti, L.; Roy, D. P.

    2015-12-01

    The potential research, policy and management applications of satellite products place a high priority on providing statements about their accuracy. A number of NASA, ESA and EU funded global and continental burned area products have been developed using coarse spatial resolution satellite data, and have the potential to become part of a long-term fire Climate Data Record. These products have usually been validated by comparison with reference burned area maps derived by visual interpretation of Landsat or similar spatial resolution data selected on an ad hoc basis. More optimally, a design-based validation method should be adopted that is characterized by the selection of reference data via a probability sampling that can subsequently be used to compute accuracy metrics, taking into account the sampling probability. Design based techniques have been used for annual land cover and land cover change product validation, but have not been widely used for burned area products, or for the validation of global products that are highly variable in time and space (e.g. snow, floods or other non-permanent phenomena). This has been due to the challenge of designing an appropriate sampling strategy, and to the cost of collecting independent reference data. We propose a tri-dimensional sampling grid that allows for probability sampling of Landsat data in time and in space. To sample the globe in the spatial domain with non-overlapping sampling units, the Thiessen Scene Area (TSA) tessellation of the Landsat WRS path/rows is used. The TSA grid is then combined with the 16-day Landsat acquisition calendar to provide tri-dimensonal elements (voxels). This allows the implementation of a sampling design where not only the location but also the time interval of the reference data is explicitly drawn by probability sampling. The proposed sampling design is a stratified random sampling, with two-level stratification of the voxels based on biomes and fire activity (Figure 1). The novel

  1. High resolution 3-D temperature and salinity fields derived from in situ and satellite observations

    Directory of Open Access Journals (Sweden)

    S. Guinehut

    2012-10-01

    Full Text Available This paper describes an observation-based approach that efficiently combines the main components of the global ocean observing system using statistical methods. Accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 yr are merged with the lower accuracy but high-resolution synthetic data derived from satellite altimeter and sea surface temperature observations to provide global 3-D temperature and salinity fields at high temporal and spatial resolution. The first step of the method consists in deriving synthetic temperature fields from altimeter and sea surface temperature observations, and salinity fields from altimeter observations, through multiple/simple linear regression methods. The second step of the method consists in combining the synthetic fields with in situ temperature and salinity profiles using an optimal interpolation method. Results show the revolutionary nature of the Argo observing system. Argo observations now allow a global description of the statistical relationships that exist between surface and subsurface fields needed for step 1 of the method, and can constrain the large-scale temperature and mainly salinity fields during step 2 of the method. Compared to the use of climatological estimates, results indicate that up to 50% of the variance of the temperature fields can be reconstructed from altimeter and sea surface temperature observations and a statistical method. For salinity, only about 20 to 30% of the signal can be reconstructed from altimeter observations, making the in situ observing system essential for salinity estimates. The in situ observations (step 2 of the method further reduce the differences between the gridded products and the observations by up to 20% for the temperature field in the mixed layer, and the main contribution is for salinity and the near surface layer with an improvement up to 30%. Compared to estimates derived using in situ observations only, the

  2. High Resolution 3-D temperature and salinity fields derived from in situ and satellite observations

    Directory of Open Access Journals (Sweden)

    S. Guinehut

    2012-03-01

    Full Text Available This paper describes an observation-based approach that combines efficiently the main components of the global ocean observing system using statistical methods. Accurate but sparse in situ temperature and salinity profiles (mainly from Argo for the last 10 years are merged with the lower accuracy but high-resolution synthetic data derived from altimeter and sea surface temperature satellite observations to provide global 3-D temperature and salinity fields at high temporal and spatial resolution. The first step of the method consists in deriving synthetic temperature fields from altimeter and sea surface temperature observations and salinity fields from altimeter observations through multiple/simple linear regression methods. The second step of the method consists in combining the synthetic fields with in situ temperature and salinity profiles using an optimal interpolation method. Results show the revolution of the Argo observing system. Argo observations now allow a global description of the statistical relationships that exist between surface and subsurface fields needed for step 1 of the method and can constrain the large-scale temperature and mainly salinity fields during step 2 of the method. Compared to the use of climatological estimates, results indicate that up to 50 % of the variance of the temperature fields can be reconstructed from altimeter and sea surface temperature observations and a statistical method. For salinity, only about 20 to 30 % of the signal can be reconstructed from altimeter observations, making the in situ observing system mandatory for salinity estimates. The in situ observations (step 2 of the method reduce additionally the error by up to 20 % for the temperature field in the mixed layer and the main contribution is for salinity and the near surface layer with an improvement up to 30 %. Compared to estimates derived using in situ observations only, the merged fields provide a better reconstruction of the high

  3. "Cloud Slicing" : A New Technique to Derive Tropospheric Ozone Profile Information from Satellite Measurements

    Science.gov (United States)

    Ziemke, J. R.; Chandra, S.; Bhartia, P. K.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    A new technique denoted cloud slicing has been developed for estimating tropospheric ozone profile information. All previous methods using satellite data were only capable of estimating the total column of ozone in the troposphere. Cloud slicing takes advantage of the opaque property of water vapor clouds to ultraviolet wavelength radiation. Measurements of above-cloud column ozone from the Nimbus 7 total ozone mapping spectrometer (TOMS) instrument are combined together with Nimbus 7 temperature humidity and infrared radiometer (THIR) cloud-top pressure data to derive ozone column amounts in the upper troposphere. In this study tropical TOMS and THIR data for the period 1979-1984 are analyzed. By combining total tropospheric column ozone (denoted TCO) measurements from the convective cloud differential (CCD) method with 100-400 hPa upper tropospheric column ozone amounts from cloud slicing, it is possible to estimate 400-1000 hPa lower tropospheric column ozone and evaluate its spatial and temporal variability. Results for both the upper and lower tropical troposphere show a year-round zonal wavenumber 1 pattern in column ozone with largest amounts in the Atlantic region (up to approx. 15 DU in the 100-400 hPa pressure band and approx. 25-30 DU in the 400-1000 hPa pressure band). Upper tropospheric ozone derived from cloud slicing shows maximum column amounts in the Atlantic region in the June-August and September-November seasons which is similar to the seasonal variability of CCD derived TCO in the region. For the lower troposphere, largest column amounts occur in the September-November season over Brazil in South America and also southern Africa. Localized increases in the tropics in lower tropospheric ozone are found over the northern region of South America around August and off the west coast of equatorial Africa in the March-May season. Time series analysis for several regions in South America and Africa show an anomalous increase in ozone in the lower

  4. Improvement in the geopotential derived from satellite and surface data /Gem 7 and 8/

    Science.gov (United States)

    Wagner, C. A.; Lerch, F. J.; Brownd, J. E.; Richardson, J. A.

    1977-01-01

    A refinement has been obtained in the earth's gravitational field by using satellite and surface data. In addition to a more complete treatment of data previously employed on 27 satellites, the new satellite solution Gem 7 (Goddard Earth Model 7) includes 64,000 laser measurements taken on seven satellites. Gem 7, containing 400 harmonic terms, is complete through degree and order 16. The companion solution Gem 8 combines the same satellite data as Gem 7 with surface gravimetry over 39% of the earth. Gem 8 is complete to degree and order 25. Extensive tests on data independent of the solution show that the undulations of the geoidal surface computed by Gem 7 have an accuracy of about 2.5 m (rms). The overall accuracy of the geoid calculated by Gem 8 is estimated to be about 4 m (rms). The new combination solution is the first to show signs of 'convection rolls' in the upper mantle below the Pacific Ocean.

  5. Improvement in the geopotential derived from satellite and surface data /Gem 7 and 8/

    Science.gov (United States)

    Wagner, C. A.; Lerch, F. J.; Brownd, J. E.; Richardson, J. A.

    1977-01-01

    A refinement has been obtained in the earth's gravitational field by using satellite and surface data. In addition to a more complete treatment of data previously employed on 27 satellites, the new satellite solution Gem 7 (Goddard Earth Model 7) includes 64,000 laser measurements taken on seven satellites. Gem 7, containing 400 harmonic terms, is complete through degree and order 16. The companion solution Gem 8 combines the same satellite data as Gem 7 with surface gravimetry over 39% of the earth. Gem 8 is complete to degree and order 25. Extensive tests on data independent of the solution show that the undulations of the geoidal surface computed by Gem 7 have an accuracy of about 2.5 m (rms). The overall accuracy of the geoid calculated by Gem 8 is estimated to be about 4 m (rms). The new combination solution is the first to show signs of 'convection rolls' in the upper mantle below the Pacific Ocean.

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

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

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

  7. Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

    Directory of Open Access Journals (Sweden)

    A. Brut

    2009-08-01

    Full Text Available A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France is used to simulate photosynthesis and Leaf Area Index (LAI in southwestern France for a 3-year period (2001–2003. A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the interannual variability of LAI at a regional scale, is assessed with satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and two products are based on MODIS data. The comparison reveals discrepancies between the satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops than the satellite observations, which may be due to a saturation effect within the satellite signal or to uncertainties in model parameters. The simulated leaf onset presents a significant delay for C3 crops and mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

  8. Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

    Directory of Open Access Journals (Sweden)

    A. Brut

    2009-04-01

    Full Text Available A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France is used to simulate photosynthesis and Leaf Area Index (LAI in southwestern France for a 3-year period (2001–2003. A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the inter-annual variability of LAI at a regional scale, is assessed with two satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and the second is based on MODIS data. The comparison reveals discrepancies between the two satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops and coniferous trees than the satellite observations, which may be due to a saturation effect within the satellite signal. The simulated leaf onset presents a significant delay for mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

  9. Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

    Science.gov (United States)

    Brut, A.; Rüdiger, C.; Lafont, S.; Roujean, J.-L.; Calvet, J.-C.; Jarlan, L.; Gibelin, A.-L.; Albergel, C.; Le Moigne, P.; Soussana, J.-F.; Klumpp, K.

    2009-04-01

    A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001-2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the inter-annual variability of LAI at a regional scale, is assessed with two satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and the second is based on MODIS data. The comparison reveals discrepancies between the two satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops and coniferous trees than the satellite observations, which may be due to a saturation effect within the satellite signal. The simulated leaf onset presents a significant delay for mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

  10. A Merging Framework for Rainfall Estimation at High Spatiotemporal Resolution for Distributed Hydrological Modeling in a Data-Scarce Area

    Directory of Open Access Journals (Sweden)

    Yinping Long

    2016-07-01

    Full Text Available Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolution of satellite data are available. The objective of the study is to present a satellite and rain gauge data-merging framework adapting for coarse resolution and data-sparse designs. In the framework, a statistical spatial downscaling method based on the relationships among precipitation, topographical features, and weather conditions was used to downscale the 0.25° daily rainfall field derived from the Tropical Rainfall Measuring Mission (TRMM Multisatellite Precipitation Analysis (TMPA precipitation product version 7. The nonparametric merging technique of double kernel smoothing, adapting for data-sparse design, was combined with the global optimization method of shuffled complex evolution, to merge the downscaled TRMM and gauged rainfall with minimum cross-validation error. An indicator field representing the presence and absence of rainfall was generated using the indicator kriging technique and applied to the previously merged result to consider the spatial intermittency of daily rainfall. The framework was applied to estimate daily precipitation at a 1 km resolution in the Qinghai Lake Basin, a data-scarce area in the northeast of the Qinghai-Tibet Plateau. The final estimates not only captured the spatial pattern of daily and annual precipitation with a relatively small estimation error, but also performed very well in stream flow simulation when applied to force the geomorphology-based hydrological model (GBHM. The proposed framework thus appears feasible for rainfall estimation at high spatiotemporal resolution in data-scarce areas.

  11. Estimation of rainfall using remote sensing for Riyadh climate, KSA

    Science.gov (United States)

    AlHassoun, Saleh A.

    2013-05-01

    Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

  12. Spatial and Quantitative Comparison of Satellite-Derived Land Cover Products over China

    Institute of Scientific and Technical Information of China (English)

    GAO Hao; JIA Gen-Suo

    2012-01-01

    Because land cover plays an important role in global climate change studies, assessing the agreement among different land cover products is critical. Significant discrepancies have been reported among satellite-derived land cover products, especially at the regional scale. Dif- ferent classification schemes are a key obstacle to the comparison of products and are considered the main fac- tor behind the disagreement among the different products. Using a feature-based overlap metric, we investigated the degree of spatial agreement and quantified the overall and class-specific agreement among the Moderate Resolution Imaging Spectoradiometer (MODIS), Global Land Cover 2000 (GLC2000), and the National Land Cover/Use Data- sets (NLCD) products, and the author assessed the prod- ucts by ground reference data at the regional scale over China. The areas with a low degree of agreement mostly occurred in heterogeneous terrain and transition zones, while the areas with a high degree of agreement occurred in major plains and areas with homogeneous vegetation. The overall agreement of the MODIS and GLC2000 products was 50.8% and 52.9%, and the overall accuracy was 50.3% and 41.9%, respectively. Class-specific agree- ment or accuracy varied significantly. The high-agreement classes are water, grassland, cropland, snow and ice, and bare areas, whereas classes with low agreement are shru- bland and wetland in both MODIS and GLC2000. These characteristics of spatial patterns and quantitative agree- ment could be partly explained by the complex landscapes, mixed vegetation, low separability of spectro-temporal- texture signals, and coarse pixels. The differences of class definition among different the classification schemes also affects the agreement. Each product had its advantages and limitations, but neither the overall accuracy nor the class-specific accuracy could meet the requirements of climate modeling.

  13. Developing a new global network of river reaches from merged satellite-derived datasets

    Science.gov (United States)

    Lion, C.; Allen, G. H.; Beighley, E.; Pavelsky, T.

    2015-12-01

    In 2020, the Surface Water and Ocean Topography satellite (SWOT), a joint mission of NASA/CNES/CSA/UK will be launched. One of its major products will be the measurements of continental water extent, including the width, height, and slope of rivers and the surface area and elevations of lakes. The mission will improve the monitoring of continental water and also our understanding of the interactions between different hydrologic reservoirs. For rivers, SWOT measurements of slope must be carried out over predefined river reaches. As such, an a priori dataset for rivers is needed in order to facilitate analysis of the raw SWOT data. The information required to produce this dataset includes measurements of river width, elevation, slope, planform, river network topology, and flow accumulation. To produce this product, we have linked two existing global datasets: the Global River Widths from Landsat (GRWL) database, which contains river centerline locations, widths, and a braiding index derived from Landsat imagery, and a modified version of the HydroSHEDS hydrologically corrected digital elevation product, which contains heights and flow accumulation measurements for streams at 3 arcsecond spatial resolution. Merging these two datasets requires considerable care. The difficulties, among others, lie in the difference of resolution: 30m versus 3 arseconds, and the age of the datasets: 2000 versus ~2010 (some rivers have moved, the braided sections are different). As such, we have developed custom software to merge the two datasets, taking into account the spatial proximity of river channels in the two datasets and ensuring that flow accumulation in the final dataset always increases downstream. Here, we present our preliminary results for a portion of South America and demonstrate the strengths and weaknesses of the method.

  14. Surface diurnal warming in the East China Sea derived from satellite remote sensing

    Science.gov (United States)

    Song, Dan; Duan, Zhigang; Zhai, Fangguo; He, Qiqi

    2017-09-01

    Process of sea surface diurnal warming has drawn a lot of attention in recent years, but that occurs in shelf seas was rarely addressed. In the present work, surface diurnal warming strength in the East China Sea was calculated by the sea surface temperature (SST) data derived from the MODIS sensors carried by the satellites Aqua and Terra. Due to transit time difference, both the number of valid data and the surface diurnal warming strength computed by the MODIS-Aqua data are relatively larger than Terra. Therefore, the 10-year MODIS-Aqua data from 2005 to 2014 were used to analyze the monthly variability of the surface diurnal warming. Generally, the surface diurnal warming in the East China sea is stronger in summer and autumn but weaker in winter and spring, while it shows different peaks in different regions. Large events with ΔT≥5 K have also been discussed. They were found mainly in coastal area, especially near the Changjiang (Yangtze) River estuary. And there exists a high-incidence period from April to July. Furthermore, the relationship between surface diurnal warming and wind speed was discussed. Larger diurnal warming mainly lies in areas with low wind speed. And its possibility decreases with the increase of wind speed. Events with ΔT≥2.5 K rarely occur when wind speed is over 12 m/s. Study on surface diurnal warming in the East China Sea may help to understand the daily scale air-sea interaction in the shelf seas. A potential application might be in the marine weather forecasts by numerical models. Its impact on the coastal eco-system and the activities of marine organisms can also be pursued.

  15. Using GIS data and satellite derived irradiance to optimize siting of PV installations in Switzerland

    Science.gov (United States)

    Kahl, Annelen; Nguyen, Viet-Anh; Bartlett, Stuart; Sossan, Fabrizio; Lehning, Michael

    2016-04-01

    For a successful distribution strategy of PV installations, it does not suffice to choose the locations with highest annual total irradiance. Attention needs to be given to spatial correlation patterns of insolation to avoid large system-wide variations, which can cause extended deficits in supply or might even damage the electrical network. One alternative goal instead is to seek configurations that provide the smoothest energy production, with the most reliable and predictable supply. Our work investigates several scenarios, each pursuing a different strategy for a future renewable Switzerland without nuclear power. Based on an estimate for necessary installed capacity for solar power [Bartlett, 2015] we first use heuristics to pre-select realistic placements for PV installations. Then we apply optimization methods to find a subset of locations that provides the best possible combined electricity production. For the first part of the selection process, we use a DEM to exclude high elevation zones which would be difficult to access and which are prone to natural hazards. Then we use land surface cover information to find all zones with potential roof area, deemed suitable for installation of solar panels. The optimization employs Principal Component Analysis of satellite derived irradiance data (Surface Incoming Shortwave Radiation (SIS), based on Meteosat Second Generation sensors) to incorporate a spatial aspect into the selection process that does not simply maximize annual total production but rather provides the most robust supply, by combining regions with anti-correlated cloud cover patterns. Depending on the initial assumptions and constraints, the resulting distribution schemes for PV installations vary with respect to required surface area, annual total and lowest short-term production, and illustrate how important it is to clearly define priorities and policies for a future renewable Switzerland.

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

    Science.gov (United States)

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

    2017-05-01

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

  17. Using Social Media and Mobile Devices to Discover and Share Disaster Data Products Derived From Satellites

    Science.gov (United States)

    Mandl, Daniel; Cappelaere, Patrice; Frye, Stuart; Evans, John; Moe, Karen

    2014-01-01

    Data products derived from Earth observing satellites are difficult to find and share without specialized software and often times a highly paid and specialized staff. For our research effort, we endeavored to prototype a distributed architecture that depends on a standardized communication protocol and applications program interface (API) that makes it easy for anyone to discover and access disaster related data. Providers can easily supply the public with their disaster related products by building an adapter for our API. Users can use the API to browse and find products that relate to the disaster at hand, without a centralized catalogue, for example floods, and then are able to share that data via social media. Furthermore, a longerterm goal for this architecture is to enable other users who see the shared disaster product to be able to generate the same product for other areas of interest via simple point and click actions on the API on their mobile device. Furthermore, the user will be able to edit the data with on the ground local observations and return the updated information to the original repository of this information if configured for this function. This architecture leverages SensorWeb functionality [1] presented at previous IGARSS conferences. The architecture is divided into two pieces, the frontend, which is the GeoSocial API, and the backend, which is a standardized disaster node that knows how to talk to other disaster nodes, and also can communicate with the GeoSocial API. The GeoSocial API, along with the disaster node basic functionality enables crowdsourcing and thus can leverage insitu observations by people external to a group to perform tasks such as improving water reference maps, which are maps of existing water before floods. This can lower the cost of generating precision water maps. Keywords-Data Discovery, Disaster Decision Support, Disaster Management, Interoperability, CEOS WGISS Disaster Architecture

  18. Trends in a satellite-derived vegetation index and environmental variables in a restored brackish lagoon

    Directory of Open Access Journals (Sweden)

    Ji Yoon Kim

    2015-07-01

    Full Text Available We evaluated relative influence of climatic variables on the plant productivity after lagoon restoration. Chilika Lagoon, the largest brackish lake ecosystem in East Asia, experienced severe problems such as excessive dominance of freshwater exotic plants and rapid debasement of biodiversity associated with decreased hydrologic connectivity between the lagoon and the ocean. To halt the degradation of the lagoon ecosystem, the Chilika Development Authority implemented a restoration project, creating a new channel to penetrate the barrier beach of the lagoon. Using a satellite-derived normalized difference vegetation index (NDVI dataset, we compared the trend of vegetation changes after the lagoon restoration, from April 1998 to May 2014. The time series of NDVI data were decomposed into trend, seasonal, and random components using a local regression method. The results were visualized to understand the traits of spatial distribution in the lagoon. The NDVI trend, indicative of primary productivity, decreased rapidly during the restoration period, and gradually increased (slope coefficient: 2.1×10−4, p<0.05 after two years of restoration. Level of seawater exchange had more influences on plant productivity than local precipitation in the restored lagoon. Higher El Niño/Southern Oscillation increased sea level pressure, and caused intrusion of seawater into the lagoon, and the subsequently elevated salinity decreased the annual mean NDVI. Our findings suggest that lagoon restoration plans for enhancing interconnectivity with the ocean should consider oceanographic effects due to meteorological forcing, and long-term NDVI results can be used as a valuable index for adaptive management of the restoration site.

  19. Surface Solar Radiation in North America: Observations, Reanalyses, Satellite and Derived Products

    Science.gov (United States)

    Slater, A. G.

    2015-12-01

    Observations of daily surface solar/shortwave radiation data from over 4000 stations have been gathered, covering much of the lower 48 continental states of the US as well as portions of Alberta and British Columbia, Canada. The quantity of data increases almost linearly from 1998 when only several hundred stations had data. A quality control procedure utilizing threshold values along with computing the clear sky radiation envelope for individual stations was implemented to both screen bad data and rescue informative data. Over two thirds of the observations are seen as acceptable. Fifteen different surface solar radiation products are assessed relative to observations, including reanalyses (20thC, CFSRR, ERAI, JRA-55, MERRA, NARR, NCEP), derived products (CRU_NCEP, DAYMET, GLDAS, GSWP3, MsTMIP, NLDAS) and two satellite products (CERES and GOES). All except the CERES product are daily or finer in temporal resolution. The root mean square error of spatial biases is greater than 18Wm-2 for 13 of the 15 products over the summer season (June, July, August). None of the daily resolution products fulfill all three desirable criteria of low (<5%) annual or seasonal bias, high correlation with observed cloudiness and correct distribution of clear sky radiation. Some products display vestiges of underlying algorithm issues (e.g. from MTCLIM ver4.3) or bias correction methods. A new bias correction method is introduced that preserves clear sky radiation values and better replicates cloudiness statistics. The current quantity of data over the continental US suggests a solar radiation product based on, or enhanced with, observations is feasible.

  20. Long-term changes of tropospheric NO2 over megacities derived from multiple satellite instruments

    Science.gov (United States)

    Hilboll, A.; Richter, A.; Burrows, J. P.

