WorldWideScience

Sample records for satellite infrared rainfall

  1. 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.

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

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    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.

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

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    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

  4. Initialization with diabatic heating from satellite-derived rainfall

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    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.

  5. A Combined Infrared and Microwave Technique for Studying the Diurnal Variation of Rainfall Over Amazonia

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    Negri, Andrew J.; Xu, L.; Adler, R. F.; Anagnostou, E.; Rickenbach, T. M.

    1999-01-01

    In this paper we present results from the application of a satellite infrared (IR) technique for estimating rainfall over northern South America. Our main objectives are to examine the diurnal variability of rainfall and to investigate the relative contributions from the convective and stratiform components. Additional information is contained in the original.

  6. A method for combining passive microwave and infrared rainfall observations

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    Kummerow, Christian; Giglio, Louis

    1995-01-01

    Because passive microwave instruments are confined to polar-orbiting satellites, rainfall estimates must interpolate across long time periods, during which no measurements are available. In this paper the authors discuss a technique that allows one to partially overcome the sampling limitations by using frequent infrared observations from geosynchronous platforms. To accomplish this, the technique compares all coincident microwave and infrared observations. From each coincident pair, the infrared temperature threshold is selected that corresponds to an area equal to the raining area observed in the microwave image. The mean conditional rainfall rate as determined from the microwave image is then assigned to pixels in the infrared image that are colder than the selected threshold. The calibration is also applied to a fixed threshold of 235 K for comparison with established infrared techniques. Once a calibration is determined, it is applied to all infrared images. Monthly accumulations for both methods are then obtained by summing rainfall from all available infrared images. Two examples are used to evaluate the performance of the technique. The first consists of a one-month period (February 1988) over Darwin, Australia, where good validation data are available from radar and rain gauges. For this case it was found that the technique approximately doubled the rain inferred by the microwave method alone and produced exceptional agreement with the validation data. The second example involved comparisons with atoll rain gauges in the western Pacific for June 1989. Results here are overshadowed by the fact that the hourly infrared estimates from established techniques, by themselves, produced very good correlations with the rain gauges. The calibration technique was not able to improve upon these results.

  7. Satellite rainfall retrieval by logistic regression

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    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.

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

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    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.

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

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    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.

  10. 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.

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

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    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.

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

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    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

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

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

    2016-04-01

    Rainfall-induced landslides and debris flows pose a significant and widespread hazard, resulting in a large number of casualties and enormous economic damages worldwide. Rainfall thresholds are often used to identify the local or regional rainfall conditions that, when reached or exceeded, are likely to result in landslides or debris flows. Rain gauge data are the typical source of information for the definition of these rainfall thresholds. However, in-situ observations over mountainous areas, where these hazards mainly occur, are very sparse or inexistent. Therefore identification and use of gauge-based rainfall thresholds is impossible in many landslide prone areas over the globe. The vast advancements in satellite-based precipitation estimation over the last couple of decades have lead to the creation of a number of global precipitation datasets at various spatiotemporal resolutions. Although several investigations have shown that these datasets can be associated with considerable uncertainty, they provide the only source of precipitation information over many areas around the globe. Therefore it is important to assess their performance in the context of landslide/debris flow prediction and investigate how we can potentially benefit from the information they provide. In this work, we evaluate the performance of three widely used quasi-global satellite precipitation products (3B42v7, PERSIANN and CMORPH) for the identification of rainfall threshold for landslide/debris flow triggering. Products are available at 0.25deg/3h resolution. The study region is focused over the Upper Adige river basin, northern Italy where a detailed database of more than 400 identified debris flows (during period 2000-2015) and a raingauge network of 95 stations, is available. Rain-gauge based rainfall thresholds are compared against satellite-based thresholds to evaluate strengths and limitations in using satellite precipitation estimates for defining rainfall thresholds. Analysis of

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

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    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.

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

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    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.

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

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    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.

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

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    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.

  18. Satellite and lunar laser ranging in infrared

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    Courde, Clement; Torre, Jean-Marie; Samain, Etienne; Martinot-Lagarde, Gregoire; Aimar, Mourad; Albanese, Dominique; Maurice, Nicolas; Mariey, Hervé; Viot, Hervé; Exertier, Pierre; Fienga, Agnes; Viswanathan, Vishnu

    2017-05-01

    We report on the implementation of a new infrared detection at the Grasse lunar laser ranging station and describe how infrared telemetry improves the situation. We present our first results on the lunar reflectors and show that infrared detection permits us to densify the observations and allows measurements during the new and the full moon periods. We also present the benefit obtained on the ranging of Global Navigation Satellite System (GNSS) satellites and on RadioAstron which have a very elliptic orbit.

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

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    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

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

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    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. Sampling errors in rainfall estimates by multiple satellites

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    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.

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

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    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.

  3. U.S. rainfall satellite missions in flux

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    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.

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

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    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

  5. 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.

  6. 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

  7. 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

    . Collaboration with GCOM-W is not only limited to its participation to GPM constellation but also coordination in areas of algorithm development and validation in Japan. Generation of high-temporal and high-accurate global rainfall map is one of targets of the GPM mission. As a proto-type for GPM era, JAXA has developed and operates the Global Precipitation Map algorithm in near-real-time since October 2008, and hourly and 0.1-degree resolution binary data and images available at http://sharaku.eorc.jaxa.jp/GSMaP/ four hours after observation. The algorithms are based on outcomes from the Global Satellite Mapping for Precipitation (GSMaP) project, which was sponsored by the Japan Science and Technology Agency (JST) under the Core Research for Evolutional Science and Technology (CREST) framework between 2002 and 2007 (Okamoto et al., 2005; Aonashi et al., 2009; Ushio et al., 2009). Target of GSMaP project is to produce global rainfall maps that are highly accurate and in high temporal and spatial resolution through the development of rain rate retrieval algorithms based on reliable precipitation physical models by using several microwave radiometer data, and comprehensive use of precipitation radar and geostationary infrared imager data. Near-real-time GSMaP data is distributed via internet and utilized by end users. Purpose of data utilization by each user covers broad areas and in world wide; Science researches (model validation, data assimilation, typhoon study, etc.), weather forecast/service, flood warning and rain analysis over river basin, oceanographic condition forecast, agriculture, and education. Toward the GPM era, operational application should be further emphasized as well as science application. JAXA continues collaboration with hydrological communities to utilize satellite-based precipitation data as inputs to future flood prediction and warning system, as well as with meteorological agencies to proceed further data utilization in numerical weather prediction

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. The Infrared Astronomical Satellite (IRAS) mission

    Science.gov (United States)

    Neugebauer, G.; Habing, H. J.; Van Duinen, R.; Aumann, H. H.; Beichman, C. A.; Baud, B.; Beintema, D. A.; Boggess, N.; Clegg, P. E.; De Jong, T.

    1984-01-01

    The Infrared Astronomical Satellite (IRAS) consists of a spacecraft and a liquid helium cryostat that contains a cooled IR telescope. The telescope's focal plane assembly is cooled to less than 3 K, and contains 62 IR detectors in the survey array which are arranged so that every source crossing the field of view can be seen by at least two detectors in each of four wavelength bands. The satellite was launched into a 900 km-altitude near-polar orbit, and its cryogenic helium supply was exhausted on November 22, 1983. By mission's end, 72 percent of the sky had been observed with three or more hours-confirming scans, and 95 percent with two or more hours-confirming scans. About 2000 stars detected at 12 and 25 microns early in the mission, and identified in the SAO (1966) catalog, have a positional uncertainty ellipse whose axes are 45 x 9 arcsec for an hours-confirmed source.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. Infrared and Microwave Image Fusion for Rainfall Detection over Northern Algeria

    Directory of Open Access Journals (Sweden)

    Fethi Ouallouche

    2014-05-01

    Full Text Available Rain areas delineation proposed in this paper is based on the image fusion from geostationary Meteosat Second Generation (MSG satellite, with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM satellite. The fusion technique described in this work used an artificial neural network (ANN. It's has been developed to detect instantaneous rainfall by using information from the IR images of MSG satellite and from TRMM Microwave Imager (TMI. The study is carried out over north of Algeria. Seven spectral parameters are used as input data of ANN to identify raining or non - raining pixels. Corresponding data of raining /non-raining pixels are taken from a PR (precipitation radar issued from TRMM. Results from the developed scheme are compared with the results of SI method (Scattering Index taken as reference method. The results show that the developed model performs very well and overcomes the deficiencies of use a single satellite.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. 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.

  9. Convective Rainfall Estimation from Digital GOES-1 Infrared Data.

    Science.gov (United States)

    1979-05-01

    Newton considered the possibilities of satellites and outlined the conditions necessary to make them possible. Three hundred years ago, in Principia ... Mathematica , Newton discussed the conditions under which a projectile must be launched to follow a specific orbit and laid the precise mathematics of

  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. 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.

  12. 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.

  13. Infrared Spectral Radiance Intercomparisons With Satellite and Aircraft Sensors

    Science.gov (United States)

    Larar, Allen M.; Zhou, Daniel K.; Liu, Xu; Smith, William L.

    2014-01-01

    Measurement system validation is critical for advanced satellite sounders to reach their full potential of improving observations of the Earth's atmosphere, clouds, and surface for enabling enhancements in weather prediction, climate monitoring capability, and environmental change detection. Experimental field campaigns, focusing on satellite under-flights with well-calibrated FTS sensors aboard high-altitude aircraft, are an essential part of the validation task. Airborne FTS systems can enable an independent, SI-traceable measurement system validation by directly measuring the same level-1 parameters spatially and temporally coincident with the satellite sensor of interest. Continuation of aircraft under-flights for multiple satellites during multiple field campaigns enables long-term monitoring of system performance and inter-satellite cross-validation. The NASA / NPOESS Airborne Sounder Testbed - Interferometer (NAST-I) has been a significant contributor in this area by providing coincident high spectral/spatial resolution observations of infrared spectral radiances along with independently-retrieved geophysical products for comparison with like products from satellite sensors being validated. This presentation gives an overview of benefits achieved using airborne sensors such as NAST-I utilizing examples from recent field campaigns. The methodology implemented is not only beneficial to new sensors such as the Cross-track Infrared Sounder (CrIS) flying aboard the Suomi NPP and future JPSS satellites but also of significant benefit to sensors of longer flight heritage such as the Atmospheric InfraRed Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI) on the AQUA and METOP-A platforms, respectively, to ensure data quality continuity important for climate and other applications. Infrared spectral radiance inter-comparisons are discussed with a particular focus on usage of NAST-I data for enabling inter-platform cross-validation.

  14. 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.

  15. 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.

  16. Low-Cost Satellite Infrared Imager Study

    Science.gov (United States)

    2007-11-02

    2,297.00 10 MATLAB , Simulink , Symbolic Math Toolbox (2 ea @ £894) £1,788.00 11 MATLAB Image Processing Toolbox (2 ea at £192) £384.00 12 MATLAB ...Figure 1: MWIR and TIR satellite imagery. On the left is a BIRD image of forest fires on the Portuguese/ Spanish border3 and the image on right is...space-borne MWIR and TIR imagers, instrument engineers are continually evaluating advances in the miniaturization of detector technology. One

  17. Cloud and Thermodynamic Parameters Retrieved from Satellite Ultraspectral Infrared Measurements

    Science.gov (United States)

    Zhou, Daniel K.; Smith, William L.; Larar, Allen M.; Liu, Xu; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

    2008-01-01

    Atmospheric-thermodynamic parameters and surface properties are basic meteorological parameters for weather forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiance observed with satellite ultraspectral infrared sounders has been developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra.

  18. Development of the first infrared satellite observatory

    Science.gov (United States)

    Smith, G. M.; Squibb, G. F.

    1984-01-01

    A development history is given for the Infrared Astronomical Satelite (IRAS), whose primary mission objective is an unbiased, all-sky survey in the 8-120 micron wavelength range. A point source catalog of more than 200,000 IR sources, to be published later this year, represents the accomplishment of this objective. IRAS has also conducted 10,000 pointed observations of specific objects. Attention is given to the cost increases and schedule slips which resulted from the substantial technical challenges of IRAS hardware and software development, and to the management techniques which had to be employed in this major international project.

  19. 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

  20. 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.

  1. Spacecraft design project: High temperature superconducting infrared imaging satellite

    Science.gov (United States)

    1991-01-01

    The High Temperature Superconductor Infrared Imaging Satellite (HTSCIRIS) is designed to perform the space based infrared imaging and surveillance mission. The design of the satellite follows the black box approach. The payload is a stand alone unit, with the spacecraft bus designed to meet the requirements of the payload as listed in the statement of work. Specifications influencing the design of the spacecraft bus were originated by the Naval Research Lab. A description of the following systems is included: spacecraft configuration, orbital dynamics, radio frequency communication subsystem, electrical power system, propulsion, attitude control system, thermal control, and structural design. The issues of testing and cost analysis are also addressed. This design project was part of the course Advanced Spacecraft Design taught at the Naval Postgraduate School.

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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,.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. Mission design for the infrared astronomical satellite /IRAS/

    Science.gov (United States)

    Lundy, S. A.; Mclaughlin, W. I.; Pouw, A.

    1979-01-01

    IRAS, a joint United States, Netherlands, United Kingdom astronomical satellite, is scheduled to be launched early in 1981 with the purpose of completing an all-sky survey in the infrared wavelengths from 8 to 120 microns and to observe objects of special interest. The mission design is driven by thermal constraints primarily determined by the Sun and Earth; the orbit and survey strategy must be chosen so as to satisfy the mission requirements before the cryogenic system is depleted of its liquid helium. Computer graphics help the designer choose valid survey strategies and evaluate resulting sky coverage.

  13. 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.

  14. The infrared astronomical satellite AKARI: overview, highlights of the mission

    Science.gov (United States)

    Murakami, Hiroshi; Matsuhara, Hideo

    2008-07-01

    The AKARI, Japanese infrared astronomical satellite, is a 68.5 cm cooled telescope with two focal-plane instruments providing continuous sky scan at six wavelength bands in mid- and far-infrared. The instruments also have capabilities of imaging and spectroscopy in the wavelength range 2-180 μm in the pointing observations occasionally inserted into the continuous survey. AKARI was launched on 21st Feb. 2006, and has performed the all-sky survey as well as 5380 pointing observations until the liquid helium exhaustion on 26th Aug. 2007. The all sky survey covers more than 90 percent of the entire sky with higher spatial resolutions and sensitivities than the IRAS. First version of the infrared source catalogue will be released in 2009. Here we report the overview of the mission, highlights on the scientific results as well as the performance of the focal-plane instruments. We also present the observation plan with the near infrared camera during the post-helium mission phase started in June 2008.

  15. 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

  16. 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

  17. 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

  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. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. A low cost thermal infrared hyperspectral imager for small satellites

    Science.gov (United States)

    Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.

    2011-06-01

    The traditional model for space-based earth observations involves long mission times, high cost, and long development time. Because of the significant time and monetary investment required, riskier instrument development missions or those with very specific scientific goals are unlikely to successfully obtain funding. However, a niche for earth observations exploiting new technologies in focused, short lifetime missions is opening with the growth of the small satellite market and launch opportunities for these satellites. These low-cost, short-lived missions provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off the shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCOR), to demonstrate the ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable the use of COTS electronics, and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230-meter pixels with 20 wavenumber spectral resolution from a 400-km orbit.

  5. A low cost thermal infrared hyperspectral imager for small satellites

    Science.gov (United States)

    Crites, S. T.; Lucey, P. G.; Wright, R.; Garbeil, H.; Horton, K. A.; Wood, M.

    2012-06-01

    The growth of the small satellite market and launch opportunities for these satellites is creating a new niche for earth observations that contrasts with the long mission durations, high costs, and long development times associated with traditional space-based earth observations. Low-cost, short-lived missions made possible by this new approach provide an experimental platform for testing new sensor technologies that may transition to larger, more long-lived platforms. The low costs and short lifetimes also increase acceptable risk to sensors, enabling large decreases in cost using commercial off-the-shelf (COTS) parts and allowing early-career scientists and engineers to gain experience with these projects. We are building a low-cost long-wave infrared spectral sensor, funded by the NASA Experimental Project to Stimulate Competitive Research program (EPSCoR), to demonstrate ways in which a university's scientific and instrument development programs can fit into this niche. The sensor is a low-mass, power-efficient thermal hyperspectral imager with electronics contained in a pressure vessel to enable use of COTS electronics and will be compatible with small satellite platforms. The sensor, called Thermal Hyperspectral Imager (THI), is based on a Sagnac interferometer and uses an uncooled 320x256 microbolometer array. The sensor will collect calibrated radiance data at long-wave infrared (LWIR, 8-14 microns) wavelengths in 230 meter pixels with 20 wavenumber spectral resolution from a 400 km orbit. We are currently in the laboratory and airborne testing stage in order to demonstrate the spectro-radiometric quality of data that the instrument provides.

  6. 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.

  7. Estimating the Retrievability of Temperature Profiles from Satellite Infrared Measurements

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A method is developed to assess retrievability, namely the retrieval potential for atmospheric temperature profiles, from satellite infrared measurements in clear-sky conditions. This technique is based upon generalized linear inverse theory and empirical orthogonal function analysis. Utilizing the NCEP global temperature reanalysis data in January and July from 1999 to 2003, the retrievabilities obtained with the Atmospheric Infrared Sounder (AIRS) and the High Resolution Infrared Radiation Sounder/3 (HIRS/3)sounding channel data are derived respectively for each standard pressure level on a global scale. As an incidental result of this study, the optimum truncation number in the method of generalized linear inverse is deduced too. The results show that the retrievabilities of temperature obtained with the two datasets are similar in spatial distribution and seasonal change characteristics. As for the vertical distribution, the retrievabilities are low in the upper and lower atmosphere, and high between 400 hPa and 850 hPa. For the geographical distribution, the retrievabilities are low in the low-latitude oceanic regions and in some regions in Antarctica, and relatively high in mid-high latitudes and continental regions. Compared with the HIRS/3 data, the retrievability obtained with the AIRS data can be improved by an amount between 0.15 and 0.40.

  8. 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.

  9. 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

  10. Investigation of Adaptive-threshold Approaches for Determining Area-Time Integrals from Satellite Infrared Data to Estimate Convective Rain Volumes

    Science.gov (United States)

    Smith, Paul L.; VonderHaar, Thomas H.

    1996-01-01

    The principal goal of this project is to establish relationships that would allow application of area-time integral (ATI) calculations based upon satellite data to estimate rainfall volumes. The research is being carried out as a collaborative effort between the two participating organizations, with the satellite data analysis to determine values for the ATIs being done primarily by the STC-METSAT scientists and the associated radar data analysis to determine the 'ground-truth' rainfall estimates being done primarily at the South Dakota School of Mines and Technology (SDSM&T). Synthesis of the two separate kinds of data and investigation of the resulting rainfall-versus-ATI relationships is then carried out jointly. The research has been pursued using two different approaches, which for convenience can be designated as the 'fixed-threshold approach' and the 'adaptive-threshold approach'. In the former, an attempt is made to determine a single temperature threshold in the satellite infrared data that would yield ATI values for identifiable cloud clusters which are closely related to the corresponding rainfall amounts as determined by radar. Work on the second, or 'adaptive-threshold', approach for determining the satellite ATI values has explored two avenues: (1) attempt involved choosing IR thresholds to match the satellite ATI values with ones separately calculated from the radar data on a case basis; and (2) an attempt involved a striaghtforward screening analysis to determine the (fixed) offset that would lead to the strongest correlation and lowest standard error of estimate in the relationship between the satellite ATI values and the corresponding rainfall volumes.

  11. Insights into correlation between satellite infrared information and fault activities

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Tectonic activities are accompanied with material movement and energy transfer, which definitely change the state of thermal radiation on the ground. Thus it is possible to infer present-day tectonic activities based on variations of the thermal radiation state on the ground. The received satellite infrared information is, however, likely influenced by many kinds of factors. Therefore, the first problem that needs to be solved is to extract information on tectonic activities and eliminate effects of external (non-tectonic) factors. In this study, we firstly make a review of the current studies on this subject, and then present the technical approach and our research goal.Using the data of 20 years from the infrared band of the satellite of National Oceanic and Atmospheric Administration (NOAA) and the method we have developed, we investigate fault activities in western China. The results show that the areas with high residual values of land surface brightness temperature (LSBT), which is presumably related to faultings in space, accord usually with the locations of followed major earthquakes. The times of their value growing are also roughly consistent with the beginning of active periods of earthquakes.The low frequency component fields of the LSBT, acquired from wavelet analysis, exhibit well the spatial distributions of active faults.The "heat penetrability index" (HPI) related with enhancement of subsurface thermal information has been expressed well for the backgrounds of accelerated tectonic motions, and some correlations exist between HPI and the local faulting and seismicity. This study provides a new approach to study temporal-spatial evolution of recent activities of faults and their interactions.

  12. 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.

  13. TIRCIS: thermal infrared compact imaging spectrometer for small satellite applications

    Science.gov (United States)

    Wright, Robert; Lucey, Paul; Crites, Sarah; Garbeil, Harold; Wood, Mark; Pilger, Eric; Gabrieli, Andrea; Honniball, Casey

    2016-10-01

    Measurements of reflectance or emittance in tens of narrow, contiguous wavebands, allow for the derivation of laboratory quality spectra remotely, from which the chemical composition and physical properties of targets can be determined. Although spaceborne (e.g. EO-1 Hyperion) hyperspectral data in the 0.4-2.5 micron (VSWIR) region are available, the provision of equivalent data in the log-wave infrared has lagged behind, there being no currently operational high spatial resolution LWIR imaging spectrometer on orbit. TIRCIS (Thermal Infra-Red Compact Imaging Spectrometer), uses a Fabry-Perot interferometer, an uncooled microbolometer array, and push-broom scanning to acquire hyperspectral image data. Radiometric calibration is provided by blackbody targets while spectral calibration is achieved using monochromatic light sources. The instrument has a mass of <15 kg and dimensions of 53 cm × 25 cm ♢ 22 cm, and has been designed to be compatible with integration into a micro-satellite platform. (A precursor to this instrument was launched onboard a 55 kg microsatellite in October 2015). The optical design yields a 120 m ground sample size given an orbit of 500 km. Over the wavelength interval of 7.5 to 14 microns up to 50 spectral samples are possible. Measured signal-to-noise ratios range from peak values of 500:1 to 1500:1, for source temperature of 10 to 100°C.

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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....

  19. 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

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. The effect of lunarlike satellites on the orbital infrared light curves of Earth-analog planets.

    Science.gov (United States)

    Moskovitz, Nicholas A; Gaidos, Eric; Williams, Darren M

    2009-04-01

    We have investigated the influence of lunarlike satellites on the infrared orbital light curves of Earth-analog extrasolar planets. Such light curves will be obtained by NASA's Terrestrial Planet Finder (TPF) and ESA's Darwin missions as a consequence of repeat observations to confirm the companion status of a putative planet and determine its orbit. We used an energy balance model to calculate disk-averaged infrared (bolometric) fluxes from planet-satellite systems over a full orbital period (one year). The satellites are assumed to lack an atmosphere, have a low thermal inertia like that of the Moon, and span a range of plausible radii. The planets are assumed to have thermal and orbital properties that mimic those of Earth, while their obliquities and orbital longitudes of inferior conjunction remain free parameters. Even if the gross thermal properties of the planet can be independently constrained (e.g., via spectroscopy or visible-wavelength detection of specular glint from a surface ocean), only the largest (approximately Mars-sized) lunarlike satellites can be detected by light curve data from a TPF-like instrument (i.e., one that achieves a photometric signal-to-noise ratio of 10 to 20 at infrared wavelengths). Nondetection of a lunarlike satellite can obfuscate the interpretation of a given system's infrared light curve so that it may resemble a single planet with high obliquity, different orbital longitude of vernal equinox relative to inferior conjunction, and in some cases drastically different thermal characteristics. If the thermal properties of the planet are not independently established, then the presence of a lunarlike satellite cannot be inferred from infrared data, which would thus demonstrate that photometric light curves alone can only be used for preliminary study, and the addition of spectroscopic data will be necessary.

  6. Application of satellite infrared measurements to mapping sea ice

    Science.gov (United States)

    Barnes, J. C.

    1972-01-01

    The application of the ITOS-SR (scanning radiometer) infrared measurements for mapping sea ice was examined. The work included detailed mapping of ice features visible in the ITOS nighttime DRSR (direct readout scanning radiometer) pictorial data and in Nimbus summertime film strip data. Analyses of digital temperature values from computer printouts of ITOS stored data and from Nimbus data listings were also undertaken, and densitometric measurements of both ITOS and Nimbus data were initiated.

  7. Identifying clouds over the Pierre Auger Observatory using infrared satellite data

    NARCIS (Netherlands)

    Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muniz, J.; Alves Batista, R.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Anticic, T.; Aramo, C.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Badescu, A. M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Baughman, B.; Baeuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Belletoile, A.; Bellidol, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Bluemer, H.; Bohacova, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Buchholz, P.; Bueno, A.; Buroker, L.; Burton, R. E.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos, J.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Colalillo, R.; Collica, L.; Coluccia, M. R.; Conceicao, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Criss, A.; Cronin, J.; Curutiu, A.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; de Jong, S. J.; De La Vega, G.; de Mello, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; del Peral, L.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Diaz, J. C.; Diaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; San Luis, P. Facal; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipcic, A.; Fliescher, S.; Fox, B. D.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Froehlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; Garcia, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Garilli, G.; Gascon Bravo, A.; Gemmeke, H.; Ghia, P. L.; Giller, M.; Gitto, J.; Glaser, C.; Glass, H.; Golup, G.; Gomez Albarracin, F.; Gomez Berisso, M.; Gomez Vitale, P. F.; Goncalves, P.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gorham, P.; Gouffon, P.; Grebe, S.; Griffith, N.; Grillo, A. F.; Grubb, T. D.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Horandel, J. R.; Horvath, P.; Hrabovsky, M.; Huber, D.; Huege, T.; Insolia, A.; Jansen, S.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Katkov, I.; Kegl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Krause, R.; Krohm, N.; Kroemer, O.; Kruppke-Hansen, D.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; LaHurd, D.; Latronico, L.; Lauer, R.; Lauscher, M.; Lautridou, P.; Le Coz, S.; Leao, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; Lopez, R.; Lopez Agueera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Malacari, M.; Maldera, S.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Maris, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martinez, H.; Martinez Bravo, O.; Martraire, D.; Masias Meza, J. J.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mayotte, E.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Messina, S.; Meyhandan, R.; Micanovic, S.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Mirarrionti, L.; Mitrica, B.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Ragaigne, D. Monnier; Montanet, F.; Morales, B.; Morello, C.; Moreno, J. C.; Mostafa, M.; Moura, C. A.; Muller, M. A.; Mueller, G.; Muenchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, T. J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Niggemann, T.; Nitz, D.; Nosek, D.; Nozka, L.; Oehlschlaeger, J.; Olinto, A.; Oliveira, M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Pekala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez Cabo, I.; Fernandez, G. Rodriguez; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodriguez-Frias, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouille-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Ruehle, C.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Greus, F. Salesa; Salina, G.; Sanchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovanek, P.; Schroeder, F. G.; Schulz, J.; Schuster, D.; Sciutto, Si.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Sima, O.; Smialkowski, A.; Smida, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanic, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Straub, M.; Stutz, A.; Suarez, F.; Suomijaervi, T.; Supanitsky, A. D.; Susa, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Tascau, O.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tome, B.; Tonachini, A.; Torralba Elipe, G.; Machado, D. Torres; Travnicek, P.; Tridapalli, D. B.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdes Galicia, J. F.; Valino, I.; Valore, L.; van Aar, G.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cardenas, B.; Varner, G.; Vazquez, J. R.; Vazquez, R. A.; Veberic, D.; Verzi, V.; Vicha, J.; Videla, M.; Villasenor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczynska, B.; Wilczynski, H.; Will, M.; Williams, C.; Winchen, T.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano Garcia, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhou, J.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.; Martin, L.

    2013-01-01

    We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud. identifications resulting from our method to those obtained by the Central Laser Facility of the Auger

  8. Estimation of volcanic ash refractive index from satellite infrared sounder data

    Science.gov (United States)

    Ishimoto, H.; Masuda, K.

    2014-12-01

    The properties of volcanic ash clouds (cloud height, optical depth, and effective radius of the particles) are planned to estimate from the data of the next Japanese geostationary meteorological satellite, Himawari 8/9. The volcanic ash algorithms, such as those proposed by NOAA/NESDIS and by EUMETSAT, are based on the infrared absorption properties of the ash particles, and the refractive index of a typical volcanic rock (i.e. andesite) has been used in the forward radiative transfer calculations. Because of a variety of the absorption properties for real volcanic ash particles at infrared wavelengths (9-13 micron), a large retrieval error may occur if the refractive index of the observed ash particles was different from that assumed in the retrieval algorithm. Satellite infrared sounder provides spectral information for the volcanic ash clouds. If we can estimate the refractive index of the ash particles from the infrared sounder data, a dataset of the optical properties for similar rock type of the volcanic ash can be prepared for the ash retrieval algorithms of geostationary/polar-orbiting satellites in advance. Furthermore, the estimated refractive index can be used for a diagnostic and a correction of the ash particle model in the retrieval algorithm within a period of the volcanic activities. In this work, optimal estimation of the volcanic ash parameters was conducted through the radiative transfer calculations for the window channels of the atmospheric infrared sounder (AIRS). The estimated refractive indices are proposed for the volcanic ash particles of some eruption events.

  9. Science operations management. [with Infrared Astronomy Satellite project

    Science.gov (United States)

    Squibb, G. F.

    1984-01-01

    The operation teams engaged in the IR Astronomical Satellite (IRAS) project included scientists from the IRAS International Science Team. The detailed involvement of these scientists in the design, testing, validation, and operations phases of the IRAS mission contributed to the success of this project. The Project Management Group spent a substantial amount of time discussing science-related issues, because science team coleaders were members from the outset. A single scientific point-of-contact for the Management Group enhanced the depth and continuity of agreement reached in decision-making.

  10. 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

  11. 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.

  12. 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.

  13. 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

  14. Current Sounding Capability From Satellite Meteorological Observation With Ultraspectral Infrared Instruments

    Science.gov (United States)

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

    2008-01-01

    Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. The intent of the measurement of tropospheric thermodynamic state and trace abundances is the initialization of climate models and the monitoring of air quality. The NPOESS Airborne Sounder Testbed-Interferometer (NAST-I), designed to support the development of future satellite temperature and moisture sounders, aboard high altitude aircraft has been collecting data throughout many field campaigns. An advanced retrieval algorithm developed with NAST-I is now applied to satellite data collected with the Atmospheric InfraRed Sounder (AIRS) on the Aqua satellite launched on 4 May 2002 and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite launched on October 19, 2006. These instruments possess an ultra-spectral resolution, for example, both IASI and NAST-I have 0.25 cm-1 and a spectral coverage from 645 to 2760 cm-1. The retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to

  15. Satellite Map of Port-au-Prince, Haiti-2010-Infrared

    Science.gov (United States)

    Cole, Christopher J.; Sloan, Jeff

    2010-01-01

    The U.S. Geological Survey produced 1:24,000-scale post-earthquake image base maps incorporating high- and medium-resolution remotely sensed imagery following the 7.0 magnitude earthquake near the capital city of Port au Prince, Haiti, on January 12, 2010. Commercial 2.4-meter multispectral QuickBird imagery was acquired by DigitalGlobe on January 15, 2010, following the initial earthquake. Ten-meter multispectral ALOS AVNIR-2 imagery was collected by the Japanese Space Agency (JAXA) on January 12, 2010. These data were acquired under the Remote Sensing International Charter, a global team of space and satellite agencies that provide timely imagery in support of emergency response efforts worldwide. The images shown on this map were employed to support earthquake response efforts, specifically for use in determining ground deformation, damage assessment, and emergency management decisions. The raw, unprocessed imagery was geo-corrected, mosaicked, and reproduced onto a cartographic 1:24,000-scale base map. These maps are intended to provide a temporally current representation of post-earthquake ground conditions, which may be of use to decision makers and to the general public.

  16. 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...

  17. Particle contamination from Martin Optical Black. [in design of barrel baffle of Infrared Astronomical Satellite

    Science.gov (United States)

    Young, P. J.; Noll, R.; Andreozzi, L.; Hope, J.

    1981-01-01

    The design of the barrel baffle of the Infrared Astronomical Satellite (IRAS) Optical Subsystem to minimize production of particulate contamination is described. The configuration of the 50-inch long, 28.5-inch diameter baffle required pop-rivet assembly after coating with Martin Optical Black for stray light suppression. An experiment to determine the contamination produced at assembly led to the modification of the baffle construction to preclude such damage to the coated surfaces.

  18. 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

  19. Cloud mask via cumulative discriminant analysis applied to satellite infrared observations: scientific basis and initial evaluation

    Directory of Open Access Journals (Sweden)

    U. Amato

    2014-06-01

    Full Text Available We introduce a classification method (Cumulative Discriminant Analysis of the Discriminant Analysis type to discriminate between cloudy and clear sky satellite observations in the thermal infrared. The tool is intended for the high spectral resolution infrared sounder (IRS planned for the geostationary METEOSAT (Meteorological Satellite Third Generation platform and uses IASI (Infrared Atmospheric Sounding Interferometer data as a proxy. The Cumulative Discriminant Analysis does not introduce biases intrinsic with the approximation of the probability density functions and is flexible enough to adapt to different strategies to optimize the cloud mask. The methodology is based on nine statistics computed from IASI spectral radiances, which exploit the high spectral resolution of the instrument and which effectively summarize information contained within the IASI spectrum. A Principal Component Analysis prior step is also introduced which makes the problem more consistent with the statistical assumptions of the methodology. An initial assessment of the scheme is performed based on global and regional IASI real data sets and cloud masks obtained from AVHRR (Advanced Very High Resolution Radiometer and SEVIRI (Spinning Enhanced Visible and Infrared Imager imagers. The agreement with these independent cloud masks is generally well above 80%, except at high latitudes in their winter seasons.

  20. Cloud mask via cumulative discriminant analysis applied to satellite infrared observations: scientific basis and initial evaluation

    Science.gov (United States)

    Amato, U.; Lavanant, L.; Liuzzi, G.; Masiello, G.; Serio, C.; Stuhlmann, R.; Tjemkes, S. A.

    2014-10-01

    We introduce a classification method (cumulative discriminant analysis) of the discriminant analysis type to discriminate between cloudy and clear-sky satellite observations in the thermal infrared. The tool is intended for the high-spectral-resolution infrared sounder (IRS) planned for the geostationary METEOSAT (Meteorological Satellite) Third Generation platform and uses IASI (Infrared Atmospheric Sounding Interferometer) data as a proxy. The cumulative discriminant analysis does not introduce biases intrinsic with the approximation of the probability density functions and is flexible enough to adapt to different strategies to optimize the cloud mask. The methodology is based on nine statistics computed from IASI spectral radiances, which exploit the high spectral resolution of the instrument and which effectively summarize information contained within the IASI spectrum. A principal component analysis prior step is also introduced, which makes the problem more consistent with the statistical assumptions of the methodology. An initial assessment of the scheme is performed based on global and regional IASI real data sets and cloud masks obtained from AVHRR (Advanced Very High Resolution Radiometer) and SEVIRI (Spinning Enhanced Visible and Infrared Imager) imagers. The agreement with these independent cloud masks is generally well above 80 %, except at high latitudes in the winter seasons.

  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. Search for astronomical sites suitable for infrared observations using GOES satellite images

    Science.gov (United States)

    Ducati, Jorge R.; Feijo, Eleandro S.