    2012-12-01

    Tropospheric NO2, a key pollutant in particular in cities, has been measured from space since the mid-1990s by the GOME, SCIAMACHY, OMI, and GOME-2 instruments. These data provide a unique global long-term data set of tropospheric pollution. However, the measurements differ in spatial resolution, local time of measurement, and measurement geometry. All these factors can severely impact the retrieved NO2 columns, which is why they need to be taken into account when analysing time series spanning more than one instrument. In this study, we present several ways to explicitly account for the instrumental differences in trend analyses of the NO2 columns derived from satellite measurements, while preserving their high spatial resolution. Both a physical method, based on spatial averaging of the measured earthshine spectra and extraction of a resolution pattern, and statistical methods, including instrument-dependent offsets in the fitted trend function, are developed. These methods are applied to data from GOME and SCIAMACHY separately, to the combined time series and to an extended data set comprising also GOME-2 and OMI measurements. All approaches show consistent trends of tropospheric NO2 for a selection of areas on both regional and city scales, for the first time allowing consistent trend analysis of the full time series at high spatial resolution and significantly reducing the uncertainties of the retrieved trend estimates compared to previous studies. We show that measured tropospheric NO2 columns have been strongly increasing over China, the Middle East, and India, with values over East Central China triplicating from 1996 to 2011. All parts of the developed world, including Western Europe, the United States, and Japan, show significantly decreasing NO2 amounts in the same time period. On a megacity level, individual trends can be as large as +27 ± 3.7% yr-1 and +20 ± 1.9% yr-1 in Dhaka and Baghdad, respectively, while Los Angeles shows a very strong decrease

  1. Deriving large-scale glacier velocities from a complete satellite archive : Application to the Pamir-Karakoram-Himalaya

    OpenAIRE

    Dehecq, Amaury; Gourmelen, Noel; Trouve, Emmanuel

    2015-01-01

    International audience; Mountain glaciers are pertinent indicators of climate change and their dynamics, in particular surface velocity change, is an essential climate variable. In order to retrieve the climatic signature from surface velocity, large-scale study of temporal trends spanning multiple decades is required. Satellite image feature-tracking has been successfully used to derive mountain glacier surface velocities, but most studies rely on manually selected pairs of images, which is ...

  2. Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

    Science.gov (United States)

    Bell, Thomas L.; Kundu, Prasun K.; Kummerow, Christian D.; Einaudi, Franco (Technical Monitor)

    2000-01-01

    Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

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

    National Research Council Canada - National Science Library

    Christopher D Elvidge; Daniel Ziskin; Kimberly E Baugh; Benjamin T Tuttle; Tilottama Ghosh; Dee W Pack; Edward H Erwin; Mikhail Zhizhin

    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...

  4. New empirically-derived solar radiation pressure model for GPS satellites

    Science.gov (United States)

    Bar-Sever, Y.; Kuang, D.

    2003-01-01

    Solar radiation pressure force is the second largest perturbation acting on GPS satellites, after the gravitational attraction from the Earth, Sun, and Moon. It is the largest error source in the modeling of GPS orbital dynamics.

  5. 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...

  6. Estimated Depth Maps of the Northwestern Hawaiian Islands Derived from High Resolution IKONOS Satellite Imagery

    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...

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

    CSIR Research Space (South Africa)

    Griffith, DJ

    2014-09-01

    Full Text Available layer. This has included all satellite data products that are relevant to the surface energy balance such as surface reflectance, temperature and emissivity. It was also important to identify active archive data services that can provide preprocessed...

  8. Servicing of multiple satellites using an OMV-derived transfer vehicle

    Science.gov (United States)

    Graves, Carl D.; Meissinger, Hans F.; Rosen, Alan

    Servicing vehicles and supplies to be used for extending the mission life of polar orbiting satellites will be launched into orbit by expendable launch vehicles, since the Space Shuttle currently is not expected to operate in this orbital regime. The Orbital Maneuvering Vehicle or a smaller version being designed for this purpose, and its performance potential as a permanently space-based satellite servicing vehicle, are the subject of this paper. A single servicing vehicle of this class can maneuver, as required, to visit multiple user satellites in their respective orbits. Cost-effective orbit transfer techniques are essential for a viable multi-satellite servicing scenario. Such transfer modes and servicing scenarios, and the usable payload delivery performance achievable are analyzed and compared.

  9. Inertial currents in the Indian Ocean derived from satellite tracked surface drifters

    Digital Repository Service at National Institute of Oceanography (India)

    Saji, P.K.; Shenoi, S.S.C.; Almeida, A.M.; Rao, L.V.G.

    ´sume´ – Courants d’inertie dans l’oce´an Indien estime´s a` partir de flotteurs de surface suivis par satellite. Des flotteurs de surface suivis par satellite ont e´te´ utilise´s pour analyser les caracte´ristiques des courants d’inertie dans l’oce´an Indien...

  10. Evolution of ribosomal DNA-derived satellite repeat in tomato genome

    Directory of Open Access Journals (Sweden)

    Hur Cheol-Goo

    2009-04-01

    Full Text Available Abstract Background Tandemly repeated DNA, also called as satellite DNA, is a common feature of eukaryotic genomes. Satellite repeats can expand and contract dramatically, which may cause genome size variation among genetically-related species. However, the origin and expansion mechanism are not clear yet and needed to be elucidated. Results FISH analysis revealed that the satellite repeat showing homology with intergenic spacer (IGS of rDNA present in the tomato genome. By comparing the sequences representing distinct stages in the divergence of rDNA repeat with those of canonical rDNA arrays, the molecular mechanism of the evolution of satellite repeat is described. Comprehensive sequence analysis and phylogenetic analysis demonstrated that a long terminal repeat retrotransposon was interrupted into each copy of the 18S rDNA and polymerized by recombination rather than transposition via an RNA intermediate. The repeat was expanded through doubling the number of IGS into the 25S rRNA gene, and also greatly increasing the copy number of type I subrepeat in the IGS of 25-18S rDNA by segmental duplication. Homogenization to a single type of subrepeat in the satellite repeat was achieved as the result of amplifying copy number of the type I subrepeat but eliminating neighboring sequences including the type II subrepeat and rRNA coding sequence from the array. FISH analysis revealed that the satellite repeats are commonly present in closely-related Solanum species, but vary in their distribution and abundance among species. Conclusion These results represent that the dynamic satellite repeats were originated from intergenic spacer of rDNA unit in the tomato genome. This result could serve as an example towards understanding the initiation and the expansion of the satellite repeats in complex eukaryotic genome.

  11. Analysis of long-term precipitation pattern over Antarctica derived from satellite-borne radar

    Science.gov (United States)

    Milani, L.; Porcù, F.; Casella, D.; Dietrich, S.; Panegrossi, G.; Petracca, M.; Sanò, P.

    2015-01-01

    Mass accumulation is a key geophysical parameter in understanding the Antarctic climate and its role in the global system. The local mass variation is driven by a number of different mechanisms: the deposition of snow and ice crystals on the surface from the atmosphere is generally modified by strong surface winds and variations in temperature and humidity at the ground, making it difficult to measure directly the accumulation by a sparse network of ground based instruments. Moreover, the low cloud total water/ice content and the varying radiative properties of the ground pose problems in the retrieval of precipitation from passive space-borne sensors at all frequencies. Finally, numerical models, despite their high spatial and temporal resolution, show discordant results and are difficult to be validated using ground-based measurements. A significant improvement in the knowledge of the atmospheric contribution to the mass balance over Antarctica is possible by using active space-borne instruments, such as the Cloud Profiling Radar (CPR) on board the low earth orbit CloudSat satellite, launched in 2006 and still operating. The radar measures the vertical profile of reflectivity at 94 GHz (sensitive to small ice particles) providing narrow vertical cross-sections of clouds along the satellite track. The aim of this work is to show that, after accounting for the characteristics of precipitation and the effect of surface on reflectivity in Antarctica, the CPR can retrieve snowfall rates on a single event temporal scale. Furthermore, the CPR, despite its limited temporal and spatial sampling capabilities, also effectively observes the annual snowfall cycle in this region. Two years of CloudSat data over Antarctica are analyzed and converted in water equivalent snowfall rate. Two different approaches for precipitation estimates are considered in this work. The results are analyzed in terms of annual and monthly averages, as well as in terms of instantaneous values. The

  12. Analysis of long-term precipitation pattern over Antarctica derived from satellite-borne radar

    Directory of Open Access Journals (Sweden)

    L. Milani

    2015-01-01

    Full Text Available Mass accumulation is a key geophysical parameter in understanding the Antarctic climate and its role in the global system. The local mass variation is driven by a number of different mechanisms: the deposition of snow and ice crystals on the surface from the atmosphere is generally modified by strong surface winds and variations in temperature and humidity at the ground, making it difficult to measure directly the accumulation by a sparse network of ground based instruments. Moreover, the low cloud total water/ice content and the varying radiative properties of the ground pose problems in the retrieval of precipitation from passive space-borne sensors at all frequencies. Finally, numerical models, despite their high spatial and temporal resolution, show discordant results and are difficult to be validated using ground-based measurements. A significant improvement in the knowledge of the atmospheric contribution to the mass balance over Antarctica is possible by using active space-borne instruments, such as the Cloud Profiling Radar (CPR on board the low earth orbit CloudSat satellite, launched in 2006 and still operating. The radar measures the vertical profile of reflectivity at 94 GHz (sensitive to small ice particles providing narrow vertical cross-sections of clouds along the satellite track. The aim of this work is to show that, after accounting for the characteristics of precipitation and the effect of surface on reflectivity in Antarctica, the CPR can retrieve snowfall rates on a single event temporal scale. Furthermore, the CPR, despite its limited temporal and spatial sampling capabilities, also effectively observes the annual snowfall cycle in this region. Two years of CloudSat data over Antarctica are analyzed and converted in water equivalent snowfall rate. Two different approaches for precipitation estimates are considered in this work. The results are analyzed in terms of annual and monthly averages, as well as in terms of

  13. Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

    Science.gov (United States)

    Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

    2016-10-01

    Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches

  14. Strategies for the fusion of satellite fire radiative power with burned area data for fire radiative energy derivation

    Science.gov (United States)

    Boschetti, Luigi; Roy, David P.

    2009-10-01

    Instantaneous estimates of the power released by a fire (Fire Radiative Power, FRP) are available with satellite active fire detection products. Integrating FRP in time provides an estimate of the total energy released (Fire Radiative Energy, FRE), which can be converted into burned biomass estimates needed by the atmospheric emissions modeling community. While straightforward in theory, the integration of FRP in time and space is affected by temporal and spatial undersampling imposed by the satellite sensing and orbit geometry, clouds, and active fire product omission errors. Combination of active fire FRP estimates with independently derived burned area maps provides the potential for improved and spatially explicit estimates of FRE and biomass burned. In the present work, strategies for the temporal interpolation of FRP data and for the spatial extrapolation of FRE across the burn are proposed and, as a study case, applied to an extensive grassland fire that burned for 40 days in northern Australia. The fusion of FRP estimates derived from MODIS Terra and Aqua active fire detections with the MODIS burned area product is considered, although other polar orbiting and geostationary satellite fire products could be used. Intercomparison of FRE estimated over the MODIS mapped burned area using Terra, Aqua, and Terra-Aqua combined FRP data highlights the sensitivity of FRE estimation to satellite sampling. Despite this sensitivity, FRE biomass burned estimates derived from MODIS burned area and Terra and Aqua FRP data are within 30% of regional literature estimates, suggesting that this fusion approach is a fruitful avenue for future research and validation.

  15. Handling of subpixel structures in the application of satellite derived irradiance data for solar energy system analysis - a review

    Science.gov (United States)

    Beyer, Hans Georg

    2016-04-01

    With the increasing availability of satellite derived irradiance information, this type of data set is more and more in use for the design and operation of solar energy systems, most notably PV- and CSP-systems. By this, the need for data measured on-site is reduced. However, due to basic limitations of the satellite-derived data, several requirements put by the intended application cannot be coped with this data type directly. Traw satellite information has to be enhanced in both space and time resolution by additional information to be fully applicable for all aspects of the modelling od solar energy systems. To cope with this problem, several individual and collaborative projects had been performed in the recent years or are ongoing. Approaches are on one hand based on pasting synthesized high-resolution data into the low-resolution original sets. Pre-requite is an appropriate model, validated against real world data. For the case of irradiance data, these models can be extracted either directly from ground measured data sets or from data referring to the cloud situation as gained from the images of sky cameras or from monte -carlo initialized physical models. The current models refer to the spatial structure of the cloud fields. Dynamics are imposed by moving the cloud structures according to a large scale cloud motion vector, either extracted from the dynamics interfered from consecutive satellite images or taken from a meso-scale meteorological model. Dynamic irradiance information is then derived from the cloud field structure and the cloud motion vector. This contribution, which is linked to subtask A - Solar Resource Applications for High Penetration of Solar Technologies - of IEA SHC task 46, will present the different approaches and discuss examples in view of validation, need for auxiliary information and respective general applicability.

  16. Rainfall estimation from soil moisture data: crash test for SM2RAIN algorithm

    Science.gov (United States)

    Brocca, Luca; Albergel, Clement; Massari, Christian; Ciabatta, Luca; Moramarco, Tommaso; de Rosnay, Patricia

    2015-04-01

    Soil moisture governs the partitioning of mass and energy fluxes between the land surface and the atmosphere and, hence, it represents a key variable for many applications in hydrology and earth science. In recent years, it was demonstrated that soil moisture observations from ground and satellite sensors contain important information useful for improving rainfall estimation. Indeed, soil moisture data have been used for correcting rainfall estimates from state-of-the-art satellite sensors (e.g. Crow et al., 2011), and also for improving flood prediction through a dual data assimilation approach (e.g. Massari et al., 2014; Chen et al., 2014). Brocca et al. (2013; 2014) developed a simple algorithm, called SM2RAIN, which allows estimating rainfall directly from soil moisture data. SM2RAIN has been applied successfully to in situ and satellite observations. Specifically, by using three satellite soil moisture products from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observation) and SMOS (Soil Moisture and Ocean Salinity); it was found that the SM2RAIN-derived rainfall products are as accurate as state-of-the-art products, e.g., the real-time version of the TRMM (Tropical Rainfall Measuring Mission) product. Notwithstanding these promising results, a detailed study investigating the physical basis of the SM2RAIN algorithm, its range of applicability and its limitations on a global scale has still to be carried out. In this study, we carried out a crash test for SM2RAIN algorithm on a global scale by performing a synthetic experiment. Specifically, modelled soil moisture data are obtained from HTESSEL model (Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land) forced by ERA-Interim near-surface meteorology. Afterwards, the modelled soil moisture data are used as input into SM2RAIN algorithm for testing weather or not the resulting rainfall estimates are able to reproduce ERA-Interim rainfall data. Correlation, root

  17. Long-term changes of tropospheric NO2 over megacities derived from multiple satellite instruments

    Directory of Open Access Journals (Sweden)

    A. Hilboll

    2013-04-01

    Full Text Available Tropospheric NO2, a key pollutant in particular in cities, has been measured from space since the mid-1990s by the GOME, SCIAMACHY, OMI, and GOME-2 instruments. These data provide a unique global long-term dataset of tropospheric pollution. However, the observations differ in spatial resolution, local time of measurement, viewing geometry, and other details. All these factors can severely impact the retrieved NO2 columns. In this study, we present three ways to account for instrumental differences in trend analyses of the NO2 columns derived from satellite measurements, while preserving the individual instruments' spatial resolutions. For combining measurements from GOME and SCIAMACHY into one consistent time series, we develop a method to explicitly account for the instruments' difference in ground pixel size (40 × 320 km2 vs. 30 × 60 km2. This is especially important when analysing NO2 changes over small, localised sources like, e.g. megacities. The method is based on spatial averaging of the measured earthshine spectra and extraction of a spatial pattern of the resolution effect. Furthermore, two empirical corrections, which summarise all instrumental differences by including instrument-dependent offsets in a fitted trend function, are developed. These methods are applied to data from GOME and SCIAMACHY separately, to the combined time series, and to an extended dataset comprising also GOME-2 and OMI measurements. All approaches show consistent trends of tropospheric NO2 for a selection of areas on both regional and city scales, for the first time allowing consistent trend analysis of the full time series at high spatial resolution. Compared to previous studies, the longer study period leads to significantly reduced uncertainties. We show that measured tropospheric NO2 columns have been strongly increasing over China, the Middle East, and India, with values over east-central China tripling from 1996 to 2011. All parts of the developed world

  18. Heterogeneity of Dutch rainfall

    NARCIS (Netherlands)

    Witter, J.V.

    1984-01-01

    Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the

  19. An error analysis of tropical cyclone divergence and vorticity fields derived from satellite cloud winds on the Atmospheric and Oceanographic Information Processing System (AOIPS)

    Science.gov (United States)

    Hasler, A. F.; Rodgers, E. B.

    1977-01-01

    An advanced Man-Interactive image and data processing system (AOIPS) was developed to extract basic meteorological parameters from satellite data and to perform further analyses. The errors in the satellite derived cloud wind fields for tropical cyclones are investigated. The propagation of these errors through the AOIPS system and their effects on the analysis of horizontal divergence and relative vorticity are evaluated.

  20. Analytical derivation and verification of zero-gyro control for the IUE satellite

    Science.gov (United States)

    Bowles, Tiffany; Croft, John

    1989-01-01

    The International Ultraviolet Explorer (IUE) satellite was launched January 26, 1978 into a geosynchronous orbit over South America. From its stationary position, the telescope maintains continuous communication with the control centers at NASA's Goddard Space Flight Center in Greenbelt, Maryland, and at the European Space Agency's (ESA's) Villagranca del Castillo Satellite Tracking Station in Spain. Since its launch in 1978, the satellite has gradually lost four of the original six gyroscopes in the Inertial Reference Assembly (IRA). In August 1985, the fourth of the original six gyros failed and a two-gyro system developed by NASA-GSFC was uplinked to the satellite and is currently in use. A one-gyro system also developed by NASA-GSFC is ready for use in case of another gyro failure. In the event that the sixth gyro should also fail, a zero-gyro system is being developed. The goal of this system is to provide interial target pointing without the use of gyroscopes. The satellite has sun sensors to provide attitude information about two of the three axes. It relies upon the exchange of reaction wheel momenta to determine angular position and rate of the third axis.

  1. Components of near-surface energy balance derived from satellite soundings – Part 1: Net available energy

    Directory of Open Access Journals (Sweden)

    K. Mallick

    2014-08-01

    Full Text Available This paper introduces a relatively simple method for recovering global fields of near-surface net available energy (the sum of the sensible and latent heat flux or the difference between the net radiation and surface heat accumulation using satellite visible and infra-red products derived from the AIRS (Atmospheric Infrared Sounder and MODIS (MOderate Resolution Imaging Spectroradiometer platforms. The method focuses on first specifying net surface radiation by considering its various shortwave and longwave components. This was then used in a surface energy balance equation in conjunction with satellite day–night surface temperature difference to derive 12 h discrete time estimates of surface, system heat capacity and heat accumulation, leading directly to retrieval for surface net available energy. Both net radiation and net available energy estimates were evaluated against ground truth data taken from 30 terrestrial tower sites affiliated to the FLUXNET network covering 7 different biome classes. This revealed a relatively good agreement between the satellite and tower data, with a pooled root mean square deviation of 98 and 72 W m−2 for net radiation and net available energy, respectively, although both quantities were underestimated by approximately 25 and 10%, respectively relative to the tower observations. Analysis of the individual shortwave and longwave components of the net radiation revealed the downwelling shortwave radiation to be the main source of this systematic underestimation.

  2. The vulnerability assessment of rainfall-induced debris flows in Taiwan

    Science.gov (United States)

    Lu, George Yen-Hsu

    2007-12-01

    A debris flow vulnerability assessment which incorporates topographic and rainfall effects is developed. Rainfall at a scale compatible with the resolution of digital elevation model is obtained using a neural network estimation method with a wind induced topographic effect and rainfall derived from satellite rain estimates and an improved inverse distance weight method. The technique is tested using data collected during the passage of typhoon Tori-Ji on July 2001, which caused massive debris flows in central Taiwan. Numerous debris flows triggered by the typhoon were used as control for the study. The results show that the proposed wind-topography neural network (WTNN) technique outperforms other popular interpolation techniques, including inversed distance weight method (IDW), ordinary kriging (OK), co-kriging method, and multiple linear regression method. Multiple fuzzy-logic-based debris flow susceptibility factors are used to characterize watersheds. Self-organizing maps (SOM) was adopted for the debris flow vulnerability assessment by incorporating estimated rainfall and debris flow susceptibility factors. The result examined by contingency table agrees to the assessment proposed by Soil and Water Conservation Bureau of Taiwan and National Science and Technology Center for Hazard Reduction of Taiwan. An index of vulnerability representing the degrees of hazard is implemented in a GIS-based decision support system which decision maker can use to manage debris flow environmental issues. Key Words. Debris flow, spatial interpolation, vulnerability assessment, satellite rainfall, neural network, GIS.

  3. Comparison of Satellite-Derived Wind Measurements with Other Wind Measurement Sensors

    Science.gov (United States)

    Susko, Michael; Herman, Leroy

    1995-01-01

    The purpose of this paper is to compare the good data from the Jimsphere launches with the data from the satellite system. By comparing the wind speeds from the Fixed Pedestal System 16 (FPS-16) Radar/Jimsphere Wind System and NASA's 50-MHz Radar Wind Profiler, the validation of winds from Geostationary Operational Environmental Satellite 7 (GOES-7) is performed. This study provides an in situ data quality check for the GOES-7 satellite winds. Comparison was made of the flowfields in the troposphere and the lower stratosphere of case studies of pairs of Jimsphere balloon releases and Radar Wind Profiler winds during Space Shuttle launches. The mean and standard deviation of the zonal component statistics, the meridional component statistics, and the power spectral density curves show good agreement between the two wind sensors. The standard deviation of the u and v components for the STS-37 launch (consisting of five Jimsphere/Radar Wind Profiler data sets) was 1.92 and 1.67 m/s, respectively; for the STS-43 launch (there were six Jimsphere/Wind Profiler data sets) it was 1.39 and 1.44 m/s, respectively. The overall standard deviation was 1.66 m/s for the u component and 1.55 m/s tor the v component, and a standard deviation of 2.27 m/s tor the vector wind difference. The global comparison of satellite with Jimsphere balloon vector winds shows a standard deviation of 3.15 m/s for STS-43 and 4.37 m/s for STS-37. The overall standard deviation of the vector wind was 3.76 m/s, with a root-mean-square vector difference of 4.43 m/s. These data have demonstrated that this unique comparison of the Jimsphere and satellite winds provides excellent ground truth and a frame of reference during testing and validation of satellite data

  4. Fade-durations derived from land-mobile-satellite measurements in Australia

    Science.gov (United States)

    Hase, Yoshihiro; Vogel, Wolfhard J.; Goldhirsh, Julius

    1991-01-01

    Transmissions from the Japanese ETS-V geostationary satellite were measured at L band (1.5 GHz) in a vehicle driving on roads of southeastern Australia. The measurements were part of a program designed to characterize propagation effects due to roadside trees and terrain for mobile satellite service. It is shown that the cumulative distributions of fade and nonfade durations follow a lognormal and power law, respectively. At 1 percent probability, fades last 2-8 m, and nonfades 10-100 m, depending on the degree of shadowing. Phase fluctuations are generally small, allowing the channel characteristics to be estimated from levels only.