    2003-04-01

    Images from GOES satellite were used to develop a method to search for sites suitable to astronomical observations in the infrared. An area of study located in the Peruvian Andes was chosen, with altitudes above 2500 m. Forty-three images from the GOES meteorological satellite in channels 3, 4 and 5 were used. The GOES images, spanning an 11-day period, in each channel, were combined to produced images expressing the surface visibility in each channel. Atmospheric turbulence could be estimated from the variation of visibility over six-hour periods, with one image per hour. As criteria to classify sites on the Andes, we combined information on altitude, visibility of the surface in the infrared, the amount of water vapor in the atmosphere, and atmospheric turbulence. Results of this new method showed that the region of Moquegua, in South Peru, is to be preferred in surveys for astronomical sites. Comparisons with results from other investigators, which used other approaches, indicated that this methodology can produce valid results and can be applied to studies covering larger periods. The general results of this study indicate that the method is valid and can effectively be used as an important resource in surveys for infrared astronomical sites.

  3. Search for astronomical sites suitable for infrared observations using goes satellite images release

    Science.gov (United States)

    Ducati, J. R.; Feijó, E.

    2003-08-01

    Astronomical sites are traditionally found after studies performed over many years, including preliminary selection of places based in general information on climate, clear skies and logistical adequacy. It follows extensive "in situ" monitoring of seeing and cloudiness. Theses procedures are long and expensive, and alternatives can be looked for. In this study, images from GOES meteorological satellite were used to develop a method to search for sites suitable to astronomical observations in the infrared. An area of study located in the Peruvian Andes was chosen, with altitudes above 2500 m. 43 images from the GOES meteorological satellite in chanels 3, 4 and 5 were used. The GOES images, spanning a 11-day period, in each channel, were combined to produced images expressing the surface visibility in each channel. Atmospheric turbulence could be estimated from the variation of visibility over six-hour periods, with one image per hour. As criteria to classify sites on the Andes, we combined information on altitude, visibility of the surface in the infrared, the amount of water vapor in the atmosphere, and atmospheric turbulence. Results of this new method showed that the region of Moquegua, in South Peru, is to be preferred in surveys for astronomical sites. Comparisons with results from other investigators, which used other approaches, indicated that this methodology produces valid results and can be used to studies spanning larger periods. The general results of this study indicate that the method can efectively be used as an important resource in surveys for infrared astronomical sites

  4. 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

  5. Astrometry and Near-Infrared Photometry of Neptune's Inner Satellites and Ring Arcs

    Science.gov (United States)

    Dumas, Christophe; Terrile, Richard J.; Smith, Bradford A.; Schneider, Glenn

    2002-03-01

    We report 1.87 μm photometry and astrometry of the inner satellites (Proteus, Larissa, Galatea, and Despina) and ring arcs of Neptune, obtained with the Hubble Space Telescope and its near-infrared camera NICMOS. From comparison with the Voyager data obtained at visible wavelengths, the small bodies orbiting within the ring region of Neptune have a near-infrared albedo consistently low, but higher than at visible wavelengths for most of the satellites, ranging from p1.87μm=0.058 (Despina) to p1.87μm=0.094 (Proteus). The ring arcs display a reddish spectral response similar to the satellites' in the 0.5-1.9 μm wavelength range. If we consider an earlier photometric measurement of Proteus obtained at K band, the satellite's albedo shows a depression at 2.2 μm that could be the first spectral evidence for the presence of CH or CN bearing material on its surface. Although astrometry of the inner moons of Neptune yields positions consistent with the predictions derived from Voyager images, the long time base between the Voyager and NICMOS observations allows us to refine our knowledge of their mean motions and semimajor axes, and to decrease the errors associated with these measurements. In addition, we confirm a mismatch between the mean semimajor axis of the ring arcs and the location of the 42:43 corotation inclined resonance due to Galatea. This result calls into question the ability of this resonance to confine the arcs azimuthally.

  6. Digital Meteorological Radar Data Compared with Digital Infrared Data from a Geostationary Meteorological Satellite.

    Science.gov (United States)

    1979-05-01

    datai uwere tab~ulaited for compariso;cn with the infrared satellite data) j 20 CIIA1iLTR Ml GEOSTAT] ONAPY ME LW)L- C , TIL LF K Meteorolccj isa I sate...8217):U S f 3 ’ 1 t ’ Iv . e , :]~L ’ bI 1 T-4 THY:-, L,’AClvT!P 3 AND IMVIC]l C t101 KRV~;It Tb 3 ( ji~u>:2;cat L ii 2 ’GD ~Of the L~r [2 u : ~~ I~ rtu ~j

  7. Identifying clouds over the Pierre Auger Observatory using infrared satellite data

    Science.gov (United States)

    Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Alves Batista, R.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antičić, T.; Aramo, C.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Badescu, A. M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Baughman, B.; Bäuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Buchholz, P.; Bueno, A.; Buroker, L.; Burton, R. E.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos, J.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Colalillo, R.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Criss, A.; Cronin, J.; Curutiu, A.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; de Jong, S. J.; De La Vega, G.; de Mello, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; del Peral, L.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Diaz, J. C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fox, B. D.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Garilli, G.; Gascon Bravo, A.; Gemmeke, H.; Ghia, P. L.; Giller, M.; Gitto, J.; Glaser, C.; Glass, H.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gorham, P.; Gouffon, P.; Grebe, S.; Griffith, N.; Grillo, A. F.; Grubb, T. D.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Jansen, S.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Katkov, I.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Krause, R.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; LaHurd, D.; Latronico, L.; Lauer, R.; Lauscher, M.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Malacari, M.; Maldera, S.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Mariş, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Martraire, D.; Masías Meza, J. J.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mayotte, E.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Messina, S.; Meyhandan, R.; Mićanović, S.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Miramonti, L.; Mitrica, B.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Niggemann, T.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Oliveira, M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Peķala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez Cabo, I.; Rodriguez Fernandez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F. G.; Schulz, J.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanič, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Straub, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Torralba Elipe, G.; Torres Machado, D.; Travnicek, P.; Tridapalli, D. B.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Varner, G.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano Garcia, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhou, J.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.

    2013-12-01

    We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ˜2.4 km by ˜5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

  8. Identifying clouds over the Pierre Auger Observatory using infrared satellite data

    Energy Technology Data Exchange (ETDEWEB)

    Abreu, Pedro; et al.,

    2013-12-01

    We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

  9. NOAA Climate Data Record (CDR) of Gridded Satellite Data from ISCCP B1 (GridSat-B1) Infrared Channel Brightness Temperature, Version 2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Gridded Satellite (GridSat-B1) data provides a uniform set of quality controlled geostationary satellite observations for the visible, infrared window and...

  10. 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.

  11. Near-Infrared Photometry of Irregular Satellites of Jupiter and Saturn

    CERN Document Server

    Grav, T; Grav, Tommy; Holman, Matthew J.

    2003-01-01

    We present JHKs photometry of 10 Jovian and 4 Saturnian irregular satellites, taken with the Near-InfraRed Imager (NIRI) at the 8-m Gemini North Observatory on Mauna Kea, Hawaii. The observed objects have near-infrared colors consistent with C, P and D-type asteroids, although J XII Ananke and S IX Phoebe show weak indications of possible water features in the H filter. The four members of the Himalia-family have similar near-infrared colors, as do the two members of the Gallic family, S XX Paaliaq and S XXIX Siarnaq. From low resolution normalized reflectance spectra based on the broadband colors and covering 0.4 to 2.2 microns, the irregular satellites are identified as C-type (J VII Pasiphae, J VI Himalia and S IX Phoebe), P-type (J XII Ananke and J XVIII Themisto) and D-type (J IX Carme and J X Sinope), showing a diversity of origins of these objects.

  12. Near-infrared photometry and astrometry of Neptune's inner satellites and ring-arcs

    Science.gov (United States)

    Dumas, C.; Terrile, R. J.; Smith, B. A.; Schneider, G.; Becklin, E. E.

    2000-10-01

    Until recently, the system of Neptune's inner satellites and ring-arcs had only been observed in direct imaging from the Voyager 2 spacecraft, limiting our knowledge of this system to visible wavelengths data. Nearly ten years after the Voyager fly-by, HST/NICMOS observed the close vicinity of Neptune at 1.87μ m, a wavelength that corresponds to a strong methane absorption in the atmosphere of Neptune and allows the attenuation of the scattered light produced by the planet. We derived the near-infrared geometric albedo of the ring-arcs and small moons Proteus, Larissa, Galatea and Despina, and compared their orbital positions with the predictions from the 1989 Voyager observations. The surfaces of the inner satellites of Neptune appear to be coated with dark, neutral material, with albedoes ranging from 0.077 (Proteus) to 0.033 (Despina) and their orbital position was found to be within the prediction errors of the Voyager measurements. The material located inside the ring-arcs of Neptune also displays a low-neutral reflectance (p{1.87 μm } ~ 0.055) and the HST/NICMOS measurement of the mean orbital motion of the ring-arcs shows that their confinement cannot be entirely explained by resonances produced by the nearby satellite Galatea (Nature, 400, 733-735). This work was performed at the Jet Propulsion Laboratory, Caltech, under contract with the National Aeronautics and Space Administration, and is supported by NASA grant NAG5-3042.

  13. 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

  14. Probable satellite thermal infrared anomaly before the Zhangbei MS=6.2 earthquake on January 10, 1998

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This paper used the thermal infrared data of the satellite NOAA-AAVHRR of the north part of North China (113°~119° E, 38°~42° N), and processed the remote sensing data through radiation adjustment, geometric adjustment and so on by the software "The Monitoring and Fast Process System of Earthquake Precursor Thermal Infrared Anomaly", inversed the earth surface temperature. Some disturbances effect had been excluded, and thermal infrared temperature anomaly had been extracted by the picture difference method. The Zhangbei MS=6.2 earthquake is used as the example in the paper, so that in the paper thermal infrared characteristics on time-space before earthquake and the relationship between the anomaly and the earthquake prediction have been summarized.Within more than ten days before the Zhangbei earthquake, the thermal infrared anomaly had emerged widely along Zhangjiakou-Bohai seismic belt, and the anomalous region seemed like a belt and it is also consistent with the tectonic background there; the anomaly expanded from the outside toward the earthquake focus, but the focus lay at the edge of the thermal infrared region. So it is possible to explore a new anomaly observation method for earthquake prediction by observing and studying the satellite thermal infrared anomaly before big earthquakes happen.

  15. Report of the Joint Scientific Mission Definition Team for an infrared astronomical satellite

    Science.gov (United States)

    1976-01-01

    The joint effort is reported of scientists and engineers from the Netherlands, the United Kingdom, and the United States working as a team for the purpose of exploring the possibility of a cooperative venture. The proposed mission builds upon experience gained from the successful Astronomical Netherlands Satellite (ANS). This satellite will be in a polar orbit at an altitude of 900 km. It will carry an 0.6 m diameter telescope cooled with helium to a temperature near 10K. An array of approximately 100 detectors will be used to measure the infrared flux in four wavelength bands centered at 10, 20, 50, and 100 microns. Sources will be located on the sky with positional accuracy of 1/2 arcminute. The instrument should be able to investigate the structure of extended sources with angular scales up to 1.0 deg. The entire sky will be surveyed and the full lifetime of the mission of about one year will be necessary to complete the survey. Special observational programs will also be incorporated into the mission.

  16. 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

  17. A Comparative Analysis of the Far Infrared Spectra of Saturn's Rings and Icy Satellites with Cassini CIRS

    Science.gov (United States)

    Brooks, Shawn M.; Spilker, Linda; Edgington, Scott G.

    2016-10-01

    We will report on a campaign to observe Saturn's main rings and major icy satellites with the Composite Infrared Spectrometer onboard Cassini. CIRS' three infrared detectors cover a combined spectral range of 10 to 1400 cm-1 (1 mm down to 7 microns). We focus on data from Focal Plane 1, which covers the 10 to 600 cm-1 range (1 mm to 16 microns). The apodized spectral resolution of the instrument can be varied from 15 cm-1 to 0.5 cm-1 (Flasar et al. 2004).The spectral behavior of Saturn's main rings and icy satellites in the far infrared has been the subject of previous studies with CIRS FP1 data (Spilker at al. 2005, Carvano et al. 2007, Morishima et al. 2012). These studies have shown that the infrared spectra of these icy rings and bodies are remarkably flat between about 40 to 200 microns. Longward of this, CIRS observations, as well as older spacecraft data, show a gradual decrease in ring emissivity. This roll-off in emissivity may be due to varying optical constants of water ice, which dominates the rings' composition, as one moves towards microwave wavelengths. Carvano et al. (2007), who analyzed spectra of the icy satellites Phoebe, Iapetus, Enceladus, Tethys and Hyperion, investigated the absence of emissivity features in spectra of those satellites. This absence is intriguing, as water ice, which dominates their surface composition, contains absorption features in the FP1 spectral range. They conclude that high porosity in these satellites' regoliths may explain this lack of spectral variability.To better characterize the far infrared spectra of the rings and satellites, we have implemented a series of dedicated observations. The goal is to obtain thousands of infrared spectra at 3 cm-1 resolution of each individual ring region and as many satellites as possible. We will have more spectra than Spilker et al. had for their work at a higher spectral resolution than in the analyses of Carvano et al. and Morishima et al. A preliminary analysis of these

  18. Online Visualization and Analysis of Merged Global Geostationary Satellite Infrared Dataset

    Science.gov (United States)

    Liu, Z.; Ostrenga, D.; Leptoukh, G.; Mehta, A.

    2008-12-01

    The NASA Goddard Earth Sciences Data Information Services Center (GES DISC) is home of Tropical Rainfall Measuring Mission (TRMM) data archive. The global merged IR product, also known as, the NCEP/CPC 4-km Global (60°N - 60°S) IR Dataset, is one of TRMM ancillary datasets. They are globally-merged (60°N-60°S) pixel-resolution (4 km) IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 & GMS). The availability of data from METEOSAT-5, which is located at 63E at the present time, yields a unique opportunity for total global (60°N-60°S) coverage. The GES DISC has collected over 8 years of the data beginning from February of 2000. This high temporal resolution dataset can not only provide additional background information to TRMM and other satellite missions, but also allow observing a wide range of meteorological phenomena from space, such as, mesoscale convection system, tropical cyclones, hurricanes, etc. The dataset can also be used to verify model simulations. Despite that the data can be downloaded via ftp, however, its large volume poses a challenge for many users. A single file occupies about 70 MB disk space and there is a total of ~73,000 files (~4.5 TB) for the past 8 years. Because there is a lack of data subsetting service, one has to download the entire file, which could be time consuming and require a lot of disk space. In order to facilitate data access, we have developed a web prototype, the Global Image ViewER (GIVER), to allow users to conduct online visualization and analysis of this dataset. With a web browser and few mouse clicks, users can have a full access to over 8 year and over 4.5 TB data and generate black and white IR imagery and animation without downloading any software and data. Basic functions include selection of area of interest, single imagery or animation, a time skip capability for different temporal resolution and image size. Users

  19. An Autonomous System to Take Angular Thermal-Infrared Measurements for Validating Satellite Products

    Directory of Open Access Journals (Sweden)

    Raquel Niclòs

    2015-11-01

    Full Text Available An autonomous system for field land surface temperature (LST measurements taken at different observation angles was developed to be deployed easily at any conventional meteorological tower station. The system permits ground-truth data to be acquired on a continuous basis, and angularly scans land and sky hemispheres with a single thermal-infrared (TIR radiometer. This paper describes the autonomous angular system and the methodology to assess ground-truth LST and relative-to-nadir emissivity data from system measurements. Ground-truth LSTs were used to validate satellite-retrieved LST products at two experimental sites (rice crop and shrubland areas. The relative-to-nadir emissivity values were used to analyze the anisotropy of surface emissive properties over thermally-homogeneous covers. The EOS-MODIS MOD11_L2/MYD11_L2 LST product was evaluated and shown to work within expected uncertainties (<2.0 K when tested against the system data. A slight underestimation of around −0.15 K was observed, which became greater for the off-nadir observation angles at the shrubland site. The system took angular measurements for the different seasonal homogeneous covers at the rice crop site. These measurements showed emissivity angular anisotropies, which were in good agreement with previously published data. The dual-view ENVISAT-AATSR data reproduced them, and revealed that the system data collected for thermally-homogeneous surfaces could be used to test future satellite TIR sensors with multi-angular or bi-angular capabilities, like the forthcoming SLSTR on board Copernicus Sentinel-3A.

  20. Comparison of Two Methodologies for Calibrating Satellite Instruments in the Visible and Near-Infrared

    Science.gov (United States)

    Barnes, Robert A.; Brown, Steven W.; Lykke, Keith R.; Guenther, Bruce; Butler, James J.; Schwarting, Thomas; Turpie, Kevin; Moyer, David; DeLuccia, Frank; Moeller, Christopher

    2015-01-01

    Traditionally, satellite instruments that measure Earth-reflected solar radiation in the visible and near infrared wavelength regions have been calibrated for radiance responsivity in a two-step method. In the first step, the relative spectral response (RSR) of the instrument is determined using a nearly monochromatic light source such as a lamp-illuminated monochromator. These sources do not typically fill the field-of-view of the instrument nor act as calibrated sources of light. Consequently, they only provide a relative (not absolute) spectral response for the instrument. In the second step, the instrument views a calibrated source of broadband light, such as a lamp-illuminated integrating sphere. The RSR and the sphere absolute spectral radiance are combined to determine the absolute spectral radiance responsivity (ASR) of the instrument. More recently, a full-aperture absolute calibration approach using widely tunable monochromatic lasers has been developed. Using these sources, the ASR of an instrument can be determined in a single step on a wavelength-by-wavelength basis. From these monochromatic ASRs, the responses of the instrument bands to broadband radiance sources can be calculated directly, eliminating the need for calibrated broadband light sources such as lamp-illuminated integrating spheres. In this work, the traditional broadband source-based calibration of the Suomi National Preparatory Project (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) sensor is compared with the laser-based calibration of the sensor. Finally, the impact of the new full-aperture laser-based calibration approach on the on-orbit performance of the sensor is considered.

  1. Application of satellite infrared data for mapping of thermal plume contamination in coastal ecosystem of Korea.

    Science.gov (United States)

    Ahn, Yu-Hwan; Shanmugam, Palanisamy; Lee, Jae-Hak; Kang, Yong Q

    2006-03-01

    The 5900 MW Younggwang nuclear power station on the west coast of Korea discharges warm water affecting coastal ecology [KORDI report (2003). Wide area observation of the impact of the operation of Younggwang nuclear power plant 5 and 6, No. BSPI 319-00-1426-3, KORDI, Seoul, Korea]. Here the spatial and temporal characteristics of the thermal plume signature of warm water are reported from a time series (1985-2003) of space-borne, thermal infrared data from Landsat and National Oceanic and Atmospheric Administration (NOAA) satellites. Sea surface temperature (SST) were characterized using advanced very high resolution radiometer data from the NOAA satellites. These data demonstrated the general pattern and extension of the thermal plume signature in the Younggwang coastal areas. In contrast, the analysis of SST from thematic mapper data using the Landsat-5 and 7 satellites provided enhanced information about the plume shape, dimension and direction of dispersion in these waters. The thermal plume signature was detected from 70 to 100 km to the south of the discharge during the summer monsoon and 50 to 70 km to the northwest during the winter monsoon. The mean detected plume temperature was 28 degrees C in summer and 12 degrees C in winter. The DeltaT varied from 2 to 4 degrees C in winter and 2 degrees C in summer. These values are lower than the re-circulating water temperature (6-9 degrees C). In addition the temperature difference between tidal flats and offshore (SSTtidal flats - SSToffsore) was found to vary from 5.4 to 8.5 degrees C during the flood tides and 3.5 degrees C during the ebb tide. The data also suggest that water heated by direct solar radiation on the tidal flats during the flood tides might have been transported offshore during the ebb tide. Based on these results we suggest that there is an urgent need to protect the health of Younggwang coastal marine ecosystem from the severe thermal impact by the large quantity of warm water discharged from

  2. Atmospheric influences on infrared-laser signals used for occultation measurements between Low Earth Orbit satellites

    Directory of Open Access Journals (Sweden)

    S. Schweitzer

    2011-10-01

    Full Text Available LEO-LEO infrared-laser occultation (LIO is a new occultation technique between Low Earth Orbit (LEO satellites, which applies signals in the short wave infrared spectral range (SWIR within 2 μm to 2.5 μm. It is part of the LEO-LEO microwave and infrared-laser occultation (LMIO method that enables to retrieve thermodynamic profiles (pressure, temperature, humidity and altitude levels from microwave signals and profiles of greenhouse gases and further variables such as line-of-sight wind speed from simultaneously measured LIO signals. Due to the novelty of the LMIO method, detailed knowledge of atmospheric influences on LIO signals and of their suitability for accurate trace species retrieval did not yet exist. Here we discuss these influences, assessing effects from refraction, trace species absorption, aerosol extinction and Rayleigh scattering in detail, and addressing clouds, turbulence, wind, scattered solar radiation and terrestrial thermal radiation as well. We show that the influence of refractive defocusing, foreign species absorption, aerosols and turbulence is observable, but can be rendered small to negligible by use of the differential transmission principle with a close frequency spacing of LIO absorption and reference signals within 0.5%. The influences of Rayleigh scattering and terrestrial thermal radiation are found negligible. Cloud-scattered solar radiation can be observable under bright-day conditions, but this influence can be made negligible by a close time spacing (within 5 ms of interleaved laser-pulse and background signals. Cloud extinction loss generally blocks SWIR signals, except very thin or sub-visible cirrus clouds, which can be addressed by retrieving a cloud layering profile and exploiting it in the trace species retrieval. Wind can have a small influence on the trace species absorption, which can be made negligible by using a simultaneously retrieved or a moderately accurate background wind speed profile. We

  3. Ozone Profile Retrieval from Satellite Observation Using High Spectral Resolution Infrared Sounding Instrument

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents a preliminary result on the retrieval of atmospheric ozone profiles using an im proved regression technique and utilizing the data from the Atmospheric InfraRed Sounder (AIRS), a hyper-spectral instrument expected to be flown on the EOS-AQUA platform in 2002. Simulated AIRS spectra were used to study the sensitivity of AIRS radiance on the tropospheric and stratospheric ozone changes, and to study the impact of various channel combinations on the ozone profile retrieval. Sensitivity study results indicate that the AIRS high resolution spectral channels between the wavenumber 650- 800 cm-1 provide very useful information to accurately retrieve tropospheric and stratospheric ozone pro files. Eigenvector decomposition of AIRS spectra indicate that no more than 100 eigenvectors are needed to retrieve very accurate ozone profiles. The accuracy of the retrieved atmospheric ozone profile from the pres ent technique and utilizing the AIRS data was compared with the accuracy obtained from current Advanced TIROS Operational Vertical Sounder (ATOVS) data aboard National Oceanic and Atmospheric Admini stration (NOAA) satellites. As expected, a comparison of retrieval results confirms that the ozone profile re trieved with the AIRS data is superior to that of ATOVS.

  4. Use of Real Time Satellite Infrared and Ocean Color to Produce Ocean Products

    Science.gov (United States)

    Roffer, M. A.; Muller-Karger, F. E.; Westhaver, D.; Gawlikowski, G.; Upton, M.; Hall, C.

    2014-12-01

    Real-time data products derived from infrared and ocean color satellites are useful for several types of users around the world. Highly relevant applications include recreational and commercial fisheries, commercial towing vessel and other maritime and navigation operations, and other scientific and applied marine research. Uses of the data include developing sampling strategies for research programs, tracking of water masses and ocean fronts, optimizing ship routes, evaluating water quality conditions (coastal, estuarine, oceanic), and developing fisheries and essential fish habitat indices. Important considerations for users are data access and delivery mechanisms, and data formats. At this time, the data are being generated in formats increasingly available on mobile computing platforms, and are delivered through popular interfaces including social media (Facebook, Linkedin, Twitter and others), Google Earth and other online Geographical Information Systems, or are simply distributed via subscription by email. We review 30 years of applications and describe how we develop customized products and delivery mechanisms working directly with users. We review benefits and issues of access to government databases (NOAA, NASA, ESA), standard data products, and the conversion to tailored products for our users. We discuss advantages of different product formats and of the platforms used to display and to manipulate the data.

  5. A method for retrieving clouds with satellite infrared radiances using the particle filter

    Science.gov (United States)

    Xu, Dongmei; Auligné, Thomas; Descombes, Gaël; Snyder, Chris

    2016-11-01

    Ensemble-based techniques have been widely utilized in estimating uncertainties in various problems of interest in geophysical applications. A new cloud retrieval method is proposed based on the particle filter (PF) by using ensembles of cloud information in the framework of Gridpoint Statistical Interpolation (GSI) system. The PF cloud retrieval method is compared with the Multivariate Minimum Residual (MMR) method that was previously established and verified. Cloud retrieval experiments involving a variety of cloudy types are conducted with the PF and MMR methods with measurements of infrared radiances on multi-sensors onboard both geostationary and polar satellites, respectively. It is found that the retrieved cloud masks with both methods are consistent with other independent cloud products. MMR is prone to producing ambiguous small-fraction clouds, while PF detects clearer cloud signals, yielding closer heights of cloud top and cloud base to other references. More collections of small-fraction particles are able to effectively estimate the semi-transparent high clouds. It is found that radiances with high spectral resolutions contribute to quantitative cloud top and cloud base retrievals. In addition, a different way of resolving the filtering problem over each model grid is tested to better aggregate the weights with all available sensors considered, which is proven to be less constrained by the ordering of sensors. Compared to the MMR method, the PF method is overall more computationally efficient, and the cost of the model grid-based PF method scales more directly with the number of computing nodes.

  6. The Critical Need for Future Mid-Resolution Thermal Infrared Satellite Sensors

    Science.gov (United States)

    Vincent, R. K.

    2006-12-01

    Eight future applications of data from mid-resolution thermal infrared satellite sensors are suggested, from least to most significant as follows: 8. Map thin ice unsafe for ice-fishing in the Great Lakes as a warning to winter fishermen; 7. Map ammonia plumes to locate large ammonia stockpiles (Homeland Security) and to monitor concentrated animal feeding operations (CAFOs); 6. Map types of surface algae in ocean, lakes, and rivers, especially those containing surface diatoms; 5. Monitor urban heat islands to determine the cooling affects of painting visibly dark surfaces with bright paints or coatings; 4. Map rock-types and soil-types of non- vegetated regions world-wide, a task which ASTER cannot complete in its current lifetime; 3. Detect surface warming of rocks under increased stress and pressure as an earthquake precursor; 2. Map pollutant gases, especially sulfur dioxide, which is important both for smokestack monitoring and volcanic eruption precursors; 1. Map methane escape into the atmosphere from methane clathrate destabilization as a key warning of imminent and drastic temperature rises in the troposphere. Each of these applications will be briefly discussed and past examples will be given for most of them.

  7. 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.

  8. Application of ATOVS Microwave Radiance Assimilation to Rainfall Prediction in Summer 2004

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Experiments are performed in this paper to understand the influence of satellite radiance data on the initial field of a numerical prediction system and rainfall prediction. First, Advanced Microwave Sounder Unit A (AMSU-A) and Unit B (AMSU-B) radiance data are directly used by three-dimensional variational data assimilation to improve the background field of the numerical model. Then, the detailed effect of the radiance data on the background field is analyzed. Secondly, the background field, which is formed by application of Advanced Television and Infrared Observation Satellite Operational Vertical Sounder (ATOVS) microwave radiance assimilation, is employed to simulate some heavy rainfall cases.The experiment results show that the assimilation of AMSU-A (B) microwave radiance data has a certain impact on the geopotential height, temperature, relative humidity and flow fields. And the impacts on the background field are mostly similar in the different months in summer. The heavy rainfall experiments reveal that the application of AMSU-A (B) microwave radiance data can improve the rainfall prediction significantly. In particular, the AMSU-A radiance data can significantly enhance the prediction of rainfall above 10 mm within 48 h, and the AMSU-B radiance data can improve the prediction of rainfall above 50 mm within 24 h. The present study confirms that the direct assimilation of satellite radiance data is an effective way to improve the prediction of heavy rainfall in the summer in China.

  9. 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.

  10. Maximizing the Use of Satellite Thermal Infrared Data for Advancing Land Surface Temperature Analysis

    Science.gov (United States)

    Weng, Q.; Fu, P.; Gao, F.

    2014-12-01

    Land surface temperature (LST) is a crucial parameter in investigating environmental, ecological processes and climate change at various scales, and is also valuable in the studies of evapotranspiration, soil moisture conditions, surface energy balance, and urban heat islands. These studies require thermal infrared (TIR) images at both high temporal and spatial resolution to retrieve LST. However, currently, no single satellite sensors can deliver TIR data at both high temporal and spatial resolution. Thus, various algorithms/models have been developed to enhance the spatial or the temporal resolution of TIR data, but rare of those can enhance both spatial and temporal details. This paper presents a new data fusion algorithm for producing Landsat-like LST data by blending daily MODIS and periodic Landsat TM datasets. The original Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was improved and modified for predicting thermal radiance and LST data by considering annual temperature cycle (ATC) and urban thermal landscape heterogeneity. The technique of linear spectral mixture analysis was employed to relate the Landsat radiance with the MODIS one, so that the temporal changes in radiance can be incorporated in the fusion model. This paper details the theoretical basis and the implementation procedures of the proposed data fusion algorithm, Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT). A case study was conducted that predicted LSTs of five dates in 2005 from July to October in Los Angeles County, California. The results indicate that the prediction accuracy for the whole study area ranged from 1.3 K to 2 K. Like existing spatio-temporal data fusion models, the SADFAT method has a limitation in predicting LST changes that were not recorded in the MODIS and/or Landsat pixels due to the model assumption.

  11. All sky imaging observations in visible and infrared waveband for validation of satellite cloud and aerosol products

    Science.gov (United States)

    Lu, Daren; Huo, Juan; Zhang, W.; Liu, J.

    A series of satellite sensors in visible and infrared wavelengths have been successfully operated on board a number of research satellites, e.g. NOAA/AVHRR, the MODIS onboard Terra and Aqua, etc. A number of cloud and aerosol products are produced and released in recent years. However, the validation of the product quality and accuracy are still a challenge to the atmospheric remote sensing community. In this paper, we suggest a ground based validation scheme for satellite-derived cloud and aerosol products by using combined visible and thermal infrared all sky imaging observations as well as surface meteorological observations. In the scheme, a visible digital camera with a fish-eye lens is used to continuously monitor the all sky with the view angle greater than 180 deg. The digital camera system is calibrated for both its geometry and radiance (broad blue, green, and red band) so as to a retrieval method can be used to detect the clear and cloudy sky spatial distribution and their temporal variations. A calibrated scanning thermal infrared thermometer is used to monitor the all sky brightness temperature distribution. An algorithm is developed to detect the clear and cloudy sky as well as cloud base height by using sky brightness distribution and surface temperature and humidity as input. Based on these composite retrieval of clear and cloudy sky distribution, it can be used to validate the satellite retrievals in the sense of real-simultaneous comparison and statistics, respectively. What will be presented in this talk include the results of the field observations and comparisons completed in Beijing (40 deg N, 116.5 deg E) in year 2003 and 2004. This work is supported by NSFC grant No. 4002700, and MOST grant No 2001CCA02200

  12. Detection of supercooled liquid water-topped mixed-phase clouds >from shortwave-infrared satellite observations

    Science.gov (United States)

    NOH, Y. J.; Miller, S. D.; Heidinger, A. K.

    2015-12-01

    Many studies have demonstrated the utility of multispectral information from satellite passive radiometers for detecting and retrieving the properties of cloud globally, which conventionally utilizes shortwave- and thermal-infrared bands. However, the satellite-derived cloud information comes mainly from cloud top or represents a vertically integrated property. This can produce a large bias in determining cloud phase characteristics, in particular for mixed-phase clouds which are often observed to have supercooled liquid water at cloud top but a predominantly ice phase residing below. The current satellite retrieval algorithms may report these clouds simply as supercooled liquid without any further information regarding the presence of a sub-cloud-top ice phase. More accurate characterization of these clouds is very important for climate models and aviation applications. In this study, we present a physical basis and preliminary results for the algorithm development of supercooled liquid-topped mixed-phase cloud detection using satellite radiometer observations. The detection algorithm is based on differential absorption properties between liquid and ice particles in the shortwave-infrared bands. Solar reflectance data in narrow bands at 1.6 μm and 2.25 μm are used to optically probe below clouds for distinction between supercooled liquid-topped clouds with and without an underlying mixed phase component. Varying solar/sensor geometry and cloud optical properties are also considered. The spectral band combination utilized for the algorithm is currently available on Suomi NPP Visible/Infrared Imaging Radiometer Suite (VIIRS), Himawari-8 Advanced Himawari Imager (AHI), and the future GOES-R Advance Baseline Imager (ABI). When tested on simulated cloud fields from WRF model and synthetic ABI data, favorable results were shown with reasonable threat scores (0.6-0.8) and false alarm rates (0.1-0.2). An ARM/NSA case study applied to VIIRS data also indicated promising

  13. Atmospheric influences on infrared-laser signals used for occultation measurements between Low Earth Orbit satellites

    Directory of Open Access Journals (Sweden)

    S. Schweitzer

    2011-05-01

    Full Text Available LEO-LEO infrared-laser occultation (LIO is a new occultation technique between Low Earth Orbit (LEO satellites, which applies signals in the short wave infrared spectral range (SWIR within 2 μm to 2.5 μm. It is part of the LEO-LEO microwave and infrared-laser occultation (LMIO method, recently introduced by Kirchengast and Schweitzer (2011, that enables to retrieve thermodynamic profiles (pressure, temperature, humidity and accurate altitude levels from microwave signals and profiles of greenhouse gases and further variables such as line-of-sight wind speed from simultaneously measured LIO signals. For enabling trace species retrieval based on differential transmission, the LIO signals are spectrally located as pairs, one in the centre of a suitable absorption line of a target species (absorption signal and one close by but outside of any absorption lines (reference signal. Due to the novelty of the LMIO method, detailed knowledge of atmospheric influences on LIO signals and of their suitability for accurate trace species retrieval did not yet exist. Here we discuss the atmospheric influences on the transmission and differential transmission of LIO signals. Refraction effects, trace species absorption (by target species, and cross-sensitivity to foreign species, aerosol extinction and Rayleigh scattering are studied in detail. The influences of clouds, turbulence, wind, scattered solar radiation and terrestrial thermal radiation are discussed as well. We show that the influence of defocusing, foreign species absorption, aerosols and turbulence is observable, but can be rendered small to negligible by use of the differential transmission principle and by a design with close frequency spacing of absorption and reference signals within 0.5 %. The influences of Rayleigh scattering and thermal radiation on the received signal intensities are found negligible. Cloud-scattered solar radiation can be observable under bright-day conditions but this

  14. A diagnosis of rainfall over South America during 1997/98 El Niño and 1998/99 La Niña events: Comparison between TRMM PR and GPCP rainfall estimates

    Indian Academy of Sciences (India)

    Sergio H Franchito; V Brahmananda Rao; Ana C Vasques; Clovis M E Santo; Jorge C Conforte

    2009-06-01

    A comparison between TRMM PR rainfall estimates and rain gauge data from ANEEL and combined gauge/satellite data from GPCP over South America (SA)is made.In general,the annual and seasonal regional characteristics of rainfall over SA are qualitatively well reproduced by TRMM PR and GPCP.It is found that over most of SA GPCP exceeds TRMM PR rainfall.The largest positive differences between GPCP and TRMM PR data occur in the north SA,northwestern and central Amazonia.However,there are regions where GPCP rainfall is lower than TRMM PR,particularly in the Pacific coastal regions and in southern Brazil.We suggest that the cause for the positive differences GPCP minus TRMM PR rainfall are related to the fact that satellite observations based on infrared radiation and outgoing longwave radiance sensors overestimate convective rainfall in GPCP and the cause for the negative differences are due to the random errors in TRMM PR.Rainfall differences in the latter phases of the 1997/98 El Niño and 1998/99 La Niña are analyzed.The results showed that the rainfall anomalies are generally higher in GPCP than in TRMM PR,however,as in the mean annual case,there are regions where the rainfall in GPCP is lower than in TRMM PR.The higher positive (negative)differences between the rainfall anomalies in GPCP and TRMM PR,which occur in the central Amazonia (southern Brazil),are reduced (increased) in the El Niño event.This is due to the fact that during the El Niño episode the rainfall decreases in the central Amazonia and increases in the southern Brazil.Consequently,the overestimation of the convective rainfall by GPCP is reduced and the overestimation of the rainfall by TRMM PR is increased in these two regions,respectively.