  5. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tau Island, Territory of American Samoa, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  6. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Kingman Reef, Pacific Remote Island Area, USA

    Data.gov (United States)

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

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

    Data.gov (United States)

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

  8. Mosaic of gridded multibeam bathymetry, LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Saipan Island, Commonwealth of Northern Maraina Islands, USA

    Data.gov (United States)

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

  9. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  10. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Maug Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multpectral IKONOS satellite data. Gridded (5m and 10 m cell size) multibeam bathymetry...

  11. Mosaic of gridded multibeam bathymetry, gridded LiDAR bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Tinian Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

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

  12. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Ofu and Olosega Islands, Territory of American Samoa, USA

    Data.gov (United States)

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

  13. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

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

  14. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Asuncion Island, Commonwealth of the Northern Marianas Islands, USA

    Data.gov (United States)

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

  15. Mosaic of 10 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Gridded multibeam bathymetry is integrated with bathymetry derived from multispectral IKONOS satellite data. Gridded (10 m cell size) multibeam bathymetry collected...

  16. Mosaic of 5 m gridded multibeam bathymetry and bathymetry derived from multispectral IKONOS satellite imagery of Alamagan Island, Commonwealth of Northern Mariana Islands, USA

    Data.gov (United States)

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

  17. Mosaic of 2m bathymetry derived from multispectral IKONOS World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

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

  18. Mosaic of gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Baker Island, Pacific Remote Island Areas, Central Pacific.

    Data.gov (United States)

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

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

    Data.gov (United States)

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

  20. Mosaic of 5m gridded multibeam bathymetry and bathymetry derived from multispectral World View-2 satellite imagery of Swains Island, Territory of American Samoa, South Pacific, USA

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    DEFF Research Database (Denmark)

    Olsen, Nils; Finlay, Chris; Kotsiaros, Stavros

    2016-01-01

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

  6. Rainfall estimation over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms

    Science.gov (United States)

    Massari, Christian; Brocca, Luca; Pellarin, Thierry; Kerr, Yann; Crow, Wade; Cascon, Carlos; Ciabatta, Luca

    2016-04-01

    Recent advancements in the measurement of precipitation from space have provided estimates at scales that are commensurate with the needs of the hydrological and land-surface model communities. However, as demonstrated in a number of studies (Ebert et al. 2007, Tian et al. 2007, Stampoulis et al. 2012) satellite rainfall estimates are characterized by low accuracy in certain conditions and still suffer from a number of issues (e.g., bias) that may limit their utility in over-land applications (Serrat-Capdevila et al. 2014). In recent years many studies have demonstrated that soil moisture observations from ground and satellite sensors can be used for correcting satellite precipitation estimates (e.g. Crow et al., 2011; Pellarin et al., 2013), or directly estimating rainfall (SM2RAIN, Brocca et al., 2014). In this study, we carried out a detailed scientific analysis in which these three different methods are used for: i) estimating rainfall through satellite soil moisture observations (SM2RAIN, Brocca et al., 2014); ii) correcting rainfall through a Land surface Model Assimilation Algorithm (LMAA) (an improvement of a previous work of Crow et al. 2011 and Pellarin et al. 2013) and through the Soil Moisture Analysis Rainfall Tool (SMART, Crow et al. 2011). The analysis is carried within the ESA project "SMOS plus Rainfall" and involves 9 sites in Europe, Australia, Africa and USA containing high-quality hydrometeorological and soil moisture observations. Satellite soil moisture data from Soil Moisture and Ocean Salinity (SMOS) mission are employed for testing their potential in deriving a cumulated rainfall product at different temporal resolutions. The applicability and accuracy of the three algorithms is investigated also as a function of climatic and soil/land use conditions. A particular attention is paid to assess the expected limitations soil moisture based rainfall estimates such as soil saturation, freezing/snow conditions, SMOS RFI, irrigated areas

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

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-09-01

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

  8. Derivation of the radiation budget at ground level from satellite measurements

    Science.gov (United States)

    Raschke, E.

    1982-01-01

    Determination of the Earth radiaton budget and progress in measurement of the budget components and in the treatment of imaging data from satellites are described. Methods for calculating the radiation budget in a general circulation model, radiative transfer characteristics of clouds, computation of solar radiation at ground level using meteorological data and development of a 10-channel radiometer are discussed.

  9. Application of Multi-Satellite Precipitation Analysis to Floods and Landslides

    Science.gov (United States)

    Adler, Robert; Hong, Yang; Huffman, George

    2007-01-01

    Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described

  10. Sensitivity of accumulated rainfall and errors estimates to the configuration of microwave imagers constellation for the tropical regions

    Science.gov (United States)

    Chambon, P.; Jobard, I.; Capderou, M.; Roca, R.

    2012-04-01

    Over the intertropical belt, satellites are powerful tools to measure precipitation, as surface networks of rain gauges or radars are scarce over this part of the globe. Rainfall is central to the water and energy cycle of the Tropics and the upcoming GPM program offers a unique perspective on this important challenge. We explore here, via simulations, how sensitive are rainfall accumulation estimates to the design of the details of the observing system. The Megha-Tropiques TAPEER-BRAIN Level-4 product is considered for this study. TAPEER-BRAIN is a technique that builds rainfall accumulation estimations and associated error at the one-degree/one-day scale over the whole Tropical belt. TAPEER-BRAIN relies on the use of infrared imagers onboard a fleet of geostationary satellites and Level-2 instantaneous rainfall estimates derived from passive microwave radiometers onboard a constellation of low Earth orbiting satellites. An error model involving rainfall auto-correlation calculations is then used to characterize sampling uncertainties on accumulated precipitation estimations. This framework is used to simulate the various configuration of the observing system. To this end, Level-2 instantaneous rain products are simulated through the use of an orbit simulator and a sampling method. Rainfall estimations are extracted from the GSMaP rainfall product under the swath of simulated observing systems. One-degree/one-day rain and error estimations are then computed with infrared data and the simulated Level-2 instantaneous rain products for different scenarios of constellation. Sensitivities to the sampling of sun-synchronous satellites as well as observing systems on low-inclination orbits are performed. One of the main findings of this study is that satellites on "tropical" orbits have a high contribution to the improvements of TAPEER-BRAIN quantitative precipitation estimations (rain and error estimations). This study also shows that satellites with local Equator

  11. Humidity Profiles' Effect On The Relationship Between Ice Scattering And Rainfall In Microwave Rainfall Retrievals

    Science.gov (United States)

    Petkovic, V.; Kummerow, C. D.

    2013-12-01

    Currently, satellite microwave rainfall retrievals base their algorithm on an observed global average of the relationship between high frequency brightness temperature (Tb) depression and rainfall rate. This makes them very sensitive to differences in the ratio of ice to liquid in the cloud, resulting in regional biases of rainfall estimates. To address this problem we investigate how the environmental conditions that precede raining systems influence the ice to rainfall relationship. The vertical profile of humidity was found to be a key variable in predicting this ratio. We found that dry over moist air conditions are favorable for developing intense, well organized systems such as MCSs in West Africa and the Sahel, characterized by strong Tb depressions and amounts of ice aloft significantly above the globally observed average value. As a consequence, microwave retrieval algorithms misinterpret these systems assigning them unrealistically high rainfall rates. The opposite is true in the Amazon region, where observed raining systems exhibit very little ice while producing high rainfall rates. These regional differences correspond well with a map of radar to radiometer biases of rainfall. Deeper understanding of the influence of environmental conditions on this ice to rain ratio provides a foundation for mapping a global ice-scattering to rainfall rate relationship that will improve satellite microwave rainfall retrievals and our understanding of cloud microphysics globally.

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

    Data.gov (United States)

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

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

    DEFF Research Database (Denmark)

    Püthe, Christoph; Kuvshinov, Alexey; Khan, Amir;

    2015-01-01

    We present a newmodel of the radial (1-D) conductivity structure of Earth's mantle. This model is derived frommore than 10 yr of magnetic measurements from the satellites ørsted, CHAMP, SAC-C and the Swarm trio as well as the global network of geomagnetic observatories. After removal of core...... and crustal field as predicted by a recent field model, we fit the magnetic data with spherical harmonic coefficients describing ring current activity and associated induction effects and estimate global C-responses at periods between 1.5 and 150 d. The C-responses are corrected for 3-D effects due...

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

    Science.gov (United States)

    Czernecki, Bartosz; Jabłońska, Katarzyna; Nowosad, Jakub

    2016-04-01

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

  15. A satellite digital controller or 'play that PID tune again, Sam'. [Position, Integral, Derivative feedback control algorithm for design strategy

    Science.gov (United States)

    Seltzer, S. M.

    1976-01-01

    The problem discussed is to design a digital controller for a typical satellite. The controlled plant is considered to be a rigid body acting in a plane. The controller is assumed to be a digital computer which, when combined with the proposed control algorithm, can be represented as a sampled-data system. The objective is to present a design strategy and technique for selecting numerical values for the control gains (assuming position, integral, and derivative feedback) and the sample rate. The technique is based on the parameter plane method and requires that the system be amenable to z-transform analysis.

  16. 洞庭湖植被对降水的响应%Analysis of vegetation response to rainfall with satellite images in Dongting Lake

    Institute of Scientific and Technical Information of China (English)

    蒋卫国; 侯鹏; 朱晓华; 曹广真; 刘小曼; 曹入尹

    2011-01-01

    We analyzed the Normalized Difference Vegetation Index (NDVI) from satellite images and precipitation data from meteorological stations from 1998 to 2007 in the Dongting Lake wetland watershed to better understand the eco-hydrological effect of atmospheric precipitation and its relationship with vegetation. First, we analyzed its general spatio-temporal distribution using its mean, standard deviation and linear trend. Then, we used the Empirical Orthogonal Functions (EOF) method to decompose the NDVI and precipitation data into spatial and temporal modes. We selected four leading modes based on North and Scree test rules and analyzed the synchronous seasonal and inter-annual variability between the vegetation index and precipitation, distinguishing time-lagged correlations between EOF modes with the correlative degree analysis method. According to our detailed analyses, the vegetation index and precipitation exhibit a prominent correlation in spatial distribution and seasonal variation. At the 90% confidence level, the time lag is around 110 to 140 days,which matches well with the seasonal variation.

  17. The Orbits of Saturn's Small Satellites Derived from Combined Historic and Cassini Imaging Observations

    Science.gov (United States)

    Spitale, J. N.; Jacobson, R. A.; Porco, C. C.; Owen, W. M., Jr.

    2006-08-01

    We report on the orbits of the small, inner Saturnian satellites, either recovered or newly discovered in recent Cassini imaging observations. The orbits presented here reflect improvements over our previously published values in that the time base of Cassini observations has been extended, and numerical orbital integrations have been performed in those cases in which simple precessing elliptical, inclined orbit solutions were found to be inadequate. Using combined Cassini and Voyager observations, we obtain an eccentricity for Pan 7 times smaller than previously reported because of the predominance of higher quality Cassini data in the fit. The orbit of the small satellite (S/2005 S1 [Daphnis]) discovered by Cassini in the Keeler gap in the outer A ring appears to be circular and coplanar; no external perturbations are apparent. Refined orbits of Atlas, Prometheus, Pandora, Janus, and Epimetheus are based on Cassini , Voyager, Hubble Space Telescope, and Earth-based data and a numerical integration perturbed by all the massive satellites and each other. Atlas is significantly perturbed by Prometheus, and to a lesser extent by Pandora, through high-wavenumber mean-motion resonances. Orbital integrations involving Atlas yield a mass of GMAtlas=(0.44+/-0.04)×10-3 km3 s -2, 3 times larger than reported previously (GM is the product of the Newtonian constant of gravitation G and the satellite mass M). Orbital integrations show that Methone is perturbed by Mimas, Pallene is perturbed by Enceladus, and Polydeuces librates around Dione's L5 point with a period of about 791 days. We report on the nature and orbits of bodies sighted in the F ring, two of which may have persisted for a year or more.

  18. The annual cycle of satellite-derived sea surface temperature in the southwestern Atlantic Ocean

    Science.gov (United States)

    Podesta, Guillermo P.; Brown, Otis B.; Evans, Robert H.

    1991-01-01

    The annual cycle of sea surface temperature (SST) in the southwestern Atlantic Ocean was estimated using four years (July 1984-July 1988) of NOAA Advanced Very High Resolution Radiometer observations. High resolution satellite observations at 1-km space and daily time resolution were grided at 100-km space and 5-day time intervals to develop an analysis dataset for determination of low frequency SST variability. The integral time scale, a measure of serial correlation, was found to vary from 40 to 60 days in the domain of interest. The existence of superannual trends in the SST data was investigated, but conclusive results could not be obtained. The annual cycle (and, in particular, the annual harmonic) explains a large proportion of the SST variability. The estimated amplitude of the cycle ranges between 5 deg and 13 deg C throughout the study area, with minima in August-September and maxima in February. The resultant climatology is compared with an arbitrary 5-day satellite SST field, and with the COADS/ICE SST climatology. It was found that the higher resolution satellite-based SST climatology resolves boundary current structure and has significantly better structural agreement with the observed field.

  19. Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface

    Directory of Open Access Journals (Sweden)

    S.A. Margulis

    2001-01-01

    Full Text Available Global estimates of precipitation can now be made using data from a combination of geosynchronous and low earth-orbit satellites. However, revisit patterns of polar-orbiting satellites and the need to sample mixed-clouds scenes from geosynchronous satellites leads to the coarsening of the temporal resolution to the monthly scale. There are prohibitive limitations to the applicability of monthly-scale aggregated precipitation estimates in many hydrological applications. The nonlinear and threshold dependencies of surface hydrological processes on precipitation may cause the hydrological response of the surface to vary considerably based on the intermittent temporal structure of the forcing. Therefore, to make the monthly satellite data useful for hydrological applications (i.e. water balance studies, rainfall-runoff modelling, etc., it is necessary to disaggregate the monthly precipitation estimates into shorter time intervals so that they may be used in surface hydrology models. In this study, two simple statistical disaggregation schemes are developed for use with monthly precipitation estimates provided by satellites. The two techniques are shown to perform relatively well in introducing a reasonable temporal structure into the disaggregated time series. An ensemble of disaggregated realisations was routed through two land surface models of varying complexity so that the error propagation that takes place over the course of the month could be characterised. Results suggest that one of the proposed disaggregation schemes can be used in hydrological applications without introducing significant error. Keywords: precipitation, temporal disaggregation, hydrological modelling, error propagation

  20. Detecting Rainfall Onset Using Sky Images

    CERN Document Server

    Dev, Soumyabrata; Lee, Yee Hui; Winkler, Stefan

    2016-01-01

    Ground-based sky cameras (popularly known as Whole Sky Imagers) are increasingly used now-a-days for continuous monitoring of the atmosphere. These imagers have higher temporal and spatial resolutions compared to conventional satellite images. In this paper, we use ground-based sky cameras to detect the onset of rainfall. These images contain additional information about cloud coverage and movement and are therefore useful for accurate rainfall nowcast. We validate our results using rain gauge measurement recordings and achieve an accuracy of 89% for correct detection of rainfall onset.

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

    Directory of Open Access Journals (Sweden)

    L. Fita

    2009-08-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-01

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

  3. Toward Improved Solar Irradiance Forecasts: Comparison of Downwelling Surface Shortwave Radiation in Arizona Derived from Satellite with the Gridded Datasets

    Science.gov (United States)

    Kim, Chang Ki; Holmgren, William F.; Stovern, Michael; Betterton, Eric A.

    2016-08-01

    The downwelling surface shortwave radiation derived from geostationary satellite imagery was compared with the available datasets for the Southwestern United States. The averaged root mean square errors for our instantaneous estimates ranged from 95.0 to 122.7 W m-2, which is lower than those derived from the MODerate resolution Imaging Spectroradiometer (MODIS). The Modern Era Retrospective-analysis for Research and Applications (MERRA) products were used to compare the hourly mean solar insolation. The three hourly mean downwelling surface shortwave radiation was evaluated by comparing the North American Regional Reanalysis (NARR) and the Clouds and the Earth's Radiant Energy System (CERES) products. Our estimates show the better performance than MERRA, NARR and CERES datasets because of coarse resolution that limits determining the solar dimming due to small clouds.

  4. Oceanic Weather Decision Support for Unmanned Global Hawk Science Missions into Hurricanes with Tailored Satellite Derived Products

    Science.gov (United States)

    Feltz, Wayne; Griffin, Sarah; Velden, Christopher; Zipser, Ed; Cecil, Daniel; Braun, Scott

    2017-04-01

    The purpose of this presentation is to identify in-flight hazards to high-altitude aircraft, namely the Global Hawk. The Global Hawk was used during Septembers 2012-2016 as part of two NASA funded Hurricane Sentinel-3 field campaigns to over-fly hurricanes in the Atlantic Ocean. This talk identifies the cause of severe turbulence experienced over Hurricane Emily (2005) and how a combination of NOAA funded GOES-R algorithm derived cloud top heights/tropical overshooting tops using GOES-13/SEVIRI imager radiances, and lightning information are used to identify areas of potential turbulence for near real-time navigation decision support. Several examples will demonstrate how the Global Hawk pilots remotely received and used real-time satellite derived cloud and lightning detection information to keep the aircraft safely above clouds and avoid regions of potential turbulence.

  5. Pattern-oriented memory interpolation of sparse historical rainfall records

    Science.gov (United States)

    Matos, J. P.; Cohen Liechti, T.; Portela, M. M.; Schleiss, A. J.

    2014-03-01

    The pattern-oriented memory (POM) is a novel historical rainfall interpolation method that explicitly takes into account the time dimension in order to interpolate areal rainfall maps. The method is based on the idea that rainfall patterns exist and can be identified over a certain area by means of non-linear regressions. Having been previously benchmarked with a vast array of interpolation methods using proxy satellite data under different time and space availabilities, in the scope of the present contribution POM is applied to rain gauge data in order to produce areal rainfall maps. Tested over the Zambezi River Basin for the period from 1979 to 1997 (accurate satellite rainfall estimates based on spaceborne instruments are not available for dates prior to 1998), the novel pattern-oriented memory historical interpolation method has revealed itself as a better alternative than Kriging or Inverse Distance Weighing in the light of a Monte Carlo cross-validation procedure. Superior in most metrics to the other tested interpolation methods, in terms of the Pearson correlation coefficient and bias the accuracy of POM's historical interpolation results are even comparable with that of recent satellite rainfall products. The new method holds the possibility of calculating detailed and performing daily areal rainfall estimates, even in the case of sparse rain gauging grids. Besides their performance, the similarity to satellite rainfall estimates inherent to POM interpolations can contribute to substantially extend the length of the rainfall series used in hydrological models and water availability studies in remote areas.

  6. HOW STRONG IS THE RELATIONSHIP BETWEEN RAINFALL VARIABILITY AND CAATINGA PRODUCTIVITY? A CASE STUDY UNDER A CHANGING CLIMATE.

    Science.gov (United States)

    Salimon, Cleber; Anderson, Liana

    2017-05-22

    Despite the knowledge of the influence of rainfall on vegetation dynamics in semiarid tropical Brazil, few studies address and explore quantitatively the various aspects of this relationship. Moreover, Northeast Brazil is expected to have its rainfall reduced by as much as 60% until the end of the 21st Century, under scenario AII of the IPCC Report 2010. We sampled and analyzed satellite-derived monthly rainfall and a vegetation index data for 40 sites with natural vegetation cover in Paraíba State, Brazil from 2001 to 2012. In addition, the anomalies for both variables were calculated. Rainfall variation explained as much as 50% of plant productivity, using the vegetation index as a proxy, and rainfall anomaly explained 80% of the vegetation productivity anomaly. In an extreme dry year (2012), with 65% less rainfall than average for the period 2001-2012, the vegetation index decreased by 25%. If such decrease persists in a long term trend in rainfall reduction, this could lead to a disruption in this ecosystem functioning and the dominant vegetation could become even more xeric or desert-like, bringing serious environmental, social and economical impacts.

  7. On Rainfall Modification by Major Urban Areas. Part 1; Observations from Space-borne Rain Radar Aboard TRMM

    Science.gov (United States)

    Shepherd, J. Marshell; Starr, David OC. (Technical Monitor)

    2001-01-01

    A novel approach is introduced to correlating urbanization and rainfall modification. This study represents one of the first published attempts (possibly the first) to identify and quantify rainfall modification by urban areas using satellite-based rainfall measurements. Previous investigations successfully used rain gauge networks and around-based radar to investigate this phenomenon but still encountered difficulties due to limited, specialized measurements and separation of topographic and other influences. Three years of mean monthly rainfall rates derived from the first space-based rainfall radar, Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of data at half-degree latitude resolution enables identification of rainfall patterns around major metropolitan areas of Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Preliminary results reveal an average increase of 5.6% in monthly rainfall rates (relative to a mean upwind CONTROL area) over the metropolis but an average increase of approx. 28%, in monthly rainfall rates within 30-60 kilometers downwind of the metropolis. Some portions of the downwind area exhibit increases as high as 51%. It was also found that maximum rainfall rates found in the downwind impact area exceeded the mean value in the upwind CONTROL area by 48%-116% and were generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are quite consistent studies of St. Louis (e.g' METROMEX) and Chicago almost two decades ago and more recent studies in the Atlanta and Mexico City areas.

  8. Spatial Resolution of Core Surface Flow Models Derived From Satellite Data

    Science.gov (United States)

    Eymin, C.; Hulot, G.

    Core surface flows are usually computed from observations of the internal magnetic field and its secular variation. With observatory based secular variation models, the spatial resolution of core surface flows was mainly limited by the resolution of the secular variation model itself. This resolution dramatically improved with magnetic satellite data and for the first time the main limitation on core surface flow compu- tations comes from the hiding of the smallest length scale of the internal magnetic field by the crust. Indeed, the invisible small scale magnetic field may interact with core flows to produce large scale secular variation. This interaction cannot be taken into account during the flow computation process and may alter the computed flow models, even for large length scales. We investigate here the effects of the truncation of the internal magnetic field with known flow models using two different and inde- pendent core surface flow computation methods. In particular, we try to estimate the amplitude of the error introduced by this truncation and the spatial resolution that can be obtained with the new satellite data for core surface flows.