  15. Satellite Thermal Infrared Earthquake Precursor to the Wenchuan Ms 8.0 Earthquake in Sichuan, China, and its Analysis on Geo-dynamics

    Institute of Scientific and Technical Information of China (English)

    WEI Lejun; GUO Jianfeng; LIU Jianhua; LU Zhenquan; LI Haibing; CAI Hui

    2009-01-01

    Based on an interpretation and study of the satellite remote-sensing images of FY-2C thermal infrared 1st wave band (10.3-11.3 μm) designed in China, the authors found that there existed obvious and isolated satellite thermal infrared anomalies before the 5.12 Wenchuan Ms 8.0 Earthquake. These anomalies had the following characteristics: (1) The precursor appeared rather early: on March 18, 2008, I.e., 55 days before the earthquake, thermal infrared anomalies began to occur; (2) The anomalies experienced quite many and complex evolutionary stages: the satellite thermal infrared anomalies might be divided into five stages, whose manifestations were somewhat different from each other. The existence of so many anomaly stages was probably observed for the first time in numerous cases of satellite thermal infrared research on earthquakes; (3) Each stage lasted quite a long time, with the longest one spanning 13 days; (4) An evident geothermal anomaly gradient was distributed along the Longmen seismic fracture zone, and such a phenomenon might also be discovered for the first time in satellite thermal infrared earthquake research. This discovery is therefore of great guiding and instructive significance in the study of the earthquake occurrence itself and the trend of the post-earthquake phenomena.

  16. Advancing satellite-based solar power forecasting through integration of infrared channels for automatic detection of coastal marine inversion layer

    Energy Technology Data Exchange (ETDEWEB)

    Kostylev, Vladimir; Kostylev, Andrey; Carter, Chris; Mahoney, Chad; Pavlovski, Alexandre; Daye, Tony [Green Power Labs Inc., Dartmouth, NS (Canada); Cormier, Dallas Eugene; Fotland, Lena [San Diego Gas and Electric Co., San Diego, CA (United States)

    2012-07-01

    The marine atmospheric boundary layer is a layer or cool, moist maritime air with the thickness of a few thousand feet immediately below a temperature inversion. In coastal areas as moist air rises from the ocean surface, it becomes trapped and is often compressed into fog above which a layer of stratus clouds often forms. This phenomenon is common for satellite-based solar radiation monitoring and forecasting. Hour ahead satellite-based solar radiation forecasts are commonly using visible spectrum satellite images, from which it is difficult to automatically differentiate low stratus clouds and fog from high altitude clouds. This provides a challenge for cloud motion tyracking and cloud cover forecasting. San Diego Gas and Electric {sup registered} (SDG and E {sup registered}) Marine Layer Project was undertaken to obtain information for integration with PV forecasts, and to develop a detailed understanding of long-term benefits from forecasting Marine Layer (ML) events and their effects on PV production. In order to establish climatological ML patterns, spatial extent and distribution of marine layer, we analyzed visible and IR spectrum satellite images (GOES WEST) archive for the period of eleven years (2000 - 2010). Historical boundaries of marine layers impact were established based on the cross-classification of visible spectrum (VIS) and infrared (IR) images. This approach is successfully used by us and elsewhere for evaluating cloud albedo in common satellite-based techniques for solar radiation monitoring and forecasting. The approach allows differentiation of cloud cover and helps distinguish low laying fog which is the main consequence of marine layer formation. ML occurrence probability and maximum extent inland was established for each hour and day of the analyzed period and seasonal/patterns were described. SDG and E service area is the most affected region by ML events with highest extent and probability of ML occurrence. Influence of ML was the

  17. Design of a nano-satellite demonstrator of an infrared imaging space interferometer: the HyperCube

    Science.gov (United States)

    Dohlen, Kjetil; Vives, Sébastien; Rakotonimbahy, Eddy; Sarkar, Tanmoy; Tasnim Ava, Tanzila; Baccichet, Nicola; Savini, Giorgio; Swinyard, Bruce

    2014-07-01

    The construction of a kilometer-baseline far infrared imaging interferometer is one of the big instrumental challenges for astronomical instrumentation in the coming decades. Recent proposals such as FIRI, SPIRIT, and PFI illustrate both science cases, from exo-planetary science to study of interstellar media and cosmology, and ideas for construction of such instruments, both in space and on the ground. An interesting option for an imaging multi-aperture interferometer with km baseline is the space-based hyper telescope (HT) where a giant, sparsely populated primary mirror is constituted of several free-flying satellites each carrying a mirror segment. All the segments point the same object and direct their part of the pupil towards a common focus where another satellite, containing recombiner optics and a detector unit, is located. In Labeyrie's [1] original HT concept, perfect phasing of all the segments was assumed, allowing snap-shot imaging within a reduced field of view and coronagraphic extinction of the star. However, for a general purpose observatory, image reconstruction using closure phase a posteriori image reconstruction is possible as long as the pupil is fully non-redundant. Such reconstruction allows for much reduced alignment tolerances, since optical path length control is only required to within several tens of wavelengths, rather than within a fraction of a wavelength. In this paper we present preliminary studies for such an instrument and plans for building a miniature version to be flown on a nano satellite. A design for recombiner optics is proposed, including a scheme for exit pupil re-organization, is proposed, indicating the focal plane satellite in the case of a km-baseline interferometer could be contained within a 1m3 unit. Different options for realization of a miniature version are presented, including instruments for solar observations in the visible and the thermal infrared and giant planet observations in the visible, and an

  18. Increasing spatial resolution of CHIRPS rainfall datasets for Cyprus with Artificial Neural Networks (ANN)

    Science.gov (United States)

    Tymvios, Filippos; Michaelides, Silas; Retalis, Adrianos; Katsanos, Dimitrios; Lelieveld, Jos

    2016-04-01

    The use of high resolution rainfall datasets is an alternative way of studying climatological patterns in regions where conventional rain measurements are sparse or not available. Starting in 1981 to near-present, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) dataset incorporates a 5x5km2 resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis, severe events and seasonal drought monitoring. The aim of this work is to further increase the resolution of this rainfall dataset for Cyprus to 1x1km2 by correlating the CHIRPS dataset with altitute information, NDVI vegetation index from satellite images at 1x1km2and precipitation measurements from the official raingauge network of the Cyprus Department of Meteorology, utilizing Artificial Neural Network models.

  19. A compact thermal infrared imaging radiometer with high spatial resolution and wide swath for a small satellite using a large format uncooled infrared focal plane array

    Science.gov (United States)

    Tatsumi, Kenji; Sakuma, Fumihiro; Kikuchi, Masakuni; Tanii, Jun; Kawanishi, Toneo; Ueno, Shinichi; Kuga, Hideki

    2014-10-01

    In this paper, we present a feasibility study for the potential of a high spatial resolution and wide swath thermal infrared (TIR) imaging radiometer for a small satellite using a large format uncooled infrared focal plane array (IR-FPA). The preliminary TIR imaging radiometer designs were performed. One is a panchromatic (mono-band) imaging radiometer (8-12μm) with a large format 2000 x 1000 pixels uncooled IR-FPA with a pixel pitch of 15 μm. The other is a multiband imaging radiometer (8.8μm, 10.8μm, 11.4μm). This radiometer is employed separate optics and detectors for each wave band. It is based on the use of a 640 x 480 pixels uncooled IR-FPA with a pixel pitch of 25 μm. The thermal time constant of an uncooled IR-FPA is approximately 10-16ms, and introduces a constraint to the satellite operation to achieve better signal-to-noise ratio, MTF and linearity performances. The study addressed both on-ground time-delayintegration binning and staring imaging solutions, although a staring imaging was preferred after trade-off. The staring imaging requires that the line of sight of the TIR imaging radiometer gazes at a target area during the acquisition time of the image, which can be obtained by rotating the satellite or a steering mirror around the pitch axis. The single band radiometer has been designed to yield a 30m ground sample distance over a 30km swath width from a satellite altitude of 500km. The radiometric performance, enhanced with staring imaging, is expected to yield a NETD less than 0.5K for a 300K ground scene. The multi-band radiometer has three spectral bands with spatial resolution of 50m and swath width of 24km. The radiometric performance is expected to yield a NETD less than 0.85K. We also showed some preliminary simulation results on volcano, desert/urban scenes, and wildfire.

  20. 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.

  1. THE APPLICATION OF HOMEMADE FY-2 SATELLITE INFRARED DATA TO MM5

    Institute of Scientific and Technical Information of China (English)

    LIU Qing; SHEN Tong-li

    2006-01-01

    @@ 1 INTRODUCTION In the end of 1980's, an operational system for 3-D variation and assimilation of meteorological data was set up in the U.S.A that supplemented data assimilation,retrieval of satellite data and numerical prediction each other. NWP was thus improved. Towards the end of 1990's, satellite observations were extensively used in NWP at ECMWF to upgrade the quality of analysis and forecasting.

  2. 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.

  3. TIRCIS: Hyperspectral Thermal Infrared Imaging Using a Small-Satellite Compliant Fourier-Transform Imaging Spectrometer, for Natural Hazard Applications

    Science.gov (United States)

    Wright, R.; Lucey, P. G.; Crites, S.; Garbeil, H.; Wood, M.

    2015-12-01

    Many natural hazards, including wildfires, volcanic eruptions, and, from the perspective of climate-related hazards, urban heat islands, could be better quantified via the routine availability of hyperspectral thermal infrared remote sensing data from orbit. However, no sensors are currently in operation that provide such data at high-to-moderate spatial resolution (e.g. Landsat-class resolution). In this presentation we will describe a prototype instrument, developed using funding provided by NASA's Instrument Incubator Program, that can make these important measurements. Significantly, the instrument has been designed such that its size, mass, power, and cost are consistent with its integration into small satellite platforms, or deployment as part of small satellite constellations. The instrument, TIRCIS (Thermal Infra-Red Compact Imaging Spectrometer), uses a Fabry-Perot interferometer, an uncooled microbolometer array, and push-broom scanning to acquire hyperspectral image data cubes. Radiometric calibration is provided by blackbody targets while spectral calibration is achieved using monochromatic light sources. Neither the focal plane nor the optics need to be cooled, and the instrument has a mass of <10 kg and dimensions of 53 cm × 25 cm × 22 cm. Although the prototype has four moving parts, this can easily be reduced to one. The current optical design yields a 120 m ground sample size given an orbit of 500 km. Over the wavelength interval of 7.5 to 14 microns up to 90 spectral samples are possible, by varying the physical design of the interferometer. Our performance model indicates signal-to-noise ratios of the order of about 200 to 300:1. In this presentation we will provide an overview of the instrument design, fabrication, results from our initial laboratory characterization, and some of the application areas in which small-satellite-ready instruments such as TIRCIS could make a valuable contribution to the study of natural hazards.

  4. Identification of dust outbreaks on infrared MSG-SEVIRI data by using a Robust Satellite Technique (RST)

    Science.gov (United States)

    Sannazzaro, Filomena; Filizzola, Carolina; Marchese, Francesco; Corrado, Rosita; Paciello, Rossana; Mazzeo, Giuseppe; Pergola, Nicola; Tramutoli, Valerio

    2014-01-01

    Dust storms are meteorological phenomena of great interest for scientific community because of their potential impact on climate changes, for the risk that may pose to human health and due to other issues as desertification processes and reduction of the agricultural production. Satellite remote sensing, thanks to global coverage, high frequency of observation and low cost data, may highly contribute in monitoring these phenomena, provided that proper detection methods are used. In this work, the known Robust Satellite Techniques (RST) multitemporal approach, used for studying and monitoring several natural/environmental hazards, is tested on some important dust events affecting Mediterranean region in May 2004 and Arabian Peninsula in February 2008. To perform this study, data provided by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) have been processed, comparing the generated dust maps to some independent satellite-based aerosol products. Outcomes of this work show that the RST technique can be profitably used for detecting dust outbreaks from space, providing information also about areas characterized by a different probability of dust presence. They encourage further improvements of this technique in view of its possible implementation in the framework of operational warning systems.

  5. Provisional maps of thermal areas in Yellowstone National Park, based on satellite thermal infrared imaging and field observations

    Science.gov (United States)

    Vaughan, R. Greg; Heasler, Henry; Jaworowski, Cheryl; Lowenstern, Jacob B.; Keszthelyi, Laszlo P.

    2014-01-01

    Maps that define the current distribution of geothermally heated ground are useful toward setting a baseline for thermal activity to better detect and understand future anomalous hydrothermal and (or) volcanic activity. Monitoring changes in the dynamic thermal areas also supports decisions regarding the development of Yellowstone National Park infrastructure, preservation and protection of park resources, and ensuring visitor safety. Because of the challenges associated with field-based monitoring of a large, complex geothermal system that is spread out over a large and remote area, satellite-based thermal infrared images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to map the location and spatial extent of active thermal areas, to generate thermal anomaly maps, and to quantify the radiative component of the total geothermal heat flux. ASTER thermal infrared data acquired during winter nights were used to minimize the contribution of solar heating of the surface. The ASTER thermal infrared mapping results were compared to maps of thermal areas based on field investigations and high-resolution aerial photos. Field validation of the ASTER thermal mapping is an ongoing task. The purpose of this report is to make available ASTER-based maps of Yellowstone’s thermal areas. We include an appendix containing the names and characteristics of Yellowstone’s thermal areas, georeferenced TIFF files containing ASTER thermal imagery, and several spatial data sets in Esri shapefile format.

  6. Near-infrared spectrophotometry of the satellites and rings of Uranus

    Science.gov (United States)

    Soifer, B. T.; Neugebauer, G.; Matthews, K.

    1981-01-01

    New spectrophotometry from 1.5 to 2.5 microns is reported for the Uranian satellites Titania, Oberon, and Umbriel. A spectrum of the rings of Uranus from 2.0 to 2.4 microns is also reported. No evidence is found for frost covering the surface of the ring material, consistent with the low albedo of the rings previously reported by Nicholson and Jones (1980). The surfaces of the satellites are found to be covered by dirty water frost. Assuming albedos of the frost and gray components covering the Uranian satellites to be the same as the light and dark faces of Iapetus, radii are derived that are roughly twice those inferred from the assumption of a visual albedo of 0.5.

  7. 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...

  8. USING OF THE MULTITEMPORAL THERMAL INFRARED SATELLITE IMAGERY FOR NATURAL AREAS MAPPING (CASE OF MENDELEEV VOLCANO

    Directory of Open Access Journals (Sweden)

    M. Y. Grishchenko

    2014-01-01

    Full Text Available In the paper authors examine the mountain group of Mendeleev volcano situated on the Kunashir island, Kuril archipelago, Russia. Ground observations were led to examine the vegetation cover of the area as well as its typical landscapes. The other type of used data is Landsat imagery. Images were combined into multitemporal thermal infrared and multispectral pictures, which were classified to reveal the heterogeneity of the study area. Ground observations and comparison of the classification results with landscape map derive that the multitemporal thermal infrared image classification result describes better the vegetation cover structure of the area and particularity of its typical landscapes distribution. It leads to the proposition that miltitemporal thermal infrared imagery can be used to refine landscape and vegetation cover contours. 

  9. Reconstruction of an infrared band of meteorological satellite imagery with abductive networks

    Science.gov (United States)

    Singer, Harvey A.; Cockayne, John E.; Versteegen, Peter L.

    1995-01-01

    As the current fleet of meteorological satellites age, the accuracy of the imagery sensed on a spectral channel of the image scanning system is continually and progressively degraded by noise. In time, that data may even become unusable. We describe a novel approach to the reconstruction of the noisy satellite imagery according to empirical functional relationships that tie the spectral channels together. Abductive networks are applied to automatically learn the empirical functional relationships between the data sensed on the other spectral channels to calculate the data that should have been sensed on the corrupted channel. Using imagery unaffected by noise, it is demonstrated that abductive networks correctly predict the noise-free observed data.

  10. Satellite-based forest monitoring: spatial and temporal forecast of growing index and short-wave infrared band.

    Science.gov (United States)

    Bayr, Caroline; Gallaun, Heinz; Kleb, Ulrike; Kornberger, Birgit; Steinegger, Martin; Winter, Martin

    2016-04-18

    For detecting anomalies or interventions in the field of forest monitoring we propose an approach based on the spatial and temporal forecast of satellite time series data. For each pixel of the satellite image three different types of forecasts are provided, namely spatial, temporal and combined spatio-temporal forecast. Spatial forecast means that a clustering algorithm is used to group the time series data based on the features normalised difference vegetation index (NDVI) and the short-wave infrared band (SWIR). For estimation of the typical temporal trajectory of the NDVI and SWIR during the vegetation period of each spatial cluster, we apply several methods of functional data analysis including functional principal component analysis, and a novel form of random regression forests with online learning (streaming) capability. The temporal forecast is carried out by means of functional time series analysis and an autoregressive integrated moving average model. The combination of the temporal forecasts, which is based on the past of the considered pixel, and spatial forecasts, which is based on highly correlated pixels within one cluster and their past, is performed by functional data analysis, and a variant of random regression forests adapted to online learning capabilities. For evaluation of the methods, the approaches are applied to a study area in Germany for monitoring forest damages caused by wind-storm, and to a study area in Spain for monitoring forest fires.

  11. An Autonomous System to Take Angular Thermal-Infrared Measurements for Validating Satellite Products

    OpenAIRE

    Raquel Niclòs; José A. Valiente; Maria J. Barberà; César Coll

    2015-01-01

    An autonomous system for field land surface temperature (LST) measurements taken at different observation angles was developed to be deployed easily at any conventional meteorological tower station. The system permits ground-truth data to be acquired on a continuous basis, and angularly scans land and sky hemispheres with a single thermal-infrared (TIR) radiometer. This paper describes the autonomous angular system and the methodology to assess ground-truth LST and relative-to-nadir emissivit...

  12. Specification for an Infrared Satellite Surveillance System for the Detection of Aircraft

    Science.gov (United States)

    1987-11-01

    In the monolithic IRCCD, the infrared sensitive substrate is either e narrow bandgap semiconductor or an extrinsic semiconductor with appropriate...thermally generated to bring the potential well into thermal equilibrium. Clock Feedt.hrough This noise is due to capacitance coupling Noise from the...Noise This noise is associated with a MOSFET of a given transconductance. Detector This noise is variations across the video Uniformity Noise output

  13. Long-Term Record of Arctic and Antarctic Sea and Ice Surface Temperatures from Thermal Infrared Satellite Sensors

    Science.gov (United States)

    Luis, Cristina; Dybkjær, Gorm; Eastwood, Steinar; Tonboe, Rasmus; Høyer, Jacob

    2015-04-01

    Surface temperature is among the most important variables in the surface energy balance equation and it significantly affects the atmospheric boundary layer structure, the turbulent heat exchange and, over ice, the ice growth rate. Here we measure the surface temperature using thermal infrared sensors from 10-12 µm wavelength, a method whose primary limitation over sea ice is the detection of clouds. However, in the Arctic and around Antarctica there are very few conventional observations of surface temperature from buoys, and it is sometimes difficult to determine if the temperature is measured at the surface or within the snowpack, the latter of which often results in a warm bias. To reduce this bias, much interest is being paid to alternative remote sensing methods for monitoring high latitude surface temperature. We used Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data to produce a high latitude sea surface temperature (SST), ice surface temperature (IST) and ice cap skin temperature dataset spanning 27 years (1982-2009). This long-term climate record is the first of its kind for IST. In this project we used brightness temperatures from the infrared channels of AVHRR sensors aboard NOAA and Metop polar-orbiting satellites. Surface temperatures were calculated using separate split window algorithms for day SST, night SST, and IST. The snow surface emissivity across all angles of the swath were simulated specifically for all sensors using an emission model. Additionally, all algorithms were tuned to the Arctic using simulated brightness temperatures from a radiative transfer model with atmospheric profiles and skin temperatures from European Centre for Medium-Range Forecasts (ECMWF) re-analysis data (ERA-Interim). Here we present the results of product quality as compared to in situ measurements from buoys and infrared radiometers, as well as a preliminary analysis of climate trends revealed by the record.

  14. 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

  15. Lava discharge rate estimates from thermal infrared satellite data for Pacaya Volcano during 2004-2010

    Science.gov (United States)

    Morgan, Hilary A.; Harris, Andrew J. L.; Gurioli, Lucia

    2013-08-01

    Pacaya is one of the most active volcanoes in Central America and has produced lava flows frequently since 1961. All effusive activity between 1961 and 2009 was confined by an arcuate collapse scarp surrounding the northern and eastern flanks. However, the recent breaching of this topographic barrier, and the eruption of a large lava flow outside of the main center of activity, have allowed lava to extend into nearby populated areas, indicating the need for assessment and monitoring of lava flow hazards. We investigated whether a commonly used satellite-based model could produce accurate lava discharge rates for the purpose of near-real-time assessment of hazards during future eruptions and to assess the dynamics of this persistently degassing system. The model assumes a linear relationship between active lava flow area and time-averaged discharge rate (TADR) via a simple conversion factor. We calculated the conversion factor via two methods: (1) best-fitting of satellite-derived flow areas to ground-based estimates of lava flow volume, and (2) theoretically via a parameterized model that takes into account the physical properties of the lava. To apply the latter method, we sampled four lava flows and measured density, vesicularity, crystal content, and major element composition. We found the best agreement of conversion factors in the eruption with the most complete satellite coverage, and used data for these flows to define the linear relationship between area and discharge rate. The physical properties of the sampled flows were essentially identical, so that any discrepancy between the two methods of calculating conversion factors must be due to modeling errors or environmental factors unaccounted for by the parameterized model. However, our best-fitting method provides a new means to set the conversion appropriately, and to obtain self-consistent TADRs. We identified two distinct types of effusive activity at Pacaya: Type 1 activity characterized by initially

  16. Geostationary Satellite (GOES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from radiometer instruments on SMS (ATS) and GOES satellites in geostationary orbit. These satellites produced...

  17. Time-resolved visible/near-infrared spectrometric observations of the Galaxy 11 geostationary satellite

    Science.gov (United States)

    Bédard, Donald; Wade, Gregg A.

    2017-01-01

    Time-resolved spectrometric measurements of the Galaxy 11 geostationary satellite were collected on three consecutive nights in July 2014 with the 1.6-m telescope at the Observatoire du Mont-Mégantic in Québec, Canada. Approximately 300 low-resolution spectra (R ≈ 700 , where R = λ / Δλ) of the satellite were collected each night, covering a spectral range between 425 and 850 nm. The two objectives of the experiment were to conduct material-type identification from the spectra and to study how the spectral energy distribution inferred from these measurements varied as the illumination and observation geometry changed on nightly timescales. We present results that indicate the presence of a highly reflective aluminized surface corresponding to the solar concentrator arrays of the Galaxy 11 spacecraft. Although other material types could not be identified using the spectra, the results showed that the spectral energy distribution of the reflected sunlight from the Galaxy 11 spacecraft varied significantly, in a systematic manner, over each night of observation. The variations were quantified using colour indices calculated from the time-resolved spectrometric measurements.

  18. Visible and infrared techniques for flash flood, hydrological, and agricultural applications

    Science.gov (United States)

    Scofield, R. A.

    1981-01-01

    A common requirement of these agriculture, climatology and hydrology fields is the accurate and timely estimation of precipitation. Yet, it is often difficult to obtain such estimates by conventional means. The advent of satellite remote sensing however has opened the possibility of making rain estimates over time and space scale never before available. A computer automated technique that estimates a summertime convective rainfall from the thermal infrared imagery of geosynchronous satellites is reviewed.

  19. Far-infrared photometric observations of the outer planets and satellites with Herschel-PACS

    CERN Document Server

    Müller, T G; Nielbock, M; Moreno, R; Klaas, U; Moór, A; Linz, H; Feuchtgruber, H

    2016-01-01

    We present all Herschel PACS photometer observations of Mars, Saturn, Uranus, Neptune, Callisto, Ganymede, and Titan. All measurements were carefully inspected for quality problems, were reduced in a (semi-)standard way, and were calibrated. The derived flux densities are tied to the standard PACS photometer response calibration, which is based on repeated measurements of five fiducial stars. The overall absolute flux uncertainty is dominated by the estimated 5% model uncertainty of the stellar models in the PACS wavelength range between 60 and 210 micron. A comparison with the corresponding planet and satellite models shows excellent agreement for Uranus, Neptune, and Titan, well within the specified 5%. Callisto is brighter than our model predictions by about 4-8%, Ganymede by about 14-21%. We discuss possible reasons for the model offsets. The measurements of these very bright point-like sources, together with observations of stars and asteroids, show the high reliability of the PACS photometer observation...

  20. Near real-time routine for volcano monitoring using infrared satellite data

    Directory of Open Access Journals (Sweden)

    Claudia Spinetti

    2011-12-01

    Full Text Available An Advanced Very-High-Resolution Radiometer (AVHRR routine for hot-spot detection and effusion rate estimation (AVHotRR using AVHRR infrared space-borne images is presented here for the monitoring of active lava flow. AVHotRR uses directly broadcast National Oceanic and Atmospheric Administration (NOAA-AVHRR remotely sensed data. The 2006 summit eruption of Mount Etna provided the opportunity to test the products generated by AVHotRR for monitoring purposes. Low spatial and high temporal resolution products can also be used as inputs of flow models to drive numerical simulations of lava-flow paths and thus to provide quantitative hazard assessment and volcanic risk mitigation.

  1. Hoar crystal development and disappearance at Dome C, Antarctica: observation by near-infrared photography and passive microwave satellite

    Directory of Open Access Journals (Sweden)

    N. Champollion

    2013-08-01

    Full Text Available Hoar crystals episodically cover the snow surface in Antarctica and affect the roughness and reflective properties of the air–snow interface. However, little is known about their evolution and the processes responsible for their development and disappearance despite a probable influence on the surface mass balance and energy budget. To investigate hoar evolution, we use continuous observations of the surface by in situ near-infrared photography and by passive microwave remote sensing at Dome C in Antarctica. From the photography data, we retrieved a daily indicator of the presence/absence of hoar crystals using a texture analysis algorithm. The analysis of this 2 yr long time series shows that Dome C surface is covered almost half of the time by hoar. The development of hoar crystals takes a few days and seems to occur whatever the meteorological conditions. In contrast, the disappearance of hoar is rapid (a few hours and coincident with either strong winds or with moderate winds associated with a change in wind direction from southwest (the prevailing direction to southeast. From the microwave satellite data, we computed the polarisation ratio (i.e. horizontal over vertical polarised brightness temperatures, an indicator known to be sensitive to hoar in Greenland. Photography data and microwave polarisation ratio are correlated, i.e. high values of polarisation ratio which theoretically correspond to low snow density values near the surface are associated with the presence of hoar crystals in the photography data. Satellite data over nearly ten years (2002–2011 confirm that a strong decrease of the polarisation ratio (i.e. signature of hoar disappearance is associated with an increase of wind speed or a change in wind direction from the prevailing direction. The photography data provides, in addition, evidence of interactions between hoar and snowfall. Further adding the combined influence of wind speed and wind direction results in a

  2. Global Cloud Detection and Distribution with Night Time using Satellite Infrared Data

    Science.gov (United States)

    Kadosaki, G.; Yamanouchi, T.; Hirasawa, N.

    2007-12-01

    Knowledge of the current climate system is necessary to clearly estimate large-scale global warming and abnormal weather in the future. Net radiation is one of the main factors that influence a climate system. The earth, which is covered by cloud of dozens of surface giving it a high albedo, reflects a large part of solar radiation. In addition, during nights, when the earth's radiation increases, the earth acts as a radiator. There is no doubt that clouds are closely related to the radiation balance. Satellite data analysis is the most useful method to understand cloud climatology. The targets are to establish an algorithm to detect clouds for night term of the earth, and to get to know more about global cloud distribution with night term. Brightness temperature difference of split window channels is used in this method. We decided three thresholds which have some slopes are used in the case of over land, open sea, and snow or ice surface including sea ice, respectively. We examined on some sensors which has difference response function in itself plat home, GLI/ADEOS2, AVHRR/NOAA, MODIS/Terra and Aqua.

  3. Infrared

    Science.gov (United States)

    Vollmer, M.

    2013-11-01

    'Infrared' is a very wide field in physics and the natural sciences which has evolved enormously in recent decades. It all started in 1800 with Friedrich Wilhelm Herschel's discovery of infrared (IR) radiation within the spectrum of the Sun. Thereafter a few important milestones towards widespread use of IR were the quantitative description of the laws of blackbody radiation by Max Planck in 1900; the application of quantum mechanics to understand the rotational-vibrational spectra of molecules starting in the first half of the 20th century; and the revolution in source and detector technologies due to micro-technological breakthroughs towards the end of the 20th century. This has led to much high-quality and sophisticated equipment in terms of detectors, sources and instruments in the IR spectral range, with a multitude of different applications in science and technology. This special issue tries to focus on a few aspects of the astonishing variety of different disciplines, techniques and applications concerning the general topic of infrared radiation. Part of the content is based upon an interdisciplinary international conference on the topic held in 2012 in Bad Honnef, Germany. It is hoped that the information provided here may be useful for teaching the general topic of electromagnetic radiation in the IR spectral range in advanced university courses for postgraduate students. In the most general terms, the infrared spectral range is defined to extend from wavelengths of 780 nm (upper range of the VIS spectral range) up to wavelengths of 1 mm (lower end of the microwave range). Various definitions of near, middle and far infrared or thermal infrared, and lately terahertz frequencies, are used, which all fall in this range. These special definitions often depend on the scientific field of research. Unfortunately, many of these fields seem to have developed independently from neighbouring disciplines, although they deal with very similar topics in respect of the

  4. Estimation of soil moisture-thermal infrared emissivity relation in arid and semi-arid environments using satellite observations

    Science.gov (United States)

    Grazia Blasi, Maria; Masiello, Guido; Serio, Carmine; Venafra, Sara; Liuzzi, Giuliano; Dini, Luigi

    2016-04-01

    The retrieval of surface parameters is very important for various aspects concerning the climatological and meteorological context. At this purpose surface emissivity represents one of the most important parameters useful for different applications such as the estimation of climate changes and land cover features. It is known that thermal infrared (TIR) emissivity is affected by soil moisture, but there are very few works in literature on this issue. This study is aimed to analyze and find a relation between satellite soil moisture data and TIR emissivity focusing on arid and semi-arid environments. These two parameters, together with the land surface temperature, are fundamental for a better understanding of the physical phenomena implied in the soil-atmosphere interactions and the surface energy balance. They are also important in several fields of study, such as climatology, meteorology, hydrology and agriculture. In particular, there are several studies stating a correlation between soil moisture and the emissivity at 8-9 μm in desertic soils, which corresponds to the quartz Reststrahlen, a feature which is typical of sandy soils. We investigated several areas characterized by arid or semi-arid environments, focusing our attention on the Dahra desert (Senegal), and on the Negev desert (Israel). For the Dahra desert we considered both in situ, provided by the International Soil Moisture Network, and satellite soil moisture data, from ASCAT and AMSR-E sensors, for the whole year 2011. In the case of the Negev desert soil moisture data are derived from ASCAT observations and we computed a soil moisture index from a temporal series of SAR data acquired by the Cosmo-SkyMed constellation covering a period of six months, from June 2015 to November 2015. For both cases soil moisture data were related to the retrieved TIR emissivity from the geostationary satellite SEVIRI in three different spectral channels, at 8.7 μm, 10.8 μm and 12 μm. A Kalman filter physical

  5. Quantification of the Beauce's Groundwater contribution to the Loire River discharge using satellite infrared imagery

    Directory of Open Access Journals (Sweden)

    E. Lalot

    2015-02-01

    Full Text Available Seven Landsat Thermal InfraRed (TIR images, taken over the period 2000–2010, were used to establish longitudinal temperature profiles of the middle Loire River, where it flows above the Beauce aquifer. Results showed that 75% of the temperature differences, between in situ observations and TIR image based estimations, remained within the ±1 °C interval. The groundwater discharge along the River course was quantified for each identified groundwater catchment areas using a heat budget based on the Loire River temperature variations, estimated from the TIR images. The main discharge area of the Beauce aquifer into the Loire River was located between river kilometers 630 and 650. This result confirms what was obtained using a groundwater budget and spatially locates groundwater input within the Middle sector of the Loire River. According to the heat budgets, groundwater discharge is higher during winter period (13.5 m3 s−1 than during summer (5.3 m3 s−1. Groundwater input is also higher during the flow recession periods of the Loire River.

  6. An Analysis of Thermally-Related Surface Rainfall Budgets Associated with Convective and Stratiform Rainfall

    Institute of Scientific and Technical Information of China (English)

    ZHOU Yushu; Xiaofan LI

    2011-01-01

    Both water vapor and heat processes play key roles in producing surface rainfall.While the water vapor effects of sea surface temperature and cloud radiative and microphysical processes on surface rainfall have been investigated in previous studies,the thermal effects on rainfall are analyzed in this study using a series of two-dimensional equilibrium cloud-resolving model experiments forced by zonally-uniform,constant,large-scale zonal wind and zero large-scale vertical velocity.The analysis of thermally-related surface rainfall budget reveals that the model domain mean surface rain rate is primarily associated with the mean infrared cooling rate.Convective rainfall and transport of hydrometeor concentration from convective regions to raining stratiform regions corresponds to the heat divergence over convective regions,whereas stratiform rainfall corresponds to the transport of hydrometeor concentration from convective regions and heat divergence over raining stratiform regions.The heat divergence over convective regions is mainly balanced by the heat convergence over rainfall-free regions,which is,in turn,offset by the radiative cooling over rainfall-free regions.The sensitivity experiments of rainfall to the effects of sea surface temperature and cloud radiative and microphysical processes show that the sea surface temperature and cloud processes affect convective rainfall through the changes in infrared cooling rate over rainfall-free regions and transport rate of heat from convective regions to rainfall-free regions.

  7. Global Transients in ultraviolet and red-infrared ranges from data of the "Universitetsky-Tatiana-2" satellite

    CERN Document Server

    Garipov, G K; Klimov, P A; Klimenko, V V; Mareev, E A; Martines, O; Morozenko, V S; Panasyuk, M I; Park, I H; Ponce, E; Salazar, H; Tulupov, V I; Vedenkin, N N; Yashin, I V

    2011-01-01

    Detectors of fast flashes (duration of 1-128 ms) in near ultraviolet (240-400 nm) and red-infrared (>610 nm) ranges on board the "Universitetsky-Tatiana-2" satellite have measured transient luminous events global distribution. Events with number of photons 10^20-5{\\cdot}10^21 radiated in the atmosphere are uniformly distributed over latitudes and longitudes. Events with number of photons more than 5{\\cdot}10^21 are concentrated near the equator above continents. Measured ratio of photons number radiated in red-IR range to photons number radiated in UV related to excitation of nitrogen molecular indicates a high altitude (>50 km) of the atmospheric electric discharges responsible for the observed transients. Series of every minute transients (from 3 to 16 transients in the series) were observed. The detection of transients out of thunderstorm area, in cloudless region- sometimes thousands km away of thunderstorms is remarkable. The obtained data allow us to assume that transient events are not only consequence...

  8. 基于卫星红外窗亮温探测上冲云顶%Satellite-based detection of overshooting cloud tops using infrared window channel brightness temperature

    Institute of Scientific and Technical Information of China (English)

    王雪芹; 黄勇; 官莉

    2013-01-01

    An overshooting convective cloud top is a domelike protrusion above a cumulonimbus anvil and signifies strong troposphere shear and intense updrafts. The deep convective storms with overshooting tops are capable of producing hazardous weather conditions such as aviation turbulence, heavy rainfall, large hail, damaging wind, tornado and so on. This paper took a heavy rainfall process in the north of Anhui province on 6 Sep 2010 for example. Based of satellite infrared window channel brightness temperature , overshooting tops was detected and local analysis prediction system(LAPS) of the high temporal and spatial resolutions was used to compare. The results are shown as follows; the convection system which caused this heavy rainfall process is a strong thunderstorm which accompanies overshooting cloud tops; LAPS mesoscale data proved the presence of the overshooting cloud tops.%上冲云顶是卷云砧上的穹顶状突起,表示存在强对流切变和强烈上升气流,是强雷暴的重要指示者.伴随上冲云顶的雷暴经常产生灾害性天气,如航空湍流、强降雨、冰雹、破坏性的风和龙卷等.本文以2010年9月6日发生在安徽北部地区的一次特大暴雨过程为例,用卫星红外窗区通道观测亮温探测上冲云顶,并将高时空分辨率的局地分析预报系统(LAPS)的中尺度分析场资料与用红外窗方法探测到的上冲云顶进行定性比较,结果表明造成此次强降雨过程的对流系统即为一个伴随上冲云顶的强雷暴系统,LAPS中尺度分析场资料客观地验证了上冲云顶的存在.

  9. Satellite observation of lowermost tropospheric ozone by multispectral synergism of IASI thermal infrared and GOME-2 ultraviolet measurements over Europe

    Science.gov (United States)

    Cuesta, J.; Eremenko, M.; Liu, X.; Dufour, G.; Cai, Z.; Hoepfner, M.; von Clarmann, T.; Sellitto, P.; Foret, G.; Gaubert, B.; Beekmann, M.; Orphal, J. J.; Chance, K.; Spurr, R. J.; Flaud, J.

    2013-12-01

    Lowermost tropospheric ozone is a major factor determining air quality, which directly affects human health in megacities and causes damages to ecosystems. Monitoring tropospheric ozone is a key societal issue which can be addressed at the regional scale by spaceborne observation. However, current satellite retrievals of tropospheric ozone using uncoupled either ultraviolet (UV) or thermal infrared (TIR) observations show limited sensitivity to ozone at the lowermost troposphere (LMT, up to 3 km asl of altitude above sea level), which is the major concern for air quality. In this framework, we have developed a new multispectral approach for observing lowermost tropospheric ozone from space by synergism of atmospheric TIR radiances observed by IASI and earth UV reflectances measured by GOME-2. Both instruments are onboard the series of MetOp satellites (in orbit since 2006 and expected until 2022) and their scanning capabilities offer global coverage every day, with a relatively fine ground pixel resolution (12-km-diameter pixels spaced by 25 km for IASI at nadir). Our technique uses altitude-dependent Tikhonov-Phillips-type constraints, which optimize sensitivity to lower tropospheric ozone. It integrates the VLIDORT and KOPRA radiative transfer codes for simulating UV reflectance and TIR radiance, respectively. We have used our method to analyze real observations over Europe during an ozone pollution episode in the summer of 2009. The results show that the multispectral synergism of IASI (TIR) and GOME-2 (UV) enables the observation of the spatial distribution of ozone plumes in the LMT, in good agreement with the CHIMERE regional chemistry-transport model. In this case study, when high ozone concentrations extend vertically above 3 km asl, they are similarly observed over land by both the multispectral and IASI retrievals. On the other hand, ozone plumes located below 3 km asl are only clearly depicted by the multispectral retrieval (both over land and over ocean

  10. Characterization of the 3D distribution of ozone and coarse aerosols in the Troposphere using IASI thermal infrared satellite observations

    Science.gov (United States)

    Cuesta, J.; Eremenko, M.; Dufour, G.; Hoepfner, M.; Orphal, J.

    2012-04-01

    Both tropospheric ozone and aerosols significantly affect air quality in megacities during pollution events. Moreover, living conditions may be seriously aggravated when such agglomerations are affected by wildfires (e.g. Russian fires over Moscow in 2010), which produce smoke and pollutant precursors, or even during dense desert dust outbreaks (e.g. recurrently over Beijing or Cairo). Moreover, since aerosols diffuse and absorb solar radiation, they have a direct impact on the photochemical production of tropospheric ozone. These interactions during extreme events of high aerosol loads are nowadays poorly known, even though they may significantly affect the tropospheric photochemical equilibrium. In order to address these issues, we have developed a new retrieval technique to jointly characterize the 3D distribution of both tropospheric ozone and coarse aerosols, using spaceborne observations of the infrared spectrometer IASI onboard MetOp-A satellite. Our methodology is based on the inversion of Earth radiance spectra in the atmospheric window from 8 to 12 μm measured by IASI and a «Tikhonov-Philipps»-type regularisation with constraints varying in altitude (as in [Eremenko et al., 2008, GRL; Dufour et al., 2010 ACP]) to simultaneously retrieve ozone profiles, aerosol optical depths at 10 μm and aerosol layer effective heights. Such joint retrieval prevents biases in the ozone profile retrieval during high aerosol load conditions. Aerosol retrievals using thermal infrared radiances mainly account for desert dust and the coarse fraction of biomass burning aerosols. We use radiances from 15 micro-windows within the 8-12 μm atmospheric window, which were carefully chosen (following [Worden et al., 2006 JGR]) for extracting the maximum information on aerosols and ozone and minimizing contamination by other species. We use the radiative transfer code KOPRA, including line-by-line calculations of gas absorption and single scattering for aerosols [Hoepfner et al

  11. Retrieval of SO2 from thermal infrared satellite measurements: correction procedures for the effects of volcanic ash

    Directory of Open Access Journals (Sweden)

    S. Corradini

    2009-05-01

    Full Text Available The simultaneous presence of SO2 and ash in a volcanic plume can lead to a significant error in the SO2 column abundance retrieval when multispectral Thermal InfraRed (TIR data are used. The ash particles within the plume with effective radii from 1 to 10 μm reduce the Top Of Atmosphere (TOA radiance in the entire TIR spectral range, including the channels used for SO2 retrieval. The net effect is a significant SO2 overestimation. In this work the interference of ash is discussed and two correction procedures for satellite SO2 volcanic plume retrieval in the TIR spectral range are developed to achieve an higher computational speed and a better accuracy. The ash correction can be applied when the sensor spectral range includes the 7.3 and/or 8.7 μm SO2 absorption bands, and the split window bands centered around 11 and 12 μm required for ash retrieval. This allows the possibility of simultaneous estimation of both volcanic SO2 and ash in the same data set. The proposed ash correction procedures have been applied to the Moderate Resolution Imaging Spectroradiometer (MODIS and the Spin Enhanced Visible and Infrared Imager (SEVIRI measurements. Data collected during the 24 November 2006 Mt. Etna eruption have been used to illustrate the technique. The SO2 and ash estimation is carried out by using a best weighted least squares fit method and the Brightness Temperature Difference (BTD procedures, respectively. The simulated TOA radiance Look-Up Table (LUT needed for the SO2 column abundance and the ash retrievals have been computed using the MODTRAN 4 Radiative Transfer Model. The results show the importance of the ash correction on SO2 retrievals at 8.7 μm, where the corrected SO2 column abundance values are less than 50% of the uncorrected values. The ash correction on SO2 retrieval at 7.3 μm is much less important and only significant for low SO2 column abundances. Results also show that the simplified and faster correction procedure

  12. Retrieval of SO2 from thermal infrared satellite measurements: correction procedures for the effects of volcanic ash

    Directory of Open Access Journals (Sweden)

    A. J. Prata

    2009-02-01

    Full Text Available The simultaneous presence of SO2 and ash in a volcanic plume can lead to a significant error in the SO2 columnar abundance retrieval when multispectral Thermal InfraRed (TIR data are used. The ash particles within the plume with effective radii (from 1 to 10 μm reduce the Top Of Atmosphere (TOA radiance in the entire TIR spectral range, including the channels used for SO2 retrieval. The net effect is a significant SO2 overestimation. In this work the interference of ash is discussed and two correction procedures for satellite SO2 volcanic plume retrieval in the TIR spectral range are developed to achieve an higher computation speed and a better accuracy. The ash correction can be applied when the sensor spectral range includes the 7.3 and/or 8.7 μm SO2 absorption bands, and the split window bands centered around 11 and 12 μm required for ash retrieval. This allows the possibility of a simultaneous estimation of both volcanic SO2 and ash in the same data set. The proposed ash correction procedures have been applied to the Moderate Resolution Imaging Spectroradiometer (MODIS and the Spin Enhanced Visible and Infrared Imager (SEVIRI measurements. Data collected during the 24 November 2006 Mt. Etna eruption have been used to illustrate the technique. The SO2 and ash estimations are carried out by using a least squares fit method and the Brightness Temperature Difference (BTD procedures, respectively. The simulated TOA radiance Look-Up Table (LUT needed for the SO2 columnar abundance and the ash retrievals have been computed using the MODTRAN 4 Radiative Transfer Model. The results show the importance of the ash correction on SO2 retrieval at 8.7 μm – the SO2 columnar abundance corrected by the ash influence is less than one half of the values retrieved without the correction. The ash correction on SO2 retrieval at 7.3 μm is much less important and only significant for low SO2 columnar abundances. Results also show that the simplified and

  13. 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

  14. Recent Improvements in Estimating Convective and Stratiform Rainfall in Amazonia

    Science.gov (United States)

    Negri, Andrew J.

    1999-01-01

    In this paper we present results from the application of a satellite infrared (IR) technique for estimating rainfall over northern South America. Our main objectives are to examine the diurnal variability of rainfall and to investigate the relative contributions from the convective and stratiform components. We apply the technique of Anagnostou et al (1999). In simple functional form, the estimated rain area A(sub rain) may be expressed as: A(sub rain) = f(A(sub mode),T(sub mode)), where T(sub mode) is the mode temperature of a cloud defined by 253 K, and A(sub mode) is the area encompassed by T(sub mode). The technique was trained by a regression between coincident microwave estimates from the Goddard Profiling (GPROF) algorithm (Kummerow et al, 1996) applied to SSM/I data and GOES IR (11 microns) observations. The apportionment of the rainfall into convective and stratiform components is based on the microwave technique described by Anagnostou and Kummerow (1997). The convective area from this technique was regressed against an IR structure parameter (the Convective Index) defined by Anagnostou et al (1999). Finally, rainrates are assigned to the Am.de proportional to (253-temperature), with different rates for the convective and stratiform

  15. 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

  16. Analysis of the sensitivity of thermal infrared nadir satellite observations to the chemical and micro-physical properties of upper tropospheric-lower stratospheric sulphate aerosols

    Science.gov (United States)

    Sellitto, Pasquale; Sèze, Geneviève; Legras, Bernard

    2015-04-01

    Secondary sulphate aerosols are the predominant typology of aerosols in the upper troposphere/lower stratosphere (UTLS), and can have an important impact on radiative transfer and climate, cirrus formation and chemistry in the UTLS. Despite their importance, the satellite observation at the regional scale of sulphate aerosols in the UTLS is limited. In this work, we address the sensitivity of the thermal infrared satellite observations to secondary sulphate aerosols in the UTLS. The absorption properties of sulphuric acid/water droplets, for different sulphuric acid mixing ratios and temperatures, are systematically analysed. The absorption coefficients are derived by means of a Mie code, using refractive indexes taken from the GEISA (Gestion et Etude des Informations Spectroscopiques Atmosphériques : Management and Study of Spectroscopic Information) spectroscopic database and log-normal size distributions with different effective radii and number concentrations. IASI (Infrared Atmospheric Sounding Interferometer) and SEVIRI (Spinning Enhanced Visible and Infrared Imager) pseudo-observations are generated using forward radiative transfer calculations performed with the 4A (Automatized Atmospheric Absorption Atlas) radiative transfer model, to estimate the impact of the absorption of idealized aerosol layers, at typical UTLS conditions, on the radiance spectra observed by these simulated satellite instruments. We found a marked spectral signature of these aerosol layers between 700 and 1200 cm-1, due to the absorption bands of the sulphate and bi-sulphate ions and the undissociated sulphuric acid, with absorption peaks at 1170 and 905 cm-1. Micro-windows with a sensitivity to chemical and micro-physical properties of the sulphate aerosol layer are identified, and the role of interfering species, and temperature and water vapour profile is discussed.

  17. 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.

  18. 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.

  19. Synopsis of current satellite snow mapping techniques, with emphasis on the application of near-infrared data

    Science.gov (United States)

    Barnes, J. C.; Smallwood, M. D.

    1975-01-01

    The Skylab EREP S192 Multispectral Scanner data have provided for the first time an opportunity to examine the reflectance characteristics of snowcover in several spectral bands extending from the visible into the near-infrared spectral region. The analysis of the S192 imagery and digital tape data indicates a sharp drop in reflectance of snow in the near-infrared, with snow becoming essentially nonreflective in Bands 11 (1.55-1.75 micron) and 12 (2.10-2.35 micron). Two potential applications to snow mapping of measurements in the near-infrared spectral region are possible: (1) the use of a near-infrared band in conjunction with a visible band to distinguish automatically between snow and water droplet clouds; and (2) the use of one or more near-infrared bands to detect areas of melting snow.

  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. 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

  2. Satellites of Xe transitions induced by infrared active vibrational modes of CF4 and C2F6 molecules.

    Science.gov (United States)

    Alekseev, Vadim A; Schwentner, Nikolaus

    2011-07-28

    Absorption and luminescence excitation spectra of Xe/CF(4) mixtures were studied in the vacuum UV region at high resolution using tunable synchrotron radiation. Pressure-broadened resonance bands and bands associated with dipole-forbidden states of the Xe atom due to collision-induced breakdown of the optical selection rules are reported. The spectra display in addition numerous satellite bands corresponding to transitions to vibrationally excited states of a Xe-CF(4) collisional complex. These satellites are located at energies of Xe atom transition increased by one quantum energy in the IR active v(3) vibrational mode of CF(4) (v(3) = 1281 cm(-1)). Satellites of both resonance and dipole-forbidden transitions were observed. Satellites of low lying resonance states are spectrally broad bands closely resembling in shape their parent pressure-broadened resonance bands. In contrast, satellites of dipole-forbidden states and of high lying resonance states are spectrally narrow bands (FWHM ∼10 cm(-1)). The satellites of dipole-forbidden states are orders of magnitude stronger than transitions to their parent states due to collision-induced breakdown of the optical selection rules. These satellites are attributed to a coupling of dipole-forbidden and resonance states induced by the electric field of the transient CF(4) (v(3) = 0 ↔ v(3) = 1) dipole. Similar satellites are present in spectra of Xe/C(2)F(6) mixtures where these bands are induced by the IR active v(10) mode of C(2)F(6). Transitions to vibrationally excited states of Xe-CF(4)(C(2)F(6)) collision pairs were also observed in two-photon LIF spectra.

  3. Improved infrared precipitation estimation approaches based on k-means clustering: Application to north Algeria using MSG-SEVIRI satellite data

    Science.gov (United States)

    Mokdad, Fatiha; Haddad, Boualem

    2017-06-01

    In this paper, two new infrared precipitation estimation approaches based on the concept of k-means clustering are first proposed, named the NAW-Kmeans and the GPI-Kmeans methods. Then, they are adapted to the southern Mediterranean basin, where the subtropical climate prevails. The infrared data (10.8 μm channel) acquired by MSG-SEVIRI sensor in winter and spring 2012 are used. Tests are carried out in eight areas distributed over northern Algeria: Sebra, El Bordj, Chlef, Blida, Bordj Menael, Sidi Aich, Beni Ourthilane, and Beni Aziz. The validation is performed by a comparison of the estimated rainfalls to rain gauges observations collected by the National Office of Meteorology in Dar El Beida (Algeria). Despite the complexity of the subtropical climate, the obtained results indicate that the NAW-Kmeans and the GPI-Kmeans approaches gave satisfactory results for the considered rain rates. Also, the proposed schemes lead to improvement in precipitation estimation performance when compared to the original algorithms NAW (Nagri, Adler, and Wetzel) and GPI (GOES Precipitation Index).

  4. 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.

  5. Investigation on the monthly variation of cirrus optical properties over the Indian subcontinent using cloud-aerosol lidar and infrared pathfinder satellite observation (Calipso)

    Science.gov (United States)

    Dhaman, Reji K.; Satyanarayana, Malladi; Jayeshlal, G. S.; Mahadevan Pillai, V. P.; Krishnakumar, V.

    2016-05-01

    Cirrus clouds have been identified as one of the atmospheric component which influence the radiative processes in the atmosphere and plays a key role in the Earth Radiation Budget. CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) is a joint NASA-CNES satellite mission designed to provide insight in understanding of the role of aerosols and clouds in the climate system. This paper reports the study on the variation of cirrus cloud optical properties of over the Indian sub - continent for a period of two years from January 2009 to December 2010, using cloud-aerosol lidar and infrared pathfinder satellite observations (Calipso). Indian Ocean and Indian continent is one of the regions where cirrus occurrence is maximum particularly during the monsoon periods. It is found that during the south-west monsoon periods there is a large cirrus cloud distribution over the southern Indian land masses. Also it is observed that the north-east monsoon periods had optical thick clouds hugging the coast line. The summer had large cloud formation in the Arabian Sea. It is also found that the land masses near to the sea had large cirrus presence. These cirrus clouds were of high altitude and optical depth. The dependence of cirrus cloud properties on cirrus cloud mid-cloud temperature and geometrical thickness are generally similar to the results derived from the ground-based lidar. However, the difference in macrophysical parameter variability shows the limits of space-borne-lidar and dissimilarities in regional climate variability and the nature and source of cloud nuclei in different geographical regions.

  6. A Satellite Time Slots Climatology of the Urban Heat Island of Guadalajara Megacity in Mexico from NOAA ¡/AVHRR THERMAL Infrared Monitoring (TIR)

    Science.gov (United States)

    Galindo, I.

    2009-04-01

    The urban heat island (UHI) of the metropolitan area of the second megacity of Mexico, named Guadalajara in Mexico is studied using thermal infrared data (TIR) (10 £ l £ 12 mm) obtained from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbitters whose signals are received on real time at our ground station for the period 1996-2006. The TIR data are selected by means of a software, since they depend on natural causes (e.g., atmospheric transparency, surface temperature, spectral emissivity and topography) and observational (time and incidence angle of the satellite pass, season of the year, etc.). The above conditions have a variable contribution to the measurements which it can be so high that they simulate the temporal-space fluctuations considered as thermal anomalies. Using a Geographic Information System and spatial analysis techniques temperatures are obtained for diofferent times of the day (satellite slots) and dropped into a grid with a 2.5 km distance between points (latitude, longitude). The temperatures obtained for each satellite pass slot (four per day) are monthly averaged and the temperature anomalies are represented in thermal isolines for the study area. The temperature difference usually is larger at night than during the day, reaching a thermal gradient of 9 °C.

  7. Increasing spatial resolution of CHIRPS rainfall datasets for Cyprus with artificial neural networks

    Science.gov (United States)

    Tymvios, Filippos; Michaelides, Silas; Retalis, Adrianos; Katsanos, Dimitrios; Lelieveld, Jos

    2016-08-01

    The use of high resolution rainfall datasets is an alternative way of studying climatological regions where conventional rain measurements are sparse or not available. Starting in 1981 to near-present, the CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) dataset incorporates a 5km×5km resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis, severe events and seasonal drought monitoring. The aim of this work is to further increase the resolution of the rainfall dataset for Cyprus to 1km×1km, by correlating the CHIRPS dataset with elevation information, the NDVI index (Normalized Difference Vegetation Index) from satellite images at 1km×1km and precipitation measurements from the official raingauge network of the Cyprus' Department of Meteorology, utilizing Artificial Neural Networks. The Artificial Neural Networks' architecture that was implemented is the Multi-Layer Perceptron (MLP) trained with the back propagation method, which is widely used in environmental studies. Seven different network architectures were tested, all with two hidden layers. The number of neurons ranged from 3 to10 in the first hidden layer and from 5 to 25 in the second hidden layer. The dataset was separated into a randomly selected training set, a validation set and a testing set; the latter is independently used for the final assessment of the models' performance. Using the Artificial Neural Network approach, a new map of the spatial analysis of rainfall is constructed which exhibits a considerable increase in its spatial resolution. A statistical assessment of the new spatial analysis was made using the rainfall ground measurements from the raingauge network. The assessment indicates that the methodology is promising for several applications.

  8. 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

  9. 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

  10. The Fertilizing Role of African Dust in the Amazon Rainforest. A First Multiyear Assessment Based on Data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Hongbin [Univ. of Maryland, College Park, MD (United States); NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Chin, Mian [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Yuan, Tianle [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Univ. of Maryland, Baltimore, MD (United States); Bian, Huisheng [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Univ. of Maryland, Baltimore, MD (United States); Remer, L. A. [Univ. of Maryland, Baltimore, MD (United States); Prospero, J. [Univ. of Miami, FL (United States); Omar, Ali [NASA Langley Research Center, Hampton, VA (United States); Winker, D. [NASA Langley Research Center, Hampton, VA (United States); Yang, Yuekui [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Universities Space Research Association, Columbia, MD (United States); Zhang, Yan [NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Universities Space Research Association, Columbia, MD (United States); Zhang, Zhibo [Univ. of Maryland, Baltimore, MD (United States); Zhao, Chun [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-03-18

    The productivity of the Amazon rainforest is constrained by the availability of nutrients, in particular phosphorus (P). Deposition of long-range transported African dust is recognized as a potentially important but poorly quantified source of phosphorus. This study provides a first multiyear satellite-based estimate of dust deposition into the Amazon Basin using three dimensional (3D) aerosol measurements over 2007-2013 from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The 7-year average of dust deposition into the Amazon Basin is estimated to be 28 (8~48) Tg a-1 or 29 (8~50) kg ha-1 a-1. The dust deposition shows significant interannual variation that is negatively correlated with the prior-year rainfall in the Sahel. The CALIOP-based multi-year mean estimate of dust deposition matches better with estimates from in-situ measurements and model simulations than a previous satellite-based estimate does. The closer agreement benefits from a more realistic geographic definition of the Amazon Basin and inclusion of meridional dust transport calculation in addition to the 3D nature of CALIOP aerosol measurements. The imported dust could provide about 0.022 (0.006~0.037) Tg P of phosphorus per year, equivalent to 23 (7~39) g P ha-1 a-1 to fertilize the Amazon rainforest. This out-of-Basin P input is comparable to the hydrological loss of P from the Basin, suggesting an important role of African dust in preventing phosphorus depletion on time scales of decades to centuries.

  11. 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.

  12. 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.

  13. 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.

  14. Comparability of red/near-infrared reflectance and NDVI based on the spectral response function between MODIS and 30 other satellite sensors using rice canopy spectra.

    Science.gov (United States)

    Huang, Weijiao; Huang, Jingfeng; Wang, Xiuzhen; Wang, Fumin; Shi, Jingjing

    2013-11-26

    Long-term monitoring of regional and global environment changes often depends on the combined use of multi-source sensor data. The most widely used vegetation index is the normalized difference vegetation index (NDVI), which is a function of the red and near-infrared (NIR) spectral bands. The reflectance and NDVI data sets derived from different satellite sensor systems will not be directly comparable due to different spectral response functions (SRF), which has been recognized as one of the most important sources of uncertainty in the multi-sensor data analysis. This study quantified the influence of SRFs on the red and NIR reflectances and NDVI derived from 31 Earth observation satellite sensors. For this purpose, spectroradiometric measurements were performed for paddy rice grown under varied nitrogen levels and at different growth stages. The rice canopy reflectances were convoluted with the spectral response functions of various satellite instruments to simulate sensor-specific reflectances in the red and NIR channels. NDVI values were then calculated using the simulated red and NIR reflectances. The results showed that as compared to the Terra MODIS, the mean relative percentage difference (RPD) ranged from -12.67% to 36.30% for the red reflectance, -8.52% to -0.23% for the NIR reflectance, and -9.32% to 3.10% for the NDVI. The mean absolute percentage difference (APD) compared to the Terra MODIS ranged from 1.28% to 36.30% for the red reflectance, 0.84% to 8.71% for the NIR reflectance, and 0.59% to 9.32% for the NDVI. The lowest APD between MODIS and the other 30 satellite sensors was observed for Landsat5 TM for the red reflectance, CBERS02B CCD for the NIR reflectance and Landsat4 TM for the NDVI. In addition, the largest APD between MODIS and the other 30 satellite sensors was observed for IKONOS for the red reflectance, AVHRR1 onboard NOAA8 for the NIR reflectance and IKONOS for the NDVI. The results also indicated that AVHRRs onboard NOAA7-17 showed

  15. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nuristan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nuristan mineral district, which has gem, lithium, and cesium deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

  16. Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA

  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. Frequency based detection and monitoring of small scale explosive activity by comparing satellite and ground based infrared observations at Stromboli Volcano, Italy

    Science.gov (United States)

    Worden, Anna; Dehn, Jonathan; Ripepe, Maurizio; Donne, Dario Delle

    2014-08-01

    Thermal activity is a common precursor to explosive volcanic activity. The ability to use these thermal precursors to monitor the volcano and obtain early warning about upcoming activity is beneficial for both human safety and infrastructure security. By using a very reliably active volcano, Stromboli Volcano in Italy, a method has been developed and tested to look at changes in the frequency of small scale explosive activity and how this activity changes prior to larger, ash producing explosive events. Thermal camera footage was used to designate parameters for typical explosions at Stromboli (size of spatter field, cooling rate, frequency of explosions) and this information was applied to characterize explosions in satellite imagery. Satellite data from The National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer (MODIS) and US/Japan designed Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) for numerous periods in 2002 to 2009 were analyzed for thermal features which were used to calculate an estimate of the level of activity during the given time period. The results at Stromboli showed a high level of small scale explosions which stop completely prior to large paroxysmal eruptive episodes. This activity also corresponds well to seismic and infrasonic records at Stromboli, indicating that this thermal infrared monitoring method may be used in conjunction with other detection methods where available, and also indicates that it may be a useful method for volcano monitoring when other methods (e.g. seismic instrumentation, infrasound arrays, etc.) are not available.

  19. Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the Greenhouse Gases Observing Satellite

    Directory of Open Access Journals (Sweden)

    I. Morino

    2010-11-01

    Full Text Available The Greenhouse gases Observing SATellite (GOSAT was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS. The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from the instrumental noise. The interferences by auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and the temporal variation patterns of the retrieved column abundances agree well with the current state of knowledge.

  20. Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite

    Directory of Open Access Journals (Sweden)

    I. Morino

    2011-04-01

    Full Text Available The Greenhouse gases Observing SATellite (GOSAT was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here, we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS. The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from instrumental noise. The interferences due to auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and temporal variation patterns of the retrieved column abundances show features similar to those of an atmospheric transport model.

  1. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ahankashan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ahankashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008, 2009, 2010),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Bamyan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Bamyan mineral district, which has areas with a spectral reflectance anomaly that require field investigation. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008),but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Bamyan mineral district in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Bamyan mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  4. 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

  5. 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%.

  6. 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

  7. Polar-Orbiting Satellite (POES) Images

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Visible and Infrared satellite imagery taken from camera systems or radiometer instruments on satellites in orbit around the poles. Satellite campaigns include...

  8. 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 ...

  9. Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth's Radiant Energy System Instrument on the Tropical Rainfall Measuring Mission Satellite. Part II; Validation

    Science.gov (United States)

    Loeb, N. G.; Loukachine, K.; Wielicki, B. A.; Young, D. F.

    2003-01-01

    Top-of-atmosphere (TOA) radiative fluxes from the Clouds and the Earth s Radiant Energy System (CERES) are estimated from empirical angular distribution models (ADMs) that convert instantaneous radiance measurements to TOA fluxes. This paper evaluates the accuracy of CERES TOA fluxes obtained from a new set of ADMs developed for the CERES instrument onboard the Tropical Rainfall Measuring Mission (TRMM). The uncertainty in regional monthly mean reflected shortwave (SW) and emitted longwave (LW) TOA fluxes is less than 0.5 W/sq m, based on comparisons with TOA fluxes evaluated by direct integration of the measured radiances. When stratified by viewing geometry, TOA fluxes from different angles are consistent to within 2% in the SW and 0.7% (or 2 W/sq m) in the LW. In contrast, TOA fluxes based on ADMs from the Earth Radiation Budget Experiment (ERBE) applied to the same CERES radiance measurements show a 10% relative increase with viewing zenith angle in the SW and a 3.5% (9 W/sq m) decrease with viewing zenith angle in the LW. Based on multiangle CERES radiance measurements, 18 regional instantaneous TOA flux errors from the new CERES ADMs are estimated to be 10 W/sq m in the SW and, 3.5 W/sq m in the LW. The errors show little or no dependence on cloud phase, cloud optical depth, and cloud infrared emissivity. An analysis of cloud radiative forcing (CRF) sensitivity to differences between ERBE and CERES TRMM ADMs, scene identification, and directional models of albedo as a function of solar zenith angle shows that ADM and clear-sky scene identification differences can lead to an 8 W/sq m root-mean-square (rms) difference in 18 daily mean SW CRF and a 4 W/sq m rms difference in LW CRF. In contrast, monthly mean SW and LW CRF differences reach 3 W/sq m. CRF is found to be relatively insensitive to differences between the ERBE and CERES TRMM directional models.

  10. Defense Meteorological Satellite Program (DMSP)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Defense Meteorological Satellite Program (DMSP) satellites collect visible and infrared cloud imagery as well as monitoring the atmospheric, oceanographic,...

  11. Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This DS consists of the locally enhanced ALOS image mosaics for each of the 24 mineral project areas (referred to herein as areas of interest), whose locality names, locations, and main mineral occurrences are shown on the index map of Afghanistan (fig. 1). ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency, but the image processing has altered the original pixel structure and all image values of the JAXA

  12. On-board Data Processing to Lower Bandwidth Requirements on an Infrared Astronomy Satellite: Case of Herschel-PACS Camera

    Directory of Open Access Journals (Sweden)

    Christian Reimers

    2005-09-01

    Full Text Available This paper presents a new data compression concept, “on-board processing,” for infrared astronomy, where space observatories have limited processing resources. The proposed approach has been developed and tested for the PACS camera from the European Space Agency (ESA mission, Herschel. Using lossy and lossless compression, the presented method offers high compression ratio with a minimal loss of potentially useful scientific data. It also provides higher signal-to-noise ratio than that for standard compression techniques. Furthermore, the proposed approach presents low algorithmic complexity such that it is implementable on the resource-limited hardware. The various modules of the data compression concept are discussed in detail.

  13. 美军SBIRS GEO-1预警卫星探测预警能力分析%Analysis on infrared detecting and early warning capabilities of America's SBIRS GEO-1 satellite

    Institute of Scientific and Technical Information of China (English)

    李小将; 金山; 廖海玲; 王建华

    2013-01-01

    For effectively responding to the threats of ballistic missiles and protecting the US's national and allies' interests, the US army continually develops and consummates the space-based infrared early warning system. The paper introduces the status and development of US's space-based infrared system,explores the coverage characteristic of the first space-based infrared geosynchronous orbit satellite,builds the GEO-1 satellite's infrared detecting model and early warning model, analyzes the detecting and early warning efficiencies of SBIRS GEO-1 satellite.%为有效应对弹道导弹威胁,维护本土与盟国利益,美军不断发展完善其天基红外预警系统.介绍了美军天基红外系统的发展现状,分析了首颗天基红外系统静止轨道(SBIRS GEO-1)卫星的覆盖范围,建立了SBIRS GEO-1卫星的红外探测模型和弹道预警模型,对其在轨探测预警能力进行了初步仿真分析.

  14. 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.

  15. Laboratory-Measured Rainfall Effects on LWIR Soil Reflectance

    Science.gov (United States)

    Howington, S. E.; Ballard, J., Jr.; Wilhelms, S.

    2012-12-01

    The long-wave infrared reflectance of soils will often have distinct spectral characteristics that depend on the soil's physical and spectral properties. Rainfall has the effect of sorting soil particles at the ground surface, thus changing its long-wave infrared reflectance. This study examines how rainfall alters the measured directional-hemispherical thermal infrared (8-14 μm) spectral reflectance by comparing disturbed soil with undisturbed soil and pre-rain with post-rain conditions. The study uses a soil with a specified sand/silt ratio and a calibrated, laboratory rainfall simulator. For an accumulated rainfall of 8 cm, the mean disturbed soil thermal infrared spectral reflectance within 8.1 - 9.2 μm waveband increases from an initial reflectance of 13 percent to a maximum reflectance of 31 percent. Sixty percent of this reflectance change occurred with only 1 cm accumulated rainfall. This study shows that, for this described disturbed sand/silt soil mixture, small accumulated rainfall amounts significantly alter the directional-hemispherical thermal infrared spectral reflectance.

  16. MISTiC Winds, a Micro-Satellite Constellation Approach to High Resolution Observations of the Atmosphere using Infrared Sounding and 3D Winds Measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Susskind, J.; Aumann, H. H.

    2015-12-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sun-synchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's Atmospheric Infrared Sounder that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  17. Near-infrared brightness of the Galilean satellites eclipsed in Jovian shadow: A new technique to investigate Jovian upper atmosphere

    Energy Technology Data Exchange (ETDEWEB)

    Tsumura, K. [Frontier Research Institute for Interdisciplinary Science, Tohoku University, Sendai, Miyagi 980-8578 (Japan); Arimatsu, K.; Matsuura, S.; Shirahata, M.; Wada, T. [Department of Space Astronomy and Astrophysics, Institute of Space and Astronoutical Science, Japan Aerospace Exploration Agency, Sagamihara, Kanagawa 252-5210 (Japan); Egami, E. [Department of Astronomy, Arizona University, Tucson, AZ 85721 (United States); Hayano, Y.; Minowa, Y. [Hawaii Observatory, National Astronomical Observatory of Japan, Hilo, HI 96720 (United States); Honda, C. [Research Center for Advanced Information Science and Technology, Aizu Research Cluster for Space Science, The University of Aizu, Aizu-Wakamatsu, Fukushima 965-8589 (Japan); Kimura, J. [Earth-Life Science Institute, Tokyo Institute of Technology, Tokyo 152-8550 (Japan); Kuramoto, K.; Takahashi, Y. [Department of Cosmosciences, Graduate School of Science, Hokkaido University, Sapporo, Hokkaido 060-0810 (Japan); Nakajima, K. [Department of Earth and Planetary Sciences, Kyushu University, Fukuoka 812-8581 (Japan); Nakamoto, T. [Department of Earth and Planetary Sciences, Graduate School of Science and Engineering, Tokyo Institute of Technology, Tokyo 152-8551 (Japan); Surace, J., E-mail: tsumura@astr.tohoku.ac.jp [Spitzer Science Center, California Institute of Technology, Pasadena, CA 91125 (United States)

    2014-07-10

    Based on observations from the Hubble Space Telescope and the Subaru Telescope, we have discovered that Europa, Ganymede, and Callisto are bright around 1.5 μm even when not directly lit by sunlight. The observations were conducted with non-sidereal tracking on Jupiter outside of the field of view to reduce the stray light subtraction uncertainty due to the close proximity of Jupiter. Their eclipsed luminosity was 10{sup –6}-10{sup –7} of their uneclipsed brightness, which is low enough that this phenomenon has been undiscovered until now. In addition, Europa in eclipse was <1/10 of the others at 1.5 μm, a potential clue to the origin of the source of luminosity. Likewise, Ganymede observations were attempted at 3.6 μm by the Spitzer Space Telescope, but it was not detected, suggesting a significant wavelength dependence. It is still unknown why they are luminous even when in the Jovian shadow, but forward-scattered sunlight by hazes in the Jovian upper atmosphere is proposed as the most plausible candidate. If this is the case, observations of these Galilean satellites while eclipsed by the Jovian shadow provide us with a new technique to investigate the Jovian atmospheric composition. Investigating the transmission spectrum of Jupiter by this method is important for investigating the atmosphere of extrasolar giant planets by transit spectroscopy.