  9. A point rainfall model and rainfall intensity-duration-frequency analysis

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Chul-Sang; Jung, Kwang-Sik [Korea University, Jochiwon(Korea); Kim, Nam-Won [Korea Institute of Construction Technology, Koyang(Korea)

    2001-12-31

    This study proposes a theoretical methodology for deriving a rainfall intensity-duration-frequency(I-D-F) curve using a simple rectangular pulses Poisson process model. As the I-D-F curve derived by considering the model structure is dependent on the rainfall model parameters estimated using the observed first and second order statistics, it becomes less sensitive to the unusual rainfall events than that derived using the annual maxima rainfall series. This study has been applied to the rainfall data at Seoul and Incheon stations to check its applicability by comparing the two I-D-F curves from the model and the data. The results obtained are as followed. (1) As the duration becomes longer, the overlap probability increases significantly. However, its contribution to the rainfall intensity decreases a little. (2) When considering the overlap of each rainfall event, especially for large duration and return period, we could see obvious increases of rainfall intensity. This result is normal as the rainfall intensity is calculated by considering both the overlap probability and return period. Also, the overlap effect for Seoul station is found much higher than that for Incheon station, which is mainly due to the different overlap probabilities calculated using different rainfall model parameter sets. (3) As the rectangular pulses Poisson processes model used in this study cannot consider the clustering characteristics of rainfall, the derived I-D-F curves show less rainfall intensities than those from the annual maxima series. However, overall pattern of both I-D-F curves are found very similar, and the difference is believed to be overcome by use of a rainfall model with the clustering consideration. (author). 14 refs., 6 tabs., 2 figs.

  10. Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

    Science.gov (United States)

    Adler, Robert; Hong, Yang; Huffman, George

    2007-01-01

    Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described

  11. Validation of three satellite-derived databases of surface solar radiation using measurements performed at 42 stations in Brazil

    Science.gov (United States)

    Thomas, Claire; Wey, Etienne; Blanc, Philippe; Wald, Lucien

    2016-06-01

    The SoDa website (www.soda-pro.com) is populated with numerous solar-related Web services. Among them, three satellite-derived irradiation databases can be manually or automatically accessed to retrieve radiation values within the geographical coverage of the Meteosat Second Generation (MSG) satellite: the two most advanced versions of the HelioClim-3 database (versions 4 and 5, respectively HC3v4 and HC3v5), and the CAMS radiation service. So far, these databases have been validated against measurements of several stations in Europe and North Africa only. As the quality of such databases depends on the geographical regions and the climates, this paper extends this validation campaign and proposes an extensive comparison on Brazil and global irradiation received on a horizontal surface. Eleven stations from the Brazilian Institute of Space Research (INPE) network offer 1 min observations, and thirty-one stations from the Instituto Nacional de Meteorologia (INMET) network offer hourly observations. The satellite-derived estimates have been compared to the corresponding observations on hourly, daily and monthly basis. The bias relative to the mean of the measurements for HC3v5 is mostly comprised between 1 and 3 %, and that for HC3v4 between 2 and 5 %. These are very satisfactory results and they demonstrate that HC3v5, and to a lesser extent HC3v4, may be used in studies of long-term changes in SSI in Brazil. The situation is not so good with CAMS radiation service for which the relative bias is mostly comprised between 5 and 10 %. For hourly irradiation, the relative RMSE ranges from 15 to 33 %. The correlation coefficient is very large for all stations and the three databases, with an average of 0.96. The three databases reproduce well the hour from hour changes in SSI. The errors show a tendency to increase with the viewing angle of the MSG satellite. They are greater in tropical areas where the relative humidity in the atmosphere is important. It is concluded

  12. Derived bathymetry from WorldView-2 satellite imagery of nearshore benthic habitats

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Methods used were adapted from a "cookbook" of instructions developed by Kyle Hogref for using IKONOS imagery data to derive seafloor elevations in optically clear...

  13. Assessment of Satellite-Derived Essential Climate Variables in the Terrestrial Domain: Overview and Status of the CEOS LPV Subgroup

    Science.gov (United States)

    Roman, M. O.

    2015-12-01

    The validation of satellite-derived terrestrial observations has perennially faced the challenge of finding a consistent set of in-situ measurements that can both cover a wide range of surface conditions and provide timely and traceable product accuracy and uncertainty information. The Committee on Earth Observation Satellites (CEOS), the space arm of the Group on Earth Observations (GEO), plays a key role in coordinating the land product validation process. The Land Product Validation (LPV) sub-group of the CEOS Working Group on Calibration and Validation (WGCV) aims to address the challenges associated with the validation of global land products. This paper will provide a status of LPV subgroup focus area activities, which cover seven Global Climate Observing System (GCOS) terrestrial Essential Climate Variables (ECVs): (1) Snow Cover, (2) Surface Albedo, (3) Land Cover, (4) Leaf Area Index, (5) Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), (6) Active Fires, and (7) Soil Moisture; as well as two additional variables (Land Surface Phenology and Land Surface Temperature), which are deemed of high priority of the LPV community. A primary focus of LPV is the implementation of a global validation framework for product intercomparison and validation (fig. 1). This framework is based on a citable protocol, fiducial reference data, and automated subsetting. Ideally, each of these parts will be integrated into an online platform where quantitative tests are run, and standardized intercomparison and validation results reported for all products used in the validation exercise. The establishment of consensus guidelines for in situ measurements as well as inter-comparison of trends derived from independently-obtained reference data and derived products will enhance coordination of the scientific needs of the Earth system communities with global LPV activities (http://lpvs.gsfc.nasa.gov/).

  14. Deriving required model structures to predict global wildfire burned area from multiple satellite and climate observations

    Science.gov (United States)

    Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten

    2017-04-01

    Vegetation fires have important effects on human infrastructures and ecosystems, and affect atmospheric composition and the climate system. Consequently, it is necessary to accurately represent fire dynamics in global vegetation models to realistically represent the role of fires in the Earth system. However, it is unclear which model structures are required in global vegetation/fire models to represent fire activity at regional to global scales. Here we aim to identify required structural components and necessary complexities of global vegetation/fire models to predict spatial-temporal dynamics of burned area. For this purpose, we developed the SOFIA (satellite observations for fire activity) modelling approach to predict burned area from several satellite and climate datasets. A large ensemble of SOFIA models was generated and each model was optimized against observed burned area data. Models that account for a suppression of fire activity at wet conditions result in the highest performances in predicting burned area. Models that include vegetation optical depth data from microwave satellite observations reach higher performances in predicting burned area than models that do not include this dataset. Vegetation optical depth is a proxy for vegetation biomass, density and water content and thus indicates a strong control of vegetation states and dynamics on fire activity. We further compared the best performing SOFIA models with the global process-oriented vegetation/fire model JSBACH-SPITFIRE, and with the GFED and Fire_CCI burned area datasets. SOFIA models outperform JSBACH-SPITFIRE in predicting regional variabilities of burned area. We further applied the best SOFIA model to identify controlling factors for burned area. The results indicate that fire activity is controlled by regionally diverse and complex interactions of human, vegetation and climate factors. Our results demonstrate that the use of multiple observational datasets on climate, hydrological

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

    Directory of Open Access Journals (Sweden)

    Mikhail Zhizhin

    2009-08-01

    Full Text Available 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 m3 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 billion. The 2008 flaring added more than 278 million metric tons of carbon dioxide equivalent (CO2e 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

  16. Modeling directional effects in land surface temperature derived from geostationary satellite data

    DEFF Research Database (Denmark)

    Rasmussen, Mads Olander

    This PhD-thesis investigates the directional effects in land surface temperature (LST) estimates from the SEVIRI sensor onboard the Meteosat Second Generation (MSG) satellites. The directional effects are caused by the land surface structure (i.e. tree size and shape) interacting with the changing...... sun-target-sensor geometry. The directional effects occur because the different surface components, e.g. tree canopies and bare soil surfaces, will in many cases have significantly different temperatures. Depending on the viewing angle, different fractions of each of the components will be viewed......; shaded and sunlit canopy and background, respectively. Given data on vegetation structure and density, the model estimates the fractions of the four components as well as the directional composite temperature in the view of a sensor, given the illumination and viewing geometry. The modeling results show...

  17. The Transverse velocity of the Andromeda system, derived from the M31 satellite population

    CERN Document Server

    Salomon, J -B; Famaey, B; Martin, N F; Lewis, G F

    2015-01-01

    We present a dynamical measurement of the tangential motion of the Andromeda system, the ensemble consisting of the Andromeda Galaxy (M31) and its satellites. The system is modelled as a structure with cosmologically-motivated velocity dispersion and density profiles, and we show that our method works well when tested using the most massive substructures in high-resolution {\\Lambda} Cold Dark Matter ({\\Lambda}CDM) simulations. Applied to the sample of 40 currently-known galaxies of this system, we find a value for the transverse velocity of 164.4 +/- 61.8 km/s (v_{East} = -111.5 +/- 70.2 km/s and v{North} = 99.4 +/- 60.0 km/s), significantly higher than previous estimates of the proper motion of M31 itself. This result has significant implications on estimates of the mass of the Local Group, as well as on its past and future history.

  18. Variations in transport derived from satellite altimeter data over the Gulf Stream

    Science.gov (United States)

    Molinelli, E.; Lambert, R. B.

    1981-01-01

    Variations in total change of sea surface height (delta h) across the Gulf Stream are observed using Seasat radar altimeter data. The sea surface height is related to transport within the stream by a two layer model. Variations in delta h are compared with previously observed changes in transport found to increase with distance downstream. No such increase is apparent since the satellite transports show no significant dependence on distance. Though most discrepancies are less than 50 percent, a few cases differ by about 100 percent and more. Several possible reasons for these discrepancies are advanced, including geoid error, but only two oceanographic contributions to the variability are examined, namely, limitations in the two layer model and meanders in the current. It is concluded that some of the discrepancies could be explained as changes in the density structure not accounted for by the two layer model.

  19. Potential for a biogenic influence on cloud microphysics over the ocean: a correlation study with satellite-derived data

    Directory of Open Access Journals (Sweden)

    A. Lana

    2012-09-01

    Full Text Available Aerosols have a large potential to influence climate through their effects on the microphysics and optical properties of clouds and, hence, on the Earth's radiation budget. Aerosol–cloud interactions have been intensively studied in polluted air, but the possibility that the marine biosphere plays an important role in regulating cloud brightness in the pristine oceanic atmosphere remains largely unexplored. We used 9 yr of global satellite data and ocean climatologies to derive parameterizations of the temporal variability of (a production fluxes of sulfur aerosols formed by the oxidation of the biogenic gas dimethylsulfide emitted from the sea surface; (b production fluxes of secondary organic aerosols from biogenic organic volatiles; (c emission fluxes of biogenic primary organic aerosols ejected by wind action on sea surface; and (d emission fluxes of sea salt also lifted by the wind upon bubble bursting. Series of global monthly estimates of these fluxes were correlated to series of potential cloud condensation nuclei (CCN numbers derived from satellite (MODIS. More detailed comparisons among weekly series of estimated fluxes and satellite-derived cloud droplet effective radius (re data were conducted at locations spread among polluted and clean regions of the oceanic atmosphere. The outcome of the statistical analysis was that positive correlation to CCN numbers and negative correlation to re were common at mid and high latitude for sulfur and organic secondary aerosols, indicating both might be important in seeding cloud droplet activation. Conversely, primary aerosols (organic and sea salt showed widespread positive correlations to CCN only at low latitudes. Correlations to re were more variable, non-significant or positive, suggesting that, despite contributing to large shares of the marine aerosol mass, primary aerosols are not widespread major drivers of the variability of cloud

  20. Nonlinear responses of southern African rainfall to forcing from Atlantic SST in a high-resolution regional climate model

    Science.gov (United States)

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

    2009-04-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, high resolution satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA) are used as a basis for undertaking model experiments using a state-of-the-art regional climate model. The MIRA dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the regional climate model's domain size are briefly presented, before a comparison of simulated daily rainfall from the model with the satellite-derived dataset. Secondly, simulations of current climate and rainfall extremes from the model are compared to the MIRA dataset at daily timescales. Finally, the results from the idealised SST experiments are presented, suggesting highly nonlinear associations between rainfall extremes

  1. Response of African elephants (Loxodonta africana to seasonal changes in rainfall.

    Directory of Open Access Journals (Sweden)

    Michael Garstang

    Full Text Available The factors that trigger sudden, seasonal movements of elephants are uncertain. We hypothesized that savannah elephant movements at the end of the dry season may be a response to their detection of distant thunderstorms. Nine elephants carrying Global Positioning System (GPS receivers were tracked over seven years in the extremely dry and rugged region of northwestern Namibia. The transition date from dry to wet season conditions was determined annually from surface- and satellite-derived rainfall. The distance, location, and timing of rain events relative to the elephants were determined using the Tropical Rainfall Measurement Mission (TRMM satellite precipitation observations. Behavioral Change Point Analysis (BCPA was applied to four of these seven years demonstrating a response in movement of these elephants to intra- and inter-seasonal occurrences of rainfall. Statistically significant changes in movement were found prior to or near the time of onset of the wet season and before the occurrence of wet episodes within the dry season, although the characteristics of the movement changes are not consistent between elephants and years. Elephants in overlapping ranges, but following separate tracks, exhibited statistically valid non-random near-simultaneous changes in movements when rainfall was occurring more than 100 km from their location. While the environmental trigger that causes these excursions remains uncertain, rain-system generated infrasound, which can travel such distances and be detected by elephants, is a possible trigger for such changes in movement.

  2. Response of African elephants (Loxodonta africana) to seasonal changes in rainfall.

    Science.gov (United States)

    Garstang, Michael; Davis, Robert E; Leggett, Keith; Frauenfeld, Oliver W; Greco, Steven; Zipser, Edward; Peterson, Michael

    2014-01-01

    The factors that trigger sudden, seasonal movements of elephants are uncertain. We hypothesized that savannah elephant movements at the end of the dry season may be a response to their detection of distant thunderstorms. Nine elephants carrying Global Positioning System (GPS) receivers were tracked over seven years in the extremely dry and rugged region of northwestern Namibia. The transition date from dry to wet season conditions was determined annually from surface- and satellite-derived rainfall. The distance, location, and timing of rain events relative to the elephants were determined using the Tropical Rainfall Measurement Mission (TRMM) satellite precipitation observations. Behavioral Change Point Analysis (BCPA) was applied to four of these seven years demonstrating a response in movement of these elephants to intra- and inter-seasonal occurrences of rainfall. Statistically significant changes in movement were found prior to or near the time of onset of the wet season and before the occurrence of wet episodes within the dry season, although the characteristics of the movement changes are not consistent between elephants and years. Elephants in overlapping ranges, but following separate tracks, exhibited statistically valid non-random near-simultaneous changes in movements when rainfall was occurring more than 100 km from their location. While the environmental trigger that causes these excursions remains uncertain, rain-system generated infrasound, which can travel such distances and be detected by elephants, is a possible trigger for such changes in movement.

  3. Modeling of groundwater draft based on satellite-derived crop acreage estimation over an arid region of northwest India

    Science.gov (United States)

    Bhadra, Bidyut Kumar; Kumar, Sanjay; Paliwal, Rakesh; Jeyaseelan, A. T.

    2016-11-01

    Over-exploitation of groundwater for agricultural crops puts stress on the sustainability of natural resources in the arid region of Rajasthan state, India. Hydrogeological study of groundwater levels of the study area during the pre-monsoon (May to June), post-monsoon (October to November) and post-irrigation (February to March) seasons of 2004-2005 to 2011-2012 shows a steady decline of groundwater levels at the rate of 1.28-1.68 m/year, mainly due to excessive groundwater draft for irrigation. Due to the low density of the groundwater observation-well network in the study area, assessment of groundwater draft, and thus groundwater resource management, becomes a difficult task. To overcome the situation, a linear groundwater draft model (LGDM) has been developed based on the empirical relationship between satellite-derived crop acreage and the observed groundwater draft for the year 2003-2004. The model has been validated for a decade, during three year-long intervals (2005-2006, 2008-2009 and 2011-2012) using groundwater draft, estimated through a discharge factor method. Further, the estimated draft was validated through observed pumping data from random sampled villages (2011-2012). The results suggest that the developed LGDM model provides a good alternative to the estimation of groundwater draft based on satellite-based crop area in the absence of groundwater observation wells in arid regions of northwest India.

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

    DEFF Research Database (Denmark)

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

    2009-01-01

    coefficients up to n = 20 are described by order 5 splines (with 6-month knot spacing) spanning the years from 1997.0 to 2009.5. Compared to its predecessors, the temporal regularization of the CHAOS-2 model is also modified. Indeed, second and higher order time derivatives of the core field are damped...

  5. Determining the Pixel-to-Pixel Uncertainty in Satellite-Derived SST Fields

    Directory of Open Access Journals (Sweden)

    Fan Wu

    2017-08-01

    Full Text Available The primary measure of the quality of sea surface temperature (SST fields obtained from satellite-borne infrared sensors has been the bias and variance of matchups with co-located in-situ values. Because such matchups tend to be widely separated, these bias and variance estimates are not necessarily a good measure of small scale (several pixels gradients in these fields because one of the primary contributors to the uncertainty in satellite retrievals is atmospheric contamination, which tends to have large spatial scales compared with the pixel separation of infrared sensors. Hence, there is not a good measure to use in selecting SST fields appropriate for the study of submesoscale processes and, in particular, of processes associated with near-surface fronts, both of which have recently seen a rapid increase in interest. In this study, two methods are examined to address this problem, one based on spectra of the SST data and the other on their variograms. To evaluate the methods, instrument noise was estimated in Level-2 Visible-Infrared Imager-Radiometer Suite (VIIRS and Advanced Very High Resolution Radiometer (AVHRR SST fields of the Sargasso Sea. The two methods provided very nearly identical results for AVHRR: along-scan values of approximately 0.18 K for both day and night and along-track values of 0.21 K for day and night. By contrast, the instrument noise estimated for VIIRS varied by method, scan geometry and day-night. Specifically, daytime, along-scan (along-track, spectral estimates were found to be approximately 0.05 K (0.08 K and the corresponding nighttime values of 0.02 K (0.03 K. Daytime estimates based on the variogram were found to be 0.08 K (0.10 K with the corresponding nighttime values of 0.04 K (0.06 K. Taken together, AVHRR instrument noise is significantly larger than VIIRS instrument noise, along-track noise is larger than along-scan noise and daytime levels are higher than nighttime levels. Given the similarity of

  6. Deriving supraglacial debris thickness using satellite data on the Lirung Glacier in the Nepalese Himalayas

    Science.gov (United States)

    Petersen, Lene; Schauwecker, Simone; Brock, Ben; Immerzeel, Walter; Pellicciotti, Francesca

    2013-04-01

    Glaciers with debris-covered ablation zones are widely present in mountain ranges such as the Alps, the Himalayas and the Andes. An expansion of rock debris-covered areas has been documented in recent decades. It is therefore increasingly important to take the effect of debris cover into account in glacio-hydrological modelling. Debris thickness is a key control on a glacier's energy balance and it governs the melt rate beneath debris, hence the estimation of debris extent and thickness is crucial to predict melt. Data on debris thickness are scarce on most glaciers and thus simplified assumptions are commonly used. In this study we test a new, recently developed physically based method to produce debris thickness maps from satellite imagery. The model is based on a solution of the energy balance equation at the debris surface to reconstruct debris thickness as a residual in each satellite pixel. This approach requires ASTER thermal images and reanalysis meteorological data and has the potential to map distribution of debris thickness without the need for detailed field data. In a previous study we tested the model for glaciers with different characteristics and in different climatic regions of the world. The validation of debris thickness, however, is problematic due to data scarcity, the inhomogeneous debris distribution and the resolution of the ASTER product (90 m). The standard application of the model seems to work for glaciers for which debris characteristics such as the effective conductivity are known and reanalysis data are representative. In this study we additionally test the approach with a recently collected data set over the Lirung glacier in the Nepalese Himalayas, where initial application of the remote sensing method using reanalysis data led to a significant underestimation of debris thickness. Extensive field data were collected from May to October 2012 consisting of data from an AWS, spatially distributed air and surface temperature, effective

  7. Improvement of global and regional mean sea level derived from satellite altimetry multi missions

    Science.gov (United States)

    Ablain, M.; Faugere, Y.; Larnicol, G.; Picot, N.; Cazenave, A.; Benveniste, J.

    2012-04-01

    With the satellite altimetry missions, the global mean sea level (GMSL) has been calculated on a continual basis since January 1993. 'Verification' phases, during which the satellites follow each other in close succession (Topex/Poseidon--Jason-1, then Jason-1--Jason-2), help to link up these different missions by precisely determining any bias between them. Envisat, ERS-1 and ERS-2 are also used, after being adjusted on these reference missions, in order to compute Mean Sea Level at high latitudes (higher than 66°N and S), and also to improve spatial resolution by combining all these missions together. The global mean sea level (MSL) deduced from TOPEX/Poseidon, Jason-1 and Jason-2 provide a global rate of 3.2 mm from 1993 to 2010 applying the post glacial rebound (MSL aviso website http://www.jason.oceanobs.com/msl). Besides, the regional sea level trends bring out an inhomogeneous repartition of the ocean elevation with local MSL slopes ranging from + 8 mm/yr to - 8 mm/year. A study published in 2009 [Ablain et al., 2009] has shown that the global MSL trend unceratainty was estimated at +/-0.6 mm/year with a confidence interval of 90%. The main sources of errors at global and regional scales are due to the orbit calculation and the wet troposphere correction. But others sea-level components have also a significant impact on the long-term stability of MSL as for instance the stability of instrumental parameters and the atmospheric corrections. Thanks to recent studies performed in the frame of the SALP project (supported by CNES) and Sea-level Climate Change Initiative project (supported by ESA), strong improvements have been provided for the estimation of the global and regional MSL trends. In this paper, we propose to describe them; they concern the orbit calculation thanks to new gravity fields, the atmospheric corrections thanks to ERA-interim reanalyses, the wet troposphere corrections thanks to the stability improvement, and also empirical corrections

  8. Rainfall Effects on the Kuroshio Current East of Taiwan

    Science.gov (United States)

    Hsu, Po-Chun; Lin, Chen-Chih; Ho, Chung-Ru

    2017-04-01

    Changes of sea surface salinity (SSS) in the open oceans are related to precipitation and evaporation. SSS has been an indicator of water cycle. It may be related to the global change. The Kuroshio Current, a western boundary current originating from the North Equatorial Current, transfers warm and higher salinity to higher latitudes. It flows northward along the east coasts of Luzon Island and Taiwan Island to Japan. In this study, effects of heavy rainfall on the Kuroshio surface salinity east of Taiwan are investigated. Sea surface salinity (SSS) data taken by conductivity temperature depth (CTD) sensor on R/V Ocean Researcher I cruises, conductivity sensor on eight glider cruises, and Aquarius satellite data are used in this study. The rain rate data derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are also employed. A glider is a kind of autonomous underwater vehicle, which uses small changes in its buoyancy in conjunction with wings to convert vertical motion to horizontal in the underwater without requiring input from an operator. It can take sensors to measure salinity, temperature, and pressure. The TRMM/TMI data from remote sensing system are daily and are mapped to 0.25-degree grid. The results show a good correlation between the rain rate and SSS with a correlation coefficient of 0.86. The rainfall causes SSS of the Kuroshio surface water drops 0.176 PSU per 1 mm/hr rain rate.