  18. Spatial variability in tropospheric peroxyacetyl nitrate in the tropics from infrared satellite observations in 2005 and 2006

    Science.gov (United States)

    Payne, Vivienne H.; Fischer, Emily V.; Worden, John R.; Jiang, Zhe; Zhu, Liye; Kurosu, Thomas P.; Kulawik, Susan S.

    2017-05-01

    Peroxyacetyl nitrate (PAN) plays a fundamental role in the global ozone budget and is the primary reservoir of tropospheric reactive nitrogen over much of the globe. However, large uncertainties exist in how surface emissions, transport and lightning affect the global distribution, particularly in the tropics. We present new satellite observations of free-tropospheric PAN in the tropics from the Aura Tropospheric Emission Spectrometer. This dataset allows us to test expected spatiotemporal distributions that have been predicted by models but previously not well observed. We compare here with the GEOS-Chem model with updates specifically for PAN. We observe an austral springtime maximum over the tropical Atlantic, a feature that model predictions attribute primarily to lightning. Over northern central Africa in December, observations show strong interannual variability, despite low variation in fire emissions, that we attribute to the combined effects of changes in biogenic emissions and lightning. We observe small enhancements in free-tropospheric PAN corresponding to the extreme burning event over Indonesia associated with the 2006 El Niño.

  19. Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

    Science.gov (United States)

    Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

    2008-07-01

    SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

  20. 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

  1. 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).

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. ASTER Urgent Response to the 2006 Eruption of Augustine Volcano, Alaska: Science and Decision Support Gained From Frequent High-resolution, Satellite Thermal Infrared Imaging of Volcanic Events

    Science.gov (United States)

    Wessels, R. L.; Ramsey, M. S.; Schneider, D. S.; Coombs, M.; Dehn, J.; Realmuto, V. J.

    2006-12-01

    Augustine Volcano, Alaska explosively erupted on January 11, 2006 after nearly eight months of increasing seismicity, deformation, gas emission, and small phreatic explosions. The volcano produced a total of 13 explosive eruptions during the last three weeks of January 2006. A new summit lava dome and two short, blocky lava flows grew during February and March 2006. A series of 7 daytime and 15 nighttime Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes were acquired in response to this new activity. This response was facilitated by a new ASTER Urgent Request Protocol system. The ASTER data provided several significant observations as a part of a much larger suite of real-time or near-real-time data from other satellite (AVHRR, MODIS), airborne (FLIR, visual, gas), and ground-based (seismometers, radiometers) sensors used at the Alaska Volcano Observatory (AVO). ASTER is well-suited to volcanic observations because of its 15-m to 90-m spatial resolution, its ability to be scheduled and point off-nadir, and its ability to collect visible-near infrared (VNIR) to thermal infrared (TIR) data during both the day and night. Aided by the volcano's high latitude (59.4°N) ASTER was able to provide frequent repeat imaging as short as one day between scenes with an average 6-day repeat during the height of activity. These data provided a time series of high-resolution VNIR, shortwave infrared (SWIR - detects temperatures from about 200°C to > 600°C averaged over a 30-m pixel), and TIR (detects temperatures up to about 100°C averaged over a 90-m pixel) data of the volcano and its eruptive products. Frequent satellite imaging of volcanoes is necessary to record rapid changes in activity and to avoid recurring cloud cover. Of the 22 ASTER scenes acquired between October 30, 2005 and May 30, 2006, the volcano was clear to partly cloudy in 13 scenes. The most useful pre-eruption ASTER Urgent Request image was acquired on December 20. These data

  7. Short period forecasting of catchment-scale precipitation. Part II: a water-balance storm model for short-term rainfall and flood forecasting

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2000-01-01

    Full Text Available A simple two-dimensional rainfall model, based on advection and conservation of mass in a vertical cloud column, is investigated for use in short-term rainfall and flood forecasting at the catchment scale under UK conditions. The model is capable of assimilating weather radar, satellite infra-red and surface weather observations, together with forecasts from a mesoscale numerical weather prediction model, to obtain frequently updated forecasts of rainfall fields. Such data assimilation helps compensate for the simplified model dynamics and, taken together, provides a practical real-time forecasting scheme for catchment scale applications. Various ways are explored for using information from a numerical weather prediction model (16.8 km grid within the higher resolution model (5 km grid. A number of model variants is considered, ranging from simple persistence and advection methods used as a baseline, to different forms of the dynamic rainfall model. Model performance is assessed using data from the Wardon Hill radar in Dorset for two convective events, on 10 June 1993 and 16 July 1995, when thunderstorms occurred over southern Britain. The results show that (i a simple advection-type forecast may be improved upon by using multiscan radar data in place of data from the lowest scan, and (ii advected, steady-state predictions from the dynamic model, using 'inferred updraughts', provides the best performance overall. Updraught velocity is inferred at the forecast origin from the last two radar fields, using the mass-balance equation and associated data and is held constant over the forecast period. This inference model proves superior to the buoyancy parameterisation of updraught employed in the original formulation. A selection of the different rainfall forecasts is used as input to a catchment flow forecasting model, the IH PDM (Probability Distributed Moisture model, to assess their effect on flow forecast accuracy for the 135 km2 Brue catchment

  8. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kunduz mineral district in Afghanistan: Chapter S in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kunduz mineral district, which has celestite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

  9. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Haji-Gak mineral district in Afghanistan: Chapter C in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Haji-Gak mineral district, which has iron ore deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  10. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kharnak-Kanjar mineral district in Afghanistan: Chapter K in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kharnak-Kanjar mineral district, which has mercury deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  11. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dudkash mineral district in Afghanistan: Chapter R in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dudkash mineral district, which has industrial mineral deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS

  12. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghunday-Achin mineral district in Afghanistan, in Davis, P.A, compiler, Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghunday-Achin mineral district, which has magnesite and talc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  13. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Dusar-Shaida mineral district in Afghanistan: Chapter I in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Dusar-Shaida mineral district, which has copper and tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the

  14. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  15. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Tourmaline mineral district in Afghanistan: Chapter J in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Tourmaline mineral district, which has tin deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  16. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

  17. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products

  18. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kundalyan mineral district in Afghanistan: Chapter H in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kundalyan mineral district, which has porphyry copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  19. Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of the Orbiting Carbon Observatory-2 Mission

    Directory of Open Access Journals (Sweden)

    Charles Miller

    2011-02-01

    Full Text Available The global characteristics of retrievals of the column-averaged CO2 dry air mole fraction, XCO2, from shortwave infrared observations has been studied using the expected measurement performance of the NASA Orbiting Carbon Observatory-2 (OCO-2 mission. This study focuses on XCO2 retrieval precision and averaging kernels and their sensitivity to key parameters such as solar zenith angle (SZA, surface pressure, surface type and aerosol optical depth (AOD, for both nadir and sunglint observing modes. Realistic simulations have been carried out and the single sounding retrieval errors for XCO2 have been derived from the formal retrieval error covariance matrix under the assumption that the retrieval has converged to the correct answer and that the forward model can adequately describe the measurement. Thus, the retrieval errors presented in this study represent an estimate of the retrieval precision. For nadir observations, we find single-sounding retrieval errors with values typically less than 1 part per million (ppm over most land surfaces for SZAs less than 70° and up to 2.5 ppm for larger SZAs. Larger errors are found over snow/ice and ocean surfaces due to their low albedo in the spectral regions of the CO2 absorption bands and, for ocean, also in the O2 A band. For sunglint observations, errors over the ocean are significantly smaller than in nadir mode with values in the range of 0.3 to 0.6 ppm for small SZAs which can decrease to values as small as 0.15 for the largest SZAs. The vertical sensitivity of the retrieval that is represented by the column averaging kernel peaks near the surface and exhibits values near unity throughout most of the troposphere for most anticipated scenes. Nadir observations over dark ocean or snow/ice surfaces and observations with large AOD and large SZA show a decreased sensitivity to near-surface CO2. All simulations are carried out for a mid-latitude summer atmospheric profile, a given aerosol type and

  20. Application of a Cloud-Texture Analysis Scheme to the Cloud Cluster Structure Recognition and Rainfall Estimation in a Mesoscale Rainstorm Process

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    It is thought that satellite infrared (IR) images can aid the recognition of the structure of the cloud and aid the rainfall estimation. In this article, the authors explore the application of a classification method relevant to four texture features, viz. energy, entropy, inertial-quadrature and local calm, to the study of the structure of a cloud cluster displaying a typical meso-scale structure on infrared satellite images.The classification using the IR satellite images taken during 4-5 July 2003, a time when a meso-scale torrential rainstorm was occurring over the Yangtze River basin, illustrates that the detailed structure of the cloud cluster can be obviously seen by means of the neural network classification method relevant to textural features, and the relationship between the textural energy and rainfall indicates that the structural variation of a cloud cluster can be viewed as an exhibition of the convection intensity evolvement. These facts suggest that the scheme of following a classification method relevant to textural features applied to cloud structure studies is helpful for weather analysis and forecasting.

  1. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Kandahar mineral district in Afghanistan: Chapter Z in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Kandahar mineral district, which has bauxite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2006,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS

  2. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  4. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Uruzgan mineral district in Afghanistan: Chapter V in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Uruzgan mineral district, which has tin and tungsten deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  5. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni1 mineral district in Afghanistan: Chapter DD in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni1 mineral district, which has spectral reflectance anomalies indicative of clay, aluminum, gold, silver, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such

  6. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Ghazni2 mineral district in Afghanistan: Chapter EE in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Ghazni2 mineral district, which has spectral reflectance anomalies indicative of gold, mercury, and sulfur deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2008, 2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image

  7. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

  8. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match

  9. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Bakhud mineral district in Afghanistan: Chapter U in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Bakhud mineral district, which has industrial fluorite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  10. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Zarkashan mineral district in Afghanistan: Chapter G in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Zarkashan mineral district, which has copper and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  11. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Takhar mineral district in Afghanistan: Chapter Q in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Takhar mineral district, which has industrial evaporite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  12. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Farah mineral district in Afghanistan: Chapter FF in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2014-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Farah mineral district, which has spectral reflectance anomalies indicative of copper, zinc, lead, silver, and gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that

  13. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Khanneshin mineral district in Afghanistan: Chapter A in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.; Arko, Scott A.; Harbin, Michelle L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Khanneshin mineral district, which has uranium, thorium, rare-earth-element, and apatite deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be

  14. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the South Helmand mineral district in Afghanistan: Chapter O in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the South Helmand mineral district, which has travertine deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  15. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As

  16. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Baghlan mineral district in Afghanistan: Chapter P in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.; Cagney, Laura E.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Baghlan mineral district, which has industrial clay and gypsum deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2006, 2007, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from

  17. Variability of the infrared complex refractive index of African mineral dust: experimental estimation and implications for radiative transfer and satellite remote sensing

    Directory of Open Access Journals (Sweden)

    C. Di Biagio

    2014-04-01

    Full Text Available Experimental estimations of the infrared refractive index of African mineral dust have been retrieved from laboratory measurements of particle transmission spectra in the wavelength range 2.5–25 μm. Five dust samples collected at Banizoumbou (Niger and Tamanrasset (Algeria during dust events originated from different Western Saharan and Sahelian areas have been investigated. The obtained real (n and imaginary (k parts of the refractive index for the different dust cases vary in the range 1.1–2.7 and 0.05–1.0, respectively, and appear to be strongly sensitive to the mineralogical composition of the particles, especially in the 8–12 μm and 17–25 μm spectral intervals. Dust absorption is controlled mainly by clays, and, in minor fraction, by quartz and Ca-rich minerals. Size distribution, and the coarse fraction in particular, plays also a role in determining the refractive index. Significant differences are obtained when comparing our results with existing experimental estimations available in the literature, and with the values of the OPAC (Optical Properties of Aerosols and Clouds database. The different datasets appear comparable in magnitude, with our values of n and k falling in the range of variability of past studies. However, literature data fail in accurately reproducing the spectral signatures of main minerals, in particular clays, and they significantly overestimate the contribution of quartz. We also found that the real and the imaginary parts of the refractive index from part of literature studies do not verify Kramers–Kronig relations, thus resulting theoretically incorrect. The comparison between our results, from Western Africa, and literature data, from different locations in Europe, Africa, and the Caribbean, nonetheless, confirms the expected large variability of the infrared refractive index of dust, thus highlighting the necessity for an extended systematic investigation. Aerosol intensive optical properties

  18. 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.

  19. Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite

    Science.gov (United States)

    Cao, Changyong; DeLuccia, Frank J.; Xiong, Xiaoxiong; Wolfe, Robert; Weng, Fuzhong

    2014-01-01

    The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key environmental remote-sensing instruments onboard the Suomi National Polar-Orbiting Partnership spacecraft, which was successfully launched on October 28, 2011 from the Vandenberg Air Force Base, California. Following a series of spacecraft and sensor activation operations, the VIIRS nadir door was opened on November 21, 2011. The first VIIRS image acquired signifies a new generation of operational moderate resolution-imaging capabilities following the legacy of the advanced very high-resolution radiometer series on NOAA satellites and Terra and Aqua Moderate-Resolution Imaging Spectroradiometer for NASA's Earth Observing system. VIIRS provides significant enhancements to the operational environmental monitoring and numerical weather forecasting, with 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns, providing the sensor data records for 23 environmental data records including aerosol, cloud properties, fire, albedo, snow and ice, vegetation, sea surface temperature, ocean color, and nigh-time visible-light-related applications. Preliminary results from the on-orbit verification in the postlaunch check-out and intensive calibration and validation have shown that VIIRS is performing well and producing high-quality images. This paper provides an overview of the onorbit performance of VIIRS, the calibration/validation (cal/val) activities and methodologies used. It presents an assessment of the sensor initial on-orbit calibration and performance based on the efforts from the VIIRS-SDR team. Known anomalies, issues, and future calibration efforts, including the long-term monitoring, and intercalibration are also discussed.

  20. 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...

  1. EPSAT-SG: a satellite method for precipitation estimation; its concepts and implementation for the AMMA experiment

    Directory of Open Access Journals (Sweden)

    J. C. Bergès

    2010-01-01

    Full Text Available This paper presents a new rainfall estimation method, EPSAT-SG which is a frame for method design. The first implementation has been carried out to meet the requirement of the AMMA database on a West African domain. The rainfall estimation relies on two intermediate products: a rainfall probability and a rainfall potential intensity. The first one is computed from MSG/SEVIRI by a feed forward neural network. First evaluation results show better properties than direct precipitation intensity assessment by geostationary satellite infra-red sensors. The second product can be interpreted as a conditional rainfall intensity and, in the described implementation, it is extracted from GPCP-1dd. Various implementation options are discussed and comparison of this embedded product with 3B42 estimates demonstrates the importance of properly managing the temporal discontinuity. The resulting accumulated rainfall field can be presented as a GPCP downscaling. A validation based on ground data supplied by AGRHYMET (Niamey indicates that the estimation error has been reduced in this process. The described method could be easily adapted to other geographical area and operational environment.

  2. 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.

  3. Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Parwan mineral district in Afghanistan: Chapter CC in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan

    Science.gov (United States)

    Davis, Philip A.

    2013-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Parwan mineral district, which has gold and copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006, 2007), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such

  4. 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

  5. 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...

  6. Evaluation of rainfall retrievals from SEVIRI reflectances over West Africa using TRMM-PR and CMORPH

    Science.gov (United States)

    Wolters, E. L. A.; van den Hurk, B. J. J. M.; Roebeling, R. A.

    2011-02-01

    This paper describes the evaluation of the KNMI Cloud Physical Properties - Precipitation Properties (CPP-PP) algorithm over West Africa. The algorithm combines condensed water path (CWP), cloud phase (CPH), cloud particle effective radius (re), and cloud-top temperature (CTT) retrievals from visible, near-infrared and thermal infrared observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellites to estimate rain occurrence frequency and rain rate. For the 2005 and 2006 monsoon seasons, it is investigated whether the CPP-PP algorithm is capable of retrieving rain occurrence frequency and rain rate over West Africa with sufficient accuracy, using Tropical Monsoon Measurement Mission Precipitation Radar (TRMM-PR) as reference. As a second goal, it is assessed whether SEVIRI is capable of monitoring the seasonal and daytime evolution of rainfall during the West African monsoon (WAM), using Climate Prediction Center Morphing Technique (CMORPH) rainfall observations. The SEVIRI-detected rainfall area agrees well with TRMM-PR, with the areal extent of rainfall by SEVIRI being ~10% larger than from TRMM-PR. The mean retrieved rain rate from CPP-PP is about 8% higher than from TRMM-PR. Examination of the TRMM-PR and CPP-PP cumulative frequency distributions revealed that differences between CPP-PP and TRMM-PR are generally within +/-10%. Relative to the AMMA rain gauge observations, CPP-PP shows very good agreement up to 5 mm h-1. However, at higher rain rates (5-16 mm h-1) CPP-PP overestimates compared to the rain gauges. With respect to the second goal of this paper, it was shown that both the accumulated precipitation and the seasonal progression of rainfall throughout the WAM is in good agreement with CMORPH, although CPP-PP retrieves higher amounts in the coastal region of West Africa. Using latitudinal Hovmüller diagrams, a fair correspondence between CPP-PP and CMORPH was found, which is reflected

  7. Evaluation of rainfall retrievals from SEVIRI reflectances over West Africa using TRMM-PR and CMORPH

    Directory of Open Access Journals (Sweden)

    E. L. A. Wolters

    2011-02-01

    Full Text Available This paper describes the evaluation of the KNMI Cloud Physical Properties – Precipitation Properties (CPP-PP algorithm over West Africa. The algorithm combines condensed water path (CWP, cloud phase (CPH, cloud particle effective radius (re, and cloud-top temperature (CTT retrievals from visible, near-infrared and thermal infrared observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI onboard the Meteosat Second Generation (MSG satellites to estimate rain occurrence frequency and rain rate. For the 2005 and 2006 monsoon seasons, it is investigated whether the CPP-PP algorithm is capable of retrieving rain occurrence frequency and rain rate over West Africa with sufficient accuracy, using Tropical Monsoon Measurement Mission Precipitation Radar (TRMM-PR as reference. As a second goal, it is assessed whether SEVIRI is capable of monitoring the seasonal and daytime evolution of rainfall during the West African monsoon (WAM, using Climate Prediction Center Morphing Technique (CMORPH rainfall observations. The SEVIRI-detected rainfall area agrees well with TRMM-PR, with the areal extent of rainfall by SEVIRI being ~10% larger than from TRMM-PR. The mean retrieved rain rate from CPP-PP is about 8% higher than from TRMM-PR. Examination of the TRMM-PR and CPP-PP cumulative frequency distributions revealed that differences between CPP-PP and TRMM-PR are generally within +/−10%. Relative to the AMMA rain gauge observations, CPP-PP shows very good agreement up to 5 mm h−1. However, at higher rain rates (5–16 mm h−1 CPP-PP overestimates compared to the rain gauges. With respect to the second goal of this paper, it was shown that both the accumulated precipitation and the seasonal progression of rainfall throughout the WAM is in good agreement with CMORPH, although CPP-PP retrieves higher amounts in the coastal region of West Africa. Using latitudinal Hovmüller diagrams, a fair

  8. Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi

    Directory of Open Access Journals (Sweden)

    D. Kneis

    2014-01-01

    Full Text Available 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 gage-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 gage data was evaluated at the sub-basin scale. Second, the quality of the rainfall estimates was assessed by analyzing 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 gage-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 gage 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 gage-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 regionalization of rain gage 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 gage data were used as model input (Nash–Sutcliffe Index of 0.76–0.88 at gages not

  9. Rainfall Controls on Land Surface Phenology over "Never-green" and "Ever-green" Lands in Africa

    Science.gov (United States)

    Yan, D.; Zhang, X.; Yu, Y.; Guo, W.

    2015-12-01

    The characteristics of land surface phenology (LSP) in the "Never-green" Sahara desert and the "Ever-green" equatorial Congo Basin were rarely discussed due to the extremely low seasonal greenness variations across the Sahara desert and the prolonged cloud cover over the Congo Basin. Based on 30-minute observations acquired by the Spinning Enhanced Visible and Infrared Imager onboard the METEOSAT geostationary satellites, we generated a three-day angularly corrected Two-band Enhanced Vegetation Index (EVI2) time series for each year between 2006 and 2013. We further reconstructed EVI2 temporal trajectories and retrieved LSP transitions using the Hybrid Piecewise Logistic Model. We associated the LSP transitions with the rainy season transitions derived from the Tropical Rainfall Measurement Mission Product 3B42. Results show that LSP within both the Sahara Desert and the Congo Basin was strongly controlled by the rainfall seasonality. Specially, although there is no vegetation growth in most part of the Sahara Desert, recurring LSP was spatially detected in irrigation agriculture and the geomorphological regions of wadis, dayas, chotts/sebkhas and rocky hills. These geomorphological features are able to store moisture in soil to keep plants growing during the long dry seasons after vegetation greenup is triggered by rainfall events. The spatial shift of phenological timing is controlled by the Mediterranean rainfall regime in the north and the rainfalls brought by the Intertropical Convergence Zone (ITCZ) in the south. Across the equatorial Congo Basin, EVI2 time series reveals that canopy greenness cycles (CGC) of the seasonal leaf variation occur in tropical rainforests, which differs from the commonly termed "growing season" with complete leafless canopies. The seasonal EVI2 amplitude is very small and represents the gradual "leaf-exchange" processes. Two annual CGC are found and their spatial shifts closely follow the seasonal migration of ITCZ precipitation.

  10. 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.

  11. Verification of ensemble forecasts of Mediterranean high-impact weather events against satellite observations

    Directory of Open Access Journals (Sweden)

    J.-P. Chaboureau

    2012-08-01

    Full Text Available Ensemble forecasts at kilometre scale of two severe storms over the Mediterranean region are verified against satellite observations. In complement to assessing the forecasts against ground-based measurements, brightness temperature (BT images are computed from forecast fields and directly compared to BTs observed from satellite. The so-called model-to-satellite approach is very effective in identifying systematic errors in the prediction of cloud cover for BTs in the infrared window and in verifying the forecasted convective activity with BTs in the microwave range. This approach is combined with the calculation of meteorological scores for an objective evaluation of ensemble forecasts. The application of the approach is shown in the context of two Mediterranean case studies, a tropical-like storm and a heavy precipitating event. Assessment of cloud cover and convective activity using satellite observations in the infrared (10.8 μm and microwave regions (183–191 GHz provides results consistent with other traditional methods using rainfall measurements. In addition, for the tropical-like storm, differences among forecasts occur much earlier in terms of cloud cover and deep convective activity than they do in terms of deepening and track. Further, the underdispersion of the ensemble forecasts of the two high-impact weather events is easily identified with satellite diagnostics. This suggests that such an approach could be a useful method for verifying ensemble forecasts, particularly in data-sparse regions.

  12. 天基红外卫星协同预警临空高速目标配置优化%Optimization of space-based infrared satellites deployment for near-space hypersonic target warning

    Institute of Scientific and Technical Information of China (English)

    谢鑫; 李为民; 黄仁全

    2015-01-01

    围绕天基红外卫星协同预警临空高速目标配置问题,考虑临空高速目标预警的任务需求和不同轨道卫星的覆盖特性,建立了 GEO、HEO 和 LEO 红外预警卫星的配置优化模型。在给定的威胁想定和传感器参数设置下,经仿真求解,构型为“5GEO +3HEO +24/4/2LEO”的天基红外预警卫星星座可满足临空高速目标防御对天基预警系统的预警需求。%Aiming at the problem of space-based infrared satellites deployment for near-space hypersonic target warning, the optimization models for the deployments of GEO,HEO and LEO infrared satellites are established respectively,ac-cording to the requirements of near-space hypersonic target warning and the coverage characteristics of satellites on dif-ferent orbits.Under the conditions of the fixed threat assumption and the sensors parameter setting,the models were sim-ulated and analyzed.The simulation results show that the space-based infrared warning system with the construction of‘5GEO +3HEO +24/4/2LEO’can satisfy the warning requirements for near-space hypersonic target defense.

  13. Quantitative mapping of rainfall rates over the oceans utilizing Nimbus-5 ESMR data

    Science.gov (United States)

    Rao, M. S. V.; Abbott, W. V.

    1976-01-01

    The electrically scanning microwave radiometer (ESMR) data from the Nimbus 5 satellite was used to deduce estimates of precipitation amount over the oceans. An atlas of the global oceanic rainfall was prepared and the global rainfall maps analyzed and related to available ground truth information as well as to large scale processes in the atmosphere. It was concluded that the ESMR system provides the most reliable and direct approach yet known for the estimation of rainfall over sparsely documented, wide oceanic regions.

  14. Spatial Variability of Rainfall

    DEFF Research Database (Denmark)

    Jensen, N.E.; Pedersen, Lisbeth

    2005-01-01

    As a part of a Local Area Weather Radar (LAWR) calibration exercise 15 km south of Århus, Denmark, the variability in accumulated rainfall within a single radar pixel (500 by 500 m) was measured using nine high-resolution rain gauges. The measured values indicate up to a 100% variation between...

  15. The Wageningen Rainfall Simulator

    NARCIS (Netherlands)

    Lassu, Tamas; Seeger, K.M.; Peters, P.D.; Keesstra, S.D.

    2015-01-01

    The set-up and characterisation of an indoor nozzle-type rainfall simulator (RS) at Wageningen University, the Netherlands, are presented. It is equipped with four Lechler nozzles (two nr. 460·788 and two nr. 461·008). The tilting irrigation plot is 6 m long and 2·5 m wide. An electrical pump

  16. On the sensitivity of Tropical Rainfall Measuring Mission (TRMM) Microwave Imager channels to overland rainfall

    Science.gov (United States)

    You, Yalei; Liu, Guosheng; Wang, Yu; Cao, Jie

    2011-06-01

    The response of brightness temperatures at different microwave frequencies to overland precipitation is investigated by using the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and Microwave Imager (TMI) data. The Spearman correlation coefficients between observations at TMI channels or channel combinations and PR-measured near-surface rain are computed using 3 years of TRMM data. The results showed that the brightness temperature combinations from 19 and 37 GHz, that is, V19-V37 (the letter V denotes vertical polarization, and the numbers denote frequency in GHz) or V21-V37, can explain ˜10% more variance of near-surface rainfall rate than can the V85 brightness temperature. Also, the global distribution of the above correlation revealed that over almost all of the tropical land area covered by TRMM satellite, the V19-V37 channel has a closer response to the overland rainfall than does the V85 channel. This result is somewhat counterintuitive, because it has been long believed that the dominant signature of overland rainfall is the brightness temperature depression caused by ice scattering at high microwave frequencies (e.g., 85 GHz). To understand the underlying physics of this better low-frequency response, data analysis and radiative transfer modeling have been conducted to assess the influence on brightness temperatures from clouds with different ice and liquid water partitions. The results showed that under the condition of low frozen water and medium liquid water in the atmospheric column, the signal from the V19-V37 channel responded better to rainfall rate than did the one from the V85 channel. A plausible explanation to this result is that in addition to ice scattering signature, the V19-V37 channel contains liquid water information as well, which is more directly related to surface rain than to ice water aloft. At heavy rainfall conditions, the V19-V37, V37, and V85 channels all are correlated with near-surface rain reasonably well

  17. 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

  18. The Winter Rainfall of Malaysia

    National Research Council Canada - National Science Library

    Chen, Tsing-Chang; Tsay, Jenq-Dar; Yen, Ming-Cheng; Matsumoto, Jun

    2013-01-01

    .... The major cause of the rainfall maximum of Peninsular Malaysia is cold surge vortices (CSVs) and heavy rainfall/flood (HRF) events propagating from the Philippine area and Borneo. In contrast, the major cause of the rainfall maximum of Borneo is these rain-producing disturbances trapped in Borneo. Disturbances of the former group are formed by the cold sur...

  19. The Structure and Rainfall Features of Tropical Cyclone Rammasun (2002)

    Institute of Scientific and Technical Information of China (English)

    马雷鸣; 端义宏; 朱永褆

    2004-01-01

    Tropical Rainfall Measuring Mission (TRMM) data [TRMM Microwave Imager/Precipitation Radar/Visible and Infrared Scanner (TMI/PR/VIRS)] and a numerical model are used to investigate the structure and rainfall features of Tropical Cyclone (TC) Rammasun (2002). Based on the analysis of TRMM data, which are diagnosed together with NCEP/AVN [Aviation (global model)] analysis data,some typical features of TC structure and rainfall are preliminary discovered. Since the limitations of TRMM data are considered for their time resolution and coverage, the world observed by TRMM at several moments cannot be taken as the representation of the whole period of the TC lifecycle, therefore the picture should be reproduced by a numerical model of high quality. To better understand the structure and rainfall features of TC Rammasun, a numerical simulation is carried out with mesoscale model MM5in which the validations have been made with the data of TRMM and NCEP/AVN analysis.

  20. Evaluation of TRMM rainfall estimates over a large Indian river basin (Mahanadi

    Directory of Open Access Journals (Sweden)

    D. Kneis

    2014-07-01

    Full Text Available 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

  1. GHRSST Level 2P Global 1 meter Sea Surface Temperature from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS)....

  2. A rainfall-based warning model for shallow landslides

    Science.gov (United States)

    Zeng, Yi-Chao; Wang, Ji-Shang; Jan, Chyan-Deng; Yin, Hsiao-Yuan; Lo, Wen-Chun

    2016-04-01

    According to the statistical data of past rainfall events, the climate has changed in recent decades. Rainfall patterns have presented a more concentrated, high-intensity and long-duration trend in Taiwan. The most representative event is Typhoon Morakot which induced a total of 67 enormous landslides by the extreme amount of rain during August 7 to 10 in 2009 and resulted in the heaviest casualties in southern Taiwan. In addition, the nature of vulnerability such as steep mountains and rushing rivers, fragile geology and loose surface soil results in more severe sediment-relative disasters, in which shallow landslides are widespread hazards in mountainous regions. This research aims to develop and evaluate a model for predicting shallow landslides triggered by rainfall in mountainous area. Considering the feasibility of large-scale application and practical operation, the statistical techniques is adopted to form the landslide model based on abundant historical rainfall data and landslide events. The 16 landslide inventory maps and 15 variation results by comparing satellite images taken before and after the rainfall event were interpreted and delineated since 2004 to 2011. Logit model is utilized for interpreting the relationship between rainfall characteristics and landslide events delineated from satellite. Based on the analysis results of logistic regression, the rainfall factors that are highly related to shallow landslide occurrence are selected which are 3 hours rainfall intensity I3 (mm/hr) and the effective cumulative precipitation Rt (mm) including accumulated rainfall at time t and antecedent rainfall. A landslide rainfall triggering index (LRTI) proposed for assessing the occurrence potential of shallow landslides is defined as the product of I3 and Rt. A form of probability of shallow landslide triggered threshold is proposed to offer a measure of the likelihood of landslide occurrence. Two major critical lines which represent the lower and upper

  3. The asymmetry of rainfall process

    Institute of Scientific and Technical Information of China (English)

    YU RuCong; YUAN WeiHua; LI Jian

    2013-01-01

    Using hourly station rain gauge data in the warm season (May-October) during 1961-2006,the climatological features of the evolution of the rainfall process are analyzed by compositing rainfall events centered on the maximum hourly rainfall amount of each event.The results reveal that the rainfall process is asymmetric,which means rainfall events usually reach the maximum in a short period and then experience a relatively longer retreat to the end of the event.The effects of rainfall intensity,duration and peak time,as well as topography,are also considered.It is found that the asymmetry is more obvious in rainfall events with strong intensity and over areas with complex terrain,such as the eastern margin of the Tibetan Plateau,the Hengduan Mountains,and the Yungui Plateau.The asymmetry in short-duration rainfall is more obvious than that in long-duration rainfall,but the regional differences are weaker.The rainfall events that reach the maximum during 14:00-02:00 LST exhibit the strongest asymmetry and those during 08:00-14:00 LST show the weakest asymmetry.The rainfall intensity at the peak time stands out,which means that the rainfall intensity increases and decreases quickly both before and after the peak.These results can improve understanding of the rainfall process and provide metrics for the evaluation of climate models.Moreover,the strong asymmetry of the rainfall process should be highly noted when taking measures to defending against geological hazards,such as collapses,landslides and debris flows throughout southwestern China.

  4. Saturn's satellites - Near-infrared spectrophotometry (0.65-2.5 microns) of the leading and trailing sides and compositional implications

    Science.gov (United States)

    Steele, A.; Clark, R. N.; Brown, R. H.; Owensby, P. D.

    1984-01-01

    Water ice absorptions at 2.0, 1.5, and 1.25 microns are noted in near-IR spectra of Tethys, Dione, Rhea, Iapetus, and Hyperion, and the weak 1.04-micron ice absorption, which is detected for Rhea and Dione, is studied to establish band depth upper limits. The leading-trailing side 1.04-micron ice band depth differences on Saturn's satellites are similar to those for the Galilean satellites, indicating possible surface modification by magnetospheric charged particle bombardment. Limits are obtained for the amounts of particulates, trapped gases, and ammonium hydroxide on the surface. With the exception of the dark side of Iapetus, the surfaces of all of Saturn's satellites are nearly pure ice water.

  5. Comparison of recorded rainfall with quantitative precipitation forecast in a rainfall-runoff simulation for the Langat River Basin, Malaysia

    Science.gov (United States)

    Billa, Lawal; Assilzadeh, Hamid; Mansor, Shattri; Mahmud, Ahmed; Ghazali, Abdul

    2011-09-01

    Observed rainfall is used for runoff modeling in flood forecasting where possible, however in cases where the response time of the watershed is too short for flood warning activities, a deterministic quantitative precipitation forecast (QPF) can be used. This is based on a limited-area meteorological model and can provide a forecasting horizon in the order of six hours or less. This study applies the results of a previously developed QPF based on a 1D cloud model using hourly NOAA-AVHRR (Advanced Very High Resolution Radiometer) and GMS (Geostationary Meteorological Satellite) datasets. Rainfall intensity values in the range of 3-12 mm/hr were extracted from these datasets based on the relation between cloud top temperature (CTT), cloud reflectance (CTR) and cloud height (CTH) using defined thresholds. The QPF, prepared for the rainstorm event of 27 September to 8 October 2000 was tested for rainfall runoff on the Langat River Basin, Malaysia, using a suitable NAM rainfall-runoff model. The response of the basin both to the rainfall-runoff simulation using the QPF estimate and the recorded observed rainfall is compared here, based on their corresponding discharge hydrographs. The comparison of the QPF and recorded rainfall showed R2 = 0.9028 for the entire basin. The runoff hydrograph for the recorded rainfall in the Kajang sub-catchment showed R2 = 0.9263 between the observed and the simulated, while that of the QPF rainfall was R2 = 0.819. This similarity in runoff suggests there is a high level of accuracy shown in the improved QPF, and that significant improvement of flood forecasting can be achieved through `Nowcasting', thus increasing the response time for flood early warnings.

  6. 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...