  9. Global Electric Circuit Diurnal Variation Derived from Storm Overflight and Satellite Optical Lightning Datasets

    Science.gov (United States)

    Mach, Douglas M.; Blakeslee, R. J.; Bateman, M. J.; Bailey, J. C.

    2011-01-01

    We have combined analyses of over 1000 high altitude aircraft observations of electrified clouds with diurnal lightning statistics from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to produce an estimate of the diurnal variation in the global electric circuit. Using basic assumptions about the mean storm currents as a function of flash rate and location, and the global electric circuit, our estimate of the current in the global electric circuit matches the Carnegie curve diurnal variation to within 4% for all but two short periods of time. The agreement with the Carnegie curve was obtained without any tuning or adjustment of the satellite or aircraft data. Mean contributions to the global electric circuit from land and ocean thunderstorms are 1.1 kA (land) and 0.7 kA (ocean). Contributions to the global electric circuit from ESCs are 0.22 kA for ocean storms and 0.04 kA for land storms. Using our analysis, the mean total conduction current for the global electric circuit is 2.0 kA.

  10. Observed daily large-scale rainfall patterns during BOBMEX-1999

    Indian Academy of Sciences (India)

    A K Mitra; M Das Gupta; R K Paliwal; S V Singh

    2003-06-01

    A daily rainfall dataset and the corresponding rainfall maps have been produced by objective analysis of rainfall data. The satellite estimate of rainfall and the raingauge values are merged to form the final analysis. Associated with epochs of monsoon these rainfall maps are able to show the rainfall activities over India and the Bay of Bengal region during the BOBMEX period. The intra-seasonal variations of rainfall during BOBMEX are also seen using these data. This dataset over the oceanic region compares well with other available popular datasets like GPCP and CMAP. Over land this dataset brings out the features of monsoon in more detail due to the availability of more local raingauge stations.

  11. Simulation of suspended sediment transport initialized with satellite derived suspended sediment concentrations

    Indian Academy of Sciences (India)

    Ratheesh Ramakrishnan; A S Rajawat

    2012-10-01

    Suspended sediment transport in the Gulf of Kachchh is simulated utilizing the suspended sediment concentration (SSC) derived from Oceansat OCM imagery, as the initial condition in MIKE-21 Mud Transport model. Optimization of the model mud parameters, like settling velocity and critical shear stress for erosion are realized with respect to the sediment size distribution and the bottom bed materials observed in the Gulf. Simulated SSCs are compared with alternate OCM derived SSC. The results are observed to be impetus where the model is able to generate the spatial dynamics of the sediment concentrations. Sediment dynamics like deposition, erosion and dispersion are explained with the simulated tidal currents and OCM derived sediment concentrations. Tidal range is observed as the important physical factor controlling the deposition and resuspension of sediments within the Gulf. From the simulation studies; maximum residual current velocities, tidal fronts and high turbulent zones are found to characterise the islands and shoals within the Gulf, which results in high sediment concentrations in those regions. Remarkable variability in the bathymetry of the Gulf, different bed materials and varying tidal conditions induces several circulation patterns and turbulence creating the unique suspended sediment concentration pattern in the Gulf.

  12. Urban rainfall estimation employing commercial microwave links

    Science.gov (United States)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire

    2015-04-01

    Urban areas often lack rainfall information. To increase the number of rainfall observations in cities, microwave links from operational cellular telecommunication networks may be employed. Although this new potential source of rainfall information has been shown to be promising, its quality needs to be demonstrated more extensively. In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Part of this project is rainfall estimation using new measurement techniques. Innovative sensing techniques will be utilized such as rainfall estimation from microwave links, umbrellas for weather sensing, low-cost sensors at lamp posts and in drainage pipes for water level observation. These will be combined with information provided by citizens in an active way through smartphone apps and in a passive way through social media posts (Twitter, Flickr etc.). Sensor information will be integrated, visualized and made accessible to citizens to help raise citizen awareness of urban water management challenges and promote resilience by providing information on how citizens can contribute in addressing these. Moreover, citizens and businesses can benefit from reliable weather information in planning their social and commercial activities. In the end city-wide high-resolution rainfall maps will be derived, blending rainfall information from microwave links and weather radars. This information will be used for urban water management. This presentation focuses on rainfall estimation from commercial microwave links. Received signal levels from tens of microwave links within the Amsterdam region (roughly 1 million inhabitants) in the Netherlands are utilized to estimate rainfall with high spatial and temporal resolution. Rainfall maps will be presented and compared to a gauge-adjusted radar rainfall data set. Rainfall time series from gauge(s), radars and links will be compared.

  13. A Satellite-Derived Climatological Analysis of Urban Heat Island over Shanghai during 2000–2013

    Directory of Open Access Journals (Sweden)

    Weijiao Huang

    2017-06-01

    Full Text Available The urban heat island is generally conducted based on ground observations of air temperature and remotely sensing of land surface temperature (LST. Satellite remotely sensed LST has the advantages of global coverage and consistent periodicity, which overcomes the weakness of ground observations related to sparse distributions and costs. For human related studies and urban climatology, canopy layer urban heat island (CUHI based on air temperatures is extremely important. This study has employed remote sensing methodology to produce monthly CUHI climatology maps during the period 2000–2013, revealing the spatiotemporal characteristics of daytime and nighttime CUHI during this period of rapid urbanization in Shanghai. Using stepwise linear regression, daytime and nighttime air temperatures at the four overpass times of Terra/Aqua were estimated based on time series of Terra/Aqua-MODIS LST and other auxiliary variables including enhanced vegetation index, normalized difference water index, solar zenith angle and distance to coast. The validation results indicate that the models produced an accuracy of 1.6–2.6 °C RMSE for the four overpass times of Terra/Aqua. The models based on Terra LST showed higher accuracy than those based on Aqua LST, and nighttime air temperature estimation had higher accuracy than daytime. The seasonal analysis shows daytime CUHI is strongest in summer and weakest in winter, while nighttime CUHI is weakest in summer and strongest in autumn. The annual mean daytime CUHI during 2000–2013 is 1.0 and 2.2 °C for Terra and Aqua overpass, respectively. The annual mean nighttime CUHI is about 1.0 °C for both Terra and Aqua overpass. The resultant CUHI climatology maps provide a spatiotemporal quantification of CUHI with emphasis on temperature gradients. This study has provided information of relevance to urban planners and environmental managers for assessing and monitoring urban thermal environments which are constantly

  14. Using satellite-derived optical thickness to assess the influence of clouds on terrestrial carbon uptake

    Science.gov (United States)

    Cheng, S. J.; Steiner, A. L.; Hollinger, D. Y.; Bohrer, G.; Nadelhoffer, K. J.

    2016-07-01

    Clouds scatter direct solar radiation, generating diffuse radiation and altering the ratio of direct to diffuse light. If diffuse light increases plant canopy CO2 uptake, clouds may indirectly influence climate by altering the terrestrial carbon cycle. However, past research primarily uses proxies or qualitative categories of clouds to connect the effect of diffuse light on CO2 uptake to sky conditions. We mechanistically link and quantify effects of cloud optical thickness (τc) to surface light and plant canopy CO2 uptake by comparing satellite retrievals of τc to ground-based measurements of diffuse and total photosynthetically active radiation (PAR; 400-700 nm) and gross primary production (GPP) in forests and croplands. Overall, total PAR decreased with τc, while diffuse PAR increased until an average τc of 6.8 and decreased with larger τc. When diffuse PAR increased with τc, 7-24% of variation in diffuse PAR was explained by τc. Light-use efficiency (LUE) in this range increased 0.001-0.002 per unit increase in τc. Although τc explained 10-20% of the variation in LUE, there was no significant relationship between τc and GPP (p > 0.05) when diffuse PAR increased. We conclude that diffuse PAR increases under a narrow range of optically thin clouds and the dominant effect of clouds is to reduce total plant-available PAR. This decrease in total PAR offsets the increase in LUE under increasing diffuse PAR, providing evidence that changes within this range of low cloud optical thickness are unlikely to alter the magnitude of terrestrial CO2 fluxes.

  15. Management and climate contributions to satellite-derived active fire trends in the contiguous United States

    Science.gov (United States)

    Lin, Hsiao-Wen; McCarty, Jessica L.; Wang, Dongdong; Rogers, Brendan M.; Morton, Douglas C.; Collatz, G. James; Jin, Yufang; Randerson, James T.

    2014-04-01

    Fires in croplands, plantations, and rangelands contribute significantly to fire emissions in the United States, yet are often overshadowed by wildland fires in efforts to develop inventories or estimate responses to climate change. Here we quantified decadal trends, interannual variability, and seasonality of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of active fires (thermal anomalies) as a function of management type in the contiguous U.S. during 2001-2010. We used the Monitoring Trends in Burn Severity database to identify active fires within the perimeter of large wildland fires and land cover maps to identify active fires in croplands. A third class of fires defined as prescribed/other included all residual satellite active fire detections. Large wildland fires were the most variable of all three fire types and had no significant annual trend in the contiguous U.S. during 2001-2010. Active fires in croplands, in contrast, increased at a rate of 3.4% per year. Cropland and prescribed/other fire types combined were responsible for 77% of the total active fire detections within the U.S and were most abundant in the south and southeast. In the west, cropland active fires decreased at a rate of 5.9% per year, likely in response to intensive air quality policies. Potential evaporation was a dominant regulator of the interannual variability of large wildland fires, but had a weaker influence on the other two fire types. Our analysis suggests it may be possible to modify landscape fire emissions within the U.S. by influencing the way fires are used in managed ecosystems.

  16. New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

    Science.gov (United States)

    Liberman, Y.; Samuels, R.; Alpert, P.; Messer, H.

    2014-10-01

    One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date, the most effective methods for large-scale rainfall estimates are radar, satellites, and, more recently, received signal level (RSL) measurements derived from commercial microwave networks (CMNs). While these methods provide improved spatial resolution over traditional rain gauges, they have their limitations as well. For example, wireless CMNs, which are comprised of microwave links (ML), are dependant upon existing infrastructure and the ML' arbitrary distribution in space. Radar, on the other hand, is known in its limitation for accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rainfall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that, by using the proposed new method, we not only generate more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show that our method outperforms CMNs or the radar alone in rain rate estimation, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, as well as the accurate rainfall measurements over large areas at sub-hourly timescales, will allow for improved understanding, initialization, and calibration of hydrological and meteorological models mainly necessary for water resource management and planning.

  17. Passive microwave rainfall retrieval: A mathematical approach via sparse learning

    Science.gov (United States)

    Ebtehaj, M.; Lerman, G.; Foufoula-Georgiou, E.

    2013-12-01

    Detection and estimation of surface rainfall from spaceborne radiometric imaging is a challenging problem. The main challenges arise due to the nonlinear relationship of surface rainfall with its microwave multispectral signatures, the presence of noise, insufficient spatial resolution in observations, and the mixture of the earth surface and atmospheric radiations. A mathematical approach is presented for the detection and retrieval of surface rainfall from radiometric observations via supervised learning. In other words, we use a priori known libraries of high-resolution rainfall observations (e.g., obtained by an active radar) and their coincident spectral signatures (i.e., obtained by a radiometer) to design a mathematical model for rainfall retrieval. This model views the rainfall retrieval as a nonlinear inverse problem and relies on sparsity-promoting Bayesian inversion techniques. In this approach, we assume that small neighborhoods of the rainfall fields and their spectral signatures live on manifolds with similar local geometry and encode those neighborhoods in two joint libraries, the so-called rainfall and spectral dictionaries. We model rainfall passive microwave images by sparse linear combinations of the atoms of the spectral dictionary and then use the same representation coefficients to retrieve surface rain rates from the corresponding rainfall dictionary. The proposed methodology is examined by the use of spectral and rainfall dictionaries provided by the microwave imager (TMI) and precipitation radar (PR), aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. Pros and cons of the presented approach are studied by extensive comparisons with the current operational rainfall algorithm of the TRMM satellite. Future extensions are also highlighted for potential application in the era of the Global Precipitation Measurement (GPM) mission. Comparing the retrieved rain rates for Hurricane Danielle 08/29/2010 (UTC 09:48:00). (Top panel) PR-2A

  18. How consistent is the satellite derived SST-LHF relationship in comparison with observed values ?

    Digital Repository Service at National Institute of Oceanography (India)

    Muraleedharan, P.M.; Pankajakshan, T.

    derived products. It is quite natural that the relationship, in general, resembled one another in the left and right panels except that of SST and D q with LHF, where the mean trend appears to be opposite (figure 3 (a),(b),(e),(f)). The reason...C and 2ms 21 , respectively and underestimates the humidity gradient by 2 g kg 21 (figure 6(b),(d),(f)). The process of underestimation of SST below 28.5uC, therefore, induces high LHF by invoking the thumb rule proposed by Zhang and McPhaden (1995...

  19. The Hamburg Ocean-Atmosphere Parameters and Fluxes from Satellite Data (HOAPS): A climatological atlas of satellite-derived air-sea interaction parameters over the world oceans

    Digital Repository Service at National Institute of Oceanography (India)

    Grassl, H.; Jost, V.; Schulz, J.; RameshKumar, M.R.; Bauer, P.; Schluessel, P.

    temperature, specific humidity at air and sea surface temperature, difference in humidity, Dalton number, wind speed and the air sea fluxes such as latent heat, sensible heat and longwave radiation. The atlas also provides the hydrological cycle parameters..., the humidity difference, wind speed, the Dalton num- ber used for the parameterisation of latent heat flux, latent heat flux, sensible heat flux, net longwave radiation at the surface, evaporation, rainfall, and the freshwater flux computed as their difference...

  20. Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data: a case study of reintroduced red kites.

    Science.gov (United States)

    van der Wal, René; Zeng, Cheng; Heptinstall, Danny; Ponnamperuma, Kapila; Mellish, Chris; Ben, Stuart; Siddharthan, Advaith

    2015-11-01

    Analysis of satellite-telemetry data mostly occurs long after it has been collected, due to the time and effort needed to collate and interpret such material. Delayed reporting reduces the usefulness of such data for nature conservation where timely information about animal movements is required. To counter this problem, we present a novel approach which combines automated analysis of satellite-telemetry data with rapid communication of insights derived from such data. A relatively simple algorithm (based on radial and angular velocity calculated from fixes) allowed instantaneous detection of excursions away from settlement areas and automated calculation of home ranges on the remaining data. Automating the detection of both excursions and home-range calculations enabled us to disseminate ecological insights from satellite-tag data instantaneously through a dedicated web portal. The automated analysis, interpretation, and communication of satellite-tag and other ecological data offer clear benefits to nature conservation research and practice.

  1. Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data

    Science.gov (United States)

    Wu, Mousong; Sholze, Marko

    2017-04-01

    We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.

  2. A Geostatistical Approach to Reducing Uncertainty in Rainfall Estimates Using Terrain Characteristics: A Case Study in the Central-North Regional Water Administration of Mozambique (ARA Centro-Norte)

    Science.gov (United States)

    Raheem, Y. T.; Freyberg, D. L.

    2012-12-01

    Many data-sparse regions, such as southern Africa, will likely face significant changes in water resources availability and timing in the future due land use change, climate change and population growth. Improved estimates of rainfall and streamflow are necessary to improve water resources decision-making, risk management, and uncertainty quantification. In this study, we use a universal kriging framework to associate various watershed terrain characteristics with gauged rainfall data to improve the estimation of monthly rainfall fields. We focus on available gauge data because other precipitation data sources, such as satellite precipitation products, are unavailable over historic periods of interest and exhibit bias in our context of streamflow estimation. Our study area is the 185,000 sq km Central-North Regional Water Administration of Mozambique (ARA Centro-Norte), which is predominantly rural tropical savanna. We use fifty years of spatially and temporally sparse monthly rainfall observations from 316 rainfall gauges. Most of the watershed terrain characteristics we use are derived from the 90m HydroSHEDS Digital Elevation Model dataset. These include elevation, aspect, slope, distance to large water bodies, distance to ridges, and distance to watershed rainfall maximum. We quantify the importance of these characteristics for reducing uncertainty in rainfall estimates using the Bayes information criterion (BIC) approach. Future work includes using these rainfall estimates to drive the semi-distributed monthly time-step Pitman rainfall-runoff model, in order to reduce uncertainty in streamflow estimates in gauged and ungauged basins.

  3. On the surface circulation of the Levantine sub-basin derived from Lagrangian drifters and satellite altimetry data

    Science.gov (United States)

    Menna, Milena; Poulain, Pierre-Marie; Zodiatis, George; Gertman, Isaac

    The surface currents of the Levantine sub-basin (Mediterranean Sea) are described using 18 years (1992-2010) of drifter data and satellite-derived sea level anomalies. The combination of drifter and satellite data allowed to estimate maps of surface geostrophic circulation and to obtain more accurate pseudo-Eulerian velocity statistics for different time periods. Seasonal and interannual variability of surface currents are investigated with particular focus on the main sub-basin eddies of the eastern Levantine. The mean velocity field depicts the typical patterns of the along-slope and offshore currents and outlines the sub-regions where eddies are generated recurrently (west Egyptian coast, Ierapetra, Mersa-Matruh, south-west of Cyprus, Israel-Lebanon coast, Latakia) or persist steadily (Rhodes Gyre). Highly variable and energetic currents are observed between the Ierapetra and Mersa-Matruh regions, as the result of the interaction of the Mid-Mediterranean Jet meandering in between, and interacting with, the eddies generated by the instability of the coastal current. Seasonal pseudo-Eulerian maps show the current field stronger in summer and weaker in winter, mainly in the western Levantine and in the Cyprus-Syria Passage. The Shikmona Eddy displays a periodic nature with higher intensities during the cold months and an enhanced activity in the period 1998-2005. The Cyprus Eddy has a less periodic nature, characterised by events of high activity and periods in which it dominates as a single enlarged eddy in the southeast Levantine, eventually including the Shikmona Eddy. The Latakia Eddy is mainly cyclonic with higher intensities in summer and fall; occasional weekly or monthly inversions of circulation from cyclonic to anticyclonic are triggered by the interaction between the MMJ and the northward coastal meandering current.

  4. Nature of the Venus thermosphere derived from satellite drag measurements (solicited paper)

    Science.gov (United States)

    Keating, G.; Theriot, M.; Bougher, S.

    2008-09-01

    From drag measurements obtained by Pioneer Venus and Magellan, the Venus upper atmosphere was discovered to be much colder than Earth's, even though Venus is much closer to the Sun than the Earth. On the dayside, exospheric temperatures are near 300K compared to Earth's of near 1200K [1]. This is thought to result principally from 15 micron excitation of carbon dioxide by atomic oxygen resulting in very strong 15 micron emission to space, cooling off the upper atmosphere [2]. On the nightside the Venus upper atmosphere is near 100K [3], compared to Earth where temperatures are near 900K. The nightside Venus temperatures drop with altitude contrary to a thermosphere where temperatures rise with altitude. As a result, the very cold nightside is called a "cryosphere" rather than a thermosphere. This is the first cryosphere discovered in the solar system [1]. Temperatures sharply drop near the terminator. Apparently, heat is somehow blocked near the terminator from being significantly transported to the nightside [4]. Recently, drag studies were performed on a number of Earth satellites to establish whether the rise of carbon dioxide on Earth was cooling the Earth's thermosphere similar to the dayside of Venus. Keating et al. [5] discovered that a 10 percent drop in density near 350km at solar minimum occurred globally over a period of 20 years with a 10 per cent rise in carbon dioxide. This should result in about a factor of 2 decline in density from 1976 values, by the end of the 21st century brought on by thermospheric cooling. Subsequent studies have confirmed these results. Thus we are beginning to see the cooling of Earth's upper atmosphere apparently from the same process cooling the Venus thermosphere. Fig. 1 VIRA Exospheric Temperatures Atmospheric drag data from the Pioneer Venus Orbiter and Magellan were combined to generate an improved version of the Venus International Reference Atmosphere (VIRA) [6], [7]. A "fountain effect" was discovered where the

  5. Multiannual changes of CO2 emissions in China: indirect estimates derived from satellite measurements of tropospheric NO2 columns

    Directory of Open Access Journals (Sweden)

    M. Beekmann

    2013-01-01

    Full Text Available Multi-annual satellite measurements of tropospheric NO2 columns are used for evaluation of CO2 emission changes in China in the period from 1996 to 2008. Indirect annual top-down estimates of CO2 emissions are derived from the satellite NO2 columns measurements by means of a simple inverse modeling procedure involving simulations performed with the CHIMERE mesoscale chemistry transport model and the CO2 to NOx emission ratios from the Emission Database for Global Atmospheric Research version 4.2 (EDGAR v4.2 global anthropogenic emission inventory. Exponential trends in the normalized time series of annual emission are evaluated separately for the periods from 1996 to 2001 and from 2001 to 2008. The results indicate that the both periods manifest strong positive trends in the CO2 emissions, and that the trend in the second period was significantly larger than the trend in the first period. Specifically, the trends in the first and second periods are estimated to be in the range from 3.7 to 8.0 and from 9.5 to 13.0 percent per year, respectively, taking into account both statistical and probable systematic uncertainties. Comparison of our top-down estimates of the CO2 emission changes with the corresponding bottom-up estimates provided by EDGAR v4.2 and Global Carbon Project (GCP emission inventories reveals that while acceleration of the CO2 emission growth in the considered period is a common feature of the both kinds of estimates, nonlinearity in the CO2 emission changes may be strongly exaggerated in the emission inventories. Specifically, the atmospheric NO2 observations do not confirm the existence of a sharp bend in the emission inventory data time series in the period from 2000 to 2002. A significant quantitative difference is revealed between the bottom-up and top-down estimates of the CO2 emission trend in the period from 1996 to 2001 (specifically, the trend was not positive according to the emission inventories, but is strongly

  6. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NARCIS (Netherlands)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2016-01-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can

  7. Climate and the inter-annual variability of fire in southern Africa: a meta-analysis using long-term field data and satellite-derived burnt area data

    CSIR Research Space (South Africa)

    Archibald, S

    2010-11-01

    Full Text Available -explicit meteorological data for Africa are di cult to ob- tain. The Tropical Rainfall Measuring Mission (TRMM) provides relatively high-resolution (0.25 degree) monthly rainfall data for the region, but temperature, relative humidity and wind data are best derived...-sensed burned area data to test whether it is possible to develop a general model. Location: Africa south of the equator Methods: Linear mixed e ects models were used to determine the e ect of rainfall, season- ality, and re weather in driving variation...

  8. A photogrammetric DEM of Greenland based on 1978-1987 aerial photos: validation and integration with laser altimetry and satellite-derived DEMs

    DEFF Research Database (Denmark)

    Korsgaard, Niels Jákup; Kjær, Kurt H.; Nuth, Christopher

    50 km to ICESat laser altimetry in order to evaluate the coherency. We complement the aero-photogrammetric DEM with modern laser altimetry and DEMs derived from stereoscopic satellite imagery (AST14DMO) to examine the mass variability of the Northeast Greenland Ice Stream (NEGIS). Our analysis...

  9. 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.