  7. Borneo vortex and mesoscale convective rainfall

    Science.gov (United States)

    Koseki, S.; Koh, T.-Y.; Teo, C.-K.

    2014-05-01

    We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite data sets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the Equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a "perpetual" cold surge. The Borneo vortex is manifested as a meso-α cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth/maintenance of the meso-α cyclone was achieved mainly by the vortex stretching. This vortex stretching is due to the upward motion forced by the latent heat release around the cyclone centre. The comma-shaped rainband consists of clusters of meso-β-scale rainfall cells. The intense rainfall in the comma head (comma tail) is generated by the confluence of the warmer and wetter cyclonic easterly flow (cyclonic southeasterly flow) and the cooler and drier northeasterly surge in the northwestern (northeastern) sector of the cyclone. Intense upward motion and heavy rainfall resulted due to the low-level convergence and the favourable thermodynamic profile at the confluence zone. In particular, the convergence in the northwestern sector is responsible for maintenance of the meso-α cyclone system. At both meso-α and meso-β scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is significantly self-enhanced by the nonlinear dynamics.

  8. Advances in satellite oceanography

    Science.gov (United States)

    Brown, O. B.; Cheney, R. E.

    1983-01-01

    Technical advances and recent applications of active and passive satellite remote sensing techniques to the study of oceanic processes are summarized. The general themes include infrared and visible radiometry, active and passive microwave sensors, and buoy location systems. The surface parameters of sea surface temperature, windstream, sea state, altimetry, color, and ice are treated as applicable under each of the general methods.

  9. Ballistic missile tracking performance in boost phase based on dual infrared early warning satellites%红外预警双星弹道导弹主动段跟踪性能

    Institute of Scientific and Technical Information of China (English)

    钟宇; 吴晓燕; 黄树彩; 吴建峰; 李成景; 唐意东

    2015-01-01

    为研究反导作战中红外预警卫星系统对弹道导弹主动段弹道的跟踪性能,提出以后验克拉美-罗下界(Posterior Cramer-Rao Lower Bound, PCRLB)为衡量指标,结合8态重力转弯主动段运动模型和双星纯方位无源定位获取的量测量,系统分析了运动建模精度、量测精度、采样周期、测源不确定性下检测概率和虚警数目等因素对跟踪时效性和准确性的影响.仿真算例给出了上述因素对位置和速度跟踪性能的影响程度和规律,可为预警卫星反导作战、战技指标关联建模以及星载探测器优化设计等提供有意义的参考.%To study the ballistic missile tracking performance in boost phase based on infrared early warning satellites system, Posterior Cramer-Rao Lower Bound (PCRLB) was proposed as a measurement index. After modeling ballistic target motion by 8-state gravity turn model and locating target position by dual satellites' bearing-only passive localization, PCRLB was used to evaluate the effects of factors, including target motion model accuracy, measurement accuracy, sampling period, detection probability and false alarm number conditioned by measurement origin uncertainty, on tracking timeliness and accuracy. One simulation example showed the extent and rules of said factors on position and tracking performance of velocity. It can contribute to the anti-ballistic missile operation by early warning satellite, the relationship modeling between tactical and technical indices and the optimal design of satellite-based infrared detector.

  10. Global detection and analysis of coastline associated rainfall using objective pattern recognition techniques

    CERN Document Server

    Bergemann, Martin; Lane, Todd P

    2015-01-01

    Coastally induced rainfall is a common feature especially in tropical and subtropical regions. However, it has been difficult to quantify the contribution of coastal rainfall features to the overall local rainfall. We develop a novel technique to objectively identify precipitation associated with land-sea interaction and apply it to satellite based rainfall estimates. The Maritime Continent, the Bight of Panama, Madagascar and the Mediterranean are found to be regions where land-sea interactions plays a crucial role in the formation of precipitation. In these regions $\\approx$ 40\\% to 60\\% of the total rainfall can be related to coastline effects. Due to its importance for the climate system, the Maritime Continent is a particular region of interest with high overall amounts of rainfall and large fractions resulting from land-sea interactions throughout the year. To demonstrate the utility of our identification method we investigate the influence of several modes of variability, such as the Madden-Julian-Osci...

  11. 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.

  12. Satellite Communication.

    Science.gov (United States)

    Technology Teacher, 1985

    1985-01-01

    Presents a discussion of communication satellites: explains the principles of satellite communication, describes examples of how governments and industries are currently applying communication satellites, analyzes issues confronting satellite communication, links mathematics and science to the study of satellite communication, and applies…

  13. Bayesian spatiotemporal interpolation of rainfall in the Central Chilean Andes

    Science.gov (United States)

    Ossa-Moreno, Juan; Keir, Greg; McIntyre, Neil

    2016-04-01

    Water availability in the populous and economically significant Central Chilean region is governed by complex interactions between precipitation, temperature, snow and glacier melt, and streamflow. Streamflow prediction at daily time scales depends strongly on accurate estimations of precipitation in this predominantly dry region, particularly during the winter period. This can be difficult as gauged rainfall records are scarce, especially in the higher elevation regions of the Chilean Andes, and topographic influences on rainfall are not well understood. Remotely sensed precipitation and topographic products can be used to construct spatiotemporal multivariate regression models to estimate rainfall at ungauged locations. However, classical estimation methods such as kriging cannot easily accommodate the complicated statistical features of the data, including many 'no rainfall' observations, as well as non-normality, non-stationarity, and temporal autocorrelation. We use a separable space-time model to predict rainfall using the R-INLA package for computationally efficient Bayesian inference, using the gridded CHIRPS satellite-based rainfall dataset and digital elevation models as covariates. We jointly model both the probability of rainfall occurrence on a given day (using a binomial likelihood) as well as amount (using a gamma likelihood or similar). Correlation in space and time is modelled using a Gaussian Markov Random Field (GMRF) with a Matérn spatial covariance function which can evolve over time according to an autoregressive model if desired. It is possible to evaluate the GMRF at relatively coarse temporal resolution to speed up computations, but still produce daily rainfall predictions. We describe the process of model selection and inference using an information criterion approach, which we use to objectively select from competing models with various combinations of temporal smoothing, likelihoods, and autoregressive model orders.

  14. 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

  15. Máscara de espalhamento e precipitação para os canais microondas do satélite NOAA Scattering and rainfall mask for microwave channels of NOAA satellite

    Directory of Open Access Journals (Sweden)

    João C. Carvalho

    2005-12-01

    Full Text Available Propõe-se, com o presente trabalho, avaliar uma metodologia para identificação de pixels contaminados por precipitação e/ou espalhamento utilizando-se dados dos canais do Advanced Microwave Sensor Unit (AMSU. A aplicação de metodologias desse tipo é útil para a inferência de perfis verticais de temperatura e umidade no Brasil, em situações de céu coberto. A validação dos resultados foi feita com base em um estudo de caso, em que se aplicou uma análise subjetiva, tomando-se como modelo a comparação com imagens das bandas infravermelho, visível e microondas. Os resultados mostraram excelente concordância entre os topos de nuvens com temperaturas de brilho baixas, afetadas pelo efeito de espalhamento devido à presença de chuva e gelo, e as áreas identificadas pelo algoritmo como sendo contaminadas por este efeito. O algoritmo conseguiu identificar adequadamente os locais sob influência de precipitação e/ou espalhamento.This work presents a methodology to identify precipitation and/or scattering pixels in the Advanced Microwave Sensor Unit (AMSU channels. This procedure is useful for applications in atmospheric temperature and moisture retrievals over Brazil under cloudy sky conditions. A subjective analysis based on a case study involving comparisons with infrared, visible and microwave images was applied for validation purpose. The results show an excellent relationship of cloud tops with low brightness temperature affected by scattering due to water drops and ice and the areas identified by the algorithm as being influenced by precipitation and/or scattering effect.

  16. Rainfall statistics changes in Sicily

    Directory of Open Access Journals (Sweden)

    E. Arnone

    2013-02-01

    Full Text Available Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles which can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood prone areas.

    In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends while for longer durations the trends are mainly negative.

    Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the non parametric Mann–Kendall test.

    Particularly, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration while daily rainfall properties have been analyzed in term of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations

  17. Rainfall statistics changes in Sicily

    Directory of Open Access Journals (Sweden)

    E. Arnone

    2013-07-01

    Full Text Available Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles that can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood-prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends, while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the nonparametric Mann–Kendall test. In particular, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration, while daily rainfall properties have been analyzed in terms of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for 1 h rainfall

  18. Internationally coordinated multi-mission planning is now critical to sustain the space-based rainfall observations needed for managing floods globally

    Science.gov (United States)

    Reed, Patrick M.; Chaney, Nathaniel W.; Herman, Jonathan D.; Ferringer, Matthew P.; Wood, Eric F.

    2015-02-01

    At present 4 of 10 dedicated rainfall observing satellite systems have exceeded their design life, some by more than a decade. Here, we show operational implications for flood management of a ‘collapse’ of space-based rainfall observing infrastructure as well as the high-value opportunities for a globally coordinated portfolio of satellite missions and data services. Results show that the current portfolio of rainfall missions fails to meet operational data needs for flood management, even when assuming a perfectly coordinated data product from all current rainfall-focused missions (i.e., the full portfolio). In the full portfolio, satellite-based rainfall data deficits vary across the globe and may preclude climate adaptation in locations vulnerable to increasing flood risks. Moreover, removing satellites that are currently beyond their design life (i.e., the reduced portfolio) dramatically increases data deficits globally and could cause entire high intensity flood events to be unobserved. Recovery from the reduced portfolio is possible with internationally coordinated replenishment of as few as 2 of the 4 satellite systems beyond their design life, yielding rainfall data coverages that outperform the current full portfolio (i.e., an optimized portfolio of eight satellites can outperform ten satellites). This work demonstrates the potential for internationally coordinated satellite replenishment and data services to substantially enhance the cost-effectiveness, sustainability and operational value of space-based rainfall observations in managing evolving flood risks.

  19. Spatial dependence of extreme rainfall

    Science.gov (United States)

    Radi, Noor Fadhilah Ahmad; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Azman, Muhammad Az-zuhri

    2017-05-01

    This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

  20. Gridded daily Indian monsoon rainfall for 14 seasons: Merged TRMM and IMD gauge analyzed values

    Indian Academy of Sciences (India)

    Ashis K Mitra; I M Momin; E N Rajagopal; S Basu; M N Rajeevan; T N Krishnamurti

    2013-10-01

    Indian monsoon is an important component of earth’s climate system. Daily rainfall data for longer period is vital to study components and processes related to Indian monsoon. Daily observed gridded rainfall data covering both land and adjoining oceanic regions are required for numerical model validation and model development for monsoon. In this study, a new gridded daily Indian rainfall dataset at 1° × 1° latitude/longitude resolution covering 14 monsoon seasons (1998–2011) are described. This merged satellite gauge rainfall dataset (NMSG) combines TRMM TMPA rainfall estimates with gauge information from IMD gridded data. Compared to TRMM and GPCP daily rainfall data, the current NMSG daily data has more information due to inclusion of local gauge analysed values. In terms of bias and skill scores this dataset is superior to other daily rainfall datasets. In a mean climatological sense and also for anomalous monsoon seasons, this merged satellite gauge data brings out more detailed features of monsoon rainfall. The difference of NMSG and GPCP looks significant. This dataset will be useful to researchers for monsoon intraseasonal studies and monsoon model development research.

  1. Spatial random downscaling of rainfall signals in Andean heterogeneous terrain

    Science.gov (United States)

    Posadas, A.; Duffaut Espinosa, L. A.; Yarlequé, C.; Carbajal, M.; Heidinger, H.; Carvalho, L.; Jones, C.; Quiroz, R.

    2015-07-01

    Remotely sensed data are often used as proxies for indirect precipitation measures over data-scarce and complex-terrain areas such as the Peruvian Andes. Although this information might be appropriate for some research requirements, the extent at which local sites could be related to such information is very limited because of the resolution of the available satellite data. Downscaling techniques are used to bridge the gap between what climate modelers (global and regional) are able to provide and what decision-makers require (local). Precipitation downscaling improves the poor local representation of satellite data and helps end-users acquire more accurate estimates of water availability. Thus, a multifractal downscaling technique complemented by a heterogeneity filter was applied to TRMM (Tropical Rainfall Measuring Mission) 3B42 gridded data (spatial resolution ~ 28 km) from the Peruvian Andean high plateau or Altiplano to generate downscaled rainfall fields that are relevant at an agricultural scale (spatial resolution ~ 1 km).

  2. A map-based South Pacific rainfall climatology

    Science.gov (United States)

    Lorrey, A.; Diamond, H.; Renwick, J.; Salinger, J.; Gergis, J.; Dalu, G.

    2008-12-01

    set which can be supplemented with subsequent data rescue operations. This map-based time series will also allow us to assess the value of generating a rainfall-based SPCZ reconstruction. We feel this effort could usefully extend the historical documentation of the SPCZ motions that are currently offered by satellite measurements, and complement other historical reconstructions of this major circulation feature.

  3. 热控涂层红外发射率对GEO卫星蓄电池温度波动的影响%Effect of Thermal Control Battery Temperature Coatings Infrared Emittance on Variation in GEO Satellite

    Institute of Scientific and Technical Information of China (English)

    刘百麟; 周佐新

    2012-01-01

    Based on DFH-3 satellite platform, the simplified south satellite battery cabin is presen- ted as the thermal analysis model. According to the mechanism of battery temperature variation, five combination schemes, in which the thermal control coatings of white paint,aluminized kapton and graphite-epoxy facesheet are used for inner panel of service module board, are proposed and used to analyze the effect of thermal control coatings infrared emittance on battery temperature. The analysis results show that the range of battery temperature variation can be reduced effectively by decreasing the thermal control coatings infrared emittance of inner panel in battery cabin, especially decreasing the thermal control coatings infrared emittance of fixing panel in battery cabin. The range of battery temperature variation in optimization scheme is decreased by 50% than that in original design scheme.%在东方红一3卫星平台的基础上,将合理简化后的南蓄电池舱作为热分析模型。根据影响蓄电池温度波动的机理,提出服务舱舱板内表面常用热控涂层(白漆、镀铝膜、碳蒙皮)的5种组合方案,并量化分析了热控涂层红外发射率对蓄电池温度波动的影响。分析结果表明:降低蓄电池舱舱板内表面热控涂层红外发射率,尤其是降低蓄电池安装舱板表面的热控涂层红外发射率,可有效减小蓄电池温度波动幅度。与基准方案相比,最优组合方案能使蓄电池温度波动幅度降低50%。

  4. On merging rainfall data from diverse sources using a Bayesian approach

    Science.gov (United States)

    Bhattacharya, Biswa; Tarekegn, Tegegne

    2014-05-01

    Numerous studies have presented comparison of satellite rainfall products, such as from Tropical Rainfall Measuring Mission (TRMM), with rain gauge data and have concluded, in general, that the two sources of data are comparable at suitable space and time scales. The comparison is not a straightforward one as they employ different measurement techniques and are dependent on very different space-time scales of measurements. The number of available gauges in a catchment also influences the comparability and thus adds to the complexity. The TRMM rainfall data also has been directly used in hydrological modelling. As the space-time scale reduces so does the accuracy of these models. It seems that combining the two sources of rainfall data, or more sources of rainfall data, can enormously benefit hydrological studies. Various rainfall data, due to the differences in their space-time structure, contains information about the spatio-temporal distribution of rainfall, which is not available to a single source of data. In order to harness this benefit we have developed a method of merging these two (or more) rainfall products under the framework of Bayesian Data Fusion (BDF) principle. By applying this principle the rainfall data from the various sources can be combined to a single time series of rainfall data. The usefulness of the approach has been explored in a case study on Lake Tana Basin of Upper Blue Nile Basin in Ethiopia. A 'leave one rain gauge out' cross validation technique was employed for evaluating the accuracy of the rainfall time series with rainfall interpolated from rain gauge data using Inverse Distance Weighting (referred to as IDW), TRMM and the fused data (BDF). The result showed that BDF prediction was better compared to the TRMM and IDW. Further evaluation of the three rainfall estimates was done by evaluating the capability in predicting observed stream flow using a lumped conceptual rainfall-runoff model using NAM. Visual inspection of the

  5. Wageningen Urban Rainfall Experiment 2014 (WURex14): Experimental Setup and First Results

    Science.gov (United States)

    van Leth, Thomas; Uijlenhoet, Remko; Overeem, Aart; Leijnse, Hidde; Hazenberg, Pieter

    2015-04-01

    Microwave links from cellular communication networks have been shown to be able to provide valuable information concerning the space-time variability of rainfall. In particular over urban areas, where network densities are generally high, they have the potential to complement existing dedicated infrastructure to measure rainfall (gauges, radars). In addition, microwave links provide a great opportunity for ground-based rainfall measurement for those land surface areas of the world where gauges and radars are generally lacking, e.g. Africa, Latin America, and large parts of Asia. Such information is not only crucial for water management and agriculture, but also for instance for ground validation of space-borne rainfall estimates such as those provided by the recently launched core satellite of the GPM (Global Precipitation Measurement) mission. WURex14 is dedicated to address several errors and uncertainties associated with such quantitative precipitation estimates in detail. The core of the experiment is provided by two co-located microwave links installed between two major buildings on the Wageningen University campus, approximately 2 km apart: a 38 GHz commercial microwave link, kindly provided to us by T-Mobile NL, and a 38 GHz dual-polarization research microwave link from RAL. Transmitting and receiving antennas have been attached to masts installed on the roofs of the two buildings, about 30 m above the ground. This setup has been complemented with a Scintec infrared Large-Aperture Scintillometer, installed over the same path, as well as a Parsivel optical disdrometer, located close to the mast on the receiving end of the links. During the course of the experiment, a 26 GHz RAL research microwave link was added to the experimental setup. Temporal sampling of the received signals was performed at a rate of 20 Hz. In addition, two time-lapse cameras have been installed on either side of the path to monitor the wetness of the antennas as well as the state of

  6. Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

    Science.gov (United States)

    Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

    2017-04-01

    Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

  7. Rainfall estimation over a Mediterranean region using a method based on various spectral parameters of SEVIRI-MSG

    Science.gov (United States)

    Lazri, Mourad; Ameur, Zohra; Ameur, Soltane; Mohia, Yacine; Brucker, Jean Michel; Testud, Jacques

    2013-10-01

    The ultimate objective of this paper is the estimation of rainfall over an area in Algeria using data from the SEVIRI radiometer (Spinning Enhanced Visible and Infrared Imager). To achieve this aim, we use a new Convective/Stratiform Rain Area Delineation Technique (CS-RADT). The satellite rainfall retrieval technique is based on various spectral parameters of SEVIRI that express microphysical and optical cloud properties. It uses a multispectral thresholding technique to distinguish between stratiform and convective clouds. This technique (CS-RADT) is applied to the complex situation of the Mediterranean climate of this region. The tests have been conducted during the rainy seasons of 2006/2007 and 2010/2011 where stratiform and convective precipitation is recorded. The developed scheme (CS-RADT) is calibrated by instantaneous meteorological radar data to determine thresholds, and then rain rates are assigned to each cloud type by using radar and rain gauge data. These calibration data are collocated with SEVIRI data in time and space.

  8. Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

    Science.gov (United States)

    Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

    2015-12-01

    Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

  9. Rainfall Characterization In An Arid Area

    OpenAIRE

    Bazaraa, A. S.; Ahmed, Shamim

    1991-01-01

    The objective of this work is to characterize the rainfall in Doha which lies in an arid region. The rainfall data included daily rainfall depth since 1962 and the hyetographs of the individual storms since 1976. The rainfall is characterized by high variability and severe thunderstorms which are of limited geographical extent. Four probability distributions were used to fit the maximum rainfall in 24 hours and the annual rainfall depth. The extreme value distribution was found to have the be...

  10. The impacts of Middle East dust on Indian summer rainfall

    Science.gov (United States)

    Jin, Q.; Yang, Z. L.; Wei, J.

    2014-12-01

    Using the Weather Research and Forecasting model with online chemistry (WRF-Chem), the impact of Middle East dust aerosols on the Indian summer monsoon rainfall was studied. Eight numerical experiments were conducted to take into account uncertainties related to dust-absorbing properties, various assumptions used in calculating aerosol optical depth (AOD), and various radiation schemes. In order to obtain reasonable dust emission, model-simulated AOD and radiation forcing at the top of the atmosphere were compared with multiple satellite- and surface-based observations. Consistent with observations, modeled results show heavy dust loadings in the Arabian Peninsula and Pakistan, which can be transported through long distance to the Arabian Sea and the Indian Peninsula. By heating the atmosphere in the lower troposphere over the Iranian Plateau, these dust aerosols result in strengthened Indian summer monsoon circulations, which in turn transport more water vapor to the Indian Peninsula. The model shows that northern India becomes wetter during the monsoon season in dust cases than non-dust cases. Further observational analyses show an increasing trend in AOD over the Arabian Peninsula, which corresponds to an increasing trend of rainfall in northern India during summer monsoon seasons from 2000 to 2013. These observed trends of AOD and rainfall are consistent with the model-simulated positive relationship between Middle East dust and Indian summer monsoon rainfall. Our results highlight long-term (decadal) impacts of Middle East dust aerosols on the Indian summer rainfall.

  11. Oceanography from satellites

    Science.gov (United States)

    Wilson, W. S.

    1981-01-01

    It is pointed out that oceanographers have benefited from the space program mainly through the increased efficiency it has brought to ship operations. For example, the Transit navigation system has enabled oceanographers to compile detailed maps of sea-floor properties and to more accurately locate moored subsurface instrumentation. General descriptions are given of instruments used in satellite observations (altimeter, color scanner, infrared radiometer, microwave radiometer, scatterometer, synthetic aperture radar). It is pointed out that because of the large volume of data that satellite instruments generate, the development of algorithms for converting the data into a form expressed in geophysical units has become especially important.

  12. Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

    Science.gov (United States)

    Joiner, J.; Gaunter, L.; Lindstrot, R.; Voigt, M.; Vasilkov, A. P.; Middleton, E. M.; Huemmrich, K. F.; Yoshida, Y.; Frankenberg, C.

    2013-01-01

    Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg

  13. MISTiC Winds: A micro-satellite constellation approach to high resolution observations of the atmosphere using infrared sounding and 3D winds measurements

    Science.gov (United States)

    Maschhoff, K. R.; Polizotti, J. J.; Aumann, H. H.; Susskind, J.

    2016-09-01

    MISTiCTM Winds is an approach to improve short-term weather forecasting based on a miniature high resolution, wide field, thermal emission spectrometry instrument that will provide global tropospheric vertical profiles of atmospheric temperature and humidity at high (3-4 km) horizontal and vertical ( 1 km) spatial resolution. MISTiC's extraordinarily small size, payload mass of less than 15 kg, and minimal cooling requirements can be accommodated aboard a 27U-class CubeSat or an ESPA-Class micro-satellite. Low fabrication and launch costs enable a LEO sunsynchronous sounding constellation that would collectively provide frequent IR vertical profiles and vertically resolved atmospheric motion vector wind observations in the troposphere. These observations are highly complementary to present and emerging environmental observing systems, and would provide a combination of high vertical and horizontal resolution not provided by any other environmental observing system currently in operation. The spectral measurements that would be provided by MISTiC Winds are similar to those of NASA's AIRS that was built by BAE Systems and operates aboard the AQUA satellite. These new observations, when assimilated into high resolution numerical weather models, would revolutionize short-term and severe weather forecasting, save lives, and support key economic decisions in the energy, air transport, and agriculture arenas-at much lower cost than providing these observations from geostationary orbit. In addition, this observation capability would be a critical tool for the study of transport processes for water vapor, clouds, pollution, and aerosols. Key remaining technical risks are being reduced through laboratory and airborne testing under NASA's Instrument Incubator Program.

  14. Rainfall erosivity in New Zealand

    Science.gov (United States)

    Klik, Andreas; Haas, Kathrin; Dvorackova, Anna; Fuller, Ian

    2014-05-01

    Rainfall and its kinetic energy expressed by the rainfall erosivity is the main driver of soil erosion processes by water. The Rainfall-Runoff Erosivity Factor (R) of the Revised Universal Soil Loss Equation is one oft he most widely used parameters describing rainfall erosivity. This factor includes the cumulative effects of the many moderate-sized storms as well as the effects oft he occasional severe ones: R quantifies the effect of raindrop impact and reflects the amopunt and rate of runoff associated with the rain. New Zealand is geologically young and not comparable with any other country in the world. Inordinately high rainfall and strong prevailing winds are New Zealand's dominant climatic features. Annual rainfall up to 15000 mm, steep slopes, small catchments and earthquakes are the perfect basis for a high rate of natural and accelerated erosion. Due to the multifacted landscape of New Zealand its location as island between the Pacific and the Tasmanian Sea there is a high gradient in precipitation between North and South Island as well as between West and East Coast. The objective of this study was to determine the R-factor for the different climatic regions in New Zealand, in order to create a rainfall erosivity map. We used rainfall data (breakpoint data in 10-min intervals) from 34 gauging stations for the calcuation of the rainfall erosivity. 15 stations were located on the North Island and 19 stations on the South Island. From these stations, a total of 397 station years with 12710 rainstorms were analyzed. The kinetic energy for each rainfall event was calculated based on the equation by Brown and Foster (1987), using the breakpoint precipitation data for each storm. On average, a mean annual precipitation of 1357 mm was obtained from the 15 observed stations on the North Island. Rainfall distribution throughout the year is relatively even with 22-24% of annual rainfall occurring in spring , fall and winter and 31% in summer. On the South Island

  15. Hydrological Evaluation of TRMM Rainfall over the Upper Senegal River Basin

    Directory of Open Access Journals (Sweden)

    Ansoumana Bodian

    2016-04-01

    Full Text Available The availability of climatic data, especially on a daily time step, has become very rare in West Africa over the last few years due to the high costs of climate data monitoring. This scarcity of climatic data is a huge obstacle to conduct hydrological studies over some watersheds. In this context, our study aimed to evaluate the capacity of Tropical Rainfall Measuring Mission (TRMM satellite data to simulate the observed runoffs over the Bafing (the main important tributary of the Senegal River before their potential integration in hydrological studies. The conceptual hydrological model GR4J (modèle du Génie Rural (Agricultural Engineering Model à 4 paramètres Journalier (4 parameters Daily has been used, calibrated and validated over the 1961–1997 period with rainfall and Potential Evapotranspiration (PET as inputs. Then, the parameters that best reflect the rainfall-runoff relation, obtained during the cross-calibration-validation phase, were used to simulate runoff over the 1998–2004 period using observed and TRMM rainfalls. The findings of this study show that there is a high consistency between satellite-based estimates and ground-based observations of rainfall. Over the 1998–2004 simulation period, the two rainfall data series show quite satisfactorily results. The output hydrographs from satellite-based estimates and ground-based observations of rainfall coincide quite well with the shape of observed hydrographs with Nash-Sutcliffe Efficiency coefficient (NSE of 0.88 and 0.80 for observed rainfalls and TRMM rainfalls, respectively.

  16. Analysis of an Unsuccessful Forecast for a Heavy Rainfall Event in Yingkou

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    [Objective] The reason for the unsuccessful forecast of a heavy rainfall event in Yingkou was analyzed. [Method] Based on the precipitation data observed by automatic weather stations and MICAPS data, a heavy rainfall Event was studied in Yingkou from 19 July to 21 July in 2010. Then the analysis of an unsuccessful forecasting for the heavy rainfall on 21 July was illustrated by CINRAD-SA data, satellite data and numerical forecast products. [Result] The main reason for the unsuccessful forecast was that th...

  17. 红外预警卫星弹道导弹主动段探测能力%Detection ability of infrared early warning satellite for ballistic missile in boost phase

    Institute of Scientific and Technical Information of China (English)

    钟宇; 吴晓燕; 黄树彩; 吴建峰; 李成景

    2015-01-01

    为研究反导作战背景下红外预警卫星对弹道导弹主动段弹道的探测能力,在作战需求驱动下,构建了预警卫星探测能力战术、技术和性能指标的关联结构,以技术指标为桥梁,通过建立视场、扫描周期、检测概率、虚警概率、信噪比及最大作用距离等计算模型,系统分析了战术、技术和性能指标之间的关联及其对探测能力的影响.结合典型的目标和背景辐射特性以及大气透过率,仿真分析了星载探测器性能指标的不同组合对预警卫星最大作用距离和预警时间的影响程度和规律.该研究可为评估预警卫星反导作战效能和优化设计星载红外探测系统提供有意义的参考.%To study the detection ability of infrared early warning satellite for ballistic missile in boost phase in the background of anti-missile operation, driven by the operational requirements, the tactical, technical and performance indices association structure of detection ability was built. The tactical and performance indices were interconnected by the technical indices, and furthermore, some key technical indices models were built including Field of View (FOV), revisit time, detection probability, false alarm rate, Signal to Noise Ratio (SNR) and maximum operating range. The tactical, technical and performance indices association and its effect on detection ability were analyzed. Based on the typical radiation characteristics of target and background and the atmospheric transmittance, simulation examples showed the impacts and rules of different performance indices combination on maximum operating range and early warning time. The work can provide reference for evaluating anti-missile operation effectiveness and designing optimum satellite-borne infrared detection system.

  18. Analysis of Spatial Characteristics of Rainfall for Optimal Observation Network in Korea

    Science.gov (United States)

    Park, Sojung; Lee, Ebony; Park, Seon Ki; Park, Yunho; Lee, Jeung Whan

    2017-04-01

    Accurate prediction of high impact weather phenomena can reduce damages to people as well as property. Among the meteorological disasters occurred in Korea, heavy rainfall causes the second largest damage, next to typhoons. Therefore, proper observation network of rainfall is important for better understanding of the rainfall characteristics and for more accurate rainfall forecast over Korea. Precipitating weather systems in Korea are highly influenced by East Asian Monsoon, hence they have not only high seasonal variation in rainfall, but also high spatial variation due to complex topographic characteristics. In this study, we identify the spatial characteristics of rainfall in Korea with the geostatistical analyses, including autocorrelogram, variogram, Moran's I, and general G. We develop a testbed system to design an appropriate observation network for rainfall, which can be applied to other high impact weather systems. Geostatistical analyses are conducted using data sets collected from Automatic Weather Stations (AWS; 600 rain gauge data), global/regional numerical weather prediction outputs (i.e., temperature, geopotential height and humidity), Himawari satellite measurements (i.e., water vapor) over Korea in a period of 2013 - 2015. A heavy rainfall is defined as a case with the rainfall rate larger than 80 mm/24 hr over at least one station. In order to consider different characteristics of heavy rainfall systems, we have classified them into several groups: isolated thunderstorms, convective bands, squall lines, cloud clusters, migratory cyclones, typhoons, Changma (monsoon) frontal systems, and showers. We also perform the spatial analyses of rainfall by dividing Korea into several areas based on topographic characteristics. Our results show different properties for different heavy rainfall systems in terms of correlation distances, separation distances, clustered vs. random patterns, and hot vs. cold spots; thus suggesting clues for optimal observation

  19. Rainfall variability modelling in Rwanda

    Science.gov (United States)

    Nduwayezu, E.; Kanevski, M.; Jaboyedoff, M.

    2012-04-01

    Support to climate change adaptation is a priority in many International Organisations meetings. But is the international approach for adaptation appropriate with field reality in developing countries? In Rwanda, the main problems will be heavy rain and/or long dry season. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). The spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front » mechanism. The torrential rainfall that occurs every year in Rwanda disturbs the circulation for many days, damages the houses and, more seriously, causes heavy losses of people. All districts are affected by bad weather (heavy rain) but the costs of such events are the highest in mountains districts. The objective of the current research is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. The research will include rainfalls variability mapping and probabilistic analyses of extreme events.

  20. Retrieval of HCFC-142b (CH3CClF2) from ground-based high-resolution infrared solar spectra: Atmospheric increase since 1989 and comparison with surface and satellite measurements

    Science.gov (United States)

    Mahieu, Emmanuel; Lejeune, Bernard; Bovy, Benoît; Servais, Christian; Toon, Geoffrey C.; Bernath, Peter F.; Boone, Christopher D.; Walker, Kaley A.; Reimann, Stefan; Vollmer, Martin K.; O'Doherty, Simon

    2017-01-01

    We have developed an approach for retrieving HCFC-142b (CH3CClF2) from ground-based high-resolution infrared solar spectra, using its ν7 band Q branch in the 900-906 cm-1 interval. Interferences by HNO3, CO2 and H2O have to be accounted for. Application of this approach to observations recorded within the framework of long-term monitoring activities carried out at the northern mid-latitude, high-altitude Jungfraujoch station in Switzerland (46.5°N, 8.0°E, 3580 m above sea level) has provided a total column times series spanning the 1989 to mid-2015 time period. A fit to the HCFC-142b daily mean total column time series shows a statistically-significant long-term trend of (1.23±0.08×1013 molec cm-2) per year from 2000 to 2010, at the 2-σ confidence level. This corresponds to a significant atmospheric accumulation of (0.94±0.06) ppt (1 ppt=1/1012) per year for the mean tropospheric mixing ratio, at the 2-σ confidence level. Over the subsequent time period (2010-2014), we note a significant slowing down in the HCFC-142b buildup. Our ground-based FTIR (Fourier Transform Infrared) results are compared with relevant data sets derived from surface in situ measurements at the Mace Head and Jungfraujoch sites of the AGAGE (Advanced Global Atmospheric Gases Experiment) network and from occultation measurements by the ACE-FTS (Atmospheric Chemistry Experiment-Fourier Transform Spectrometer) instrument on-board the SCISAT satellite.

  1. Evaluation of remote-sensing-based rainfall products through predictive capability in hydrological runoff modelling

    DEFF Research Database (Denmark)

    Stisen, Simon; Sandholt, Inge

    2010-01-01

    The emergence of regional and global satellite-based rainfall products with high spatial and temporal resolution has opened up new large-scale hydrological applications in data-sparse or ungauged catchments. Particularly, distributed hydrological models can benefit from the good spatial coverage...... and distributed nature of satellite-based rainfall estimates (SRFE). In this study, five SRFEs with temporal resolution of 24 h and spatial resolution between 8 and 27 km have been evaluated through their predictive capability in a distributed hydrological model of the Senegal River basin in West Africa. The main...

  2. Heavy precipitation retrieval from combined satellite observations and ground-based lightning measurements

    Science.gov (United States)

    Mugnai, A.; Dietrich, S.; Casella, D.; di Paola, F.; Formenton, M.; Sanò, P.

    2010-09-01

    We have developed a series of algorithms for the retrieval of precipitation (especially, heavy precipitation) over the Mediterranean area using satellite observations from the available microwave (MW) radiometers onboard low Earth orbit (LEO) satellites and from the visible-infrared (VIS-IR) SEVIRI radiometer onboard the European geosynchronous (GEO) satellite Meteosat Second Generation (MSG), in conjunction with lightning data from ground-based networks - such as ZEUS and LINET. These are: • A new approach for precipitation retrieval from space (which we call the Cloud Dynamics and Radiation Database approach, CDRD) that incorporates lightning and environmental/dynamical information in addition to the upwelling microwave brightness temperatures (TB’s) so as to reduce the retrieval uncertainty and improve the retrieval performance; • A new combined MW-IR technique for producing frequent precipitation retrievals from space (which we call PM-GCD technique), that uses passive-microwave (PM) retrievals in conjunction with lightning information and the Global Convection Detection (GCD) technique to discriminate deep convective clouds within the GEO observations; • A new morphing approach (which we call the Lightning-based Precipitation Evolving Technique, L-PET) that uses the available lightning measurements for propagating the rainfall estimates from satellite-borne MW radiometers to a much higher time resolution than the MW observations. We will present and discuss our combined MW/IR/lightning precipitation algorithms and analyses with special reference to some case studies over the western Mediterranean.