    -6538 versión on-line Gayana (Concepc.) v.68 n.2 supl.TIIProc Concepción 2004 Como citar este artículo Gayana 68(2): 420-426, 2004 VALIDATION OF SATELLITE DERIVED LHF USING COARE_3.0 SCHEME AND TIME SERIES DATA OVER NORTH-EAST INDIAN...

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

    NARCIS (Netherlands)

    Pandey, S.

    2015-01-01

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

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

    NARCIS (Netherlands)

    Pandey, S.

    2015-01-01

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

  12. Deriving the effect of wind speed on clean marine aerosol optical properties using the A-Train satellites

    Directory of Open Access Journals (Sweden)

    V. P. Kiliyanpilakkil

    2011-11-01

    Full Text Available The relationship between "clean marine" aerosol optical properties and ocean surface wind speed is explored using remotely sensed data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP on board the CALIPSO satellite and the Advanced Microwave Scanning Radiometer (AMSR-E on board the AQUA satellite. Detailed data analyses are carried out over 15 regions selected to be representative of different areas of the global ocean for the time period from June 2006 to April 2011. Based on remotely sensed optical properties the CALIPSO algorithm is capable of discriminating "clean marine" aerosols from other types often present over the ocean (such as urban/industrial pollution, desert dust and biomass burning. The global mean optical depth of "clean marine" aerosol at 532 nm (AOD532 is found to be 0.052 ± 0.038 (mean plus or minus standard deviation. The mean layer integrated particulate depolarization ratio of marine aerosols is 0.02 ± 0.016. Integrated attenuated backscatter and color ratio of marine aerosols at 532 nm were found to be 0.003 ± 0.002 sr−1 and 0.530 ± 0.149, respectively. A logistic regression between AOD532 and 10-m surface wind speed (U10 revealed three distinct regimes. For U10 ≤ 4 m s−1 the mean CALIPSO-derived AOD532 is found to be 0.02 ± 0.003 with little dependency on the surface wind speed. For 4 < U10 ≤ 12 m s−1, representing the dominant fraction of all available data, marine aerosol optical depth is linearly correlated with the surface wind speed values, with a slope of 0.006 s m−1. In this intermediate wind speed region, the AOD532 vs. U10 regression slope derived here is comparable to previously reported values. At very high wind speed values (U10 > 18 m s−1, the AOD532-wind speed relationship

  13. Solar Occultation Satellite Data and Derived Meteorological Products: Sampling Issues and Comparisons with Aura MLS

    Science.gov (United States)

    Manney, Gloria; Daffer, William H.; Zawodny, Joseph M.; Bernath, Peter F.; Hoppel, Karl W.; Walker, Kaley A.; Knosp, Brian W.; Boone, Chris; Remsberg, Ellis E.; Santee, Michelle L.; Harvey, V. Lynn; Pawson, Steven; Jackson, David R.; Deaver, Lance; Pumphrey, Hugh C.; Lambert, Alyn; Schwartz, Michael J.; Froidevaux, Lucien; McLeod, Sean; Takacs, Lawrence L.; Suarez, Max J.; Trepte, Charles R.; Livesey, Nathaniel; Harwood, Robert S.; Waters, Joe W.

    2007-01-01

    Derived Meteorological Products (DMPs, including potential temperature (theta), potential vorticity, equivalent latitude (EqL), horizontal winds and tropopause locations) have been produced for the locations and times of measurements by several solar occultation (SO) instruments and the Aura Microwave Limb Sounder (MLS). DMPs are calculated from several meteorological analyses for the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer, Stratospheric Aerosol and Gas Experiment II and III, Halogen Occultation Experiment, and Polar Ozone and Aerosol Measurement II and III SO instruments and MLS. Time-series comparisons of MLS version 1.5 and SO data using DMPs show good qualitative agreement in time evolution of O3, N2O, H20, CO, HNO3, HCl and temperature; quantitative agreement is good in most cases. EqL-coordinate comparisons of MLS version 2.2 and SO data show good quantitative agreement throughout the stratosphere for most of these species, with significant biases for a few species in localized regions. Comparisons in EqL coordinates of MLS and SO data, and of SO data with geographically coincident MLS data provide insight into where and how sampling effects are important in interpretation of the sparse SO data, thus assisting in fully utilizing the SO data in scientific studies and comparisons with other sparse datasets. The DMPs are valuable for scientific studies and to facilitate validation of non-coincident measurements.

  14. Snow cover variability across central Canada (1978-2002) derived from satellite passive microwave data

    Energy Technology Data Exchange (ETDEWEB)

    Wulder, M.A.; Seemann, D. [Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, V8Z 1M5, British Columbia (Canada); Nelson, T.A. [Department of Geography, University of Victoria, Victoria, V8W 3P5, British Columbia (Canada); Derksen, C. [Climate Research Division, Climate Processes Section, Environment Canada, Downsview, M3H 5T4, Ontario (Canada)

    2007-05-15

    Twenty-four winter seasons (1978-2002) of mean February snow water equivalent (SWE) values were analyzed in an exploration of the spatial pattern of temporal variability in snow cover across the non-mountainous interior of Canada. The SWE data were derived from space-borne passive microwave brightness temperatures processed with a land cover-sensitive suite of algorithms. Spatial patterns in the frequency and amount of variability were investigated on an annual basis through comparisons with average trends over all 24 years. Changes in temporal variability through time were also investigated by comparing three eight year time periods to general trends. Analyses were synthesized at the ecozone scale in order to link results both to potential land cover influences on algorithm performance and climatological variability in SWE. Prairie and northern ecozones were typically found to be the most variable in terms of SWE magnitude. Analyses indicate that non-treed land cover classes are generally more variable than treed classes. The results also indicate that extreme weather events appear to be occurring with increasing consistency in the Prairie and Arctic regions. Discerning climatologically significant variability in the time series, compared to algorithm-related issues can be a challenge, but in an era of eroding surface observing networks the passive microwave time series represents an important resource for monitoring and detecting trends and variability in terrestrial snow cover.

  15. Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

    Directory of Open Access Journals (Sweden)

    Wenwen Cai

    2014-09-01

    Full Text Available Terrestrial gross primary production (GPP is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000–2010 varied from 95.10 to 139.71 Pg C∙yr−1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.

  16. A multiplier-based method of generating stochastic areal rainfall from point rainfalls

    Science.gov (United States)

    Ndiritu, J. G.

    Catchment modelling for water resources assessment is still mainly based on rain gauge measurements as these are more easily available and cover longer periods than radar and satellite-based measurements. Rain gauges however measure the rain falling on an extremely small proportion of the catchment and the areal rainfall obtained from these point measurements are consequently substantially uncertain. These uncertainties in areal rainfall estimation are generally ignored and the need to assess their impact on catchment modelling and water resources assessment is therefore imperative. A method that stochastically generates daily areal rainfall from point rainfall using multiplicative perturbations as a means of dealing with these uncertainties is developed and tested on the Berg catchment in the Western Cape of South Africa. The differences in areal rainfall obtained by alternately omitting some of the rain gauges are used to obtain a population of plausible multiplicative perturbations. Upper bounds on the applicable perturbations are set to prevent the generation of unrealistically large rainfall and to obtain unbiased stochastic rainfall. The perturbations within the set bounds are then fitted into probability density functions to stochastically generate the perturbations to impose on areal rainfall. By using 100 randomly-initialized calibrations of the AWBM catchment model and Sequent Peak Analysis, the effects of incorporating areal rainfall uncertainties on storage-yield-reliability analysis are assessed. Incorporating rainfall uncertainty is found to reduce the required storage by up to 20%. Rainfall uncertainty also increases flow-duration variability considerably and reduces the median flow-duration values by an average of about 20%.

  17. On the relationship of coastal tropical rainfall and the large-scale atmosphere

    CERN Document Server

    Bergemann, Martin; Lane, Todd P

    2015-01-01

    Rainfall in coastal areas of the tropics is often shaped by the presence of circulations directly associated with the topography, such as land-sea and/or mountain-valley breezes. In many regions the coastally-affected rainfall consitutes more than half of the overall rainfall received. Weather and climate models with parametrized convection produce large errors in rainfall in tropical coastal regions, most commonly underestimating rainfall over land and overestimating it over the ocean. Building on an algorithm to objectively identify rainfall that is associated with land-sea interaction we investigate whether the relationship between rainfall in coastal regions and the large-scale atmosphere differs from that over the open ocean or over inland areas. We combine 3-hourly satellite estimates of rainfall with estimates of the large-scale atmospheric state from reanalyses. We find that when grouped by rainfall intensity, medium-intensity coastal rainfall in the tropics occurs in more stable conditions and drier ...

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

    Directory of Open Access Journals (Sweden)

    John C. Lehrter

    2017-09-01

    Full Text Available Relationships between satellite-derived water quality variables and river discharges, concentrations and loads of nutrients, organic carbon, and sediments were investigated over a 9-year period (2003–2011 in Pensacola Bay, Florida, USA. These analyses were conducted to better understand which river forcing factors were the primary drivers of estuarine variability in several water quality variables. Remote sensing reflectance time-series data were retrieved from the MEdium Resolution Imaging Spectrometer (MERIS and used to calculate monthly and annual estuarine time-series of chlorophyll a (Chla, colored dissolved organic matter (CDOM, and total suspended sediments (TSS. Monthly MERIS Chla varied from 2.0 mg m−3 in the lower region of the bay to 17.2 mg m−3 in the upper bay. MERIS CDOM and TSS exhibited similar patterns with ranges of 0.51–2.67 (m−1 and 0.11–8.9 (g m−3. Variations in the MERIS-derived monthly and annual Chla, CDOM, and TSS time-series were significantly related to monthly and annual river discharge and loads of nitrogen, organic carbon, and suspended sediments from the Escambia and Yellow rivers. Multiple regression models based on river loads (independent variables and MERIS Chla, CDOM, or TSS (dependent variables explained significant fractions of the variability (up to 62% at monthly and annual scales. The most significant independent variables in the regressions were river nitrogen loads, which were associated with increased MERIS Chla, CDOM, and TSS concentrations, and river suspended sediment loads, which were associated with decreased concentrations. In contrast, MERIS water quality variations were not significantly related to river total phosphorus loads. The spatially synoptic, nine-year satellite record expanded upon the spatial extent of past field studies to reveal previously unseen system-wide responses to river discharge and loading variation. The results indicated that variations in Pensacola Bay Chla

  19. Ecosystem evaluation (1989-2012) of Ramsar wetland Deepor Beel using satellite-derived indices.

    Science.gov (United States)

    Mozumder, Chitrini; Tripathi, N K; Tipdecho, Taravudh

    2014-11-01

    The unprecedented urban growth especially in developing countries has laid immense pressure on wetlands, finally threatening their existence altogether. A long-term monitoring of wetland ecosystems is the basis of planning conservation measures for a sustainable development. Deepor Beel, a Ramsar wetland and major storm water basin of the River Brahmaputra in the northeastern region of India, needs particular attention due to its constant degradation over the past decades. A rule-based classification algorithm was developed using Landsat (2011)-derived indices, namely Normalised Difference Water Index (NDWI), Modified Normalised Difference Water Index (MNDWI), Normalised Difference Pond Index (NDPI), Normalised Difference Vegetation Index (NDVI) and field data as ancillary information. Field data, ALOS AVNIR and Google Earth images were used for accuracy assessment. A fuzzy accuracy assessment of the classified data sets showed an overall accuracy of 82 % for MAX criteria and 90 % for RIGHT criteria. The rules were used to classify major wetland cover types during low water season (January) in 1989, 2001 and 2012. The statistical analysis of the classified wetland showed heavy manifestation in aquatic vegetation and other features indicating severe eutrophication over the past 23 years. This degradation was closely related to major contributing anthropogenic factors, such as a railway line construction, growing croplands, waste disposal and illegal human settlements in the wetland catchment. In addition, the landscape development index (LDI) indicated a rapid increase in the impact of the surrounding land use on the wetland from 1989 to 2012. The techniques and results from this study may prove useful for top-down landscape analyses of this and other freshwater wetlands.

  20. Satellite theory

    Science.gov (United States)

    Kozai, Y.

    1981-04-01

    The dynamical characteristics of the natural satellite of Mars, Jupiter, Saturn, Uranus and Neptune are analyzed on the basis of the solar tidal perturbation factor and the oblateness factor of the primary planet for each satellite. For the inner satellites, for which the value of the solar tidal factor is much smaller than the planetary oblateness factor, it is shown that the eccentricity and inclination of satellite orbits are generally very small and almost constant; several pairs of inner satellites are also found to exhibit commensurable mean motions, or secular accelerations in mean longitude. In the case of the outer satellites, for which solar perturbations are dominant, secular perturbations and long-period perturbations may be derived by the solution of equations of motion reduced to one degree of freedom. The existence of a few satellites, termed intermediary satellites, for which the solar tidal perturbation is on the order of the planetary oblateness factor, is also observed, and the pole of the orbital plane of the satellite is noted to execute a complex motion around the pole of the planet or the orbital plane of the planet.

  1. Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

    Science.gov (United States)

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

    2010-01-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with

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

    Science.gov (United States)

    Ocko, Ilissa B.; Ginoux, Paul A.

    2017-04-01

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

  3. Inter-annual variations of snow days over Switzerland from 2000–2010 derived from MODIS satellite data

    Directory of Open Access Journals (Sweden)

    G. Seiz

    2012-03-01

    Full Text Available Snow cover plays a vital role in the Swiss Alps and therefore it is of major interest to determine and understand its variability on different spatiotemporal scales. Within the activities of the National Climate Observing System (GCOS Switzerland inter-annual variations of snow days over Switzerland were derived from 2000 to 2010 based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Terra satellite. To minimize the impact of cloud cover on the MODIS snow product MOD10C1, we implemented a post-processing technique based on a forward and backward gap-filling approach. Using the proposed methodology it was possible to determine the total number of annual snow days over Switzerland from 2000 to 2010 (SCDMODIS. The accuracy of the calculated snow days per year were quantitatively evaluated against three in situ snow observation sites representing different climatological regimes (SCDin_situ. Various statistical indices were computed and analysed over the entire period. The overall accuracy between SCDMODIS and SCDin_situ on a daily basis over 10 yr is 88% to 94%, depending on the regional characteristics of each validation site. Differences between SCDMODIS and SCDin_situ vary during the snow accumulation period in autumn and smaller differences after spring, in particularly for the Central Alps.

  4. Inter-annual variations of snow days over Switzerland from 2000-2010 derived from MODIS satellite data

    Science.gov (United States)

    Foppa, N.; Seiz, G.

    2012-03-01

    Snow cover plays a vital role in the Swiss Alps and therefore it is of major interest to determine and understand its variability on different spatiotemporal scales. Within the activities of the National Climate Observing System (GCOS Switzerland) inter-annual variations of snow days over Switzerland were derived from 2000 to 2010 based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite. To minimize the impact of cloud cover on the MODIS snow product MOD10C1, we implemented a post-processing technique based on a forward and backward gap-filling approach. Using the proposed methodology it was possible to determine the total number of annual snow days over Switzerland from 2000 to 2010 (SCDMODIS). The accuracy of the calculated snow days per year were quantitatively evaluated against three in situ snow observation sites representing different climatological regimes (SCDin_situ). Various statistical indices were computed and analysed over the entire period. The overall accuracy between SCDMODIS and SCDin_situ on a daily basis over 10 yr is 88% to 94%, depending on the regional characteristics of each validation site. Differences between SCDMODIS and SCDin_situ vary during the snow accumulation period in autumn and smaller differences after spring, in particularly for the Central Alps.

  5. Modelling dengue fever risk in the State of Yucatan, Mexico using regional-scale satellite-derived sea surface temperature.

    Science.gov (United States)

    Laureano-Rosario, Abdiel E; Garcia-Rejon, Julian E; Gomez-Carro, Salvador; Farfan-Ale, Jose A; Muller-Karger, Frank E

    2017-08-01

    Accurately predicting vector-borne diseases, such as dengue fever, is essential for communities worldwide. Changes in environmental parameters such as precipitation, air temperature, and humidity are known to influence dengue fever dynamics. Furthermore, previous studies have shown how oceanographic variables, such as El Niño Southern Oscillation (ENSO)-related sea surface temperature from the Pacific Ocean, influences dengue fever in the Americas. However, literature is lacking on the use of regional-scale satellite-derived sea surface temperature (SST) to assess its relationship with dengue fever in coastal areas. Data on confirmed dengue cases, demographics, precipitation, and air temperature were collected. Incidence of weekly dengue cases was examined. Stepwise multiple regression analyses (AIC model selection) were used to assess which environmental variables best explained increased dengue incidence rates. SST, minimum air temperature, precipitation, and humidity substantially explained 42% of the observed variation (r(2)=0.42). Infectious diseases are characterized by the influence of past cases on current cases and results show that previous dengue cases alone explained 89% of the variation. Ordinary least-squares analyses showed a positive trend of 0.20±0.03°C in SST from 2006 to 2015. An important element of this study is to help develop strategic recommendations for public health officials in Mexico by providing a simple early warning capability for dengue incidence. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Quality of Life Assessment Based on Spatial and Temporal Analysis of the Vegetation Area Derived from Satellite Images

    Directory of Open Access Journals (Sweden)

    MARIA IOANA VLAD

    2011-01-01

    Full Text Available The quality of life in urban areas is a function of many parameters among which, one highly important is the number and quality of green areas for people and wildlife to thrive. The quality of life is also a political concept often used to describe citizen satisfaction within different residential locations. Only in the last decades green areas have suffered a progressive decrease in quality, pointing out the ecological urban risk with a negative impact on the standard of living and population health status. This paper presents the evolution of green areas in the cities of South-Eastern Romania within the last 20 years and sets forth the current state of quality of life from the perspective of vegetation reference. By using state-of-the-art processing tools applied on high-resolution satellite images, we have derived knowledge about the spatial and temporal expansion of urbanized regions. Our semi-automatic technologies for analysis of remote sensing data such as Landsat 7 ETM+, correlated with statistical information inferred from urban charts, demonstrate a negative trend in the distribution of green areas within the analyzed cities, with long-term implications on multiple areas in our lives.

  7. Main diurnal cycle pattern of rainfall in East Java

    Science.gov (United States)

    Rais, Achmad Fahruddin; Yunita, Rezky

    2017-08-01

    The diurnal cycle pattern of rainfall was indicated as an intense feature in East Java. The research of diurnal cycle generally was only based on satellite estimation which had limitations in accuracy and temporal resolution. The hourly rainfall data of Climate Prediction Center Morphing Technique (CMORPH) and gauge were blended using the best correction method between transformation distribution (DT) and quantile mapping (QM) to increase the accuracy. We used spatiotemporal composite to analyse the concentration patterns of maximum rainfall and principal component analysis (PCA) to identify the spatial and temporal dominant patterns of diurnal rainfall. QM was corrected CMORPH data since it was best method. The eastern region of East Java had a rainfall peak at 14 local time (LT) and the western region had a rainfall peak at 16 LT.

  8. Verification of SPCZ and ENSO dynamics in the extended reanalysis period using the South Pacific Rainfall Atlas

    Science.gov (United States)

    Lorrey, Andrew; Dalu, Giovanni; Diamond, Howard; Gaetani, Marco; Renwick, James

    2010-05-01

    Ground-based rainfall observations during the pre-satellite era in the South West Pacific were examined for an extreme La Niña event that occurred in 1955-56. The rainfall observations were derived from the South Pacific Rainfall Atlas (SPRAT), a data compilation contributed by the regional meteorological services. The influence of tropical cyclone activity on both monthly and warm season rainfall anomalies were also accounted for using the International Best Tracks Archive for Climate Stewardship (IBTrACS) tropical cyclone database. The rainfall anomalies from more than 60 southwest Pacific Island stations showed a region of enhanced rainfall in the southwest half of the south Pacific encompassing the Southern Cook Islands, Tonga, Fiji, New Caledonia, and Vanuatu. Suppressed rainfall was observed in the northeast corner of the region over the Marquesas, the Northern Cook Islands, Tokelau, and Tuvalu. This pattern is similar to what is expected for La Nina events that occurred during the classic re-analysis period (1958 onward). Elimination of anomalously high historical rainfall totals for individual islands using the IBTrACS data allowed a 'best guess' of the past SPCZ position, suggesting it was probably southwest of the its normal climatological position during the 1955-56 La Nina. A comparison of the 'best guess' SPCZ position fit derived from the rainfall anomalies to the omega velocity furnished by the NOAA-CIRES reanalysis show a remarkably similar position of the SPCZ during the 1955-56 ENSO event. Ground-based rainfall observations that support SPRAT (which extend into the early 1900s and beyond) can therefore confirm the fidelity of the NOAA-CIRES extended 20th century reanalysis and can help to reveal past ENSO and SPCZ dynamics. In addition, the high-resolution daily reanalysis data and IBTrACS information indicate a unique SPCZ control on regional tropical cyclone trajectories into the Southern Hemisphere mid-latitudes during ex-tropical transition

  9. Varying applicability of four different satellite-derived soil moisture products to global gridded crop model evaluation

    Science.gov (United States)

    Sakai, Toru; Iizumi, Toshichika; Okada, Masashi; Nishimori, Motoki; Grünwald, Thomas; Prueger, John; Cescatti, Alessandro; Korres, Wolfgang; Schmidt, Marius; Carrara, Arnaud; Loubet, Benjamin; Ceschia, Eric

    2016-06-01

    Satellite-derived daily surface soil moisture products have been increasingly available, but their applicability to global gridded crop model (GGCM) evaluation is unclear. This study compares four different soil moisture products with the flux tower site observation at 18 cropland sites across the world where either of maize, soybean, rice and wheat is grown. These products include the first and second versions of Climate Change Initiative Soil Moisture (CCISM-1 and CCISM-2) datasets distributed by the European Space Agency and two different AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System)-derived soil moisture datasets, separately provided by the Japan Aerospace Exploration Agency (AMSRE-J) and U.S. National Aeronautics and Space Administration (AMSRE-N). The comparison demonstrates varying reliability of these products in representing major characteristics of temporal pattern of cropland soil moisture by product and crop. Possible reasons for the varying reliability include the differences in sensors, algorithms, bands and criteria used when estimating soil moisture. Both the CCISM-1 and CCISM-2 products appear the most reliable for soybean- and wheat-growing area. However, the percentage of valid data of these products is always lower than other products due to relatively strict criteria when merging data derived from multiple sources, although the CCISM-2 product has much more data with valid retrievals than the CCISM-1 product. The reliability of the AMSRE-J product is the highest for maize- and rice-growing areas and comparable to or slightly lower than the CCISM products for soybean- and wheat-growing areas. The AMSRE-N is the least reliable in most location-crop combinations. The reliability of the products for rice-growing area is far lower than that of other upland crops likely due to the extensive use of irrigation and patch distribution of rice paddy in the area examined here. We conclude that the CCISM-1, CCISM-2 and AMSRE

  10. Improving radar rainfall estimation by merging point rainfall measurements within a model combination framework

    Science.gov (United States)

    Hasan, Mohammad Mahadi; Sharma, Ashish; Mariethoz, Gregoire; Johnson, Fiona; Seed, Alan

    2016-11-01

    While the value of correcting raw radar rainfall estimates using simultaneous ground rainfall observations is well known, approaches that use the complete record of both gauge and radar measurements to provide improved rainfall estimates are much less common. We present here two new approaches for estimating radar rainfall that are designed to address known limitations in radar rainfall products by using a relatively long history of radar reflectivity and ground rainfall observations. The first of these two approaches is a radar rainfall estimation algorithm that is nonparametric by construction. Compared to the traditional gauge adjusted parametric relationship between reflectivity (Z) and ground rainfall (R), the suggested new approach is based on a nonparametric radar rainfall estimation method (NPR) derived using the conditional probability distribution of reflectivity and gauge rainfall. The NPR method is applied to the densely gauged Sydney Terrey Hills radar network, where it reduces the RMSE in rainfall estimates by 10%, with improvements observed at 90% of the gauges. The second of the two approaches is a method to merge radar and spatially interpolated gauge measurements. The two sources of information are combined using a dynamic combinatorial algorithm with weights that vary in both space and time. The weight for any specific period is calculated based on the error covariance matrix that is formulated from the radar and spatially interpolated rainfall errors of similar reflectivity periods in a cross-validation setting. The combination method reduces the RMSE by about 20% compared to the traditional Z-R relationship method, and improves estimates compared to spatially interpolated point measurements in sparsely gauged areas.