  3. Tropical Storm Beryl as Observed by NASA's Spaceborne Atmospheric Infrared Sounder (AIRS)

    Science.gov (United States)

    2006-01-01

    [figure removed for brevity, see original site] Figure 1: AIRS Microwave Image This is an infrared image of Tropical Storm Beryl in the western Atlantic, from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite on July 20, 2006, 1:30 am local time. This AIRS image shows the temperature of the cloud tops or the surface of the Earth in cloud-free regions. The lowest temperatures (in purple) are associated with high, cold cloud tops that make up the top of the hurricane. The infrared signal does not penetrate through clouds. Where there are no clouds the AIRS instrument reads the infrared signal from the surface of the Earth, revealing warmer temperatures (red). This infrared image shows three large regions of strong convection surrounding the core of the storm. The largest, on the northern edge of the core, also appears in the companion microwave image to contain intense precipitation. The image in figure 1 is created from microwave radiation emitted by Earth's atmosphere and received by the instrument. It shows where the heaviest rainfall is taking place (in blue) in the storm. Blue areas outside of the tropical storm, where there are either some clouds or no clouds indicate where the sea surface shines through. The Atmospheric Infrared Sounder Experiment, with its visible, infrared, and microwave detectors, provides a three-dimensional look at Earth's weather. Working in tandem, the three instruments can make simultaneous observations all the way down to the Earth's surface, even in the presence of heavy clouds. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global, 3-D map of atmospheric temperature and humidity and provides information on clouds, greenhouse gases, and many other atmospheric phenomena. The AIRS Infrared Sounder Experiment flies onboard NASA's Aqua spacecraft and is managed by NASA's Jet Propulsion Laboratory, Pasadena, Calif., under contract to NASA. JPL is a division of the California

  4. 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.

  5. Monitoring the Impacts of Wildfires on Forest Ecosystems and Public Health in the Exo-Urban Environment Using High-Resolution Satellite Aerosol Products from the Visible Infrared Imaging Radiometer Suite (VIIRS).

    Science.gov (United States)

    Huff, Amy K; Kondragunta, Shobha; Zhang, Hai; Hoff, Raymond M

    2015-01-01

    Increasing development of exo-urban environments and the spread of urbanization into forested areas is making humans and forest ecosystems more susceptible to the risks associated with wildfires. Larger and more damaging wildfires are having a negative impact on forest ecosystem services, and smoke from wildfires adversely affects the public health of people living in exo-urban environments. Satellite aerosol measurements are valuable tools that can track the evolution of wildfires and monitor the transport of smoke plumes. Operational users, such as air quality forecasters and fire management officials, can use satellite observations to complement ground-based and aircraft measurements of wildfire activity. To date, wildfire applications of satellite aerosol products, such as aerosol optical depth (AOD), have been limited by the relatively coarse resolution of available AOD data. However, the new Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on the Suomi National Polar-orbiting Partnership (S-NPP) satellite has high-resolution AOD that is ideally suited to monitoring wildfire impacts on the exo-urban scale. Two AOD products are available from VIIRS: the 750-m × 750-m nadir resolution Intermediate Product (IP) and the 6-km × 6-km resolution Environmental Data Record product, which is aggregated from IP measurements. True color (red, green, and blue [RGB]) imagery and a smoke mask at 750-m × 750-m resolution are also available from VIIRS as decision aids for wildfire applications; they serve as counterparts to AOD measurements by providing visible information about areas of smoke in the atmosphere. To meet the needs of operational users, who do not have time to process raw data files and need access to VIIRS products in near-real time (NRT), VIIRS AOD and RGB NRT imagery are available from the Infusing satellite Data into Environmental Applications (IDEA) web site. A key feature of IDEA is an interactive visualization tool that allows users to

  6. An ensemble Kalman filter dual assimilation of thermal infrared and microwave satellite observations of soil moisture into the Noah land surface model

    Science.gov (United States)

    Hain, Christopher R.; Crow, Wade T.; Anderson, Martha C.; Mecikalski, John R.

    2012-11-01

    Studies that have assimilated remotely sensed soil moisture (SM) into land surface models (LSMs) have generally focused on retrievals from microwave (MW) sensors. However, retrievals from thermal infrared (TIR) sensors have also been shown to add unique information, especially where MW sensors are not able to provide accurate retrievals (due to, e.g., dense vegetation). In this study, we examine the assimilation of a TIR product based on surface evaporative flux estimates from the Atmosphere Land Exchange Inverse (ALEXI) model and the MW-based VU Amsterdam NASA surface SM product generated with the Land Parameter Retrieval Model (LPRM). A set of data assimilation experiments using an ensemble Kalman filter are performed over the contiguous United States to assess the impact of assimilating ALEXI and LPRM SM retrievals in isolation and together in a dual-assimilation case. The relative skill of each assimilation case is assessed through a data denial approach where a LSM is forced with an inferior precipitation data set. The ability of each assimilation case to correct for precipitation errors is quantified by comparing with a simulation forced with a higher-quality precipitation data set. All three assimilation cases (ALEXI, LPRM, and Dual assimilation) show relative improvements versus the open loop (i.e., reduced RMSD) for surface and root zone SM. In the surface zone, the dual assimilation case provides the largest improvements, followed by the LPRM case. However, the ALEXI case performs best in the root zone. Results from the data denial experiment are supported by comparisons between assimilation results and ground-based SM observations from the Soil Climate Analysis Network.

  7. Research on the Fine-Scale Spatial Uniformity of Natural Rainfall and Rainfall from a Rainfall Simulator with a Rotary Platform (RSRP)

    National Research Council Canada - National Science Library

    Bo Liu; Xiaolei Wang; Lihua Shi; Xichuan Liu; Zhaojing Kang; Zhentao Chen

    2017-01-01

    ... and the rainfall uniformity was evaluated using the Christiansen Uniformity Coefficient (CU). Simultaneously, factors influencing the spatial uniformity of natural rainfall, including the average rainfall accumulation (RA...

  8. Quantifying uncertainty in observational rainfall datasets

    Science.gov (United States)

    Lennard, Chris; Dosio, Alessandro; Nikulin, Grigory; Pinto, Izidine; Seid, Hussen

    2015-04-01

    The CO-ordinated Regional Downscaling Experiment (CORDEX) has to date seen the publication of at least ten journal papers that examine the African domain during 2012 and 2013. Five of these papers consider Africa generally (Nikulin et al. 2012, Kim et al. 2013, Hernandes-Dias et al. 2013, Laprise et al. 2013, Panitz et al. 2013) and five have regional foci: Tramblay et al. (2013) on Northern Africa, Mariotti et al. (2014) and Gbobaniyi el al. (2013) on West Africa, Endris et al. (2013) on East Africa and Kalagnoumou et al. (2013) on southern Africa. There also are a further three papers that the authors know about under review. These papers all use an observed rainfall and/or temperature data to evaluate/validate the regional model output and often proceed to assess projected changes in these variables due to climate change in the context of these observations. The most popular reference rainfall data used are the CRU, GPCP, GPCC, TRMM and UDEL datasets. However, as Kalagnoumou et al. (2013) point out there are many other rainfall datasets available for consideration, for example, CMORPH, FEWS, TAMSAT & RIANNAA, TAMORA and the WATCH & WATCH-DEI data. They, with others (Nikulin et al. 2012, Sylla et al. 2012) show that the observed datasets can have a very wide spread at a particular space-time coordinate. As more ground, space and reanalysis-based rainfall products become available, all which use different methods to produce precipitation data, the selection of reference data is becoming an important factor in model evaluation. A number of factors can contribute to a uncertainty in terms of the reliability and validity of the datasets such as radiance conversion algorithims, the quantity and quality of available station data, interpolation techniques and blending methods used to combine satellite and guage based products. However, to date no comprehensive study has been performed to evaluate the uncertainty in these observational datasets. We assess 18 gridded

  9. Stochastic generation of daily rainfall events based on rainfall pattern classification and Copula-based rainfall characteristics simulation

    Science.gov (United States)

    Xu, Y. P.; Gao, C.

    2016-12-01

    To deal with the problem of having no or insufficiently long rainfall record, developing a stochastic rainfall model is very essential. This study first proposed a stochastic model of daily rainfall events based on classification and simulation of different rainfall patterns, and copula-based joint simulation of rainfall characteristics. Compared with current stochastic rainfall models, this new model not only keeps the dependence structure of rainfall characteristics by using copula functions, but also takes various rainfall patterns that may cause different hydrological responses to watershed into consideration. In order to determine the appropriate number of representative rainfall patterns in an objective way, we also introduced clustering validation measures to the stochastic model. Afterwards, the developed stochastic rainfall model is applied to 39 gauged meteorological stations in Zhejiang province, East China, and is then extended to ungauged stations for validation by applying the self-organizing map (SOM) method. The final results show that the 39 stations can be classified into seven regions that further fall into three categories based on rainfall generation mechanisms, i.e., plum-rain control region, typhoon-rain control region and typhoon-plum-rain compatible region. Rainfall patterns of each station can be classified into five or six types based on clustering validation measures. This study shows that the stochastic rainfall model is robust and can be applied to both gauged and ungauged stations for generating long rainfall record.

  10. Radiometric consistency assessment of hyperspectral infrared sounders

    OpenAIRE

    Wang, L.; Y. Han; Jin, X.; Y. Chen; D. A. Tremblay

    2015-01-01

    The radiometric and spectral consistency among the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) is fundamental for the creation of long-term infrared (IR) hyperspectral radiance benchmark datasets for both inter-calibration and climate-related studies. In this study, the CrIS radiance measurements on Suomi National Polar-orbiting Partnership (SNPP) satellite are directly com...

  11. A Deep Neural Network Model for Rainfall Estimation UsingPolarimetric WSR-88DP Radar Observations

    Science.gov (United States)

    Tan, H.; Chandra, C. V.; Chen, H.

    2016-12-01

    Rainfall estimation based on radar measurements has been an important topic for a few decades. Generally, radar rainfall estimation is conducted through parametric algorisms such as reflectivity-rainfall relation (i.e., Z-R relation). On the other hand, neural networks are developed for ground rainfall estimation based on radar measurements. This nonparametric method, which takes into account of both radar observations and rainfall measurements from ground rain gauges, has been demonstrated successfully for rainfall rate estimation. However, the neural network-based rainfall estimation is limited in practice due to the model complexity and structure, data quality, as well as different rainfall microphysics. Recently, the deep learning approach has been introduced in pattern recognition and machine learning areas. Compared to traditional neural networks, the deep learning based methodologies have larger number of hidden layers and more complex structure for data representation. Through a hierarchical learning process, the high level structured information and knowledge can be extracted automatically from low level features of the data. In this paper, we introduce a novel deep neural network model for rainfall estimation based on ground polarimetric radar measurements .The model is designed to capture the complex abstractions of radar measurements at different levels using multiple layers feature identification and extraction. The abstractions at different levels can be used independently or fused with other data resource such as satellite-based rainfall products and/or topographic data to represent the rain characteristics at certain location. In particular, the WSR-88DP radar and rain gauge data collected in Dallas - Fort Worth Metroplex and Florida are used extensively to train the model, and for demonstration purposes. Quantitative evaluation of the deep neural network based rainfall products will also be presented, which is based on an independent rain gauge

  12. An assessment of the performance of global rainfall estimates without ground-based observations

    Directory of Open Access Journals (Sweden)

    C. Massari

    2017-09-01

    Full Text Available Satellite-based rainfall estimates over land have great potential for a wide range of applications, but their validation is challenging due to the scarcity of ground-based observations of rainfall in many areas of the planet. Recent studies have suggested the use of triple collocation (TC to characterize uncertainties associated with rainfall estimates by using three collocated rainfall products. However, TC requires the simultaneous availability of three products with mutually uncorrelated errors, a requirement which is difficult to satisfy with current global precipitation data sets. In this study, a recently developed method for rainfall estimation from soil moisture observations, SM2RAIN, is demonstrated to facilitate the accurate application of TC within triplets containing two state-of-the-art satellite rainfall estimates and a reanalysis product. The validity of different TC assumptions are indirectly tested via a high-quality ground rainfall product over the contiguous United States (CONUS, showing that SM2RAIN can provide a truly independent source of rainfall accumulation information which uniquely satisfies the assumptions underlying TC. On this basis, TC is applied with SM2RAIN on a global scale in an optimal configuration to calculate, for the first time, reliable global correlations (vs. an unknown truth of the aforementioned products without using a ground benchmark data set. The analysis is carried out during the period 2007–2012 using daily rainfall accumulation products obtained at 1° × 1° spatial resolution. Results convey the relatively high performance of the satellite rainfall estimates in eastern North and South America, southern Africa, southern and eastern Asia, eastern Australia, and southern Europe, as well as complementary performances between the reanalysis product and SM2RAIN, with the first performing reasonably well in the Northern Hemisphere and the second providing very good performance in the Southern

  13. Multi-Decadal Variability of Polynya Characteristics and Ice Production in the North Water Polynya by Means of Passive Microwave and Thermal Infrared Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Andreas Preußer

    2015-11-01

    Full Text Available The North Water (NOW Polynya is a regularly-forming area of open-water and thin-ice, located between northwestern Greenland and Ellesmere Island (Canada at the northern tip of Baffin Bay. Due to its large spatial extent, it is of high importance for a variety of physical and biological processes, especially in wintertime. Here, we present a long-term remote sensing study for the winter seasons 1978/1979 to 2014/2015. Polynya characteristics are inferred from (1 sea ice concentrations and brightness temperatures from passive microwave satellite sensors (Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2, Scanning Multichannel Microwave Radiometer (SMMR, Special Sensor Microwave Imager/Sounder (SSM/I-SSMIS and (2 thin-ice thickness distributions, which are calculated using MODIS ice-surface temperatures and European Center for Medium-Range Weather Forecasts (ECMWF atmospheric reanalysis data in a 1D thermodynamic energy-balance model. Daily ice production rates are retrieved for each winter season from 2002/2003 to 2014/2015, assuming that all heat loss at the ice surface is balanced by ice growth. Two different cloud-cover correction schemes are applied on daily polynya area and ice production values to account for cloud gaps in the MODIS composites. Our results indicate that the NOW polynya experienced significant seasonal changes over the last three decades considering the overall frequency of polynya occurrences, as well as their spatial extent. In the 1980s, there were prolonged periods of a more or less closed ice cover in northern Baffin Bay in winter. This changed towards an average opening on more than 85% of the days between November and March during the last decade. Noticeably, the sea ice cover in the NOW polynya region shows signs of a later-appearing fall freeze-up, starting in the late 1990s. Different methods to obtain daily polynya area using passive microwave AMSR-E/AMSR2 data and SSM/I-SSMIS data were applied. A comparison

  14. Chapman Conference on Rainfall Fields

    Science.gov (United States)

    Gupta, V. K.

    The Chapman Conference on Rainfall Fields, sponsored by AGU, was the first of its kind; it was devoted to strengthening scientific interaction between the North American and Latin American geophysics communities. It was hosted by Universidad Simon Bolivar and Instituto Internacional de Estudios Avanzados, in Caracas, Venezuela, during March 24-27, 1986. A total of 36 scientists from Latin America, the United States, Canada, and Europe participated. The conference, which was convened by I. Rodriguez-Iturbe (Universidad Simon Bolivar) and V. K. Gupta (University of Mississippi, University), brought together hydrologists, meteorologists, and mathematicians/statisticians in the name of enhancing an interdisciplinary focus on rainfall research.

  15. Rainfall simulation for environmental application

    Energy Technology Data Exchange (ETDEWEB)

    Shriner, D.S.; Abner, C.H.; Mann, L.K.

    1977-08-01

    Rain simulation systems have been designed for field and greenhouse studies which have the capability of reproducing the physical and chemical characteristics of natural rainfall. The systems permit the simulation of variations in rainfall and droplet size similar to that of natural precipitation. The systems are completely automatic and programmable, allowing unattended operation for periods of up to one week, and have been used to expose not only vegetation but also soils and engineering materials, making them versatile tools for studies involving simulated precipitation.

  16. Multiple data fusion for rainfall estimation using a NARX-based recurrent neural network - the development of the REIINN model

    Science.gov (United States)

    Ang, M. R. C. O.; Gonzalez, R. M.; Castro, P. P. M.

    2014-03-01

    Rainfall, one of the important elements of the hydrologic cycle, is also the most difficult to model. Thus, accurate rainfall estimation is necessary especially in localized catchment areas where variability of rainfall is extremely high. Moreover, early warning of severe rainfall through timely and accurate estimation and forecasting could help prevent disasters from flooding. This paper presents the development of two rainfall estimation models that utilize a NARX-based neural network architecture namely: REIINN 1 and REIINN 2. These REIINN models, or Rainfall Estimation by Information Integration using Neural Networks, were trained using MTSAT cloud-top temperature (CTT) images and rainfall rates from the combined rain gauge and TMPA 3B40RT datasets. Model performance was assessed using two metrics - root mean square error (RMSE) and correlation coefficient (R). REIINN 1 yielded an RMSE of 8.1423 mm/3h and an overall R of 0.74652 while REIINN 2 yielded an RMSE of 5.2303 and an overall R of 0.90373. The results, especially that of REIINN 2, are very promising for satellite-based rainfall estimation in a catchment scale. It is believed that model performance and accuracy will greatly improve with a denser and more spatially distributed in-situ rainfall measurements to calibrate the model with. The models proved the viability of using remote sensing images, with their good spatial coverage, near real time availability, and relatively inexpensive to acquire, as an alternative source for rainfall estimation to complement existing ground-based measurements.

  17. GHRSST Level 2P Atlantic Regional Skin Sea Surface Temperature from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on the Meteosat Second Generation (MSG-1) satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Meteosat Second Generation (MSG) satellites are spin stabilized geostationary satellites operated by the European Organization for the Exploitation of...

  18. GHRSST Level 2P Atlantic Regional Skin Sea Surface Temperature from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on the Meteosat Second Generation (MSG-2) satellite (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Meteosat Second Generation (MSG) satellites are spin stabilized geostationary satellites operated by the European Organization for the Exploitation of...

  19. GHRSST Level 2P Atlantic Regional Skin Sea Surface Temperature from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on the Meteosat Second Generation (MSG-3) satellite (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Meteosat Second Generation (MSG-3) satellites are spin stabilized geostationary satellites operated by the European Organization for the Exploitation of...

  20. GHRSST 2 Level 2P Global Skin Sea Surface Temperature from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite created by the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Joint Polar Satellite System (JPSS), starting with S-NPP launched on 28 October 2011, is the new generation of the US Polar Operational Environmental Satellites...

  1. Egypt satellite images for land surface characterization

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay

    Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

  2. Satellite RNAs and Satellite Viruses.

    Science.gov (United States)

    Palukaitis, Peter

    2016-03-01

    Satellite RNAs and satellite viruses are extraviral components that can affect either the pathogenicity, the accumulation, or both of their associated viruses while themselves being dependent on the associated viruses as helper viruses for their infection. Most of these satellite RNAs are noncoding RNAs, and in many cases, have been shown to alter the interaction of their helper viruses with their hosts. In only a few cases have the functions of these satellite RNAs in such interactions been studied in detail. In particular, work on the satellite RNAs of Cucumber mosaic virus and Turnip crinkle virus have provided novel insights into RNAs functioning as noncoding RNAs. These effects are described and potential roles for satellite RNAs in the processes involved in symptom intensification or attenuation are discussed. In most cases, models describing these roles involve some aspect of RNA silencing or its suppression, either directly or indirectly involving the particular satellite RNA.

  3. Research on the Fine-Scale Spatial Uniformity of Natural Rainfall and Rainfall from a Rainfall Simulator with a Rotary Platform (RSRP)

    OpenAIRE

    Bo Liu; Xiaolei Wang; Lihua Shi; Xichuan Liu; Zhaojing Kang; Zhentao Chen

    2017-01-01

    Abstract: The accurate production of a rainfall environment similar to natural rainfall by a rainfall simulator (RS) is a crucial and challenging task in rainfall instrument testing or calibration. Although the spatial uniformity of rainfall accumulation is a key parameter of an RS, the spatial uniformity comparison between simulated rainfall and natural rainfall, and the spatial uniformity improvements for an RS are scant in the literature. In this study, a fine-scale natural rainfall experi...

  4. Effects of doubled carbon dioxide on rainfall responses to large-scale forcing: A two-dimensional cloud-resolving modeling study

    Science.gov (United States)

    Li, Xiaofan; Shen, Xinyong; Liu, Jia

    2014-05-01

    Rainfall responses to doubled atmospheric carbon dioxide concentration were investigated through the analysis of two pairs of two-dimensional cloud-resolving model sensitivity experiments. One pair of experiments simulated pre-summer heavy rainfall over southern China around the summer solstice, whereas the other pair of experiments simulated tropical rainfall around the winter solstice. The analysis of the time and model domain mean heat budget revealed that the enhanced local atmospheric warming was associated with doubled carbon dioxide through the weakened infrared radiative cooling during the summer solstice. The weakened mean pre-summer rainfall corresponded to the weakened mean infrared radiative cooling. Doubled carbon dioxide increased the mean tropical atmospheric warming via the enhanced mean latent heat in correspondence with the strengthened mean infrared radiative cooling during the winter solstice. The enhanced mean tropical rainfall was associated with the increased mean latent heat.

  5. Stereoscopic observations from meteorological satellites

    Science.gov (United States)

    Hasler, A. F.; Mack, R.; Negri, A.

    The capability of making stereoscopic observations of clouds from meteorological satellites is a new basic analysis tool with a broad spectrum of applications. Stereoscopic observations from satellites were first made using the early vidicon tube weather satellites (e.g., Ondrejka and Conover [1]). However, the only high quality meteorological stereoscopy from low orbit has been done from Apollo and Skylab, (e.g., Shenk et al. [2] and Black [3], [4]). Stereoscopy from geosynchronous satellites was proposed by Shenk [5] and Bristor and Pichel [6] in 1974 which allowed Minzner et al. [7] to demonstrate the first quantitative cloud height analysis. In 1978 Bryson [8] and desJardins [9] independently developed digital processing techniques to remap stereo images which made possible precision height measurement and spectacular display of stereograms (Hasler et al. [10], and Hasler [11]). In 1980 the Japanese Geosynchronous Satellite (GMS) and the U.S. GOES-West satellite were synchronized to obtain stereo over the central Pacific as described by Fujita and Dodge [12] and in this paper. Recently the authors have remapped images from a Low Earth Orbiter (LEO) to the coordinate system of a Geosynchronous Earth Orbiter (GEO) and obtained stereoscopic cloud height measurements which promise to have quality comparable to previous all GEO stereo. It has also been determined that the north-south imaging scan rate of some GEOs can be slowed or reversed. Therefore the feasibility of obtaining stereoscopic observations world wide from combinations of operational GEO and LEO satellites has been demonstrated. Stereoscopy from satellites has many advantages over infrared techniques for the observation of cloud structure because it depends only on basic geometric relationships. Digital remapping of GEO and LEO satellite images is imperative for precision stereo height measurement and high quality displays because of the curvature of the earth and the large angular separation of the

  6. 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

  7. Where do forests influence rainfall?

    Science.gov (United States)

    Wang-Erlandsson, Lan; van der Ent, Ruud; Fetzer, Ingo; Keys, Patrick; Savenije, Hubert; Gordon, Line

    2017-04-01

    Forests play a major role in hydrology. Not only by immediate control of soil moisture and streamflow, but also by regulating climate through evaporation (i.e., transpiration, interception, and soil evaporation). The process of evaporation travelling through the atmosphere and returning as precipitation on land is known as moisture recycling. Whether evaporation is recycled depends on wind direction and geography. Moisture recycling and forest change studies have primarily focused on either one region (e.g. the Amazon), or one biome type (e.g. tropical humid forests). We will advance this via a systematic global inter-comparison of forest change impacts on precipitation depending on both biome type and geographic location. The rainfall effects are studied for three contemporary forest changes: afforestation, deforestation, and replacement of mature forest by forest plantations. Furthermore, as there are indications in the literature that moisture recycling in some places intensifies during dry years, we will also compare the rainfall impacts of forest change between wet and dry years. We model forest change effects on evaporation using the global hydrological model STEAM and trace precipitation changes using the atmospheric moisture tracking scheme WAM-2layers. This research elucidates the role of geographical location of forest change driven modifications on rainfall as a function of the type of forest change and climatic conditions. These knowledge gains are important at a time of both rapid forest and climate change. Our conclusions nuance our understanding of how forests regulate climate and pinpoint hotspot regions for forest-rainfall coupling.

  8. Centriolar satellites

    DEFF Research Database (Denmark)

    Tollenaere, Maxim A X; Mailand, Niels; Bekker-Jensen, Simon

    2015-01-01

    Centriolar satellites are small, microscopically visible granules that cluster around centrosomes. These structures, which contain numerous proteins directly involved in centrosome maintenance, ciliogenesis, and neurogenesis, have traditionally been viewed as vehicles for protein trafficking...... highlight newly discovered regulatory mechanisms targeting centriolar satellites and their functional status, and we discuss how defects in centriolar satellite components are intimately linked to a wide spectrum of human diseases....

  9. 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.

  10. The onset and cessation of seasonal rainfall over Africa

    Science.gov (United States)

    Dunning, Caroline M.; Black, Emily C. L.; Allan, Richard P.

    2016-10-01

    Variation in the seasonal cycle of African rainfall is of key importance for agriculture. Here an objective method of determining the timing of onset and cessation is, for the first time, extended to the whole of Africa. The method is applied to five observational data sets and the ERA-Interim reanalysis. Compatibility with known physical drivers of African rainfall, consistency with indigenous methods, and generally strong agreement between satellite-based rainfall data sets confirm that the method is capturing the correct seasonal progression of African rainfall. The biannual rainfall regime is correctly identified over the coastal region of Ghana and the Ivory Coast. However, the ERA-Interim reanalysis exhibits timing biases over areas with two rainy seasons, and both ERA-Interim and the ARCv2 observational data set exhibit some inconsistent deviations over West Africa. The method can be used to analyze both seasonal-interannual variability and long-term change. Over East Africa, we find that failure of the rains and subsequent humanitarian disaster is associated with shorter as well as weaker rainy seasons, e.g., on average the long rains were 11 days shorter in 2011. Cessation of the short rains over this region is 7 days later in El Niño and 5 days earlier in La Niña years with only a small change in onset date. The methodology described in this paper is applicable to multiple data sets and to large regions, including those that experience multiple rainy seasons. As such, it provides a means for investigating variability and change in the seasonal cycle over the whole of Africa.

  11. Weekend Effect" in Summertime U.S. Rainfall: Evidence for Midweek Intensification of Storms by Pollution

    Science.gov (United States)

    Bell, Thomas L.; Rosenfeld, Daniel; Kim, Kyu-Myong; Hahnenberger, Maura

    2006-01-01

    Persistent and strong dependence of rain rate on the day of the week has been found in Tropical Rainfall Measuring Mission (TRMM) satellite estimates of summer afternoon rainfall over the southeast U.S. and the nearby Atlantic from 1998 to 2005. Midweek (Tue-Thu) rain rates and rain area appear to increase over land, and this increase is accompanied by a corresponding diminution of rainfall over nearby waters. Reanalysis data from atmospheric models, suggest that there is a corresponding weekly variation in atmospheric winds consistent with the changes in rainfall. These variations are almost certainly caused by weekly variations in human activity. The most likely cause of the observed changes in rainfall is the well documented weekly variation in atmospheric pollution. Particulate pollution is highest in the middle of the week. Considerable observational and modeling evidence has accumulated concerning the effects of aerosols on precipitation. Most of this evidence relates to the suppression of precipitation by aerosols, but it has been argued that storms in highly unstable moist environments can be invigorated by aerosols, and some modeling studies seem to confirm this. The strong weekly cycle in rainfall observed over the southeast U.S. along with what appears to be dynamical suppression of rainfall over the nearby Atlantic, and the lack of an observable cycle over the southwest U.S., are consistent with this theory.

  12. 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

  13. The Latitudinal Gradient of Rainfall, Mineralogy, Albedo and Magnetic Susceptibility in West Africa

    Science.gov (United States)

    Williams, E. R.; Balsam, W.; Schaaf, C.; Yang, X.; Zhang, Q.; Ji, J.; Rossman, G.; Garimella, S.; Oldfield, F.; Lyons, J. R.; Ellwood, B.; Hartman, H.; Hicks, E.; Mansot, J. L.; Cesaire, T.; Thomas, P.

    2008-12-01

    In order to investigate the effect of climate on soil and surface sediment properties we examined four transects around the Sahara Desert. The transects were located in Mali, Niger, Benin, Togo, Egypt and Morocco and, with the exception of Egypt, each crossed a significant climatological rainfall gradient. The Egyptian transect was designed to characterize one of the driest portions of the Sahara Desert. Our study included laboratory measurements of mineralogy (XRD), elemental composition (XRF), grain size, optical reflectance (lab), magnetic susceptibility (MS)and remanences. In addition, albedo was determined from the MODIS satellite imagery from space. Many of our laboratory measurements exhibited variations with the rainfall gradient. Iron oxides (hematite and goethite), kaolinite, Al2O3, and TiO2 increased with increasing rainfall whereas SiO2, illite, and grain size decreased with increasing rainfall. Both laboratory-determined reflectivity and satellite-determine albedo decreased as rainfall increased. In part, this decrease in reflectivity/albedo with increasing rainfall appears to be the result of hematite, the dominant coloring agent for the soil in this region and the origin of the 'red' Sahel. The physical interpretation of these results centers on rainfall as a long-term leaching agent of surface material, and the control of physical properties by specific mineralogy. SiO2 is highly reflective and iron oxides are strongly absorptive in the visible range. The solubility of SiO2 in rainwater is orders of magnitude larger than all the iron oxides, with hematite the least soluble. It has long been recognized that leaching by rainfall produces dark red laterite in the near-surface oxidizing environment, a prominent geological feature throughout the high rainfall belt of West Africa. Laterite beds represent simultaneous enrichments of all iron oxides and a reduction in SiO2 by leaching. In the Sahara desert where rainfall is minimal (<10 mm/yr), SiO2 is

  14. On evaluation of ShARP passive rainfall retrievals over snow-covered land surfaces and coastal zones

    CERN Document Server

    Ebtehaj, Ardeshir M; Foufoula-Georgiou, Efi

    2015-01-01

    For precipitation retrievals over land, using satellite measurements in microwave bands, it is important to properly discriminate the weak rainfall signals from strong and highly variable background surface emission. Traditionally, land rainfall retrieval methods often rely on a weak signal of rainfall scattering on high-frequency channels (85 GHz) and make use of empirical thresholding and regression-based techniques. Due to the increased ground surface signal interference, precipitation retrieval over radiometrically complex land surfaces, especially over snow-covered lands, deserts and coastal areas, is of particular challenge for this class of retrieval techniques. This paper evaluates the results by the recently proposed Shrunken locally linear embedding Algorithm for Retrieval of Precipitation (ShARP), over a radiometrically complex terrain and coastal areas using the data provided by the Tropical Rainfall Measuring Mission (TRMM) satellite. To this end, the ShARP retrieval experiments are performed ove...

  15. Stochastic modelling of daily rainfall sequences

    NARCIS (Netherlands)

    Buishand, T.A.

    1977-01-01

    Rainfall series of different climatic regions were analysed with the aim of generating daily rainfall sequences. A survey of the data is given in I, 1. When analysing daily rainfall sequences one must be aware of the following points:
    a. Seasonality. Because of seasonal variation

  16. Interannual Variability of Tropical Precipitation: How Well Do Climate Models Agree With Current Satellite Estimates?

    Science.gov (United States)

    Robertson, Franklin R.; Marshall, Susan; Roads, John; Oglesby, Robert J.; Fitzjarrald, Dan; Goodman, H. Michael (Technical Monitor)

    2001-01-01

    Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over die tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-H effort is also examined. This integration is run with specified SSTs, but with no data assimilation. Our analysis focuses on two aspects of inter-annual variability. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean beat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability in precipitation than do the satellite observations.

  17. 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.

  18. Assessing the performance of satellite-based precipitation products over the Mediterranean region

    Science.gov (United States)

    Xaver, Angelika; Dorigo, Wouter; Brocca, Luca; Ciabatta, Luca

    2017-04-01

    Detailed knowledge about the spatial and temporal patterns and quantities of precipitation is of high importance. This applies especially in the Mediterranean region, where water demand for agricultural, industrial and touristic needs is growing and climate projections foresee a decrease of precipitation amounts and an increase in variability. In this region, ground-based rain gauges are available only limited in number, particularly in northern Africa and the Middle East and lack to capture the high spatio-temporal character of precipitation over large areas. This has motivated the development of a large number of remote sensing products for monitoring rainfall. Satellite-based precipitation products are based on various observation principles and retrieval approaches, i.e. from thermal infra-red and microwaves. Although, many individual validation studies on the performance of these precipitation datasets exist, they mostly examine only one or a few of these rainfall products at the same time and are not targeted at the Mediterranean basin as a whole. Here, we present an extensive comparative study of seven different satellite-based precipitation products, namely CMORPH 30-minutes, CMORPH 3-hourly, GPCP, PERSIANN, SM2Rain CCI, TRMM TMPA 3B42, and TRMM TMPA 3B42RT, focusing on the whole Mediterranean region and on individual Mediterranean catchments. The time frame of investigation is restricted by the common availability of all precipitation products and covers the period 2000-2013. We assess the skill of the satellite products against gridded gauge-based data provided by GPCC and E-OBS. Apart from common characteristics like biases and temporal correlations we evaluate several sophisticated dataset properties that are of particular interest for Mediterranean hydrology, including the capability of the remotely sensed products to capture extreme events and trends. A clear seasonal dependency of the correlation results can be observed for the whole Mediterranean

  19. Calibration and Validation of the InfraRed Atmospheric Sounder Onboard the FY3B Satellite%风云三号B星红外分光计的定标和验证

    Institute of Scientific and Technical Information of China (English)

    漆成莉; 陈勇; 刘辉; 吴春强; 殷德奎

    2013-01-01

    搭载于风云三号A星和B星上的红外分光计(IRAS)分别于2008年5月27日和2010年11月5日成功发射。该仪器主要提供从可见光到红外波长范围内多通道的辐射观测,并可应用于资料同化、全球大气温度和水汽廓线反演等领域。搭载于风云三号A星上的IRAS由于滤光轮转速不稳定,导致仪器观测不连续。风云三号B星上的IRAS运行正常,处于稳定的业务模式。利用仪器在轨3个月期间的资料,进行了一系列的在轨定标和验证试验,对IRAS仪器的性能进行了一系列的验证,包括冷空和暖黑体定标计数值的长期趋势、噪音等效辐射率等。利用IRAS和红外大气探测干涉仪(IASI)同时观察到的地球场景进行比较,证明了两种观测非常相似。另外,将FY3B/IRAS红外通道的观测与NOAA-19/HIRS对应的通道的辐射传输模式模拟进行了对比。对比结果显示相对于HIRS,部分IRAS红外通道,尤其是通道1到10,15,19和20偏差很小。但是少数通道,如通道13,16和18有较大的偏差。造成这些偏差的原因仍需要进一步的研究。%InfraRed Atmospheric Sounder (IRAS) instruments were successfully launched onboard the FengYun-3A (FY3A) and FengYun-3B (FY3B) satellites on May 27, 2008, and November 5, 2010, respectively. They aim at providing multichannel radiances within the spectral range of visible to infrared (IR) wavelengths for many environmental applications, including data assimilation and retrievals of global atmospheric temperature and humidity proifles. However, the velocity of the iflter wheel of the ifrst IRAS onboard FY3A is unstable and, therefore, induced a discontinuity in the measurement. The IRAS onboard FY3B works well in normal and stable operational mode since its launch without any anomaly. A variety of postlaunch calibration/validation tasks are conducted using on-orbit data during a period of three months. This paper presents

  20. Spatial variability and rainfall characteristics of Kerala

    Indian Academy of Sciences (India)

    Anu Simon; K Mohankumar

    2004-06-01

    Geographical regions of covariability in precipitation over the Kerala state are exposed using factor analysis. The results suggest that Kerala can be divided into three unique rainfall regions, each region having a similar covariance structure of annual rainfall. Stations north of 10°N (north Kerala) fall into one group and they receive more rainfall than stations south of 10°N (south Kerala). Group I stations receive more than 65% of the annual rainfall during the south-west monsoon period, whereas stations falling in Group II receive 25-30% of annual rainfall during the pre-monsoon and the north-east monsoon periods. The meteorology of Kerala is profoundly influenced by its orographical features, however it is difficult to make out a direct relationship between elevation and rainfall. Local features of the state as reflected in the rainfall distribution are also clearly brought out by the study.