  11. Rainfall simulation in education

    Science.gov (United States)

    Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

    2016-04-01

    Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain

  12. Critical Phenomena of Rainfall in Ecuador

    Science.gov (United States)

    Serrano, Sh.; Vasquez, N.; Jacome, P.; Basile, L.

    2014-02-01

    Self-organized criticality (SOC) is characterized by a power law behavior over complex systems like earthquakes and avalanches. We study rainfall using data of one day, 3 hours and 10 min temporal resolution from INAMHI (Instituto Nacional de Meteorologia e Hidrologia) station at Izobamba, DMQ (Metropolitan District of Quito), satellite data over Ecuador from Tropical Rainfall Measure Mission (TRMM,) and REMMAQ (Red Metropolitana de Monitoreo Atmosferico de Quito) meteorological stations over, respectively. Our results show a power law behavior of the number of rain events versus mm of rainfall measured for the high resolution case (10 min), and as the resolution decreases this behavior gets lost. This statistical property is the fingerprint of a self-organized critical process (Peter and Christensen, 2002) and may serve as a benchmark for models of precipitation based in phase transitions between water vapor and precipitation (Peter and Neeling, 2006).

  13. Characterizing land surface phenology and responses to rainfall in the Sahara desert

    Science.gov (United States)

    Yan, Dong; Zhang, Xiaoyang; Yu, Yunyue; Guo, Wei; Hanan, Niall P.

    2016-08-01

    Land surface phenology (LSP) in the Sahara desert is poorly understood due to the difficulty in detecting subtle variations in vegetation greenness. This study examined the spatial and temporal patterns of LSP and its responses to rainfall seasonality in the Sahara desert. We first generated daily two-band enhanced vegetation index (EVI2) from half-hourly observations acquired by the Spinning Enhanced Visible and Infrared Imager on board the Meteosat Second Generation series of geostationary satellites from 2006 to 2012. The EVI2 time series was used to retrieve LSP based on the Hybrid Piecewise Logistic Model. We further investigated the associations of spatial and temporal patterns in LSP with those in rainfall seasonality derived from the daily rainfall time series of the Tropical Rainfall Measurement Mission. Results show that the spatial shifts in the start of the vegetation growing season generally follow the rainy season onset that is controlled by the summer rainfall regime in the southern Sahara desert. In contrast, the end of the growing season significantly lags the end of the rainy season without any significant dependence. Vegetation growing season can unfold during the dry seasons after onset is triggered during rainy seasons. Vegetation growing season can be as long as 300 days or more in some areas and years. However, the EVI2 amplitude and accumulation across the Sahara region was very low indicating sparse vegetation as expected in desert regions. EVI2 amplitude and accumulated EVI2 strongly depended on rainfall received during the growing season and the preceding dormancy period.

  14. Extreme Rainfall Events Over Southern Africa: Assessment of a Climate Model to Reproduce Daily Extremes

    Science.gov (United States)

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

    2007-12-01

    It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable extreme events, due to a number of factors including extensive poverty, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of a state-of-the-art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. Once the model's ability to reproduce extremes has been assessed, idealised regions of SST anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, results from sensitivity testing of the UK Meteorological Office Hadley Centre's climate model's domain size are firstly presented. Then simulations of current climate from the model, operating in both regional and global mode, are compared to the MIRA dataset at daily timescales. Thirdly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. Finally, the results from the idealised SST experiments are briefly presented, suggesting associations between rainfall extremes and both local and remote SST anomalies.

  15. Combined Aircraft and Satellite-Derived Storm Electric Current and Lightning Rates Measurements and Implications for the Global Electric Circuit

    Science.gov (United States)

    Mach, Douglas M.; Blakeslee, Richard J.; Bateman, Monte G.

    2010-01-01

    Using rotating vane electric field mills and Gerdien capacitors, we measured the electric field profile and conductivity during 850 overflights of electrified shower clouds and thunderstorms spanning regions including the Southeastern United States, the Western Atlantic Ocean, the Gulf of Mexico, Central America and adjacent oceans, Central Brazil, and the South Pacific. The overflights include storms over land and ocean, with and without lightning, and with positive and negative fields above the storms. The measurements were made with the NASA ER-2 and the Altus-II high altitude aircrafts. Peak electric fields, with lightning transients removed, ranged from -1.0 kV/m to 16 kV/m, with a mean value of 0.9 kV/m. The median peak field was 0.29 kV/m. Integrating our electric field and conductivity data, we determined total conduction currents and flash rates for each overpass. With knowledge of the storm location (land or ocean) and type (with or without lightning), we determine the mean currents by location and type. The mean current for ocean storms with lightning is 1.6 A while the mean current for land storms with lightning is 1.0 A. The mean current for oceanic storms without lightning (i.e., electrified shower clouds) is 0.39 A and the mean current for land storms without lightning is 0.13 A. Thus, on average, land storms with or without lightning have about half the mean current as their corresponding oceanic storm counterparts. Over three-quarters (78%) of the land storms had detectable lightning, while less than half (43%) of the oceanic storms had lightning. We did not find any significant regional or latitudinal based patterns in our total conduction currents. By combining the aircraft derived storm currents and flash rates with diurnal lightning statistics derived from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) low Earth orbiting satellites, we reproduce the diurnal variation in the global electric circuit (i.e., the Carnegie

  16. Assessing Disagreement and Tolerance of Misclassification of Satellite-derived Land Cover Products Used in WRF Model Applications

    Institute of Scientific and Technical Information of China (English)

    GAO Hao; JIA Gensuo

    2013-01-01

    As more satellite-derived land cover products used in the study of global change,especially climate modeling,assessing their quality has become vitally important.In this study,we developed a distance metric based on the parameters used in weather research and forecasting (WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme (IGBP) classification scheme.We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer (MODIS) products,and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model.Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes,while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes.The degree of disagreement varied significantly among seven regions of China.The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly.High accuracy and fuzzy agreement occurred in the following classes:water,grassland,cropland,and barren or sparsely vegetated.Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals.Some classes need to be improved further; the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling.Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.

  17. Strong contribution of autumn phenology to changes in satellite-derived growing season length estimates across Europe (1982-2011).

    Science.gov (United States)

    Garonna, Irene; de Jong, Rogier; de Wit, Allard J W; Mücher, Caspar A; Schmid, Bernhard; Schaepman, Michael E

    2014-11-01

    Land Surface Phenology (LSP) is the most direct representation of intra-annual dynamics of vegetated land surfaces as observed from satellite imagery. LSP plays a key role in characterizing land-surface fluxes, and is central to accurately parameterizing terrestrial biosphere-atmosphere interactions, as well as climate models. In this article, we present an evaluation of Pan-European LSP and its changes over the past 30 years, using the longest continuous record of Normalized Difference Vegetation Index (NDVI) available to date in combination with a landscape-based aggregation scheme. We used indicators of Start-Of-Season, End-Of-Season and Growing Season Length (SOS, EOS and GSL, respectively) for the period 1982-2011 to test for temporal trends in activity of terrestrial vegetation and their spatial distribution. We aggregated pixels into ecologically representative spatial units using the European Landscape Classification (LANMAP) and assessed the relative contribution of spring and autumn phenology. GSL increased significantly by 18-24 days decade(-1) over 18-30% of the land area of Europe, depending on methodology. This trend varied extensively within and between climatic zones and landscape classes. The areas of greatest growing-season lengthening were the Continental and Boreal zones, with hotspots concentrated in southern Fennoscandia, Western Russia and pockets of continental Europe. For the Atlantic and Steppic zones, we found an average shortening of the growing season with hotspots in Western France, the Po valley, and around the Caspian Sea. In many zones, changes in the NDVI-derived end-of-season contributed more to the GSL trend than changes in spring green-up, resulting in asymmetric trends. This underlines the importance of investigating senescence and its underlying processes more closely as a driver of LSP and global change.

  18. Inter-annual variations of snow days over Switzerland from 2000–2010 derived from MODIS satellite data

    Directory of Open Access Journals (Sweden)

    N. Foppa

    2011-09-01

    Full Text Available Snow cover plays a vital role in the Swiss Alps and therefore it is of major interest to determine and understand its variability on different spatiotemporal scales. Within the activities of the National Climate Observing System (GCOS Switzerland inter-annual variations of snow days over Switzerland were derived from 2000 to 2010 based on data from the Moderate Resolution Imaging Spectroradiometer (MODIS on board the Terra satellite. To minimize the impact of cloud cover on the MODIS snow product MOD10C1, we implemented a post-processing technique based on a forward and backward gap-filling approach. Using the proposed methodology it was possible to determine the total number of annual snow days over Switzerland from 2000 to 2010 (SCDMODIS. The accuracy of the calculated snow days per year were quantitatively evaluated against three in situ snow observation sites representing different climatological regimes (SCDin_situ. The correlation (c between annual SCDMODIS and SCDin_situ is highest for the lowland regions by (c = 0.90 with a slightly lower correlation for the Central Alps of 0.82 and a mean absolute difference of −6 to −7 days (SCDin_situ − SCDMODIS. Differences were further analysed on a monthly and daily resolution over the entire period. The overall agreement between SCDMODIS and SCDin_situ on a daily basis over 10 yr is 88 % to 94 %, depending on the regional characteristics of each validation site. Differences between SCDMODIS and SCDin_situ vary with higher mean absolute differences during the snow accumulation period in autumn and smaller differences after spring, in particularly for the Central Alps. These findings are in agreement with other studies.

  19. The relationship between the Guinea Highlands and the West African offshore rainfall maximum

    Science.gov (United States)

    Hamilton, H. L.; Young, G. S.; Evans, J. L.; Fuentes, J. D.; Núñez Ocasio, K. M.

    2017-01-01

    Satellite rainfall estimates reveal a consistent rainfall maximum off the West African coast during the monsoon season. An analysis of 16 years of rainfall in the monsoon season is conducted to explore the drivers of such copious amounts of rainfall. Composites of daily rainfall and midlevel meridional winds centered on the days with maximum rainfall show that the day with the heaviest rainfall follows the strongest midlevel northerlies but coincides with peak low-level moisture convergence. Rain type composites show that convective rain dominates the study region. The dominant contribution to the offshore rainfall maximum is convective development driven by the enhancement of upslope winds near the Guinea Highlands. The enhancement in the upslope flow is closely related to African easterly waves propagating off the continent that generate low-level cyclonic vorticity and convergence. Numerical simulations reproduce the observed rainfall maximum and indicate that it weakens if the African topography is reduced.

  20. How important is tropospheric humidity for coastal rainfall in the tropics?

    Science.gov (United States)

    Bergemann, Martin; Jakob, Christian

    2016-06-01

    Climate models show considerable rainfall biases in coastal tropical areas, where approximately 33% of the overall rainfall received is associated with coastal land-sea interaction. Building on an algorithm to objectively identify rainfall that is associated with land-sea interaction we investigate whether the relationship between rainfall in coastal regions and atmospheric humidity differs from that over the open ocean or over inland areas. We combine 3-hourly satellite estimates of rainfall with humidity estimates from reanalyses and investigate if coastal rainfall reveals the well-known relationship between area-averaged precipitation and column-integrated moisture. We find that rainfall that is associated with coastal land-sea effects occurs under much drier midtropospheric conditions than that over the ocean and does not exhibit a pronounced critical value of humidity. In addition, the dependence of the amount of rainfall on midtropospheric moisture is significantly weaker when the rainfall is coastally influenced.

  1. Topographic relationships for design rainfalls over Australia

    Science.gov (United States)

    Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

    2016-02-01

    Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as

  2. Principle and geomorphological applicability of summit level and base level technique using Aster Gdem satellite-derived data and the original software Baz

    OpenAIRE

    Akihisa Motoki; Kenji Freire Motoki; Susanna Eleonora Sichel; Samuel da Silva; José Ribeiro Aires

    2015-01-01

    This article presents principle and geomorphological applicability of summit level technique using Aster Gdem satellite-derived topographicdata. Summit level corresponds to thevirtualtopographic surface constituted bylocalhighest points, such as peaks and plateau tops, and reconstitutes palaeo-geomorphology before the drainage erosion. Summit level map is efficient for reconstitution of palaeo-surfaces and detection of active tectonic movement. Base level is thevirtualsurface composed oflocal...

  3. Tropical convective systems life cycle characteristics from geostationary satellite and precipitating estimates derived from TRMM and ground weather radar observations for the West African and South American regions

    Science.gov (United States)

    Fiolleau, T.; Roca, R.; Angelis, F. C.; Viltard, N.

    2012-12-01

    In the tropics most of the rainfall comes in the form of individual storm events embedded in the synoptic circulations (e.g., monsoons). Understanding the rainfall and its variability hence requires to document these highly contributing tropical convective systems (MCS). Our knowledge of the MCS life cycle, from a physical point of view mainly arises from individual observational campaigns heavily based on ground radar observations. While this large part of observations enabled the creation of conceptual models of MCS life cycle, it nevertheless does not reach any statistically significant integrated perspective yet. To overcome this limitation, a composite technique, that will serve as a Day-1 algorithm for the Megha-Tropiques mission, is considered in this study. this method is based on a collocation in space and time of the level-2 rainfall estimates (BRAIN) derived from the TMI radiometer onboard TRMM with the cloud systems identified by a new MCS tracking algorithm called TOOCAN and based on a 3-dimensional segmentation (image + time) of the geostationary IR imagery. To complete this study, a similar method is also developed collocating the cloud systems with the precipitating features derived from the ground weather radar which has been deployed during the CHUVA campaign over several Brazilian regions from 2010 up to now. A comparison of the MCSs life cycle is then performed for the 2010-2012 summer seasons over the West African, and South American regions. On the whole region of study, the results show that the temporal evolution of the cold cloud shield associated to MCSs describes a symmetry between the growth and the decay phases. It is also shown that the parameters of the conceptual model of MCSs are strongly correlated, reducing thereby the problem to a single degree of freedom. At the system scale, over both land and oceanic regions, rainfall is described by an increase at the beginning (the first third) of the life cycle and then smoothly decreases

  4. Maximum daily rainfall in South Korea

    Indian Academy of Sciences (India)

    Saralees Nadarajah; Dongseok Choi

    2007-08-01

    Annual maxima of daily rainfall for the years 1961–2001 are modeled for five locations in South Korea (chosen to give a good geographical representation of the country). The generalized extreme value distribution is fitted to data from each location to describe the extremes of rainfall and to predict its future behavior. We find evidence to suggest that the Gumbel distribution provides the most reasonable model for four of the five locations considered. We explore the possibility of trends in the data but find no evidence suggesting trends. We derive estimates of 10, 50, 100, 1000, 5000, 10,000, 50,000 and 100,000 year return levels for daily rainfall and describe how they vary with the locations. This paper provides the first application of extreme value distributions to rainfall data from South Korea.

  5. 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.

  6. Spatial moments of catchment rainfall: rainfall spatial organisation, basin morphology, and flood response

    Directory of Open Access Journals (Sweden)

    D. Zoccatelli

    2011-12-01

    Full Text Available This paper describes a set of spatial rainfall statistics (termed "spatial moments of catchment rainfall" quantifying the dependence existing between spatial rainfall organisation, basin morphology and runoff response. These statistics describe the spatial rainfall organisation in terms of concentration and dispersion statistics as a function of the distance measured along the flow routing coordinate. The introduction of these statistics permits derivation of a simple relationship for the quantification of catchment-scale storm velocity. The concept of the catchment-scale storm velocity takes into account the role of relative catchment orientation and morphology with respect to storm motion and kinematics. The paper illustrates the derivation of the statistics from an analytical framework recently proposed in literature and explains the conceptual meaning of the statistics by applying them to five extreme flash floods occurred in various European regions in the period 2002–2007. High resolution radar rainfall fields and a distributed hydrologic model are employed to examine how effective are these statistics in describing the degree of spatial rainfall organisation which is important for runoff modelling. This is obtained by quantifying the effects of neglecting the spatial rainfall variability on flood modelling, with a focus on runoff timing. The size of the study catchments ranges between 36 to 982 km2. The analysis reported here shows that the spatial moments of catchment rainfall can be effectively employed to isolate and describe the features of rainfall spatial organization which have significant impact on runoff simulation. These statistics provide useful information on what space-time scales rainfall has to be monitored, given certain catchment and flood characteristics, and what are the effects of space-time aggregation on flood response modeling.

  7. Can SAPHIR Instrument Onboard MEGHATROPIQUES Retrieve Hydrometeors and Rainfall Characteristics ?

    Science.gov (United States)

    Goyal, J. M.; Srinivasan, J.; Satheesh, S. K.

    2014-12-01

    MEGHATROPIQUES (MT) is an Indo-French satellite launched in 2011 with the main intention of understanding the water cycle in the tropical region and is a part of GPM constellation. MADRAS was the primary instrument on-board MT to estimate rainfall characteristics, but unfortunately it's scanning mechanism failed obscuring the primary goal of the mission.So an attempt has been made to retrieve rainfall and different hydrometeors using other instrument SAPHIR onboard MT. The most important advantage of using MT is its orbitography which is specifically designed for tropical regions and can reach up to 6 passes per day more than any other satellite currently in orbit. Although SAPHIR is an humidity sounder with six channels centred around 183 GHz channel, it still operates in the microwave region which directly interacts with rainfall, especially wing channels and thus can pick up rainfall signatures. Initial analysis using radiative transfer models also establish this fact .To get more conclusive results using observations, SAPHIR level 1 brightness temperature (BT) data was compared with different rainfall products utilizing the benefits of each product. SAPHIR BT comparison with TRMM 3B42 for one pass clearly showed that channel 5 and 6 have a considerable sensitivity towards rainfall. Following this a huge database of more than 300000 raining pixels of spatially and temporally collocated 3B42 rainfall and corresponding SAPHIR BT for an entire month was created to include all kinds of rainfall events, to attain higher temporal resolution collocated database was also created for SAPHIR BT and rainfall from infrared sensor on geostationary satellite Kalpana 1.These databases were used to understand response of various channels of SAPHIR to different rainfall regimes . TRMM 2A12 rainfall product was also used to identify capabilities of SAPHIR to retrieve cloud and ice water path which also gave significant correlation. Conclusively,we have shown that SAPHIR has

  8. Satellite-derived changes in the permafrost landscape of central Yakutia, 2000-2011: wetting, drying, and fires

    Science.gov (United States)

    Boike, Julia; Grau, Thomas; Heim, Birgit; Günther, Frank; Langer, Moritz; Muster, Sina; Gouttevin, Isabelle; Lange, Stephan

    2016-04-01

    The focus of this research has been on detecting changes in lake areas, vegetation, land surface temperatures, and the area covered by snow, using data from remote sensing. The study area covers the main (central) part of the Lena River catchment in the Yakutia region of Siberia (Russia), extending from east of Yakutsk to the central Siberian Plateau, and from the southern Lena River to north of the Vilyui River. Approximately 90% of the area is underlain by continuous permafrost. Remote sensing products were used to analyze changes in water bodies, land surface temperature (LST), and leaf area index (LAI), as well as the occurrence and extent of forest fires, and the area and duration of snow cover. The remote sensing analyses (for LST, snow cover, LAI, and fire) were based on MODIS-derived NASA products for 2000 to 2011. Changes in water bodies were calculated from two mosaics of (USGS) Landsat high resolution (30 m) satellite images from 2002 and 2009. Within the study area's 315,000 km² the total area covered by lakes increased by 17.5% between 2002 and 2009, but this increase varied in different parts of the study area, ranging between 11% and 42%. The land surface temperatures showed a consistent warming trend, with an average increase of about 0.12°C/year. The average rate of warming during the April-May transition period was 0.15°C/year and 0.19°C/year in the September-October period, but ranged up to 0.45°C/year in some areas during April-May. Regional differences in the rates of land surface temperature change, and possible reasons for the temperature changes, are discussed with respect to changes in the land cover. Our analysis of a broad spectrum of variables over the study area suggests that the spring warming trend is very likely to be due to changes in the area covered by snow. The warming trend observed in fall does not, however, appear to be directly related to any changes in the area of snow cover, or to the atmospheric conditions, or to the

  9. Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

    Science.gov (United States)

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

    2009-04-01

    It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will

  10. Ammonia emissions in tropical biomass burning regions: Comparison between satellite-derived emissions and bottom-up fire inventories

    Science.gov (United States)

    Whitburn, S.; Van Damme, M.; Kaiser, J. W.; van der Werf, G. R.; Turquety, S.; Hurtmans, D.; Clarisse, L.; Clerbaux, C.; Coheur, P.-F.

    2015-11-01

    Vegetation fires emit large amounts of nitrogen compounds in the atmosphere, including ammonia (NH3). These emissions are still subject to large uncertainties. In this study, we analyze time series of monthly NH3 total columns (molec cm-2) from the IASI sounder on board MetOp-A satellite and their relation with MODIS fire radiative power (MW) measurements. We derive monthly NH3 emissions estimates for four regions accounting for a major part of the total area affected by fires (two in Africa, one in central South America and one in Southeast Asia), using a simplified box model, and we compare them to the emissions from both the GFEDv3.1 and GFASv1.0 biomass burning emission inventories. In order to strengthen the analysis, we perform a similar comparison for carbon monoxide (CO), also measured by IASI and for which the emission factors used in the inventories to convert biomass burned to trace gas emissions are thought to be more reliable. In general, a good correspondence between NH3 and CO columns and the FRP is found, especially for regions in central South America with correlation coefficients of 0.82 and 0.66, respectively. The comparison with the two biomass burning emission inventories GFASv1.0 and GFEDv3.1 shows good agreements, particularly in the time of the maximum of emissions for the central South America region and in the magnitude for the region of Africa south of the equator. We find evidence of significant non-pyrogenic emissions for the regions of Africa north of the equator (for NH3) and Southeast Asia (for NH3 and CO). On a yearly basis, total emissions calculated from IASI measurements for the four regions reproduce fairly well the interannual variability from the GFEDv3.1 and GFASv1.0 emissions inventories for NH3 but show values about 1.5-2 times higher than emissions given by the two biomass burning emission inventories, even when assuming a fairly long lifetime of 36 h for that species.