  1. 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.

  2. Borneo vortex and meso-scale convective rainfall

    Directory of Open Access Journals (Sweden)

    S. Koseki

    2013-08-01

    Full Text Available We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite datasets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a "perpetual" cold surge. The Borneo vortex is manifested as a meso-α cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth of the meso-α cyclone was achieved mainly by vortex stretching. The comma-shaped rainband consists of clusters of meso-β scale rainfall patches. The warm and wet cyclonic southeasterly flow meets with the cold and dry northeasterly surge forming a confluence front in the northeastern sector of the cyclone. Intense upward motion and heavy rainfall result both due to the low-level convergence and the favourable thermodynamic profile at the confluence front. At both meso-α and meso-β scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is much enhanced by nonlinear self-enhancement dynamics.

  3. Satellite Communications

    CERN Document Server

    Pelton, Joseph N

    2012-01-01

    The field of satellite communications represents the world's largest space industry. Those who are interested in space need to understand the fundamentals of satellite communications, its technology, operation, business, economic, and regulatory aspects. This book explains all this along with key insights into the field's future growth trends and current strategic challenges. Fundamentals of Satellite Communications is a concise book that gives all of the key facts and figures as well as a strategic view of where this dynamic industry is going. Author Joseph N. Pelton, PhD, former Dean of the International Space University and former Director of Strategic Policy at Intelstat, presents a r

  4. 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.

  5. 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

  6. The infrared astronomical mission AKARI

    NARCIS (Netherlands)

    Murakami, Hiroshi; Baba, Hajime; Barthel, Peter; Clements, David L.; Cohen, Martin; Doi, Yasuo; Enya, Keigo; Figueredo, Elysandra; Fujishiro, Naofumi; Fujiwara, Hideaki; Fujiwara, Mikio; Garcia-Lario, Pedro; Goto, Tomotsugu; Hasegawa, Sunao; Hibi, Yasunori; Hirao, Takanori; Hiromoto, Norihisa; Hong, Seung Soo; Imai, Koji; Ishigaki, Miho; Ishiguro, Masateru; Ishihara, Daisuke; Ita, Yoshifusa; Jeong, Woong-Seob; Jeong, Kyung Sook; Kaneda, Hidehiro; Kataza, Hirokazu; Kawada, Mitsunobu; Kawai, Toshihide; Kawamura, Akiko; Kessler, Martin F.; Kester, Do; Kii, Tsuneo; Kim, Dong Chan; Kim, Wjung; Kobayashi, Hisato; Koo, Bon Chul; Kwon, Suk Minn; Lee, Hyung Mok; Lorente, Rosario; Makiuti, Sin'itirou; Matsuhara, Hideo; Matsumoto, Toshio; Matsuo, Hiroshi; Matsuura, Shuji; Mueller, Thomas G.; Murakami, Noriko; Nagata, Hirohisa; Nakagawa, Takao; Naoi, Takahiro; Narita, Masanao; Noda, Manabu; Oh, Sang Hoon; Ohnishi, Akira; Ohyama, Youichi; Okada, Yoko; Okuda, Haruyuki; Oliver, Sebastian; Onaka, Takashi; Ootsubo, Takafumi; Oyabu, Shinki; Pak, Sojong; Park, Yong-Sun; Pearson, Chris P.; Rowan-Robinson, Michael; Saito, Toshinobu; Sakon, Itsuki; Salama, Alberto; Sato, Shinji; Savage, Richard S.; Serjeant, Stephen; Shibai, Hiroshi; Shirahata, Mai; Sohn, Jungjoo; Suzuki, Toyoaki; Takagi, Toshinobu; Takahashi, Hidenori; Tanabe, Toshihiko; Takeuchi, Tsutomu T.; Takita, Satoshi; Thomson, Matthew; Uemizu, Kazunori; Ueno, Munetaka; Usui, Fumihiko; Verdugo, Eva; Wada, Takehiko; Wang, Lingyu; Watabe, Toyoki; Watarai, Hidenori; White, Glenn J.; Yamamura, Issei; Yamauchi, Chisato; Yasuda, Akiko

    2007-01-01

    AKARI, the first Japanese satellite dedicated to infrared astronomy, was launched on 2006 February 21, and started observations in May of the same year. AKARI has a 68.5 cm cooled telescope, together with two focal-plane instruments, which survey the sky in six wavelength bands from mid- to far-infr

  7. The infrared astronomical mission AKARI

    NARCIS (Netherlands)

    Murakami, Hiroshi; Baba, Hajime; Barthel, Peter; Clements, David L.; Cohen, Martin; Doi, Yasuo; Enya, Keigo; Figueredo, Elysandra; Fujishiro, Naofumi; Fujiwara, Hideaki; Fujiwara, Mikio; Garcia-Lario, Pedro; Goto, Tomotsugu; Hasegawa, Sunao; Hibi, Yasunori; Hirao, Takanori; Hiromoto, Norihisa; Hong, Seung Soo; Imai, Koji; Ishigaki, Miho; Ishiguro, Masateru; Ishihara, Daisuke; Ita, Yoshifusa; Jeong, Woong-Seob; Jeong, Kyung Sook; Kaneda, Hidehiro; Kataza, Hirokazu; Kawada, Mitsunobu; Kawai, Toshihide; Kawamura, Akiko; Kessler, Martin F.; Kester, Do; Kii, Tsuneo; Kim, Dong Chan; Kim, Wjung; Kobayashi, Hisato; Koo, Bon Chul; Kwon, Suk Minn; Lee, Hyung Mok; Lorente, Rosario; Makiuti, Sin'itirou; Matsuhara, Hideo; Matsumoto, Toshio; Matsuo, Hiroshi; Matsuura, Shuji; Mueller, Thomas G.; Murakami, Noriko; Nagata, Hirohisa; Nakagawa, Takao; Naoi, Takahiro; Narita, Masanao; Noda, Manabu; Oh, Sang Hoon; Ohnishi, Akira; Ohyama, Youichi; Okada, Yoko; Okuda, Haruyuki; Oliver, Sebastian; Onaka, Takashi; Ootsubo, Takafumi; Oyabu, Shinki; Pak, Sojong; Park, Yong-Sun; Pearson, Chris P.; Rowan-Robinson, Michael; Saito, Toshinobu; Sakon, Itsuki; Salama, Alberto; Sato, Shinji; Savage, Richard S.; Serjeant, Stephen; Shibai, Hiroshi; Shirahata, Mai; Sohn, Jungjoo; Suzuki, Toyoaki; Takagi, Toshinobu; Takahashi, Hidenori; Tanabe, Toshihiko; Takeuchi, Tsutomu T.; Takita, Satoshi; Thomson, Matthew; Uemizu, Kazunori; Ueno, Munetaka; Usui, Fumihiko; Verdugo, Eva; Wada, Takehiko; Wang, Lingyu; Watabe, Toyoki; Watarai, Hidenori; White, Glenn J.; Yamamura, Issei; Yamauchi, Chisato; Yasuda, Akiko

    2007-01-01

    AKARI, the first Japanese satellite dedicated to infrared astronomy, was launched on 2006 February 21, and started observations in May of the same year. AKARI has a 68.5 cm cooled telescope, together with two focal-plane instruments, which survey the sky in six wavelength bands from mid- to

  8. Assessment of Rainfall-induced Landslide Potential and Spatial Distribution

    Science.gov (United States)

    Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Chiang, Jie-Lun; Hsieh, Shun-Chieh; Chue, Yung-Sheng

    2016-04-01

    Recently, due to the global climate change, most of the time the rainfall in Taiwan is of short duration but with high intensity. Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assesses rainfall-induced (secondary) landslide potential and spatial distribution in watershed of Southern Taiwan under extreme climate change. The study areas in this research are Baolai and Jianshan villages in the watershed of the Laonongxi River Basin in the Southern Taiwan. This study focused on the 3 years after Typhoon Morakot (2009 to 2011). During this period, the study area experienced six heavy rainfall events including five typhoons and one heavy rainfall. The genetic adaptive neural network, texture analysis and GIS were implemented in the analysis techniques for the interpretation of satellite images and to obtain surface information and hazard log data and to analyze land use change. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The interaction between (secondary) landslide mechanism, scale, and location was analyzed using association analysis of landslide historical data and regional environmental characteristics. The results of image classification before and after six heavy rainfall events show that the values of coefficient of agreement are at medium-high level. By multivariate hazards evaluation method, geology and the effective accumulative rainfall (EAR) are the most important factors. Slope, distance from fault, aspect, land disturbance

  9. 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...

  10. Satellite Geomagnetism

    DEFF Research Database (Denmark)

    Olsen, Nils; Stolle, Claudia

    2012-01-01

    Observations of Earth’s magnetic field from space began more than 50 years ago. A continuous monitoring of the field using low Earth orbit (LEO) satellites, however, started only in 1999, and three satellites have taken highprecision measurements of the geomagnetic field during the past decade...... ability to characterize and understand the many sources that contribute to Earth’s magnetic field. In this review, we summarize investigations of Earth’s interior and environment that have been possible through the analysis of high-precision magnetic field observations taken by LEO satellites........ The unprecedented time-space coverage of their data opened revolutionary new possibilities for monitoring, understanding, and exploring Earth’s magnetic field. In the near future, the three-satellite constellation Swarm will ensure continuity of such measurement and provide enhanced possibilities to improve our...

  11. Simulating atmospheric free-space optical propagation: rainfall attenuation

    Science.gov (United States)

    Achour, Maha

    2002-04-01

    With recent advances and interest in Free-Space Optics (FSO) for commercial deployments, more attention has been placed on FSO weather effects and the availability of global weather databases. The Meteorological Visual Range (Visibility) is considered one of the main weather parameters necessary to estimate FSO attenuation due to haze, fog and low clouds. Proper understanding of visibility measurements conducted throughout the years is essential. Unfortunately, such information is missing from most of the databases, leaving FSO players no choice but to use the standard visibility equation based on 2% contrast and other assumptions on the source luminance and its background. Another challenge is that visibility is measured using the visual wavelength of 550 nm. Extrapolating the measured attenuations to longer infrared wavelengths is not trivial and involves extensive experimentations. Scattering of electromagnetic waves by spherical droplets of different sizes is considered to simulate FSO scattering effects. This paper serves as an introduction to a series of publications regarding simulation of FSO atmospheric propagation. This first part focuses on attenuation due to rainfall. Additional weather parameters, such as rainfall rate, temperature and relative humidity are considered to effectively build the rain model. Comparison with already published experimental measurement is performed to validate the model. The scattering cross section due to rain is derived from the density of different raindrop sizes and the raindrops fall velocity is derived from the overall rainfall rate. Absorption due the presence of water vapor is computed using the temperature and relative humidity measurements.

  12. Satellite (Natural)

    Science.gov (United States)

    Murdin, P.

    2000-11-01

    In its most general sense, any celestial object in orbit around a similar larger object. Thus, for example, the Magellanic Clouds are satellite galaxies of our own Milky Way galaxy. Without qualification, the term is used to mean a body in orbit around a planet; an alternative term is moon. The term natural satellite distinguishes these bodies from artificial satellites—spacecraft placed in orbi...

  13. A composite analysis of the Mesoscale Convective Complexes (MCCs) development over the Central Kalimantan and its relation with the propagation of the rainfall systems

    Science.gov (United States)

    Trismidianto; Yulihastin, E.; Satyawardhana, H.; Ishida, S.

    2017-01-01

    The composite analysis for 45-cases of the MCC which identified by using infrared satellite imagery over the Central Kalimantan (110° - 116°E, 4°S - 1°N) has been observed. The data used is a combination of satellite data and reanalysis data. This study reported that the MCCs develops triggered by the orographic convective that helped by the convergent surface wind flow through interaction with the sea breeze in the afternoon until midnight and dissipated in the morning. The new convective systems are generated by the divergent outflow of the cold pool, in conjunction with the morning land breeze during MCCs mature. After dissipated, the new convective systems induce the land convection over the Java Island that became heavy rainfall. The initial and mature region are characterized by weak low-level convergence and upper-level divergence, but the low-level divergence begin appear during mature. The MCC develops largely driven by MCC-scale moisture convergence in the lower troposphere and cold core structure in the lower level. The weak surface divergence and upper-level divergence, warm advection in the lower atmosphere are dissipation characteristics. MCCs develop due to low-level cold advection and temperature and separated when dissipated that indicate the existence of the new convective systems propagation.

  14. Borneo Vortex and Meso-scale Convective Rainfall

    Science.gov (United States)

    Koh, T. Y.; Koseki, S.; Teo, C. K.

    2014-12-01

    We have investigated how the Borneo vortex develops over the equatorial South China Sea under cold surge conditions in December during the Asian winter monsoon. Composite analysis using reanalysis and satellite datasets has revealed that absolute vorticity and water vapour are transported by strong cold surges from upstream of the South China Sea to around the equator. Rainfall is correspondingly enhanced over the equatorial South China Sea. A semi-idealized experiment reproduced the Borneo vortex over the equatorial South China Sea during a perpetual cold surge. The Borneo vortex is manifested as a meso-alpha cyclone with a comma-shaped rainband in the northeast sector of the cyclone. Vorticity budget analysis showed that the growth/maintenance of the meso-alpha cyclone was achieved mainly by the vortex stretching. This vortex stretching is due to the upward motion forced by the latent heat release around the cyclone centre. The comma-shaped rainband consists of clusters of meso-beta scale rainfall cells. The intense rainfall in the comma-head (comma-tail) is generated by the confluence of the warmer and wetter cyclonic easterly flow (cyclonic southeasterly flow) and the cooler and drier northeasterly surge in the northwestern (northeastern) sector of the cyclone. Intense upward motion and heavy rainfall resulted due to the low-level convergence and the favourable thermodynamic profile at the confluence zone. In particular, the convergence in the northwestern sector is responsible for maintenance of the meso-alpha cyclone system. At both meso-alpha and meso-beta scales, the convergence is ultimately caused by the deviatoric strain in the confluence wind pattern but is significantly self-enhanced by the nonlinear dynamics. Reference: Koseki, S., T.-Y. Koh and C.-K. Teo (2014), Atmospheric Chemistry and Physics, 14, 4539-4562, doi:10.5194/acp-14-4539-2014, 2014.

  15. The Cosmic Background Explorer Satellite

    Science.gov (United States)

    Mather, J.; Kelsall, T.

    1980-01-01

    The Cosmic Background Explorer (COBE) satellite, planned for launch in 1985, will measure the diffuse infrared and microwave radiation of the universe over the entire wavelength range from a few microns to 1.3 cm. It will include three instruments: a set of microwave isotropy radiometers at 23, 31, 53, and 90 GHz, an interferometer spectrometer from 1 to 100/cm, and a filter photometer from 1 to 300 microns. The COBE satellite is designed to reach the sensitivity limits set by foreground sources such as the interstellar and interplanetary dust, starlight, and galactic synchrotron radiation, so that a diffuse residual radiation may be interpreted unambiguously as extragalactic

  16. Evaluation of global rainfall Measurement for Hydrological Applications in West Africa : sensitivity tests in Benin

    Science.gov (United States)

    Viarre, J.; Gosset, M.; Peugeot, C.

    2011-12-01

    We carried out an evaluation of currently available -real time or post-calibrated- rainfall products in West Africa. The work is oriented towards highlighting their skills and relevance from the view point of a hydrological end-user. The study is based on the densily instrumented meso-scale basins from the AMMA-CATCH hydrometeorological observing system. On these sites long term observations of the various term of the continental water budget and hydrological processes studies have been carried out for more than a decade. We focus here on the upper Oueme basin site in Benin (Sudanese climate - 1200 mm annual rainfall). A distributed hydrological model, developed in this framework is used to illustrate the effects of satellite based rainfall errors or uncertainty on the simulated outflow. Non linearities cause the rainfall bias to be enhanced through propagation in the model, leading to strong biases in the outflow. In addition to the biases the model response is very sensitive to the distortion in the rainfall intensities probability distribution, that some rainfall products exhibit. The AMMA-CATCH densified gages networks and hydrometeorological measurements will be integrated in the MeghaTropiques ground validation plan and used to asses the quality of MT products at the one degree one daily scale and below.

  17. Flood and Landslide Applications of High Time Resolution Satellite Rain Products

    Science.gov (United States)

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

    2006-01-01

    Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system

  18. 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.

  19. Maritime Continent rainfall variability during the TRMM era: The role of monsoon, topography and El Niño Modoki

    Science.gov (United States)

    As-syakur, Abd. Rahman; Osawa, Takahiro; Miura, Fusanori; Nuarsa, I. Wayan; Ekayanti, Ni Wayan; Dharma, I. Gusti Bagus Sila; Adnyana, I. Wayan Sandi; Arthana, I. Wayan; Tanaka, Tasuku

    2016-09-01

    Rainfall is among the most important climatic elements of the Maritime Continent. The Maritime Continent rainfall climate is uniquely located in the world's most active convective area. Satellite data measured by the Tropical Rainfall Measuring Mission (TRMM) 3B43 based high-resolution rainfall products represent monthly Maritime Continent rainfall characteristics over 16 years. Several statistical scores were employed to analyse annual means, linear trends, seasonal means, and anomalous Maritime Continent rainfall characteristic percentages. The effects of land and topography on rainfall quantities were also studied and compared with the Global Precipitation Climatology Project (GPCP) gridded precipitation estimates which has low-resolution. Comparison also applied on linear correlation and partial correlation techniques to determine the relationship between rainfall and the El Niño Modoki and El Niño-Southern Oscillation (ENSO; hereafter conventional El Niño). The results show that north-south Maritime Continent precipitation is associated with and generated by the northwest and southeast monsoon patterns. In addition, the large-scale circulations are linked with heavy rainfall over this land-ocean region due to large-scale island-topography-induced convective organization. The rainfall responses to El Niño Modoki and conventional El Niño clearly indicated the times at which the conventional El Niño had a higher impact than El Niño Modoki, especially during northern winter and spring, and vice versa during northern fall, and similarly affect during northern summer. Furthermore, the dynamic movements of rainfall anomaly that are caused by El Niño Modoki and the conventional El Niño events spanned from the southwest during June-July-August (JJA) to throughout the northeast ending in March-April-May (MAM).

  20. The impact of model and rainfall forcing errors on characterizing soil moisture uncertainty in land surface modeling

    Directory of Open Access Journals (Sweden)

    V. Maggioni

    2012-10-01

    Full Text Available The contribution of rainfall forcing errors relative to model (structural and parameter uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM, forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty or by adding randomly generated noise (representing model structure and parameter uncertainty to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

  1. A statistical approach for rain class evaluation using Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager observations

    Science.gov (United States)

    Ricciardelli, E.; Cimini, D.; Di Paola, F.; Romano, F.; Viggiano, M.

    2013-11-01

    Precipitation measurements are essential for short term hydrological and long term climate studies. Operational networks of rain gauges and weather radars provide fairly accurate rain rate measurements, but they leave large areas uncovered. Because of this, satellite remote sensing is a useful tool for the detection and characterization of the raining areas in regions where this information remains missing. This study exploits the Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) observations to evaluate the rain class at high spatial and temporal resolutions. The Rain Class Evaluation from Infrared and Visible (RainCEIV) observations technique is proposed. The purpose of RainCEIV is to supply continuous monitoring of convective as well as of stratiform rainfall events. It applies a supervised classifier to the spectral and textural features of infrared and visible MSG-SEVIRI images to classify the cloudy pixels as non rainy, light to moderate rain, or heavy to very heavy rain. The technique considers in input also the water vapour channels brightness temperatures differences for the MSG-SEVIRI images acquired 15/30/45 min before the time of interest. The rainfall rates used in the training phase are obtained with the Precipitation Estimation at Microwave frequencies (PEMW), an algorithm for rain rate retrievals based on Atmospheric Microwave Sounder Unit (AMSU)-B observations. The results of RainCEIV have been validated against radar-derived rainfall measurements from the Italian Operational Weather Radar Network for some case studies limited to the Mediterranean area. The dichotomous assessment shows that RainCEIV is able to detect rainy areas with an accuracy of about 91%, a Heidke skill score of 56%, a Bias score of 1.16, and a Probability of Detection of rainy areas of 66%.

  2. Scientific Satellites

    Science.gov (United States)

    1967-01-01

    followed Hale’s into orbit. In 1879, Jules Verne wrote about launching small satellites with a gun possessing a muzzle velocity of 10 000 m/sec (ref. 3...was activated in 1950.11 It was located only a few tens of miles from the spot where Jules Verne had his Baltimore Gun Club fire a manned projectile to...principle, satellites can be launched by a single impulse applied at the Earth’s surface-say, with a large cannon, & la Jules Verne (sec. 8-3). In

  3. Forecasting Hurricane by Satellite Image

    Science.gov (United States)

    Liu, M. Y.

    Earth is an endanger planet. Severe weather, especially hurricanes, results in great disaster all the world. World Meteorology Organization and United Nations Environment Program established intergovernment Panel on Climate Change (IPCC) to offer warnings about the present and future disasters of the Earth. It is the mission for scientists to design warning system to predict the severe weather system and to reduce the damage of the Earth. Hurricanes invade all the world every year and made millions damage to all the people. Scientists in weather service applied satellite images and synoptic data to forecast the information for the next hours for warning purposes. Regularly, hurricane hits on Taiwan island directly will pass through her domain and neighbor within 10 hours. In this study, we are going to demonstrate a tricky hurricane NARI invaded Taiwan on September 16, 2000. She wandered in the neighborhood of the island more than 72 hours and brought heavy rainfall over the island. Her track is so tricky that scientists can not forecast her path using the regular method. Fortunately, all scientists in the Central Weather Bureau paid their best effort to fight against the tricky hurricane. Applying the new developed technique to analysis the satellite images with synoptic data and radar echo, scientists forecasted the track, intensity and rainfall excellently. Thus the damage of the severe weather reduced significantly.

  4. The impacts of the Indian summer rainfall on North China summer rainfall

    Science.gov (United States)

    Wu, Renguang; Jiao, Yang

    2017-05-01

    Previous studies have indicated a connection between interannual variations of the Indian and North China summer rainfall. An atmospheric circulation wave pattern over the mid-latitude Asia plays an important role in the connection. The present study compares the influence of the above-normal and below-normal Indian summer rainfall on the North China summer rainfall variations. Composite analysis shows that the mid-latitude Asian atmospheric circulation and the North China rainfall anomalies during summer tend to be anti-symmetric in above-normal and below-normal Indian rainfall years. Analysis indicates that the Indian-North China summer rainfall relation tends to be stronger when larger Indian rainfall anomaly occurs during a higher mean rainfall period. The observed long-term change in the Indian-North China summer rainfall relationship cannot be explained by the impact of the El Niño-Southern Oscillation (ENSO). The present study evaluates the Indian-North China summer rainfall relationship in climate models. Analysis shows that the Indian-North China summer rainfall relationship differs largely among different climate models and among different simulations of a specific model. The relationship also displays obvious temporal variations in both individual and ensemble mean model simulations. This suggests an important role of the atmospheric internal variability in the change of the Indian-North China summer rainfall relationship.

  5. 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.

  6. Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

    Science.gov (United States)

    Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

    2011-01-01

    Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

  7. Mapping monthly rainfall erosivity in Europe

    DEFF Research Database (Denmark)

    Ballabio, C; Meusburger, K; Klik, A

    2017-01-01

    Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and...

  8. Polar Operational Environmental Satellites: Looking at Earth

    Science.gov (United States)

    Aleman, Roberto M.

    2000-01-01

    A broad overview of the Polar Operational Environmental Satellites (POES) Project is presented at a very high level. A general description of the scientific instruments on the Television Infrared Observational Satellite (TIROS) spacecraft is presented with emphasis put on their mission and the products derived from the data. Actual pictures produced from POES instruments data are shown to help the audience relate our work to their everyday life, as affected by the weather systems.

  9. Polar Operational Environmental Satellites: Looking at Earth

    Science.gov (United States)

    Aleman, Roberto M.

    2000-01-01

    A broad overview of the Polar Operational Environmental Satellites (POES) Project is presented at a very high level. A general description of the scientific instruments on the Television Infrared Observational Satellite (TIROS) spacecraft is presented with emphasis put on their mission and the products derived from the data. Actual pictures produced from POES instruments data are shown to help the audience relate our work to their everyday life, as affected by the weather systems.

  10. Developments and applications of the Global Satellite Mapping of Precipitation (GSMaP) for the Global Precipitation Measurement (GPM)

    Science.gov (United States)

    Kachi, Misako; Aonashi, Kazumasa; Kubota, Takuji; Shige, Shoichi; Ushio, Tomoo; Mega, Tomoaki; Yamamoto, Munehisa; Hamada, Atsushi; Seto, Shinta; Takayabu, Yukari N.; Oki, Riko

    2016-04-01

    The Global Satellite Mapping of Precipitation (GSMaP) is a global rainfall map based on a blended Microwave-Infrared product and has been developed in Japan for the Global Precipitation Measurement (GPM) mission. To fulfill gaps of passive microwave observations, we developed a method to interpolate observations between each microwave imager by utilizing information from the Infrared imagers on board the geostationary satellites, and achieved production of an hourly global rainfall map in 0.1-degree latitude/longitude grid. The latest GSMaP version 6 product was released in September 2014 to the public as one of Japanese GPM products after the launch of the GPM Core Observatory, which is Japan and U.S. joint mission and carrying both the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI), in February 2014. In the next version (version 7), which is scheduled to be released in the summer 2016, we plan to apply databases produced from DPR instead of those from PR, and to introduce snow retrieval algorithm for the passive microwave instruments that have higher frequency channels. The GSMaP near-real-time version (GSMaP_NRT) product is available 4-hour after observation through the "JAXA Global Rainfall Watch" web site (http://sharaku.eorc.jaxa.jp/GSMaP) since 2008. To assure near-real-time data availability, the GSMaP_NRT system simplified part of the algorithm and its processing procedure. Therefore, the GSMaP_NRT product gives higher priority to data latency than accuracy. Since its data release, GSMaP_NRT data has been used by various users for various purposes, such as rainfall monitoring, flood alert and warning, drought monitoring, crop yield forecast, and agricultural insurance. There are, however, several requirements from users for GSMaP improvements not only for accuracy but also specification. Among those requests for data specification, the most popular ones are shortening of data latency time and higher horizontal resolution. To reduce

  11. Exploration of the Saturn System by the Cassini Mission: Observations with the Cassini Infrared Spectrometer

    Science.gov (United States)

    Abbas, Mian M.

    2014-01-01

    Outline: Introduction to the Cassini mission, and Cassini mission Objectives; Cassini spacecraft, instruments, launch, and orbit insertion; Saturn, Rings, and Satellite, Titan; Composite Infrared Spectrometer (CIRS); and Infrared observations of Saturn and titan.

  12. High Temperature and High QE Broadband Longwave Infrared SLS FPA for LANDSAT Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose a high-performance broadband infrared focal plane array (FPA) for the Thermal Infrared Sensor (TIRS) on NASA's LANDSAT satellite. The FPA will feature a...

  13. Satellite-Based Sunshine Duration for Europe

    Directory of Open Access Journals (Sweden)

    Bodo Ahrens

    2013-06-01

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

  14. Weather radar rainfall data in urban hydrology

    DEFF Research Database (Denmark)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick

    2017-01-01

    Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology...... necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall...... estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological...

  15. Modelling persistence in annual Australia point rainfall

    Directory of Open Access Journals (Sweden)

    J. P. Whiting

    2003-01-01

    Full Text Available Annual rainfall time series for Sydney from 1859 to 1999 is analysed. Clear evidence of nonstationarity is presented, but substantial evidence for persistence or hidden states is more elusive. A test of the hypothesis that a hidden state Markov model reduces to a mixture distribution is presented. There is strong evidence of a correlation between the annual rainfall and climate indices. Strong evidence of persistence of one of these indices, the Pacific Decadal Oscillation (PDO, is presented together with a demonstration that this is better modelled by fractional differencing than by a hidden state Markov model. It is shown that conditioning the logarithm of rainfall on PDO, the Southern Oscillation index (SOI, and their interaction provides realistic simulation of rainfall that matches observed statistics. Similar simulation models are presented for Brisbane, Melbourne and Perth. Keywords: Hydrological persistence,hidden state Markov models, fractional differencing, PDO, SOI, Australian rainfall

  16. Infrared thermography

    CERN Document Server

    Meola, Carosena

    2012-01-01

    This e-book conveys information about basic IRT theory, infrared detectors, signal digitalization and applications of infrared thermography in many fields such as medicine, foodstuff conservation, fluid-dynamics, architecture, anthropology, condition monitoring, non destructive testing and evaluation of materials and structures.

  17. 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.

  18. 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.

  19. Flood forecasting in Niger-Benue basin using satellite and quantitative precipitation forecast data

    Science.gov (United States)

    Haile, Alemseged Tamiru; Tefera, Fekadu Teshome; Rientjes, Tom

    2016-10-01

    Availability of reliable, timely and accurate rainfall data is constraining the establishment of flood forecasting and early warning systems in many parts of Africa. We evaluated the potential of satellite and weather forecast data as input to a parsimonious flood forecasting model to provide information for flood early warning in the central part of Nigeria. We calibrated the HEC-HMS rainfall-runoff model using rainfall data from post real time Tropical Rainfall Measuring Mission (TRMM) Multi satellite Precipitation Analysis product (TMPA). Real time TMPA satellite rainfall estimates and European Centre for Medium-Range Weather Forecasts (ECMWF) rainfall products were tested for flood forecasting. The implication of removing the systematic errors of the satellite rainfall estimates (SREs) was explored. Performance of the rainfall-runoff model was assessed using visual inspection of simulated and observed hydrographs and a set of performance indicators. The forecast skill was assessed for 1-6 days lead time using categorical verification statistics such as Probability Of Detection (POD), Frequency Of Hit (FOH) and Frequency Of Miss (FOM). The model performance satisfactorily reproduced the pattern and volume of the observed stream flow hydrograph of Benue River. Overall, our results show that SREs and rainfall forecasts from weather models have great potential to serve as model inputs for real-time flood forecasting in data scarce areas. For these data to receive application in African transboundary basins, we suggest (i) removing their systematic error to further improve flood forecast skill; (ii) improving rainfall forecasts; and (iii) improving data sharing between riparian countries.

  20. PEMANFAATAN DATA SATELIT TROPICAL RAINFALL MEASURING MISSION (TRMM UNTUK PEMETAAN ZONA AGROKLIMAT OLDEMAN DI KALIMANTAN SELATAN

    Directory of Open Access Journals (Sweden)

    Riza Arian Noor

    2016-12-01

    Full Text Available The irregularity of observation sites distribution and network density, lack data availability and discontinuity are the obstacles to analyzing and producing the information of agroclimate zone in South Kalimantan. TRMM satellite needs to be researched to overcome the limitations of surface observation data. This study intended to validate TRMM 3B43 satellite data with surface rainfall, to produce Oldeman agroclimate zone based on TRMM satellite data and to analyze the agroclimate zone for agricultural resources management. Data validation is done using the statistical method by analyzing the correlation value (r and RMSE (Root Mean Square Error. The agroclimate zone is classified based on Oldeman climate classification type. The calculation results are mapped spatially using Arc GIS 10.2 software. The validation result of the TRMM satellite and surface rainfall data shows a high correlation value for the monthly average. The value of correlation coefficient is 0,97 and 25 mm for RMSE value. Oldeman agroclimate zone based on TRMM satellite data in south Kalimantan is divided into five climate zones, such as B1, B2, C1, C2, and D1.

  1. Validation strategy for satellite observations of tropospheric reactive gases

    Directory of Open Access Journals (Sweden)

    Andreas Richter

    2014-01-01

    Full Text Available Over the last twodecades, satellite observations of tropospheric composition have becomepossible using nadir viewing spectrometers operating in the UV, visible, nearinfrared, and thermal infrared spectral range. [...

  2. Satellite observations of the northeast monsoon coastal current

    Digital Repository Service at National Institute of Oceanography (India)

    Shenoi, S.S.C.; Gouveia, A.D.; Shetye, S.R.; Rao, L.V.G.

    Satellite Infrared observations, from Advanced Very High Resolution Radiometer (AVHRR), during November 1987-February 1988 and hydrographic data from the eastern Arabian Sea are used to describe the poleward flowing coastal current in the eastern...

  3. 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.

  4. Fingerprinting the Impacts of Aerosols on Long-Term Trends of the Indian Summer Monsoon Regional Rainfall

    Science.gov (United States)

    Laul, K. M.; Kim, K. M.

    2010-01-01

    In this paper, we present corroborative observational evidences from satellites, in-situ observations, and re-analysis data showing possible impacts of absorbing aerosols (black carbon and dust) on subseasonal and regional summer monsoon rainfall over India. We find that increased absorbing aerosols in the Indo-Gangetic Plain in recent decades may have lead to long-term warming of the upper troposphere over northern India and the Tibetan Plateau, enhanced rainfall in northern India and the Himalayas foothill regions in the early part (may-June) of the monsoon season, followed by diminished rainfall over central and southern India in the latter part (July-August) of the monsoon season. These signals which are consistent with current theories of atmospheric heating and solar dimming by aerosol and induced cloudiness in modulating the Indian monsoon, would have been masked by conventional method of using al-India rainfall averaged over the entire monsoon season.

  5. 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

  6. Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions

    Directory of Open Access Journals (Sweden)

    S. Yin

    2015-05-01

    Full Text Available Rainfall erosivity is the power of rainfall to cause soil erosion by water. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 min intensity of individual events. However, these data are often unavailable in many areas of the world. The purpose of this study was to develop models that relate more commonly available rainfall data resolutions, such as daily or monthly totals, to rainfall erosivity. Eleven stations with one-minute temporal resolution rainfall data collected from 1961 through 2000 in the eastern water-erosion areas of China were used to develop and calibrate 21 models. Seven independent stations, also with one-minute data, were utilized to validate those models, together with 20 previously published equations. Results showed that models in this study performed better or similar to models from previous research to estimate rainfall erosivity for these data. Prediction capabilities, as determined using symmetric mean absolute percentage errors and Nash–Sutcliffe model efficiency coefficients, were demonstrated for the 41 models including those for estimating erosivity at event, daily, monthly, yearly, average monthly and average annual time scales. Prediction capabilities were generally better using higher resolution rainfall data as inputs. For example, models with rainfall amount and maximum 60 min rainfall amount as inputs performed better than models with rainfall amount and maximum daily rainfall amount, which performed better than those with only rainfall amount. Recommendations are made for choosing the appropriate estimation equation, which depend on objectives and data availability.

  7. Heavy daily-rainfall characteristics over the Gauteng Province

    African Journals Online (AJOL)

    2009-02-09

    Feb 9, 2009 ... Department of Geography, Geoinformatics and Meteorology, Geography Building 2-12, University of .... An example of heavy rainfall 'climatology' in the scientific .... rainfall stations in the calculation of the area-average rainfall.

  8. 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 assess