  11. PPARγ and MyoD are differentially regulated by myostatin in adipose-derived stem cells and muscle satellite cells

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Feng [Key Laboratory of Swine Genetics and Breeding of the Agricultural Ministry and Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of the Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 (China); Deng, Bing [Wuhan Institute of Animal Science and Veterinary Medicine, Wuhan Academy of Agricultural Science and Technology, Wuhan, Hubei, 430208 (China); Wen, Jianghui [Wu Han University of Technology, Wuhan 430074 (China); Chen, Kun [Key Laboratory of Swine Genetics and Breeding of the Agricultural Ministry and Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of the Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 (China); Liu, Wu; Ye, Shengqiang; Huang, Haijun [Wuhan Institute of Animal Science and Veterinary Medicine, Wuhan Academy of Agricultural Science and Technology, Wuhan, Hubei, 430208 (China); Jiang, Siwen, E-mail: jiangsiwen@mail.hzau.edu.cn [Key Laboratory of Swine Genetics and Breeding of the Agricultural Ministry and Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of the Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 (China); Xiong, Yuanzhu, E-mail: xiongyzhu@163.com [Key Laboratory of Swine Genetics and Breeding of the Agricultural Ministry and Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of the Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 (China)

    2015-03-06

    Myostatin (MSTN) is a secreted protein belonging to the transforming growth factor-β (TGF-β) family that is primarily expressed in skeletal muscle and also functions in adipocyte maturation. Studies have shown that MSTN can inhibit adipogenesis in muscle satellite cells (MSCs) but not in adipose-derived stem cells (ADSCs). However, the mechanism by which MSTN differently regulates adipogenesis in these two cell types remains unknown. Peroxisome proliferator-activated receptor-γ (PPARγ) and myogenic differentiation factor (MyoD) are two key transcription factors in fat and muscle cell development that influence adipogenesis. To investigate whether MSTN differentially regulates PPARγ and MyoD, we analyzed PPARγ and MyoD expression by assessing mRNA, protein and methylation levels in ADSCs and MSCs after treatment with 100 ng/mL MSTN for 0, 24, and 48 h. PPARγ mRNA levels were downregulated after 24 h and upregulated after 48 h of treatment in ADSCs, whereas in MSCs, PPARγ levels were downregulated at both time points. MyoD expression was significantly increased in ADSCs and decreased in MSCs. PPARγ and MyoD protein levels were upregulated in ADSCs and downregulated in MSCs. The CpG methylation levels of the PPARγ and MyoD promoters were decreased in ADSCs and increased in MSCs. Therefore, this study demonstrated that the different regulatory adipogenic roles of MSTN in ADSCs and MSCs act by differentially regulating PPARγ and MyoD expression. - Highlights: • PPARγ and MyoD mRNA and protein levels are upregulated by myostatin in ADSCs. • PPARγ and MyoD mRNA and protein levels are downregulated by myostatin in MSCs. • PPARγ exhibited different methylation levels in myostatin-treated ADSCs and MSCs. • MyoD exhibited different methylation levels in myostatin-treated ADSCs and MSCs. • PPARγ and MyoD are differentially regulated by myostatin in ADSCs and MSCs.

  12. Positive response of Indian summer rainfall to Middle East dust

    KAUST Repository

    Jin, Qinjian

    2014-06-02

    Using observational and reanalyses data, we investigated the impact of dust aerosols over the Middle East and the Arabian Sea (AS) on the Indian summer monsoon (ISM) rainfall. Satellite and aerosol reanalysis data show extremely heavy aerosol loading, mainly mineral dust, over the Middle East and AS during the ISM season. Multivariate empirical orthogonal function analyses suggest an aerosol-monsoon connection. This connection may be attributed to dust-induced atmospheric heating centered over the Iranian Plateau (IP), which enhances the meridional thermal contrast and strengthens the ISM circulation and rainfall. The enhanced circulation further transports more dust to the AS and IP, heating the atmosphere (positive feedback). The aerosols over the AS and the Arabian Peninsula have a significant correlation with rainfall over central and eastern India about 2 weeks later. This finding highlights the nonlocal radiative effect of dust on the ISM circulation and rainfall and may improve ISM rainfall forecasts. © 2014. American Geophysical Union. All Rights Reserved.

  13. The influence of seasonal rainfall upon Sahel vegetation

    DEFF Research Database (Denmark)

    Proud, Simon Richard; Rasmussen, Laura Vang

    2011-01-01

    include changes in total yearly rainfall, land-use change and migration. But these factors are not fully explanatory. This study addresses other possible factors for variation in vegetation patterns through the analysis of the Normalized Difference Vegetation Index (NDVI) produced by satellite sensors. We...... focus on precipitation, but instead of looking at the total yearly amount of rainfall, the intra-annual variation is examined. Here we show that plant growth is strongly correlated with the number and frequency of days within the rainy season upon which there is no rainfall. Furthermore, we find...

  14. Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010

    OpenAIRE

    Mukabutera, Assumpta; Thomson, Dana; Murray, Megan; Basinga, Paulin; Nyirazinyoye, Laetitia; Atwood, Sidney; Savage, Kevin P.; Ngirimana, Aimable; Hedt-Gauthier, Bethany L.

    2016-01-01

    Background: Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. Methods: We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitatio...

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

    Science.gov (United States)

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

    2017-06-01

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

  16. Coping with vegetation dynamics in low-land wetlands - Integration of RS derived interception into the rainfall-runoff model WetSpa

    Science.gov (United States)

    Jarosław, J.; Szporak, S.; Verbeiren, B.; Batelaan, O.

    2012-04-01

    The effective protection of wetlands demands knowledge of hydrological processes, which can be appropriately analysed using distributed models. It is eminent that the calibration and verification of distributed models of catchments with significant wetland coverage have to focus on wetland-specific issues such as the hydrological response of natural vegetation, i.e. parameterisation and dynamics of vegetation. An important and useful parameter describing vegetation canopy structure in terrestrial ecosystems is the Leaf Area Index (LAI), which is closely related to photosynthesis, net primary productivity, evapotranspiration and interception storage capacity. LAI can be estimated with remote sensing data, its suitability to derive the actual state of vegetation is high. This study focuses on improving the interception capacity calculation in the distributed hydrological model WetSpa. The main objective is to integrate seasonal LAI data. Not only field measurements, but also remote sensing derived LAI data is integrated into a WetSpa model for the Upper Biebrza catchment (northeast Poland). Biebrza National Park is characterized by a significant coverage of wetland and large variation in vegetation types. The use of remote sensing derived LAI values considerably improves the assessment of the actual status of vegetation and its seasonal dynamics. Landsat Thematic Mapper images are used to represent the different vegetation stages during the growing season (near LAI minimum and LAI maximum). They are analysed and processed to estimate the interception storage capacity of plant communities typical for Biebrza River valley. LAI of different plant communities has been measured using LAI-2000, and empirical relationships between these measurements and several spectral vegetation indices were established using linear and non-linear regression analysis. The vegetation indices with the highest correlation and the strongest linear relationship regarding LAI are NDVI (R2 = 0

  17. Comparative mapping of a gorilla-derived alpha satellite DNA clone on great ape and human chromosomes.

    Science.gov (United States)

    Baldini, A; Miller, D A; Shridhar, V; Rocchi, M; Miller, O J; Ward, D C

    1991-11-01

    We have isolated an alpha satellite DNA clone, pG3.9, from gorilla DNA. Fluorescence in situ hybridization on banded chromosomes under high stringency conditions revealed that pG3.9 identifies homologous sequences at the centromeric region of ten gorilla chromosomes, and, with few exceptions, also recognizes the homologous chromosomes in human. A pG3.9-like alphoid DNA is present on a larger number of orangutan chromosomes, but, in contrast, is present on only two chromosomes in the chimpanzee. These results show that the chromosomal subsets of related alpha satellite DNA sequences may undergo different patterns of evolution.

  18. Winter mass balance of Drangajökull ice cap (NW Iceland) derived from satellite sub-meter stereo images

    OpenAIRE

    J. M. C. Belart; E. Berthier; E. Magnússon; Anderson, L.S.; F. Pálsson; Thorsteinsson, T; Howat, I. M.; Aðalgeirsdóttir, G.; Jóhannesson, T.; A. H. Jarosch

    2017-01-01

    Sub-meter resolution, stereoscopic satellite images allow for the generation of accurate and high-resolution digital elevation models (DEMs) over glaciers and ice caps. Here, repeated stereo images of Drangajökull ice cap (NW Iceland) from Pléiades and WorldView2 (WV2) are combined with in situ estimates of snow density and densification of firn and fresh snow to provide the first estimates of the glacier-wide geodetic winter mass balance obtained from satellite imagery. Sta...

  19. Mosaic of bathymetry derived from multispectral WV-2 satellite imagery of Agrihan Island, Territory of Mariana, USA from 2003-08-26 to 2012-05-03 (NODC Accession 0126914)

    Data.gov (United States)

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

  20. How important is tropospheric humidity for coastal rainfall in the tropics?

    CERN Document Server

    Bergemann, Martin

    2016-01-01

    Recent research has community have shown that tropical convection and rainfall is sensitive to mid-tropospheric humidity. Therefore it has been suggested to improve the representation of moist convection by making cumulus parameterizations more sensitive to mid-tropospheric moisture. Climate models show considerable rainfall biases in coastal tropical areas, where approx. 33 % of the overall rainfall received is associated with coastal land-sea interaction. Building on an algorithm to objectively identify rainfall that is associated with land-sea interaction we investigate whether the relationship between rainfall in coastal regions and atmospheric humidity differs from that over the open ocean or over inland areas. We combine 3-hourly satellite estimates of rainfall with humidity estimates from reanalyses and investigate if coastal rainfall reveals the well known relationship between area-averaged precipitation and column integrated moisture. We find that rainfall that is associated with coastal land-sea eff...

  1. Satellite- versus temperature-derived green wave indices for predicting the timing of spring migration of avian herbivores

    NARCIS (Netherlands)

    Shariati Najafabadi, M.; Darvishzadeh, R.; Skidmore, A.K.; Kölzsch, A.; Vrieling, A.; Nolet, B.A.; Exo, K.; Meratnia, N.; Havinga, P.J.M.; Stahl, J.; Toxopeus, A.G.

    2015-01-01

    According to the green wave hypothesis, herbivores follow the flush of spring growth of forage plants during their spring migration to northern breeding grounds. In this study we compared two green wave indices for predicting the timing of the spring migration of avian herbivores: the satellite-deri

  2. Comparison of satellite-derived land surface temperature and air temperature from meteorological stations on the Pan-Arctic scale

    NARCIS (Netherlands)

    Urban, M.; Eberle, J.; Hüttich, C.; Schmullius, C.; Herold, M.

    2013-01-01

    Satellite-based temperature measurements are an important indicator for global climate change studies over large areas. Records from Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR) and (Advanced) Along Track Scanning Radiometer ((A)ATSR) are pr

  3. Uncertainty of Areal Rainfall Estimation Using Point Measurements

    Science.gov (United States)

    McCarthy, D.; Dotto, C. B. S.; Sun, S.; Bertrand-Krajewski, J. L.; Deletic, A.

    2014-12-01

    The spatial variability of precipitation has a great influence on the quantity and quality of runoff water generated from hydrological processes. In practice, point rainfall measurements (e.g., rain gauges) are often used to represent areal rainfall in catchments. The spatial rainfall variability is difficult to be precisely captured even with many rain gauges. Thus the rainfall uncertainty due to spatial variability should be taken into account in order to provide reliable rainfall-driven process modelling results. This study investigates the uncertainty of areal rainfall estimation due to rainfall spatial variability if point measurements are applied. The areal rainfall is usually estimated as a weighted sum of data from available point measurements. The expected error of areal rainfall estimates is 0 if the estimation is an unbiased one. The variance of the error between the real and estimated areal rainfall is evaluated to indicate the uncertainty of areal rainfall estimates. This error variance can be expressed as a function of variograms, which was originally applied in geostatistics to characterize a spatial variable. The variogram can be evaluated using measurements from a dense rain gauge network. The areal rainfall errors are evaluated in two areas with distinct climate regimes and rainfall patterns: Greater Lyon area in France and Melbourne area in Australia. The variograms of the two areas are derived based on 6-minute rainfall time series data from 2010 to 2013 and are then used to estimate uncertainties of areal rainfall represented by different numbers of point measurements in synthetic catchments of various sizes. The error variance of areal rainfall using one point measurement in the centre of a 1-km2 catchment is 0.22 (mm/h)2 in Lyon. When the point measurement is placed at one corner of the same-size catchment, the error variance becomes 0.82 (mm/h)2 also in Lyon. Results for Melbourne were similar but presented larger uncertainty. Results

  4. Space-time organization of debris flows-triggering rainfall: effects on the identification of the rainfall threshold relationships

    Science.gov (United States)

    Borga, Marco; Nikolopoulos, Efthymios; Creutin, Jean Dominique; Marra, Francesco

    2015-04-01

    Debris flow occurrence is generally forecasted by means of empirical rainfall depth-duration thresholds which are often derived based on rain gauge observations (Guzzetti et al., 2008). Rainfall sampling errors, related to the sparse nature of raingauge data, lead to underestimation of the intensity-duration thresholds (Nikolopoulos et al., 2014, Nikolopoulos et al., 2015). This underestimation may be large when debris flows are triggered by convective rainfall events, characterized by limited spatial extent, turning into less efficient forecasts of debris flow occurrence. This work investigates the spatial and temporal structure of rainfall patterns and its effects on the derived rainfall threshold relationships using high-resolution, carefully corrected radar data for 82 debris flows events occurred in the eastern Italian Alps. We analyze the spatial organization of rainfall depths relative to the rainfall occurred over the debris flows initiation point using the distance from it as the main coordinate observing that, on average, debris flows initiation points are characterized by a maximum in the rainfall depth field. We investigate the relationship between spatial organization and duration of rainfall pointing out that the rainfall underestimation is larger for the shorter durations and increases regularly as the distance between rainfall measurement location and debris flow initiation point increases. We introduce an analytical framework that explains how the combination of the mean rainfall depth spatial pattern and its relationship with rainfall duration causes the bias observed in the raingauge-based thresholds. The consistency of this analytical framework is proved by using a Monte Carlo sampling of radar rainfall fields. References Guzzetti, F., Peruccacci, S., Rossi, M., Stark, C.P., 2008. The rainfall intensity-duration control of shallow landslides and debris flows: an update. Landslides 5, 3-17, 10.1007/s10346-625 007-0112-1 Nikolopoulos, E.I., S

  5. Determinants of southeast Ethiopia seasonal rainfall

    Science.gov (United States)

    Jury, Mark R.

    2016-12-01

    The bi-modal climate of SE Ethiopia shares attributes with East Africa, notably that El Niño enhances rainfall, particularly in Sep-Nov season. In this study SE Ethiopia's continuous and seasonal rainfall relationships to global climate are studied to extend our knowledge of its determinants and predictability. A statistical forecast algorithm for the Sep-Nov short rains accounts for 54% of variance in 1980-2010. The Apr-Jun predictors include South Atlantic sea surface temperature, east Indian Ocean sea level air pressure and China upper zonal wind. Cooling in the South Atlantic coincides with a strengthened sub-tropical anticyclone, and later to changes in low level winds that bring orographic convection to SE Ethiopia. The slower El Niño-Southern Oscillation (ENSO) interacts with the faster Indian Ocean Dipole (IOD), but both signals mature too late for direct use in statistical prediction of Sep-Nov rainfall. Composite differences of the upper divergent circulation exhibit a global wave-2 pattern consistent with satellite-observed convection. One key feature is a zonal gradient in upper velocity potential over the Indian Ocean corresponding with a zonal atmospheric circulation. One outcome of this research is useful forecasts of SE Ethiopia Sep-Nov rainfall that will assist in agricultural planning.

  6. Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi)

    Science.gov (United States)

    Kneis, D.; Chatterjee, C.; Singh, R.

    2014-07-01

    The paper examines the quality of satellite-based precipitation estimates for the lower Mahanadi River basin (eastern India). The considered data sets known as 3B42 and 3B42-RT (version 7/7A) are routinely produced by the tropical rainfall measuring mission (TRMM) from passive microwave and infrared recordings. While the 3B42-RT data are disseminated in real time, the gauge-adjusted 3B42 data set is published with a delay of some months. The quality of the two products was assessed in a two-step procedure. First, the correspondence between the remotely sensed precipitation rates and rain gauge data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analysing their performance in the context of rainfall-runoff simulation. At sub-basin level (4000 to 16 000 km2) the satellite-based areal precipitation estimates were found to be moderately correlated with the gauge-based counterparts (R2 of 0.64-0.74 for 3B42 and 0.59-0.72 for 3B42-RT). Significant discrepancies between TRMM data and ground observations were identified at high-intensity levels. The rainfall depth derived from rain gauge data is often not reflected by the TRMM estimates (hit rate 80 mm day-1). At the same time, the remotely sensed rainfall rates frequently exceed the gauge-based equivalents (false alarm ratios of 0.2-0.6). In addition, the real-time product 3B42-RT was found to suffer from a spatially consistent negative bias. Since the regionalisation of rain gauge data is potentially associated with a number of errors, the above results are subject to uncertainty. Hence, a validation against independent information, such as stream flow, was essential. In this case study, the outcome of rainfall-runoff simulation experiments was consistent with the above-mentioned findings. The best fit between observed and simulated stream flow was obtained if rain gauge data were used as model input (Nash-Sutcliffe index of 0.76-0.88 at gauges not affected by

  7. Variability of satellite derived chlorophyll-a in the southern Caspian Sea following an invasion of ctenophore Mnemiopsis leidyi

    Science.gov (United States)

    Moradi, Masoud

    2013-01-01

    The comb jellyfish Mnemiopsis leidyi invaded vastly the whole Caspian Sea in summer 2001. Sea-viewing wide field-of-view sensor and moderate resolution imaging spectroradiometer (MODIS) satellite data from 1998 to 2006 and bio-optical field measurements along six transects in the southern Caspian Sea from 2001 to 2006 were used to detect the relationships between M. leidyi abundances with satellite driven sea surface temperature (SST) and chlorophyll-a. MODIS chlorophyll-a and SST monthly composite average value showed a positive linear correlation with M. leidyi abundance in the southern Caspian Sea. Spatiotemporal distribution of MODIS chlorophyll-a high-level patches (˜5 mg.m-3) were also confirmed with the highest recorded M. leidyi and the lowest zooplankton abundances. However, there are several other factors that affect the concentration of chlorophyll-a, and it is not clear how much of the chlorophyll-a variation is related to M. leidyi abundances.

  8. Country-wide rainfall maps from cellular communication networks

    Science.gov (United States)

    Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

    2013-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. Here we show how one cellular telecommunication network can be used to retrieve the space-time dynamics of rainfall for an entire country. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (2400) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both

  9. Towards Calibration of Sentinel 3 Data: Validation of Satellite-Derived SST Against In Situ Coastal Observations of the Portuguese Marine Waters

    Science.gov (United States)

    Vicente, Ricardo; Esteves, Rita; Lamas, Luisa; Pinto, Jose Paulo; Almeida, Sara; de Azevedo, Eduardo; Correia, Cecilia; Reis, Francisco

    2016-08-01

    Validation of future Sentinel-3 SLSTR data in the Eastern Atlantic Ocean was analysed here through a comparison of satellite-derived STT against in situ mooring buoys observations.SSTskin retrieved from IR satellite radiometers on- board ERS 1-2, Envisat, and Aqua, and concurrent SSTbulk measured with 14 buoy thermistors located at 1m depth were used to assess the statistical relationships between these datasets, with 20038 match- ups spanning from 1996 to 2015.As expected, results showed consistency between SSTskin and SSTbulk, exhibiting a correlation coefficient on the order of 98 %. Biases of both (A)ATSR and MODIS for day-time suggest a warmer satellite skin retrieval of + 0.15o and + 0.06o, respectively. For the night-time dataset, biases of - 0.25o and - 0.17o for (A)A TSR and MODIS, respectively, indicate cooler skin retrievals and reveal an inversion of the upper ocean thermic gradient. The RMSE ´s found were 0.53o for (A)ATSR and 0.41o for MODIS datasets.

  10. Pseudofaults and associated seamounts in the conjugate Arabian and Eastern Somali basins, NW Indian Ocean - New constraints from high-resolution satellite-derived gravity data

    Science.gov (United States)

    Sreejith, K. M.; Chaubey, A. K.; Mishra, Akhil; Kumar, Shravan; Rajawat, A. S.

    2016-12-01

    Marine gravity data derived from satellite altimeters are effective tools in mapping fine-scale tectonic features of the ocean basins such as pseudofaults, fracture zones and seamounts, particularly when the ocean basins are carpeted with thick sediments. We use high-resolution satellite-generated gravity and seismic reflection data to map boundaries of pseudofaults and transferred crust related to the Paleocene spreading ridge propagation in the Arabian and its conjugate Eastern Somali basins. The study has provided refinement in the position of previously reported pseudofaults and their spatial extensions in the conjugate basins. It is observed that the transferred crustal block bounded by inner pseudofault and failed spreading ridge is characterized by a gravity low and rugged basement. The refined satellite gravity image of the Arabian Basin also revealed three seamounts in close proximity to the pseudofaults, which were not reported earlier. In the Eastern Somali Basin, seamounts are aligned along NE-SW direction forming ∼300 km long seamount chain. Admittance analysis and Flexural model studies indicated that the seamount chain is isostatically compensated locally with Effective Elastic Thickness (Te) of 3-4 km. Based on the present results and published plate tectonic models, we interpret that the seamounts in the Arabian Basin are formed by spreading ridge propagation and are associated with pseudofaults, whereas the seamount chain in the Eastern Somali Basin might have probably originated due to melting and upwelling of upper mantle heterogeneities in advance of migrating/propagating paleo Carlsberg Ridge.

  11. Tropospheric BrO column densities in the Arctic derived from satellite: retrieval and comparison to ground-based measurements

    OpenAIRE

    H Sihler; Platt, U.; Beirle, S.; Marbach, T.; S. Kühl; S. Dörner; Verschaeve, J.; Frieß, U.; Pöhler, D.; Vogel, L.; Sander, R.; T. Wagner

    2012-01-01

    During polar spring, halogen radicals like bromine monoxide (BrO) play an important role in the chemistry of tropospheric ozone destruction. Satellite measurements of the BrO distribution have become a particularly useful tool to investigate this probably natural phenomenon, but the separation of stratospheric and tropospheric partial columns of BrO is challenging. In this study, an algorithm was developed to retrieve tropospheric vertical...

  12. Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

    Science.gov (United States)

    Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; Xi, B.

    2016-01-01

    Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud