WorldWideScience

Sample records for satellite rainfall algorithms

  1. 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.

  2. 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.

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

    Science.gov (United States)

    Bitew, Menberu M.; Gebremichael, Mekonnen

    2011-06-01

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

  4. Satellite rainfall retrieval by logistic regression

    Science.gov (United States)

    Chiu, Long S.

    1986-01-01

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

  5. 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

  6. 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.

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

    Science.gov (United States)

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

    2007-01-01

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

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

    Science.gov (United States)

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

    2015-04-01

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

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

    Science.gov (United States)

    Veerakachen, Watcharee; Raksapatcharawong, Mongkol

    2015-09-01

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

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

    Science.gov (United States)

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

    2016-04-01

    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

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

    Science.gov (United States)

    Cutrim, Elen Maria Camara

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

  12. 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.

  13. Initialization with diabatic heating from satellite-derived rainfall

    Science.gov (United States)

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

    2007-07-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  15. 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.

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

    Science.gov (United States)

    Lazri, Mourad; Ameur, Soltane

    2016-09-01

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

  17. Sampling errors in rainfall estimates by multiple satellites

    Science.gov (United States)

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

    1993-01-01

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

  18. U.S. rainfall satellite missions in flux

    Science.gov (United States)

    Zielinski, Sarah

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

  19. 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

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

    Science.gov (United States)

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

    2009-04-01

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

  1. 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.

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

    Science.gov (United States)

    Ebert, Elizabeth E.; Weymouth, Gary T.

    1999-01-01

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

  3. 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

  4. A Regenerative Prediction Algorithm for Indian Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    SEEMA MAHAJAN

    2013-11-01

    Full Text Available Rainfall forecasting is critical for the crop planning and water management strategies. Proposed study presents a novel approach for modelling time series precipitation data. The 51 years of Indian rainfall data is used for the development of the model. We use nonlinear predictive code based on 11th order with 240 coefficients. Coefficients are optimized using gradient descendent algorithm. Algorithm is tested using 40 years of rainfall training data. Prediction error tested outside training period is found less than1% for few months. Prediction period is extended to one year by including progressive predicted values in input samples using regenerative feedback algorithm. This model is applied for different training and testing periods with average error of 2% to 10%.

  5. 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

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

    Directory of Open Access Journals (Sweden)

    F. S. Marzano

    2005-01-01

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

  7. 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.

  8. 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.

  9. A novel algorithm for satellite data transmission

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    For remote sensing satellite data transmission,a novel algorithm is proposed in this paper.It integrates different type feature descriptors into multistage recognizers.In the first level,the dynamic clustering algorithm is used.In the second level,the improved support vector machines algorithm demonstrates its validity.In the third level,the shape matrices similarity comparison algorithm shows its excellent performance.The single child recognizers are connected in series,but they are independent of each other.Objects which are not recognized correctly by the lower level recognizers are then put into the higher level recognizers.Experimental results show that the multistage recognition algorithm improves the accuracy greatly with higher level feature descriptors and higher level recognizers.The algorithm may offer a new methodology for high speed satellite data transmission.

  10. 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

  11. 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

  12. 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.

  13. 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...

  14. Comparison of satellite reflectance algorithms for estimating ...

    Science.gov (United States)

    We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop simple proxies for algal blooms and to facilitate portability between multispectral satellite imagers for regional algal bloom monitoring. Narrow band hyperspectral aircraft images were upscaled spectrally and spatially to simulate 5 current and near future satellite imaging systems. Established and new Chl-a algorithms were then applied to the synthetic satellite images and then compared to calibrated Chl-a water truth measurements collected from 44 sites within one hour of aircraft acquisition of the imagery. Masks based on the spatial resolution of the synthetic satellite imagery were then applied to eliminate mixed pixels including vegetated shorelines. Medium-resolution Landsat and finer resolution data were evaluated against 29 coincident water truth sites. Coarse-resolution MODIS and MERIS-like data were evaluated against 9 coincident water truth sites. Each synthetic satellite data set was then evaluated for the performance of a variety of spectrally appropriate algorithms with regard to the estimation of Chl-a concentrations against the water truth data set. The goal is to inform water resource decisions on the appropriate satellite data acquisition and processing for the es

  15. 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

  16. 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

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

    Science.gov (United States)

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

    2014-12-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  19. 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.

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

    Science.gov (United States)

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

    2012-04-01

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

  1. 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.

  2. 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.

  3. TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms

    Directory of Open Access Journals (Sweden)

    Patrick Marina

    2017-01-01

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

  4. 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.

  5. New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

    Science.gov (United States)

    Liberman, Y.; Samuels, R.; Alpert, P.; Messer, H.

    2014-10-01

    One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date, the most effective methods for large-scale rainfall estimates are radar, satellites, and, more recently, received signal level (RSL) measurements derived from commercial microwave networks (CMNs). While these methods provide improved spatial resolution over traditional rain gauges, they have their limitations as well. For example, wireless CMNs, which are comprised of microwave links (ML), are dependant upon existing infrastructure and the ML' arbitrary distribution in space. Radar, on the other hand, is known in its limitation for accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rainfall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that, by using the proposed new method, we not only generate more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show that our method outperforms CMNs or the radar alone in rain rate estimation, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, as well as the accurate rainfall measurements over large areas at sub-hourly timescales, will allow for improved understanding, initialization, and calibration of hydrological and meteorological models mainly necessary for water resource management and planning.

  6. 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.

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

    Science.gov (United States)

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

    2017-05-01

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

  8. Earth Observation Satellites Scheduling Based on Decomposition Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Feng Yao

    2010-11-01

    Full Text Available A decomposition-based optimization algorithm was proposed for solving Earth Observation Satellites scheduling problem. The problem was decomposed into task assignment main problem and single satellite scheduling sub-problem. In task assignment phase, the tasks were allocated to the satellites, and each satellite would schedule the task respectively in single satellite scheduling phase. We adopted an adaptive ant colony optimization algorithm to search the optimal task assignment scheme. Adaptive parameter adjusting strategy and pheromone trail smoothing strategy were introduced to balance the exploration and the exploitation of search process. A heuristic algorithm and a very fast simulated annealing algorithm were proposed to solve the single satellite scheduling problem. The task assignment scheme was valued by integrating the observation scheduling result of multiple satellites. The result was responded to the ant colony optimization algorithm, which can guide the search process of ant colony optimization. Computation results showed that the approach was effective to the satellites observation scheduling problem.

  9. New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

    Directory of Open Access Journals (Sweden)

    Y. Liberman

    2014-05-01

    Full Text Available One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date the most effective methods for large scale rainfall estimates are radar, satellites, and more recently, received signal level (RSL measurements received from commercial microwave networks (CMN. While these methods provide improved spatial resolution over traditional rain gauges, these have their limitations as well. For example, the wireless CMN, which are comprised of microwave links (ML, are dependant upon existing infrastructure, and the ML arbitrary distribution in space. Radar, on the other hand, is known in its limitation in accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rain fall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that by using the proposed new method we not only generate a more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show an improvement of rain rate estimation over CMN or radar alone, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, and the accurate rainfall measurements over large areas at sub-hourly time scales, will allow for improved understanding, initialization and calibration of hydrological and meteorological models necessary, mainly, for water resource management and planning.

  10. 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

  11. 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.

  12. Genetic Algorithms for Satellite Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Fatos Xhafa

    2012-01-01

    Full Text Available Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.

  13. 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.

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

    Science.gov (United States)

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

    2017-04-01

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

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. A Hybrid Algorithm for Satellite Data Transmission Schedule Based on Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    LI Yun-feng; WU Xiao-yue

    2008-01-01

    A hybrid scheduling algorithm based on genetic algorithm is proposed in this paper for reconnaissance satellite data transmission. At first, based on description of satellite data transmission request, satellite data transmission task modal and satellite data transmission scheduling problem model are established. Secondly, the conflicts in scheduling are discussed. According to the meaning of possible conflict, the method to divide possible conflict task set is given. Thirdly, a hybrid algorithm which consists of genetic algorithm and heuristic information is presented. The heuristic information comes from two concepts, conflict degree and conflict number. Finally, an example shows the algorithm's feasibility and performance better than other traditional algorithms.

  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. 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.

  3. An enhanced algorithm to estimate BDS satellite's differential code biases

    Science.gov (United States)

    Shi, Chuang; Fan, Lei; Li, Min; Liu, Zhizhao; Gu, Shengfeng; Zhong, Shiming; Song, Weiwei

    2016-02-01

    This paper proposes an enhanced algorithm to estimate the differential code biases (DCB) on three frequencies of the BeiDou Navigation Satellite System (BDS) satellites. By forming ionospheric observables derived from uncombined precise point positioning and geometry-free linear combination of phase-smoothed range, satellite DCBs are determined together with ionospheric delay that is modeled at each individual station. Specifically, the DCB and ionospheric delay are estimated in a weighted least-squares estimator by considering the precision of ionospheric observables, and a misclosure constraint for different types of satellite DCBs is introduced. This algorithm was tested by GNSS data collected in November and December 2013 from 29 stations of Multi-GNSS Experiment (MGEX) and BeiDou Experimental Tracking Stations. Results show that the proposed algorithm is able to precisely estimate BDS satellite DCBs, where the mean value of day-to-day scattering is about 0.19 ns and the RMS of the difference with respect to MGEX DCB products is about 0.24 ns. In order to make comparison, an existing algorithm based on IGG: Institute of Geodesy and Geophysics, China (IGGDCB), is also used to process the same dataset. Results show that, the DCB difference between results from the enhanced algorithm and the DCB products from Center for Orbit Determination in Europe (CODE) and MGEX is reduced in average by 46 % for GPS satellites and 14 % for BDS satellites, when compared with DCB difference between the results of IGGDCB algorithm and the DCB products from CODE and MGEX. In addition, we find the day-to-day scattering of BDS IGSO satellites is obviously lower than that of GEO and MEO satellites, and a significant bias exists in daily DCB values of GEO satellites comparing with MGEX DCB product. This proposed algorithm also provides a new approach to estimate the satellite DCBs of multiple GNSS systems.

  4. Advances in Satellite Microwave Precipitation Retrieval Algorithms Over Land

    Science.gov (United States)

    Wang, N. Y.; You, Y.; Ferraro, R. R.

    2015-12-01

    Precipitation plays a key role in the earth's climate system, particularly in the aspect of its water and energy balance. Satellite microwave (MW) observations of precipitation provide a viable mean to achieve global measurement of precipitation with sufficient sampling density and accuracy. However, accurate precipitation information over land from satellite MW is a challenging problem. The Goddard Profiling Algorithm (GPROF) algorithm for the Global Precipitation Measurement (GPM) is built around the Bayesian formulation (Evans et al., 1995; Kummerow et al., 1996). GPROF uses the likelihood function and the prior probability distribution function to calculate the expected value of precipitation rate, given the observed brightness temperatures. It is particularly convenient to draw samples from a prior PDF from a predefined database of observations or models. GPROF algorithm does not search all database entries but only the subset thought to correspond to the actual observation. The GPM GPROF V1 database focuses on stratification by surface emissivity class, land surface temperature and total precipitable water. However, there is much uncertainty as to what is the optimal information needed to subset the database for different conditions. To this end, we conduct a database stratification study of using National Mosaic and Multi-Sensor Quantitative Precipitation Estimation, Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Technology Microwave Sounder (ATMS) and reanalysis data from Modern-Era Retrospective Analysis for Research and Applications (MERRA). Our database study (You et al., 2015) shows that environmental factors such as surface elevation, relative humidity, and storm vertical structure and height, and ice thickness can help in stratifying a single large database to smaller and more homogeneous subsets, in which the surface condition and precipitation vertical profiles are similar. It is found that the probability of detection (POD) increases

  5. 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.

  6. 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.

  7. 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.

  8. A Minimum Cost Handover Algorithm for Mobile Satellite Networks

    Institute of Scientific and Technical Information of China (English)

    Zhang Tao; Zhang Jun

    2008-01-01

    For mobile satellite networks,an appropriate handover scheme should be devised to shorten handover delay with optimized application of network resources.By introducing the handover cost model of service,this article proposes a rerouting triggering scheme for path optimization after handover and a new minimum cost handover algorithm for mobile satellite networks.This algorithm ensures the quality of service (QoS) parameters,such as delay,during the handover and minimizes the handover costs.Simulation indicates that this algorithm is superior to other current algorithms in guaranteeing the QoS and decreasing handover costs.

  9. Packet routing algorithm for polar orbit LEO satellite constellation network

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Broadband satellite networks are capable of providing global coverage and support various services. The networks constructed by Low Earth Orbit (LEO) satellite constellations have attracted great interests because of their short round-trip delays and wide bandwidths. A challenging problem is to develop a simple and efficient packet routing algorithm for the LEO satellite constellation network. This paper presents a SpiderWeb Topological Network (SWTN) and a distributed packet routing algorithm for the LEO satellite constellation network based on the SWTN. The algorithm gives the minimum propagation delay paths with low computational complexity and requires no routing tables, which is practical for on-board processing. The performance of the algorithm is demonstrated through simulations.

  10. Improved radar data processing algorithms for quantitative rainfall estimation in real time.

    Science.gov (United States)

    Krämer, S; Verworn, H R

    2009-01-01

    This paper describes a new methodology to process C-band radar data for direct use as rainfall input to hydrologic and hydrodynamic models and in real time control of urban drainage systems. In contrast to the adjustment of radar data with the help of rain gauges, the new approach accounts for the microphysical properties of current rainfall. In a first step radar data are corrected for attenuation. This phenomenon has been identified as the main cause for the general underestimation of radar rainfall. Systematic variation of the attenuation coefficients within predefined bounds allows robust reflectivity profiling. Secondly, event specific R-Z relations are applied to the corrected radar reflectivity data in order to generate quantitative reliable radar rainfall estimates. The results of the methodology are validated by a network of 37 rain gauges located in the Emscher and Lippe river basins. Finally, the relevance of the correction methodology for radar rainfall forecasts is demonstrated. It has become clearly obvious, that the new methodology significantly improves the radar rainfall estimation and rainfall forecasts. The algorithms are applicable in real time.

  11. Algorithm of orbit determination using one or two GPS satellites

    Institute of Scientific and Technical Information of China (English)

    刘艳芳; 洪炳荣; 郭建宁; 巨涛

    1999-01-01

    The problem of orbit determination using one or two GPS satellites is discussed. Methods of getting initial values based on linear translation is presented; the Secant method and the descend Newton iterative procedure and the continuation algorithm are used synthetically to solve the nonlinear equations. Computer simulation shows that this algorithm can give preliminary state of satellite orbit with a certain precision in short time.

  12. 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

  13. Genetic algorithm optimized rainfall-runoff fuzzy inference system for row crop watersheds with claypan soils

    Science.gov (United States)

    The fuzzy logic algorithm has the ability to describe knowledge in a descriptive human-like manner in the form of simple rules using linguistic variables, and provides a new way of modeling uncertain or naturally fuzzy hydrological processes like non-linear rainfall-runoff relationships. Fuzzy infe...

  14. PACKET ROUTING ALGORITHM FOR LEO SATELLITE CONSTELLATION NETWORK

    Institute of Scientific and Technical Information of China (English)

    Wang Kaidong; Tian Bin; Yi Kechu

    2005-01-01

    A novel distributed packet routing algorithm for Low Earth Orbit (LEO) satellite networks based on spiderweb topology is presented. The algorithm gives the shortest path with very low computational complexity and without on-board routing tables, which is suitable and practical for on-board processing. Simulation results show its practicability and feasibility.

  15. Dynamic Routing Algorithm for Increasing Robustness in Satellite Networks

    Institute of Scientific and Technical Information of China (English)

    LI Dong-ni; ZHANG Da-kun

    2008-01-01

    In low earth orbit(LEO)and medium earth orbit(MEO)satellite networks,the network topology changes rapidly because of the high relative speed movement of satellites.When some inter-satellite links (ISLs)fail,they can not be repaired in a short time.In order to increase the robustness for LEO/MEO satellite networks,an effective dynamic routing algorithm is proposed.All the routes to a certain node are found by constructing a destination oriented acyclic directed graph(DOADG)with the node as the destination.In this algorithm,multiple routes are provided,loop-free is guaranteed,and as long as the DOADG maintains,it is not necessary to reroute even if some ISLs fail.Simulation results show that comparing to the conventional routing algorithms,it is more efficient and reliable,costs less transmission overhead and converges faster.

  16. 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

  17. Rainfall estimation from in situ soil moisture observations at several sites in Europe: an evaluation of the SM2RAIN algorithm

    Directory of Open Access Journals (Sweden)

    Brocca Luca

    2015-09-01

    Full Text Available Rain gauges, weather radars, satellite sensors and modelled data from weather centres are used operationally for estimating the spatial-temporal variability of rainfall. However, the associated uncertainties can be very high, especially in poorly equipped regions of the world. Very recently, an innovative method, named SM2RAIN, that uses soil moisture observations to infer rainfall, has been proposed by Brocca et al. (2013 with very promising results when applied with in situ and satellite-derived data. However, a thorough analysis of the physical consistency of the SM2RAIN algorithm has not been carried out yet. In this study, synthetic soil moisture data generated from a physically-based soil water balance model are employed to check the reliability of the assumptions made in the SM2RAIN algorithm. Next, high quality and multiyear in situ soil moisture observations, at different depths (5-30 cm, and rainfall for ten sites across Europe are used for testing the performance of the algorithm, its limitations and applicability range.

  18. 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.

  19. 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

  20. 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.

  1. Efficient Satellite Scheduling Based on Improved Vector Evaluated Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Tengyue Mao

    2012-03-01

    Full Text Available Satellite scheduling is a typical multi-peak, many-valley, nonlinear multi-objective optimization problem. How to effectively implement the satellite scheduling is a crucial research in space areas.This paper mainly discusses the performance of VEGA (Vector Evaluated Genetic Algorithm based on the study of basic principles of VEGA algorithm, algorithm realization and test function, and then improves VEGA algorithm through introducing vector coding, new crossover and mutation operators, new methods to assign fitness and hold good individuals. As a result, the diversity and convergence of improved VEGA algorithm of improved VEGA algorithm have been significantly enhanced and will be applied to Earth-Mars orbit optimization. At the same time, this paper analyzes the results of the improved VEGA, whose results of performance analysis and evaluation show that although VEGA has a profound impact upon multi-objective evolutionary research,  multi-objective evolutionary algorithm on the basis of Pareto seems to be a more effective method to get the non-dominated solutions from the perspective of diversity and convergence of experimental result. Finally, based on Visual C + + integrated development environment, we have implemented improved vector evaluation algorithm in the satellite scheduling.

  2. Mapping cultivable land from satellite imagery with clustering algorithms

    Science.gov (United States)

    Arango, R. B.; Campos, A. M.; Combarro, E. F.; Canas, E. R.; Díaz, I.

    2016-07-01

    Open data satellite imagery provides valuable data for the planning and decision-making processes related with environmental domains. Specifically, agriculture uses remote sensing in a wide range of services, ranging from monitoring the health of the crops to forecasting the spread of crop diseases. In particular, this paper focuses on a methodology for the automatic delimitation of cultivable land by means of machine learning algorithms and satellite data. The method uses a partition clustering algorithm called Partitioning Around Medoids and considers the quality of the clusters obtained for each satellite band in order to evaluate which one better identifies cultivable land. The proposed method was tested with vineyards using as input the spectral and thermal bands of the Landsat 8 satellite. The experimental results show the great potential of this method for cultivable land monitoring from remote-sensed multispectral imagery.

  3. A Fast Prediction Algorithm of Satellite Passes

    OpenAIRE

    Palmer, P. L.; Mai, Yan

    2000-01-01

    Low cost, fast access and multi-functional small satellites are being increasingly used to provide and exchange information for a wide variety of professions. They are particularly useful, for example, as a resource in very remote areas where they can provide useful information such as to rescue teams for changing conditions in a disaster zone and monitoring the sea state to warn approaching shipping. Unlike terrestrial communication systems, the receiver/transmitter in these di_erent applica...

  4. 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

  5. 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.

  6. SOLUTION OF THE SATELLITE TRANSFER PROBLEM WITH HYBRID MEMETIC ALGORITHM

    Directory of Open Access Journals (Sweden)

    A. V. Panteleyev

    2014-01-01

    Full Text Available This paper presents a hybrid memetic algorithm (MA to solve the problem of finding the optimal program control of nonlinear continuous deterministic systems based on the concept of the meme, which is one of the promising solutions obtained in the course of implementing the procedure for searching the extremes. On the basis of the proposed algorithm the software complex is formed in C#. The solution of satellite transfer problem is presented.

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. Heuristic Scheduling Algorithm Oriented Dynamic Tasks for Imaging Satellites

    Directory of Open Access Journals (Sweden)

    Maocai Wang

    2014-01-01

    Full Text Available Imaging satellite scheduling is an NP-hard problem with many complex constraints. This paper researches the scheduling problem for dynamic tasks oriented to some emergency cases. After the dynamic properties of satellite scheduling were analyzed, the optimization model is proposed in this paper. Based on the model, two heuristic algorithms are proposed to solve the problem. The first heuristic algorithm arranges new tasks by inserting or deleting them, then inserting them repeatedly according to the priority from low to high, which is named IDI algorithm. The second one called ISDR adopts four steps: insert directly, insert by shifting, insert by deleting, and reinsert the tasks deleted. Moreover, two heuristic factors, congestion degree of a time window and the overlapping degree of a task, are employed to improve the algorithm’s performance. Finally, a case is given to test the algorithms. The results show that the IDI algorithm is better than ISDR from the running time point of view while ISDR algorithm with heuristic factors is more effective with regard to algorithm performance. Moreover, the results also show that our method has good performance for the larger size of the dynamic tasks in comparison with the other two methods.

  12. 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

  13. 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

  14. 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

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

    Science.gov (United States)

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

    2012-12-01

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

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

    Science.gov (United States)

    Gosset, M.; Roca, R.

    2012-04-01

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

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

    Science.gov (United States)

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

    2015-10-01

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

  18. 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.

  19. Optimal reconfiguration of satellite constellations with the auction algorithm

    Science.gov (United States)

    de Weck, Olivier L.; Scialom, Uriel; Siddiqi, Afreen

    2008-01-01

    Traditionally, satellite constellation design has focused on optimizing global, zonal or regional coverage with a minimum number of satellites. In some instances, however, it is desirable to deploy a constellation in stages to gradually expand capacity. This requires launching additional satellites and reconfiguring the existing on-orbit satellites. Also, a constellation might be retasked and reconfigured after it is initially fielded for operational reasons. This paper presents a methodology for optimizing orbital reconfigurations of satellite constellations. The work focuses on technical aspects for transforming an initial constellation A into a new constellation, B, typically with a larger number of satellites. A general framework was developed to study the orbital reconfiguration problem. The framework was applied to low Earth orbit constellations of communication satellites. This paper specifically addresses the problem of determining the optimal assignment for transferring on-orbit satellites in constellation A to constellation B such that the total ΔV for the reconfiguration is minimized. It is shown that the auction algorithm, used for solving general network flow problems, can efficiently and reliably determine the optimum assignment of satellites of A to slots of B. Based on this methodology, reconfiguration maps can be created, which show the energy required for transforming one constellation into another as a function of type (Street-of-Coverage, Walker, Draim), altitude, ground elevation angle and fold of coverage. Suggested extensions of this work include quantification of the tradeoff between reconfiguration time and ΔV, multiple successive reconfigurations, balancing propellant consumption within the constellation during reconfiguration as well as using reconfigurability as an objective during initial constellation design.

  20. 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.

  1. Improvements and Extensions for Joint Polar Satellite System Algorithms

    Science.gov (United States)

    Grant, K. D.

    2016-12-01

    The National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation civilian weather satellite system: the Joint Polar Satellite System (JPSS). JPSS replaced the afternoon orbit component and ground processing of the old POES system managed by NOAA. JPSS satellites carry sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground processing system for JPSS is the Common Ground System (CGS), and provides command, control, and communications (C3), data processing and product delivery. CGS's data processing capability provides environmental data products (Sensor Data Records (SDRs) and Environmental Data Records (EDRs)) to the NOAA Satellite Operations Facility. The first satellite in the JPSS constellation, S-NPP, was launched in October 2011. The second satellite, JPSS-1, is scheduled for launch in January 2017. During a satellite's calibration and validation (Cal/Val) campaign, numerous algorithm updates occur. Changes identified during Cal/Val become available for implementation into the operational system for both S-NPP and JPSS-1. In addition, new capabilities, such as higher spectral and spatial resolution, will be exercised on JPSS-1. This paper will describe changes to current algorithms and products as a result of S-NPP Cal/Val and related initiatives for improved capabilities. Improvements include Cross Track Infrared Sounder high spectral processing, extended spectral and spatial ranges for Ozone Mapping and Profiler Suite ozone Total Column and Nadir Profiles, and updates to Vegetation Index, Snow Cover, Active Fires, Suspended Matter, and Ocean Color. Updates will include Sea Surface Temperature, Cloud Mask, Cloud Properties, and other improvements.

  2. 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.

  3. A new algorithm for agile satellite-based acquisition operations

    Science.gov (United States)

    Bunkheila, Federico; Ortore, Emiliano; Circi, Christian

    2016-06-01

    Taking advantage of the high manoeuvrability and the accurate pointing of the so-called agile satellites, an algorithm which allows efficient management of the operations concerning optical acquisitions is described. Fundamentally, this algorithm can be subdivided into two parts: in the first one the algorithm operates a geometric classification of the areas of interest and a partitioning of these areas into stripes which develop along the optimal scan directions; in the second one it computes the succession of the time windows in which the acquisition operations of the areas of interest are feasible, taking into consideration the potential restrictions associated with these operations and with the geometric and stereoscopic constraints. The results and the performances of the proposed algorithm have been determined and discussed considering the case of the Periodic Sun-Synchronous Orbits.

  4. 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

  5. Handoff algorithm for mobile satellite systems with ancillary terrestrial component

    KAUST Repository

    Sadek, Mirette

    2012-06-01

    This paper presents a locally optimal handoff algorithm for integrated satellite/ground communication systems. We derive the handoff decision function and present the results in the form of tradeoff curves between the number of handoffs and the number of link degradation events in a given distance covered by the mobile user. This is a practical receiver-controlled handoff algorithm that optimizes the handoff process from a user perspective based on the received signal strength rather than from a network perspective. © 2012 IEEE.

  6. A sustainable genetic algorithm for satellite resource allocation

    Science.gov (United States)

    Abbott, R. J.; Campbell, M. L.; Krenz, W. C.

    1995-01-01

    A hybrid genetic algorithm is used to schedule tasks for 8 satellites, which can be modelled as a robot whose task is to retrieve objects from a two dimensional field. The objective is to find a schedule that maximizes the value of objects retrieved. Typical of the real-world tasks to which this corresponds is the scheduling of ground contacts for a communications satellite. An important feature of our application is that the amount of time available for running the scheduler is not necessarily known in advance. This requires that the scheduler produce reasonably good results after a short period but that it also continue to improve its results if allowed to run for a longer period. We satisfy this requirement by developing what we call a sustainable genetic algorithm.

  7. Satellite Constellation Design with Adaptively Continuous Ant System Algorithm

    Institute of Scientific and Technical Information of China (English)

    He Quan; Han Chao

    2007-01-01

    The ant system algorithm (ASA) has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a (n + 1)-fold coverage rate is put forward to evaluate the coverage performance of a satellite constellation. An optimization model of constellation parameters is established on the basis of the coverage performance. As a newly developed method, ASA can be applied to optimize the constellation parameters. In order to improve the ASA,a rule for adaptive number of ants is proposed, by which the search range is obviously enlarged and the convergence speed increased.Simulation results have shown that the ASA is more quick and efficient than other methods.

  8. TCP-ATCA: Improved Transmission Control Algorithm in Satellite Network

    Institute of Scientific and Technical Information of China (English)

    Liu Feng; Liu Hengna; Zhao Han

    2008-01-01

    An adaptive transmission control algorithm based on TCP (TCP-ATCA) is proposed to reduce the effects of long propagation de- lay and high link error rate of the satellite network on the performances. The flow control and the error recovery are differentiated by combined dynamic random early detection-explicit congestion notification (DRED-ECN) algorithm, and, moreover, the pertaining con- gestion control methods are used in TCP-ATCA to improve the throughput. By introducing the entire recovery algorithm, the unneces- sary congestion window decrease is reduced, and the throughput and fairness are improved. Simulation results show that, compared with TCP-Reno, TCP-ATCA provides a better throughput performance when the link capacity is higher (≥ 600 packet/s), and roughly the same when it is lower. At the same time, TCP-ATCA also increases fairness and reduces transmission delay.

  9. 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

  10. 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

  11. 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

  12. A dual-polarisation radar rainfall estimation method using a multi-parameter fuzzy logic algorithm

    Science.gov (United States)

    Hall, Will; Rico-Ramirez, Miguel Angel

    2017-04-01

    The emergence of dual-polarisation radar has resulted in a significant enhancement of quantitative precipitation estimation (QPE). It has enabled the measurement of rain drop size and shapes within a volume, the classification of hydrometeors, and the ability to more accurately account for attenuation of the radar beam. Previous methods for QPE have used only the radar reflectivity (Zh) to estimate rainfall, but more recent methods can use a combination of ZH, differential reflectivity (Zdr), specific differential phase (Kdp), and specific attenuation (Ah). The radar variables perform differently depending on rain rate, attenuation, and bright band presence. This has led to the use of fixed threshold values within which the different estimators are used, or the variables are weighted based on performance. This new method to be presented will use fuzzy logic to try to form a more robust algorithm using combinations of the rainfall estimators R(Zh), R(Kdp), and R(Ah). For this a C-band dual-polarised radar based in Hameldon Hill, near Burnley, UK, will be used, alongside a rain gauge network for calibration adn validation.

  13. ALGORITHM OF SAR SATELLITE ATTITUDE MEASUREMENT USING GPS AIDED BY KINEMATIC VECTOR

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In this paper, in order to improve the accuracy of the Synthetic Aperture Radar (SAR)satellite attitude using Global Positioning System (GPS) wide-band carrier phase, the SAR satellite attitude kinematic vector and Kalman filter are introduced. Introducing the state variable function of GPS attitude determination algorithm in SAR satellite by means of kinematic vector and describing the observation function by the GPS wide-band carrier phase, the paper uses the Kalman filter algorithm to obtian the attitude variables of SAR satellite. Compared the simulation results of Kalman filter algorithm with the least square algorithm and explicit solution, it is indicated that the Kalman filter algorithm is the best.

  14. 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

  15. A satellite schedulability prediction algorithm for EO SPS

    Institute of Scientific and Technical Information of China (English)

    Li Jun; Li Jun; Jing Ning; Hu Weidong; Chen Hao

    2013-01-01

    With notably few exceptions,the existing satellite mission operations cannot provide the ability of schedulability prediction,including the latest satellite planning service (SPS) standard-Sensor Planning Service Interface Standard 2.0 Earth Observation Satellite Tasking Extension (EO SPS) approved by Open Geospatial Consortium (OGC).The requestor can do nothing but waiting for the results of time consuming batch scheduling.It is often too late to adjust the request when receiving scheduling failures.A supervised learning algorithm based on robust decision tree and bagging support vector machine (Bagging SVM) is proposed to solve the problem above.The Bagging SVM is applied to improve the accuracy of classification and robust decision tree is utilized to reduce the error mean and error variation.The simulations and analysis show that a prediction action can be accomplished in near real-time with high accuracy.This means the decision makers can maximize the probability of successful scheduling through changing request parameters or take action to accommodate the scheduling failures in time.

  16. Image Dodging Algorithm for GF-1 Satellite WFV Imagery

    Directory of Open Access Journals (Sweden)

    HAN Jie

    2016-12-01

    Full Text Available Image dodging method is one of the important processes that determines whether the mosaicking image can be used for remote sensing quantitative application. GF-1 satellite is the first satellite in CHEOS (Chinese high-resolution earth observation system. WFV multispectral sensor is one of the instruments onboard GF-1 satellite which consist of four cameras to mosaic imaging. According to the characteristics of WFV sensor, this paper proposes an image dodging algorithm based on cross/inter-radiometric calibration method. First, the traditional cross calibration method is applied to obtain the calibration coefficients of one WFV camera. Then statistical analysis and simulation methods are adopted to build the correlation models of DN and TOA (top of atmosphere radiances between adjacent cameras. The proposed method can not only accomplish the radiation performance transfer, but also can fulfill the image dodging. The experimental results show the cross/inter-radiometric calibration coefficients in this paper can effectively eliminate the radiation inconsistency problem of the adjacent camera image which realizes the image dodging. So our proposed dodging method can provide an important reference for other similar sensor in future.

  17. 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.

  18. Visibility conflict resolution for multiple antennae and multi-satellites via genetic algorithm

    Science.gov (United States)

    Lee, Junghyun; Hyun, Chung; Ahn, Hyosung; Wang, Semyung; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

    Satellite mission control systems typically are operated by scheduling missions to the visibility between ground stations and satellites. The communication for the mission is achieved by interacting with satellite visibility and ground station support. Specifically, the satellite forms a cone-type visibility passing over a ground station, and the antennas of ground stations support the satellite. When two or more satellites pass by at the same time or consecutively, the satellites may generate a visibility conflict. As the number of satellites increases, solving visibility conflict becomes important issue. In this study, we propose a visibility conflict resolution algorithm of multi-satellites by using a genetic algorithm (GA). The problem is converted to scheduling optimization modeling. The visibility of satellites and the supports of antennas are considered as tasks and resources individually. The visibility of satellites is allocated to the total support time of antennas as much as possible for users to obtain the maximum benefit. We focus on a genetic algorithm approach because the problem is complex and not defined explicitly. The genetic algorithm can be applied to such a complex model since it only needs an objective function and can approach a global optimum. However, the mathematical proof of global optimality for the genetic algorithm is very challenging. Therefore, we apply a greedy algorithm and show that our genetic approach is reasonable by comparing with the performance of greedy algorithm application.

  19. The SUMO Ship Detector Algorithm for Satellite Radar Images

    Directory of Open Access Journals (Sweden)

    Harm Greidanus

    2017-03-01

    Full Text Available Search for Unidentified Maritime Objects (SUMO is an algorithm for ship detection in satellite Synthetic Aperture Radar (SAR images. It has been developed over the course of more than 15 years, using a large amount of SAR images from almost all available SAR satellites operating in L-, C- and X-band. As validated by benchmark tests, it performs very well on a wide range of SAR image modes (from Spotlight to ScanSAR and resolutions (from 1–100 m and for all types and sizes of ships, within the physical limits imposed by the radar imaging. This paper describes, in detail, the algorithmic approach in all of the steps of the ship detection: land masking, clutter estimation, detection thresholding, target clustering, ship attribute estimation and false alarm suppression. SUMO is a pixel-based CFAR (Constant False Alarm Rate detector for multi-look radar images. It assumes a K distribution for the sea clutter, corrected however for deviations of the actual sea clutter from this distribution, implementing a fast and robust method for the clutter background estimation. The clustering of detected pixels into targets (ships uses several thresholds to deal with the typically irregular distribution of the radar backscatter over a ship. In a multi-polarization image, the different channels are fused. Azimuth ambiguities, a common source of false alarms in ship detection, are removed. A reliability indicator is computed for each target. In post-processing, using the results of a series of images, additional false alarms from recurrent (fixed targets including range ambiguities are also removed. SUMO can run in semi-automatic mode, where an operator can verify each detected target. It can also run in fully automatic mode, where batches of over 10,000 images have successfully been processed in less than two hours. The number of satellite SAR systems keeps increasing, as does their application to maritime surveillance. The open data policy of the EU

  20. Efficient Algorithm for Railway Tracks Detection Using Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Ali Javed

    2012-10-01

    Full Text Available Satellite imagery can produce maps including roads, railway tracks, buildings, bridges, oceans, lakes, rivers, etc. In developed countries like USA, Canada, Australia, Europe, images produced by Google map are of high resolution and good quality. On the other hand, mostly images of the third world countries like Pakistan, Asian and African countries are of poor quality and not clearly visible. Similarly railway tracks of these countries are hardly visible in Google map. We have developed an efficient algorithm for railway track detection from a low quality image of Google map. This would lead to detect damaged railway track, railway crossings and help to schedule/divert locomotive movements in order to avoid catastrophe.

  1. 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

  2. Improved interpretation of satellite altimeter data using genetic algorithms

    Science.gov (United States)

    Messa, Kenneth; Lybanon, Matthew

    1992-01-01

    Genetic algorithms (GA) are optimization techniques that are based on the mechanics of evolution and natural selection. They take advantage of the power of cumulative selection, in which successive incremental improvements in a solution structure become the basis for continued development. A GA is an iterative procedure that maintains a 'population' of 'organisms' (candidate solutions). Through successive 'generations' (iterations) the population as a whole improves in simulation of Darwin's 'survival of the fittest'. GA's have been shown to be successful where noise significantly reduces the ability of other search techniques to work effectively. Satellite altimetry provides useful information about oceanographic phenomena. It provides rapid global coverage of the oceans and is not as severely hampered by cloud cover as infrared imagery. Despite these and other benefits, several factors lead to significant difficulty in interpretation. The GA approach to the improved interpretation of satellite data involves the representation of the ocean surface model as a string of parameters or coefficients from the model. The GA searches in parallel, a population of such representations (organisms) to obtain the individual that is best suited to 'survive', that is, the fittest as measured with respect to some 'fitness' function. The fittest organism is the one that best represents the ocean surface model with respect to the altimeter data.

  3. 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.

  4. Hierarchical Supervisor and Agent Routing Algorithm in LEO/MEO Double-layered Optical Satellite Network

    Science.gov (United States)

    Li, Yongjun; Zhao, Shanghong

    2016-09-01

    A novel routing algorithm (Hierarchical Supervisor and Agent Routing Algorithm, HSARA) for LEO/MEO (low earth orbit/medium earth orbit) double-layered optical satellite network is brought forward. The so-called supervisor (MEO satellite) is designed for failure recovery and network management. LEO satellites are grouped according to the virtual managed field of MEO which is different from coverage area of MEO satellite in RF satellite network. In each LEO group, one LEO satellite which has maximal persistent link with its supervisor is called the agent. A LEO group is updated when this optical inter-orbit links between agent LEO satellite and the corresponding MEO satellite supervisor cuts off. In this way, computations of topology changes and LEO group updating can be decreased. Expense of routing is integration of delay and wavelength utilization. HSARA algorithm simulations are implemented and the results are as follows: average network delay of HSARA can reduce 21 ms and 31.2 ms compared with traditional multilayered satellite routing and single-layer LEO satellite respectively; LEO/MEO double-layered optical satellite network can cover polar region which cannot be covered by single-layered LEO satellite and throughput is 1% more than that of single-layered LEO satellite averagely. Therefore, exact global coverage can be achieved with this double-layered optical satellite network.

  5. 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....

  6. New dynamic routing algorithm based on MANET in LEO/MEO satellite network

    Institute of Scientific and Technical Information of China (English)

    LI Zhe; LI Dong-ni; WANG Guang-xing

    2006-01-01

    The features of low earth orbit/medium earth orbit (LEO/MEO) satellite networks routing algorithm based on inter-satellite link are analyzed and the similarities between satellite networks and mobile Ad Hoc network (MANET) are pointed out.The similar parts in MANET routing protocol are used in the satellite network for reference.A new dynamic routing algorithm based on MANET in LEO/MEO satellite networks,which fits for the LEO/MEO satellite communication system,is proposed.At the same time,the model of the algorithm is simulated and features are analyzed.It is shown that the algorithm has strong adaptability.It can give the network high autonomy,perfect function,low system overhead and great compatibility.

  7. A Multicast Routing Algorithm for Datagram Service in Delta LEO Satellite Constellation Networks

    Directory of Open Access Journals (Sweden)

    Yanpeng Ma

    2014-04-01

    Full Text Available Satellites can broadcast datagram over wide areas, therefore, the satellite network has congenital advantages to implement multicast service. LEO satellite has the property of efficient bandwidth usage, lower propagation delay and lower power consumption in the user terminals and satellites. Therefore, the constellation network composed by LEO satellites is an essential part of future satellite communication networks. In this paper, we propose a virtual center based multicast (VCMulticast routing algorithm for LEO satellite constellation network. The algorithm uses the geographic center information of group users to route multicast datagrams, with less memory, computer power and signaling overhead. We evaluate the delay and performance of our algorithm by means of simulations in the OPENET simulator. The results indicate that the delay of the proposed multicast method exceeds the minimum propagation by at most 29.1% on the average, which is a quite acceptable achievement, considering the resource overhead reduction that can be introduced by our proposal

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. Improvement and Simulation of an Autonomous Time Synchronization Algorithm for a Layered Satellite Constellation

    Directory of Open Access Journals (Sweden)

    Feijiang Huang

    2013-01-01

    Full Text Available Autonomous time synchronization for satellite constellations is a key technology to establish a constellation system time without the use of a ground station. The characteristics of satellite visibility time for layered satellite constellations containing geostationary earth orbit (GEO, inclined geosynchronous orbit (IGSO, and medium earth orbit (MEO satellites are simulated by establishing a visible satellite model. Based on the satellite visible simulation results for a layered constellation, this study investigates the autonomous time synchronization algorithm that corresponds to the layered constellation structure, analyzes the main error of the time synchronization algorithm, and proposes methods to improve the characteristics of satellite movement in the constellation. This study uses an improved two-way time synchronization algorithm for autonomous time synchronization in the GEO-MEO satellite layer of a layered satellite constellation. The simulation results show that in a condition with simulation errors, the time synchronization precision of this improved algorithm can be controlled within 5 ns and used in high-precision autonomous time synchronization between layered satellite constellations.

  13. 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.

  14. A DISTRIBUTED QOS ROUTING BASED ON ANT ALGORITHM FOR LEO SATELLITE NETWORK

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Low Earth Orbit (LEO) satellites provide short round-trip delays and are becoming increasingly important. One of the challenges in LEO satellite networks is the development of specialized and efficient routing algorithms. To satisfy the QoS requirements of multimedia applications, satellite routing protocols should consider handovers and minimize their effect on the active connections. A distributed QoS routing scheme based on heuristic ant algorithm is proposed for satisfying delay bound and avoiding link congestion. Simulation results show that the call blocking probabilities of this algorithm are less than that of Shortest Path First (SPF) with different delay bound.

  15. 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.

  16. Performance of TCP Vegas, Bic and Reno Congestion Control Algorithms on Iridium Satellite Constellations

    Directory of Open Access Journals (Sweden)

    M.Nirmala

    2012-11-01

    Full Text Available Satellite networking is different from wired or wireless networks. The behavior and the performance of TCP/IP in normal wireless network as well as in wired network are different from one another. The TCP/IP protocol was not designed to perform well over high-latency or noisy channels so its performance over satellite networks are totally different. Each satellite networks/constellations have different properties. The deployment height, motion, direction, link capacity – all differ from one satellite constellations to another. So, certainly the behavior of TCP/IP will considerably differ from one satellite constellations than another.The Performance of three different TCP Congestion algorithms, Vegas, Reno and Bic are taken for evaluation on the simulated satellite network Iridium and the performance of the three algorithms under the satellites constellation is measured using suitable metrics. It is observed that, irrespective of the high end to end delay, the behavior of TCP/IP under Satellite network is somewhat resembling a high latency wired network. TCP under satellite network is not like that of a mobile ADHOC network. The observation resulted that the overall performance of Vegas was good in Iridium constellations. These reasons should be explored for designing a better congestion control algorithm exclusively for Satellite Networks.

  17. On the relationship of coastal tropical rainfall and the large-scale atmosphere

    CERN Document Server

    Bergemann, Martin; Lane, Todd P

    2015-01-01

    Rainfall in coastal areas of the tropics is often shaped by the presence of circulations directly associated with the topography, such as land-sea and/or mountain-valley breezes. In many regions the coastally-affected rainfall consitutes more than half of the overall rainfall received. Weather and climate models with parametrized convection produce large errors in rainfall in tropical coastal regions, most commonly underestimating rainfall over land and overestimating it over the ocean. Building on an algorithm to objectively identify rainfall that is associated with land-sea interaction we investigate whether the relationship between rainfall in coastal regions and the large-scale atmosphere differs from that over the open ocean or over inland areas. We combine 3-hourly satellite estimates of rainfall with estimates of the large-scale atmospheric state from reanalyses. We find that when grouped by rainfall intensity, medium-intensity coastal rainfall in the tropics occurs in more stable conditions and drier ...

  18. 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.

  19. A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm.

    Science.gov (United States)

    Song, Jiancai; Xue, Guixiang; Kang, Yanan

    2016-01-01

    In this paper, a novel method for selecting a navigation satellite subset for a global positioning system (GPS) based on a genetic algorithm is presented. This approach is based on minimizing the factors in the geometric dilution of precision (GDOP) using a modified genetic algorithm (MGA) with an elite conservation strategy, adaptive selection, adaptive mutation, and a hybrid genetic algorithm that can select a subset of the satellites represented by specific numbers in the interval (4 ∼ n) while maintaining position accuracy. A comprehensive simulation demonstrates that the MGA-based satellite selection method effectively selects the correct number of optimal satellite subsets using receiver autonomous integrity monitoring (RAIM) or fault detection and exclusion (FDE). This method is more adaptable and flexible for GPS receivers, particularly for those used in handset equipment and mobile phones.

  20. Optimization of Determinant Factors of Satellite Electrical Power System with Particle Swarm Optimization (PSO Algorithm

    Directory of Open Access Journals (Sweden)

    Mojtaba Biglarahmadi

    2014-03-01

    Full Text Available Weight and dimension, cost, and performance are determinant factors for design, fabrication, and launch the satellites which are related to the mission type of the satellites. Each satellite includes several subsystems such as Electrical Power Subsystem (EPS, Navigation Subsystem, Thermal Subsystem, etc. The purpose of this paper is to optimize these determinant factors by Particle Swarm Optimization (PSO algorithm, for Electrical Power Subsystem. This paper considers the effects of selecting various types of Photovoltaic (PV cells and batteries on weight and dimension, cost, and performance of the satellite. We have used two various types of PVs and two various type of batteries in optimization of the Electrical Power Subsystem (EPS

  1. 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.

  2. 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

  3. A COMBINED ADMISSION CONTROL ALGORITHM WITH DA PROTOCOL FOR SATELLITE ATM NETWORKS

    Institute of Scientific and Technical Information of China (English)

    Lu Rong; Cao Zhigang

    2006-01-01

    Admission control is an important strategy for Quality of Service (QoS) provisioning in Asynchronous Transfer Mode (ATM) networks. Based on a control-theory model of resources on-Demand Allocation (DA) protocol, the paper studies the effect of the protocol on the statistical characteristics of network traffic,and proposes a combined connection admission control algorithm with the DA protocol to achieve full utilization of link resources in satellite communication systems. The proposed algorithm is based on the cross-layer-design approach. Theoretical analysis and system simulation results show that the proposed algorithm can admit more connections within certain admission thresholds than one that does not take into account the DA protocol. Thus, the proposed algorithm can increase admission ratio of traffic sources for satellite ATM networks and improve satellite link utilization.

  4. 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.

  5. 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...

  6. 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

  7. Comparision of Clustering Algorithms usingNeural Network Classifier for Satellite Image Classification

    Directory of Open Access Journals (Sweden)

    S.Praveena

    2015-06-01

    Full Text Available This paper presents a hybrid clustering algorithm and feed-forward neural network classifier for land-cover mapping of trees, shade, building and road. It starts with the single step preprocessing procedure to make the image suitable for segmentation. The pre-processed image is segmented using the hybrid genetic-Artificial Bee Colony(ABC algorithm that is developed by hybridizing the ABC and FCM to obtain the effective segmentation in satellite image and classified using neural network . The performance of the proposed hybrid algorithm is compared with the algorithms like, k-means, Fuzzy C means(FCM, Moving K-means, Artificial Bee Colony(ABC algorithm, ABC-GA algorithm, Moving KFCM and KFCM algorithm.

  8. Low Complexity Multiuser Detection Algorithm for Multi-Beam Satellite Systems

    Institute of Scientific and Technical Information of China (English)

    Yang Wang; Danfeng Zhao; Xi Liao

    2015-01-01

    The minimum mean square error⁃successive interference cancellation ( MMSE⁃SIC ) multiuser detection algorithm has high complexity and long processing latency. A multiuser detection algorithm is proposed for multi⁃beam satellite systems in order to decrease the complexity and latency. The spot beams are grouped base on the distance between them in the proposed algorithm. Some groups are detected in parallel after a crucial group⁃wise interference cancellation. Furthermore, the multi⁃stage structure is introduced to improve the performance. Simulation results show that the proposed algorithm can achieve better performance with less complexity compared with the existing group detection algorithm. Moreover, the proposed algorithm using one stage can reduce the complexity over the fast MMSE⁃SIC and existing group detection algorithm by 9% and 20�9%. The processing latency is reduced significantly compared with the MMSE⁃SIC.

  9. Differences in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms

    Science.gov (United States)

    Yao, Yunjun; Liang, Shunlin; Yu, Jian; Zhao, Shaohua; Lin, Yi; Jia, Kun; Zhang, Xiaotong; Cheng, Jie; Xie, Xianhong; Sun, Liang; Wang, Xuanyu; Zhang, Lilin

    2017-04-01

    Accurate estimates of terrestrial latent heat of evaporation (LE) for different biomes are essential to assess energy, water and carbon cycles. Different satellite- based Priestley-Taylor (PT) algorithms have been developed to estimate LE in different biomes. However, there are still large uncertainties in LE estimates for different PT algorithms. In this study, we evaluated differences in estimating terrestrial water flux in different biomes from three satellite-based PT algorithms using ground-observed data from eight eddy covariance (EC) flux towers of China. The results reveal that large differences in daily LE estimates exist based on EC measurements using three PT algorithms among eight ecosystem types. At the forest (CBS) site, all algorithms demonstrate high performance with low root mean square error (RMSE) (less than 16 W/m2) and high squared correlation coefficient (R2) (more than 0.9). At the village (HHV) site, the ATI-PT algorithm has the lowest RMSE (13.9 W/m2), with bias of 2.7 W/m2 and R2 of 0.66. At the irrigated crop (HHM) site, almost all models algorithms underestimate LE, indicating these algorithms may not capture wet soil evaporation by parameterization of the soil moisture. In contrast, the SM-PT algorithm shows high values of R2 (comparable to those of ATI-PT and VPD-PT) at most other (grass, wetland, desert and Gobi) biomes. There are no obvious differences in seasonal LE estimation using MODIS NDVI and LAI at most sites. However, all meteorological or satellite-based water-related parameters used in the PT algorithm have uncertainties for optimizing water constraints. This analysis highlights the need to improve PT algorithms with regard to water constraints.

  10. 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

  11. Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products

    Directory of Open Access Journals (Sweden)

    Ying Qu

    2015-01-01

    Full Text Available Surface albedo is one of the key controlling geophysical parameters in the surface energy budget studies, and its temporal and spatial variation is closely related to the global climate change and regional weather system due to the albedo feedback mechanism. As an efficient tool for monitoring the surfaces of the Earth, remote sensing is widely used for deriving long-term surface broadband albedo with various geostationary and polar-orbit satellite platforms in recent decades. Moreover, the algorithms for estimating surface broadband albedo from satellite observations, including narrow-to-broadband conversions, bidirectional reflectance distribution function (BRDF angular modeling, direct-estimation algorithm and the algorithms for estimating albedo from geostationary satellite data, are developed and improved. In this paper, we present a comprehensive literature review on algorithms and products for mapping surface broadband albedo with satellite observations and provide a discussion of different algorithms and products in a historical perspective based on citation analysis of the published literature. This paper shows that the observation technologies and accuracy requirement of applications are important, and long-term, global fully-covered (including land, ocean, and sea-ice surfaces, gap-free, surface broadband albedo products with higher spatial and temporal resolution are required for climate change, surface energy budget, and hydrological studies.

  12. Satellite Imagery Cadastral Features Extractions using Image Processing Algorithms: A Viable Option for Cadastral Science

    Directory of Open Access Journals (Sweden)

    Usman Babawuro

    2012-07-01

    Full Text Available Satellite images are used for feature extraction among other functions. They are used to extract linear features, like roads, etc. These linear features extractions are important operations in computer vision. Computer vision has varied applications in photogrammetric, hydrographic, cartographic and remote sensing tasks. The extraction of linear features or boundaries defining the extents of lands, land covers features are equally important in Cadastral Surveying. Cadastral Surveying is the cornerstone of any Cadastral System. A two dimensional cadastral plan is a model which represents both the cadastral and geometrical information of a two dimensional labeled Image. This paper aims at using and widening the concepts of high resolution Satellite imagery data for extracting representations of cadastral boundaries using image processing algorithms, hence minimizing the human interventions. The Satellite imagery is firstly rectified hence establishing the satellite imagery in the correct orientation and spatial location for further analysis. We, then employ the much available Satellite imagery to extract the relevant cadastral features using computer vision and image processing algorithms. We evaluate the potential of using high resolution Satellite imagery to achieve Cadastral goals of boundary detection and extraction of farmlands using image processing algorithms. This method proves effective as it minimizes the human demerits associated with the Cadastral surveying method, hence providing another perspective of achieving cadastral goals as emphasized by the UN cadastral vision. Finally, as Cadastral science continues to look to the future, this research aimed at the analysis and getting insights into the characteristics and potential role of computer vision algorithms using high resolution satellite imagery for better digital Cadastre that would provide improved socio economic development.

  13. Optimization of regional navigation satellite constellation by improved NSGA-II algorithm

    Science.gov (United States)

    Chang, Hui; Hu, Xiulin; Zhang, Yunyu; Zeng, Yujiang; Wang, Ying

    2009-12-01

    In this paper, the non-dominated sorting genetic algorithm II (NSGA-II) based on the concept of Pareto optimal is improved. A new algorithm with lower O(MNlogN) computational complexity to construct non-dominated set replaces the NSGA-II original fast non-dominated sorting algorithm with O(MN2) com-putational complexity. The new algorithm improves operating efficiency of NSGA-II significantly. Based on the combination of the improved NSGA-II algorithm and regional navigation satellite constellation design, a new idea to design regional navigation satellite constellation is proposed in this paper. The new idea is implemented by Satellite Tool Kits (STK) and Matlab: the improved NSGA-II algorithm is implemented by Matlab and the calculation of the objective function values is implemented by STK. STK/Connect interface is used to integrate STK and Matlab into one simulation. Simulation results show that new idea has some advantages over the traditional methods, being more efficient, more flexible and more comprehensive.

  14. 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...

  15. Research on GPS Receiver Autonomous Integrity Monitoring Algorithm In the Occurrence of Two-satellite Faults

    Directory of Open Access Journals (Sweden)

    Wang Er Shen

    2016-01-01

    Full Text Available Reliability is an essential factor for GPS navigation system. Therefore, an integrity monitoring is considered as one of the most important parts for a navigation system. GPS receiver autonomous integrity monitoring (RAIM technique can detect and isolate fault satellite. Based on particle filter, a novel RAIM method was proposed to detect two-satellite faults of the GPS signal by using hierarchical particle filter. It can deal with any system nonlinear and any noise distributions. Because GNSS measurement noise does not follow the Gaussian distribution perfectly, the particle filter can estimate the posterior distribution more accurately. In order to detect fault, the consistency test statistics is established through cumulative log-likelihood ratio (LLR between the main and auxiliary particle filters (PFs.Specifically, an approach combining PF with the hierarchical filter is used in the process of two-satellite faults. Through GPS real measurement, the performance of the proposed GPS two-satellite faults detection algorithm was illustrated. Some simulation results are given to evaluate integrity monitoring performance of the algorithm. Validated by the real measurement data, the results show that the proposed algorithm can successfully detect and isolate the faulty satellite in the case of non-Gaussian measurement noise.

  16. An autonomous navigation algorithm for high orbit satellite using star sensor and ultraviolet earth sensor.

    Science.gov (United States)

    Baohua, Li; Wenjie, Lai; Yun, Chen; Zongming, Liu

    2013-01-01

    An autonomous navigation algorithm using the sensor that integrated the star sensor (FOV1) and ultraviolet earth sensor (FOV2) is presented. The star images are sampled by FOV1, and the ultraviolet earth images are sampled by the FOV2. The star identification algorithm and star tracking algorithm are executed at FOV1. Then, the optical axis direction of FOV1 at J2000.0 coordinate system is calculated. The ultraviolet image of earth is sampled by FOV2. The center vector of earth at FOV2 coordinate system is calculated with the coordinates of ultraviolet earth. The autonomous navigation data of satellite are calculated by integrated sensor with the optical axis direction of FOV1 and the center vector of earth from FOV2. The position accuracy of the autonomous navigation for satellite is improved from 1000 meters to 300 meters. And the velocity accuracy of the autonomous navigation for satellite is improved from 100 m/s to 20 m/s. At the same time, the period sine errors of the autonomous navigation for satellite are eliminated. The autonomous navigation for satellite with a sensor that integrated ultraviolet earth sensor and star sensor is well robust.

  17. Research on handover algorithm to reduce the blocking probability in LEO satellite network

    Institute of Scientific and Technical Information of China (English)

    Chen Bingcai; Zhang Naitong; Nie Boxun; Zhou Tingxian

    2006-01-01

    Based on the characteristics of guaranteed handover (GH) algorithm, the finite capacity in one system makes the blocking probability (PB) of GH algorithm increase rapidly in the case of high traffic load. So, when large amounts of multimedia services are transmitted via a single low earth orbit (LEO) satellite system, the PB of it is much higher. In order to solve the problem, a novel handover scheme defined by multi-tier optiral layer selection is proposed. The scheme sufficienfly takes into ac count the characteristics of double-tier satellite network, which is constituted by LEO satellites combined with medium earth orbit (MEO) satellites, and the multimedia transmitted by such network, so it can augment this systematic capacity and effectively reduces the traffic load in the LEO which performs GH algorithm. The detailed processes are also presented. The simulation and numerical results show that the approach integrated with GH algorithm achieves a significant improvement in the PB and practicability, as compared to the single LEO layer network.

  18. Ozone Profile Retrieval Algorithm (OPERA) for nadir-looking satellite instruments in the UV-VIS

    NARCIS (Netherlands)

    Van Peet, J.C.A.; Van der A, R.J.; Tuinder, O.N.E.; Wolfram, E.; Salvador, J.; Levelt, P.F.; Kelder, H.M.

    2014-01-01

    For the retrieval of the vertical distribution of ozone in the atmosphere the Ozone ProfilE Retrieval Algorithm (OPERA) has been further developed. The new version (1.26) of OPERA is capable of retrieving ozone profiles from UV–VIS observations of most nadir-looking satellite instruments like GOME,

  19. UMR: A utility-maximizing routing algorithm for delay-sensitive service in LEO satellite networks

    Directory of Open Access Journals (Sweden)

    Lu Yong

    2015-04-01

    Full Text Available This paper develops a routing algorithm for delay-sensitive packet transmission in a low earth orbit multi-hop satellite network consists of micro-satellites. The micro-satellite low earth orbit (MS-LEO network endures unstable link connection and frequent link congestion due to the uneven user distribution and the link capacity variations. The proposed routing algorithm, referred to as the utility maximizing routing (UMR algorithm, improve the network utility of the MS-LEO network for carrying flows with strict end-to-end delay bound requirement. In UMR, first, a link state parameter is defined to capture the link reliability on continuing to keep the end-to-end delay into constraint; then, on the basis of this parameter, a routing metric is formulated and a routing scheme is designed for balancing the reliability in delay bound guarantee among paths and building a path maximizing the network utility expectation. While the UMR algorithm has many advantages, it may result in a higher blocking rate of new calls. This phenomenon is discussed and a weight factor is introduced into UMR to provide a flexible performance option for network operator. A set of simulations are conducted to verify the good performance of UMR, in terms of balancing the traffic distribution on inter-satellite links, reducing the flow interruption rate, and improving the network utility.

  20. Satellite constellation design with genetic algorithms based on system performance

    Institute of Scientific and Technical Information of China (English)

    Xueying Wang; Jun Li; Tiebing Wang; Wei An; Weidong Sheng

    2016-01-01

    Satelite constelation design for space optical sys-tems is essentialy a multiple-objective optimization problem. In this work, to tackle this chalenge, we first categorize the performance metrics of the space optical system by taking into account the system tasks (i.e., target detection and tracking). We then propose a new non-dominated sorting genetic algo-rithm (NSGA) to maximize the system surveilance perfor- mance. Pareto optimal sets are employed to deal with the conflicts due to the presence of multiple cost functions. Simulation results verify the validity and the improved per-formance of the proposed technique over benchmark meth-ods.

  1. Bridging Ground Validation and Algorithms: Using Scattering and Integral Tables to Incorporate Observed DSD Correlations into Satellite Algorithms

    Science.gov (United States)

    Williams, C. R.

    2012-12-01

    The NASA Global Precipitation Mission (GPM) raindrop size distribution (DSD) Working Group is composed of NASA PMM Science Team Members and is charged to "investigate the correlations between DSD parameters using Ground Validation (GV) data sets that support, or guide, the assumptions used in satellite retrieval algorithms." Correlations between DSD parameters can be used to constrain the unknowns and reduce the degrees-of-freedom in under-constrained satellite algorithms. Over the past two years, the GPM DSD Working Group has analyzed GV data and has found correlations between the mass-weighted mean raindrop diameter (Dm) and the mass distribution standard deviation (Sm) that follows a power-law relationship. This Dm-Sm power-law relationship appears to be robust and has been observed in surface disdrometer and vertically pointing radar observations. One benefit of a Dm-Sm power-law relationship is that a three parameter DSD can be modeled with just two parameters: Dm and Nw that determines the DSD amplitude. In order to incorporate observed DSD correlations into satellite algorithms, the GPM DSD Working Group is developing scattering and integral tables that can be used by satellite algorithms. Scattering tables describe the interaction of electromagnetic waves on individual particles to generate cross sections of backscattering, extinction, and scattering. Scattering tables are independent of the distribution of particles. Integral tables combine scattering table outputs with DSD parameters and DSD correlations to generate integrated normalized reflectivity, attenuation, scattering, emission, and asymmetry coefficients. Integral tables contain both frequency dependent scattering properties and cloud microphysics. The GPM DSD Working Group has developed scattering tables for raindrops at both Dual Precipitation Radar (DPR) frequencies and at all GMI radiometer frequencies less than 100 GHz. Scattering tables include Mie and T-matrix scattering with H- and V

  2. 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

  3. Model predictive control of attitude maneuver of a geostationary flexible satellite based on genetic algorithm

    Science.gov (United States)

    TayyebTaher, M.; Esmaeilzadeh, S. Majid

    2017-07-01

    This article presents an application of Model Predictive Controller (MPC) to the attitude control of a geostationary flexible satellite. SIMO model has been used for the geostationary satellite, using the Lagrange equations. Flexibility is also included in the modelling equations. The state space equations are expressed in order to simplify the controller. Naturally there is no specific tuning rule to find the best parameters of an MPC controller which fits the desired controller. Being an intelligence method for optimizing problem, Genetic Algorithm has been used for optimizing the performance of MPC controller by tuning the controller parameter due to minimum rise time, settling time, overshoot of the target point of the flexible structure and its mode shape amplitudes to make large attitude maneuvers possible. The model included geosynchronous orbit environment and geostationary satellite parameters. The simulation results of the flexible satellite with attitude maneuver shows the efficiency of proposed optimization method in comparison with LQR optimal controller.

  4. Core-based Shared Tree Multicast Routing Algorithms for LEO Satellite IP Networks

    Institute of Scientific and Technical Information of China (English)

    Cheng Lianzhen; Zhang Jun; Liu Kai

    2007-01-01

    A new core-based shared tree algorithm, viz core-cluster combination-based shared tree (CCST) algorithm and the weighted version (i.e. w-CCST algorithm) are proposed in order to resolve the channel resources waste problem in typical source-based multicast routing algorithms in low earth orbit (LEO) satellite IP networks. The CCST algorithm includes the dynamic approximate center (DAC)core selection method and the core-cluster combination multicast route construction scheme. Without complicated onboard computation,the DAC method is uniquely developed for highly dynamic networks of periodical and regular movement. The core-cluster combination method takes core node as the initial core-cluster, and expands it stepwise to construct an entire multicast tree at the lowest tree cost by a shortest path scheme between the newly-generated core-cluster and surplus group members, which results in great bandwidth utilization.Moreover, the w-CCST algorithm is able to strike a balance between performance of tree cost and that of end-to-end propagation delay by adjusting the weighted factor to meet strict end-to-end delay requirements of some real-time multicast services at the expense of a slight increase in tree cost. Finally, performance comparison is conducted between the proposed algorithms and typical algorithms in LEO satellite IP networks. Simulation results show that the CCST algorithm significantly decreases the average tree cost against to the others, and also the average end-to-end propagation delay of w-CCST algorithm is lower than that of the CCST algorithm.

  5. First Attempt of Orbit Determination of SLR Satellites and Space Debris Using Genetic Algorithms

    Science.gov (United States)

    Deleflie, F.; Coulot, D.; Descosta, R.; Fernier, A.; Richard, P.

    2013-08-01

    We present an orbit determination method based on genetic algorithms. Contrary to usual estimation methods mainly based on least-squares methods, these algorithms do not require any a priori knowledge of the initial state vector to be estimated. These algorithms can be applied when a new satellite is launched or for uncatalogued objects that appear in images obtained from robotic telescopes such as the TAROT ones. We show in this paper preliminary results obtained from an SLR satellite, for which tracking data acquired by the ILRS network enable to build accurate orbital arcs at a few centimeter level, which can be used as a reference orbit ; in this case, the basic observations are made up of time series of ranges, obtained from various tracking stations. We show as well the results obtained from the observations acquired by the two TAROT telescopes on the Telecom-2D satellite operated by CNES ; in that case, the observations are made up of time series of azimuths and elevations, seen from the two TAROT telescopes. The method is carried out in several steps: (i) an analytical propagation of the equations of motion, (ii) an estimation kernel based on genetic algorithms, which follows the usual steps of such approaches: initialization and evolution of a selected population, so as to determine the best parameters. Each parameter to be estimated, namely each initial keplerian element, has to be searched among an interval that is preliminary chosen. The algorithm is supposed to converge towards an optimum over a reasonable computational time.

  6. 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.

  7. Development of a fire detection algorithm for the COMS (Communication Ocean and Meteorological Satellite)

    Science.gov (United States)

    Kim, Goo; Kim, Dae Sun; Lee, Yang-Won

    2013-10-01

    The forest fires do much damage to our life in ecological and economic aspects. South Korea is probably more liable to suffer from the forest fire because mountain area occupies more than half of land in South Korea. They have recently launched the COMS(Communication Ocean and Meteorological Satellite) which is a geostationary satellite. In this paper, we developed forest fire detection algorithm using COMS data. Generally, forest fire detection algorithm uses characteristics of 4 and 11 micrometer brightness temperature. Our algorithm additionally uses LST(Land Surface Temperature). We confirmed the result of our fire detection algorithm using statistical data of Korea Forest Service and ASTER(Advanced Spaceborne Thermal Emission and Reflection Radiometer) images. We used the data in South Korea On April 1 and 2, 2011 because there are small and big forest fires at that time. The detection rate was 80% in terms of the frequency of the forest fires and was 99% in terms of the damaged area. Considering the number of COMS's channels and its low resolution, this result is a remarkable outcome. To provide users with the result of our algorithm, we developed a smartphone application for users JSP(Java Server Page). This application can work regardless of the smartphone's operating system. This study can be unsuitable for other areas and days because we used just two days data. To improve the accuracy of our algorithm, we need analysis using long-term data as future work.

  8. The HSBQ Algorithm with Triple-play Services for Broadband Hybrid Satellite Constellation Communication System

    Directory of Open Access Journals (Sweden)

    Anupon Boriboon

    2016-07-01

    Full Text Available The HSBQ algorithm is the one of active queue management algorithms, which orders to avoid high packet loss rates and control stable stream queue. That is the problem of calculation of the drop probability for both queue length stability and bandwidth fairness. This paper proposes the HSBQ, which drop the packets before the queues overflow at the gateways, so that the end nodes can respond to the congestion before queue overflow. This algorithm uses the change of the average queue length to adjust the amount by which the mark (or drop probability is changed. Moreover it adjusts the queue weight, which is used to estimate the average queue length, based on the rate. The results show that HSBQ algorithm could maintain control stable stream queue better than group of congestion metric without flow information algorithm as the rate of hybrid satellite network changing dramatically, as well as the presented empiric evidences demonstrate that the use of HSBQ algorithm offers a better quality of service than the traditionally queue control mechanisms used in hybrid satellite network.

  9. Satellite image processing for precision agriculture and agroindustry using convolutional neural network and genetic algorithm

    Science.gov (United States)

    Firdaus; Arkeman, Y.; Buono, A.; Hermadi, I.

    2017-01-01

    Translating satellite imagery to a useful data for decision making during this time are usually done manually by human. In this research, we are going to translate satellite imagery by using artificial intelligence method specifically using convolutional neural network and genetic algorithm to become a useful data for decision making, especially for precision agriculture and agroindustry. In this research, we are focused on how to made a sustainable land use planning with 3 objectives. The first is maximizing economic factor. Second is minimizing CO2 emission and the last is minimizing land degradation. Results show that by using artificial intelligence method, can produced a good pareto optimum solutions in a short time.

  10. Parameter Estimation in Rainfall-Runoff Modelling Using Distributed Versions of Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Michala Jakubcová

    2015-01-01

    Full Text Available The presented paper provides the analysis of selected versions of the particle swarm optimization (PSO algorithm. The tested versions of the PSO were combined with the shuffling mechanism, which splits the model population into complexes and performs distributed PSO optimization. One of them is a new proposed PSO modification, APartW, which enhances the global exploration and local exploitation in the parametric space during the optimization process through the new updating mechanism applied on the PSO inertia weight. The performances of four selected PSO methods were tested on 11 benchmark optimization problems, which were prepared for the special session on single-objective real-parameter optimization CEC 2005. The results confirm that the tested new APartW PSO variant is comparable with other existing distributed PSO versions, AdaptW and LinTimeVarW. The distributed PSO versions were developed for finding the solution of inverse problems related to the estimation of parameters of hydrological model Bilan. The results of the case study, made on the selected set of 30 catchments obtained from MOPEX database, show that tested distributed PSO versions provide suitable estimates of Bilan model parameters and thus can be used for solving related inverse problems during the calibration process of studied water balance hydrological model.

  11. Efficient estimation algorithms for a satellite-aided search and rescue mission

    Science.gov (United States)

    Argentiero, P.; Garza-Robles, R.

    1977-01-01

    It has been suggested to establish a search and rescue orbiting satellite system as a means for locating distress signals from downed aircraft, small boats, and overland expeditions. Emissions from Emergency Locator Transmitters (ELT), now available in most U.S. aircraft are to be utilized in the positioning procedure. A description is presented of a set of Doppler navigation algorithms for extracting ELT position coordinates from Doppler data. The algorithms have been programmed for a small computing machine and the resulting system has successfully processed both real and simulated Doppler data. A software system for solving the Doppler navigation problem must include an orbit propagator, a first guess algorithm, and an algorithm for estimating longitude and latitude from Doppler data. Each of these components is considered.

  12. Optical Algorithms at Satellite Wavelengths for Total Suspended Matter in Tropical Coastal Waters

    Directory of Open Access Journals (Sweden)

    Alain Muñoz-Caravaca

    2008-07-01

    Full Text Available Is it possible to derive accurately Total Suspended Matter concentration or its proxy, turbidity, from remote sensing data in tropical coastal lagoon waters? To investigate this question, hyperspectral remote sensing reflectance, turbidity and chlorophyll pigment concentration were measured in three coral reef lagoons. The three sites enabled us to get data over very diverse environments: oligotrophic and sediment-poor waters in the southwest lagoon of New Caledonia, eutrophic waters in the Cienfuegos Bay (Cuba, and sediment-rich waters in the Laucala Bay (Fiji. In this paper, optical algorithms for turbidity are presented per site based on 113 stations in New Caledonia, 24 stations in Cuba and 56 stations in Fiji. Empirical algorithms are tested at satellite wavebands useful to coastal applications. Global algorithms are also derived for the merged data set (193 stations. The performances of global and local regression algorithms are compared. The best one-band algorithms on all the measurements are obtained at 681 nm using either a polynomial or a power model. The best two-band algorithms are obtained with R412/R620, R443/R670 and R510/R681. Two three-band algorithms based on Rrs620.Rrs681/Rrs412 and Rrs620.Rrs681/Rrs510 also give fair regression statistics. Finally, we propose a global algorithm based on one or three bands: turbidity is first calculated from Rrs681 and then, if < 1 FTU, it is recalculated using an algorithm based on Rrs620.Rrs681/Rrs412. On our data set, this algorithm is suitable for the 0.2-25 FTU turbidity range and for the three sites sampled (mean bias: 3.6 %, rms: 35%, mean quadratic error: 1.4 FTU. This shows that defining global empirical turbidity algorithms in tropical coastal waters is at reach.

  13. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    OpenAIRE

    Marc Wieland; Massimiliano Pittore

    2014-01-01

    In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS) and very high resolution (WorldView-2, Quickbird, Ikonos) multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognitio...

  14. H-- Filtering Algorithms Case Study GPS-Based Satellite Orbit Determination

    Science.gov (United States)

    Kuang, Jinlu; Tan, Soonhie

    In this paper the new Hfiltering algorithms for the design of navigation systems for autonomous LEO satellite is introduced. The nominal orbit (i.e., position and velocity) is computed by integrating the classical orbital differential equations of the LEO satellite by using the 7th-8th order Runge- Kutta algorithms. The perturbations due to the atmospheric drag force, the lunar-solar attraction and the solar radiation pressure are included together with the Earth gravity model (EGM-96). The spherical harmonic coefficients of the EGM-96 are considered up to 72 for the order and degree. By way of the MATLAB GPSoft software, the simulated pseudo ranges between the user LEO satellite and the visible GPS satellites are generated when given the appropriate angle of mask. The effects of the thermal noises, tropospheric refraction, ionospheric refraction, and multipath of the antenna are also compensated numerically in the simulated pseudo ranges. The dynamic Position-Velocity (PV) model is obtained by modeling the velocity as nearly constant being the white noise process. To further accommodate acceleration in the process model, the Position-Velocity-Acceleration (PVA) model is investigated by assuming the acceleration to be the Gaussian- Markov process. The state vector for the PV model becomes 8-dimensional (3-states for positions, 3-states for velocities, 1-state for range (clock) bias error, 1-state for range (clock) drift error). The state vector for the PV model becomes 11-dimensional with the addition of three more acceleration states. Three filtering approaches are used to smooth the orbit solution based upon the GPS pseudo range observables. The numerical simulation shows that the observed orbit root-mean-square errors of 60 meters by using the least squares adjustment method are improved to be less than 5 meters within 16 hours of tracking time by using the Hfiltering algorithms. The results are compared with the ones obtained by using the Extended Kalman

  15. Swarm satellite mission scheduling & planning using Hybrid Dynamic Mutation Genetic Algorithm

    Science.gov (United States)

    Zheng, Zixuan; Guo, Jian; Gill, Eberhard

    2017-08-01

    Space missions have traditionally been controlled by operators from a mission control center. Given the increasing number of satellites for some space missions, generating a command list for multiple satellites can be time-consuming and inefficient. Developing multi-satellite, onboard mission scheduling & planning techniques is, therefore, a key research field for future space mission operations. In this paper, an improved Genetic Algorithm (GA) using a new mutation strategy is proposed as a mission scheduling algorithm. This new mutation strategy, called Hybrid Dynamic Mutation (HDM), combines the advantages of both dynamic mutation strategy and adaptive mutation strategy, overcoming weaknesses such as early convergence and long computing time, which helps standard GA to be more efficient and accurate in dealing with complex missions. HDM-GA shows excellent performance in solving both unconstrained and constrained test functions. The experiments of using HDM-GA to simulate a multi-satellite, mission scheduling problem demonstrates that both the computation time and success rate mission requirements can be met. The results of a comparative test between HDM-GA and three other mutation strategies also show that HDM has outstanding performance in terms of speed and reliability.

  16. Pre-processing Algorithm for Rectification of Geometric Distortions in Satellite Images

    Directory of Open Access Journals (Sweden)

    Narayan Panigrahi

    2011-02-01

    Full Text Available A number of algorithms have been reported to process and remove geometric distortions in satellite images. Ortho-correction, geometric error correction, radiometric error removal, etc are a few important examples. These algorithm require supplementary meta-information of the satellite images such as ground control points and correspondence, sensor orientation details, elevation profile of the terrain, etc to establish corresponding transformations. In this paper, a pre-processing algorithm has been proposed which removes systematic distortions of a satellite image and thereby removes the blank portion of the image. It is an input-to-output mapping of image pixels, where the transformation computes the coordinate of each output pixel corresponding to the input pixel of an image. The transformation is established by the exact amount of scaling, rotation and translation needed for each pixel in the input image so that the distortion induced during the recording stage is corrected.Defence Science Journal, 2011, 61(2, pp.174-179, DOI:http://dx.doi.org/10.14429/dsj.61.421

  17. A novel gridding algorithm to create regional trace gas maps from satellite observations

    Directory of Open Access Journals (Sweden)

    G. Kuhlmann

    2014-02-01

    Full Text Available The recent increase in spatial resolution for satellite instruments has made it feasible to study distributions of trace gas column densities on a regional scale. For this application a new gridding algorithm was developed to map measurements from the instrument's frame of reference (level 2 onto a longitude–latitude grid (level 3. The algorithm is designed for the Ozone Monitoring Instrument (OMI and can easily be employed for similar instruments – for example, the upcoming TROPOspheric Monitoring Instrument (TROPOMI. Trace gas distributions are reconstructed by a continuous parabolic spline surface. The algorithm explicitly considers the spatially varying sensitivity of the sensor resulting from the instrument function. At the swath edge, the inverse problem of computing the spline coefficients is very sensitive to measurement errors and is regularised by a second-order difference matrix. Since this regularisation corresponds to the penalty term for smoothing splines, it similarly attenuates the effect of measurement noise over the entire swath width. Monte Carlo simulations are conducted to study the performance of the algorithm for different distributions of trace gas column densities. The optimal weight of the penalty term is found to be proportional to the measurement uncertainty and the width of the instrument function. A comparison with an established gridding algorithm shows improved performance for small to moderate measurement errors due to better parametrisation of the distribution. The resulting maps are smoother and extreme values are more accurately reconstructed. The performance improvement is further illustrated with high-resolution distributions obtained from a regional chemistry model. The new algorithm is applied to tropospheric NO2 column densities measured by OMI. Examples of regional NO2 maps are shown for densely populated areas in China, Europe and the United States of America. This work demonstrates that the newly

  18. A novel gridding algorithm to create regional trace gas maps from satellite observations

    Directory of Open Access Journals (Sweden)

    G. Kuhlmann

    2013-08-01

    Full Text Available Recent increase of spatial resolution for satellite instruments has it made feasible to study distributions of trace gas column densities on a regional scale. For this application a new gridding algorithm was developed to map measurements from the instrument's frame of reference (Level 2 onto a longitude-latitude grid (Level 3. The algorithm is designed for the Ozone Monitoring Instrument (OMI and can be employed easily to similar instruments, for example, the upcoming TROPOspheric Monitoring Instrument (TROPOMI. Trace gas distributions are reconstructed by a continuous parabolic spline surface. The algorithm explicitly considers the spatially varying sensitivity of the sensor resulting from the instrument function. At the swath edge, the inverse problem of computing the spline coefficients is very sensitive to measurement errors and is regularised by a second-order difference matrix. Since this regularisation corresponds to the penalty term for smoothing splines, it similarly attenuates the effect of measurement noise over the entire swath width. Monte Carlo simulations are conducted to study the performance of the algorithm for different distributions of trace gas column densities. The optimal weight of the penalty term is found to be proportional to the measurement uncertainty and the width of the instrument function. A comparison with an established gridding algorithm shows improved performance for small to moderate measurement errors due to better parametrization of the distribution. The resulting maps are smoother and extreme values are more accurately reconstructed. The performance improvement is further illustrated with high-resolution distributions obtained from a regional chemistry model. The new algorithm is applied to tropospheric NO2 column densities measured by OMI. Examples of regional NO2 maps are shown for densely populated areas in China, Europe and the United States of America. This work demonstrates that the newly developed

  19. SHADOW DETECTION FROM VERY HIGH RESOLUTON SATELLITE IMAGE USING GRABCUT SEGMENTATION AND RATIO-BAND ALGORITHMS

    Directory of Open Access Journals (Sweden)

    N. M. S. M. Kadhim

    2015-03-01

    Full Text Available Very-High-Resolution (VHR satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour, the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates

  20. Geo-correction Algorithm Based on Equivalent RD Model for ScanSAR of HJ-1-C Satellite

    Directory of Open Access Journals (Sweden)

    Liu Jia-yin

    2014-06-01

    Full Text Available HJ-1-C satellite is the first Synthetic Aperture Radar (SAR satellite for civilian use in China, and it has a strip and scan mode. According to the characteristics of the ScanSAR of the HJ-1-C satellite, a geo-correction algorithm based on an equivalent RD model has been outlined in this paper on the basis of an ECS image processing algorithm and a traditional Range-Doppler location method. An azimuth mosaic was presented by a time series relationship, then the different burst was stitched by range, and the equivalent parameters were fitted to locations on the RD model. Finally, the ScanSAR image was geo-corrected. The HJ-1-C satellite data results showed that the location accuracy of ScanSAR for the HJ-1-C satellite was less than 100 m, and the geo-correction algorithm was realized in 10 s in fewer than 24 parallel cores.

  1. Parallel algorithms of relative radiometric correction for images of TH-1 satellite

    Science.gov (United States)

    Wang, Xiang; Zhang, Tingtao; Cheng, Jiasheng; Yang, Tao

    2014-05-01

    The first generation of transitive stereo-metric satellites in China, TH-1 Satellite, is able to gain stereo images of three-line-array with resolution of 5 meters, multispectral images of 10 meters, and panchromatic high resolution images of 2 meters. The procedure between level 0 and level 1A of high resolution images is so called relative radiometric correction (RRC for short). The processing algorithm of high resolution images, with large volumes of data, is complicated and time consuming. In order to bring up the processing speed, people in industry commonly apply parallel processing techniques based on CPU or GPU. This article firstly introduces the whole process and each step of the algorithm - that is in application - of RRC for high resolution images in level 0; secondly, the theory and characteristics of MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) parallel programming techniques is briefly described, as well as the superiority for parallel technique in image processing field; thirdly, aiming at each step of the algorithm in application and based on MPI+OpenMP hybrid paradigm, the parallelizability and the strategies of parallelism for three processing steps: Radiometric Correction, Splicing Pieces of TDICCD (Time Delay Integration Charge-Coupled Device) and Gray Level Adjustment among pieces of TDICCD are deeply discussed, and furthermore, deducts the theoretical acceleration rates of each step and the one of whole procedure, according to the processing styles and independence of calculation; for the step Splicing Pieces of TDICCD, two different strategies of parallelism are proposed, which are to be chosen with consideration of hardware capabilities; finally, series of experiments are carried out to verify the parallel algorithms by applying 2-meter panchromatic high resolution images of TH-1 Satellite, and the experimental results are analyzed. Strictly on the basis of former parallel algorithms, the programs in the experiments

  2. Optical Algorithms at Satellite Wavelengths for Total Suspended Matter in Tropical Coastal Waters

    Science.gov (United States)

    Ouillon, Sylvain; Douillet, Pascal; Petrenko, Anne; Neveux, Jacques; Dupouy, Cécile; Froidefond, Jean-Marie; Andréfouët, Serge; Muñoz-Caravaca, Alain

    2008-01-01

    Is it possible to derive accurately Total Suspended Matter concentration or its proxy, turbidity, from remote sensing data in tropical coastal lagoon waters? To investigate this question, hyperspectral remote sensing reflectance, turbidity and chlorophyll pigment concentration were measured in three coral reef lagoons. The three sites enabled us to get data over very diverse environments: oligotrophic and sediment-poor waters in the southwest lagoon of New Caledonia, eutrophic waters in the Cienfuegos Bay (Cuba), and sediment-rich waters in the Laucala Bay (Fiji). In this paper, optical algorithms for turbidity are presented per site based on 113 stations in New Caledonia, 24 stations in Cuba and 56 stations in Fiji. Empirical algorithms are tested at satellite wavebands useful to coastal applications. Global algorithms are also derived for the merged data set (193 stations). The performances of global and local regression algorithms are compared. The best one-band algorithms on all the measurements are obtained at 681 nm using either a polynomial or a power model. The best two-band algorithms are obtained with R412/R620, R443/R670 and R510/R681. Two three-band algorithms based on Rrs620.Rrs681/Rrs412 and Rrs620.Rrs681/Rrs510 also give fair regression statistics. Finally, we propose a global algorithm based on one or three bands: turbidity is first calculated from Rrs681 and then, if turbidity range and for the three sites sampled (mean bias: 3.6 %, rms: 35%, mean quadratic error: 1.4 FTU). This shows that defining global empirical turbidity algorithms in tropical coastal waters is at reach. PMID:27879929

  3. IPO operational algorithm teams throughout the life cycle of NPOESS environmental satellites

    Science.gov (United States)

    Duda, James L.; Emch, Pamela G.

    2004-09-01

    The tri-agency Integrated Program Office (IPO) created Operational Algorithm Teams (OATs) in 1997 to provide scientific advice for managing the development and operation of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The scientific advice focuses on (1) assuring sound science in instrument and systems design in addition to (2) assuring development and implementation of sound scientific algorithms. This paper outlines the role of IPO operational algorithm teams from mission conception, through instrument design and development, algorithm science code development and conversion to operational code, data processing system implementation, calibration, validation, and, finally, operational data and products distribution to a range of users for weather, national security, and climate science. The composition of the algorithm science teams changes substantially as the sensors and algorithms are developed, tested, integrated, launched, become operational, and age on-orbit. The concept of leveraging our heritage scientists has proven successful with many tangible benefits to the government, the contractor teams, and, ultimately, the nation's taxpayers.

  4. MPI Parallel Algorithm in Satellite Gravity Field Model Inversion on the Basis of Least Square Method

    Directory of Open Access Journals (Sweden)

    ZHOU Hao

    2015-08-01

    Full Text Available In order to solve the intensive computing tasks and high memory demand problem in satellite gravity field model inversion on the basis of huge amounts of satellite gravity observations, the parallel algorithm for high truncated order and degree satellite gravity field model inversion with least square method on the basis of MPI was introduced. After analyzing the time and space complexity of each step in the solving flow, the parallel I/O, block-organized storage and block-organized computation algorithm on the basis of MPI are introduced to design the parallel algorithm for building design matrix, establishing and solving normal equation, and the simulation results indicate that the parallel efficiency of building design matrix, establishing and solving normal equation can reach to 95%, 68%and 63% respectively. In addition, on the basis of GOCE simulated orbits and radial disturbance gravity gradient data(518 400 epochs in total, two earth gravity models truncated to degree and order 120, 240 are inversed, and the relative computation time and memory demand are only about 40 minutes and 7 hours, 290 MB and 1.57 GB respectively. Eventually, a simulation numerical calculation for earth gravity field model inversion with the simulation data, which has the equivalent noise level with GRACE and GOCE mission, is conducted. The accuracy of inversion model has a good consistent with current released model, and the combined mode can complement the spectral information of each individual mission, which indicates that the parallel algorithm in this paper can be applied to inverse the high truncated degree and order earth gravity model efficiently and stably.

  5. Evaluation of algorithms for fire detection and mapping across North America from satellite

    Science.gov (United States)

    Li, Zhanqing; Fraser, R.; Jin, J.; Abuelgasim, A. A.; Csiszar, I.; Gong, P.; Pu, R.; Hao, W.

    2003-01-01

    This paper presents an evaluation of advanced very high resolution radiometer (AVHRR)-based remote sensing algorithms for detecting active vegetation fires [, 2000a] and mapping burned areas [, 2000] throughout North America. The procedures were originally designed for application in Canada with AVHRR data aboard the NOAA 14 satellite. They were tested here with both NOAA 11 and NOAA 14 covering the period 1989-2000. It was found that the active fire detection algorithm performs well with low commission and omission error rates over forested regions in the absence of cloud cover. Moderate errors were found over semi-arid areas covered by thin clouds, as well as along rivers and around lakes observed from sun-glint angles. A modification to a fire algorithm threshold and the addition of a new test can significantly improve the detection accuracy. Burned areas mapped by satellite were compared against extensive fire polygon data acquired by U.S. forest agencies in five western states. The satellite-based mapping matches nearly 90% of total forested burned area, with the difference being mainly attributable to omission of some nonburned islands and patches within the fire polygons. In addition, it maps a significant area of burning outside the fire polygons that appear to be true fires. The 10% omission error was found to be caused mainly by three factors: lack or insufficient number of active fires, partial burning, and vegetation recovery after early season burning. In addition to total area, the location and shapes of burned scars are consistent with the ground-based maps. Overall, the two algorithms are competent for detecting and mapping forest fires in North America north of Mexico with minor modifications.

  6. Cost Analysis of Algorithm Based Billboard Manger Based Handover Method in LEO satellite Networks

    Directory of Open Access Journals (Sweden)

    Suman Kumar Sikdar

    2012-12-01

    Full Text Available Now-a-days LEO satellites have an important role in global communication system. They have some advantages like low power requirement and low end-to-end delay, more efficient frequency spectrum utilization between satellites and spot beams over GEO and MEO. So in future they can be used as a replacement of modern terrestrial wireless networks. But the handover occurrence is more due to the speed of the LEOs. Different protocol has been proposed for a successful handover among which BMBHO is more efficient. But it had a problem during the selection of the mobile node during handover. In our previous work we have proposed an algorithm so that the connection can be established easily with the appropriate satellite. In this paper we will evaluate the mobility management cost of Algorithm based Billboard Manager Based Handover method (BMBHO. A simulation result shows that the cost is lower than the cost of Mobile IP of SeaHO-LEO and PatHOLEO

  7. The Joint Polar Satellite System (JPSS) Program's Algorithm Change Process (ACP): Past, Present and Future

    Science.gov (United States)

    Griffin, Ashley

    2017-01-01

    The Joint Polar Satellite System (JPSS) Program Office is the supporting organization for the Suomi National Polar Orbiting Partnership (S-NPP) and JPSS-1 satellites. S-NPP carries the following sensors: VIIRS, CrIS, ATMS, OMPS, and CERES with instruments that ultimately produce over 25 data products that cover the Earths weather, oceans, and atmosphere. A team of scientists and engineers from all over the United States document, monitor and fix errors in operational software code or documentation with the algorithm change process (ACP) to ensure the success of the S-NPP and JPSS 1 missions by maintaining quality and accuracy of the data products the scientific community relies on. This poster will outline the programs algorithm change process (ACP), identify the various users and scientific applications of our operational data products and highlight changes that have been made to the ACP to accommodate operating system upgrades to the JPSS programs Interface Data Processing Segment (IDPS), so that the program is ready for the transition to the 2017 JPSS-1 satellite mission and beyond.

  8. Geo-correction Algorithm Based on Equivalent RD Model for ScanSAR of HJ-1-C Satellite

    OpenAIRE

    Liu Jia-yin; Wen Shuang-yan; Zhang Hong-yi; Hong Wen

    2014-01-01

    HJ-1-C satellite is the first Synthetic Aperture Radar (SAR) satellite for civilian use in China, and it has a strip and scan mode. According to the characteristics of the ScanSAR of the HJ-1-C satellite, a geo-correction algorithm based on an equivalent RD model has been outlined in this paper on the basis of an ECS image processing algorithm and a traditional Range-Doppler location method. An azimuth mosaic was presented by a time series relationship, then the different burst was stitched b...

  9. a New Algorithm for Void Filling in a Dsm from Stereo Satellite Images in Urban Areas

    Science.gov (United States)

    Gharib Bafghi, Z.; Tian, J.; d'Angelo, P.; Reinartz, P.

    2016-06-01

    Digital Surface Models (DSM) derived from stereo-pair satellite images are the main sources for many Geo-Informatics applications like 3D change detection, object classification and recognition. However since occlusion especially in urban scenes result in some deficiencies in the stereo matching phase, these DSMs contain some voids. In order to fill the voids a range of algorithms have been proposed, mainly including interpolation alone or along with auxiliary DSM. In this paper an algorithm for void filling in DSM from stereo satellite images has been developed. Unlike common previous approaches we didn't use any external DSM to fill the voids. Our proposed algorithm uses only the original images and the unfilled DSM itself. First a neighborhood around every void in the unfilled DSM and its corresponding area in multispectral image is defined. Then it is analysed to extract both spectral and geometric texture and accordingly to assign labels to each cell in the voids. This step contains three phases comprising shadow detection, height thresholding and image segmentation. Thus every cell in void has a label and is filled by the median value of its co-labelled neighbors. The results for datasets from WorldView-2 and IKONOS are shown and discussed.

  10. A NEW ALGORITHM FOR VOID FILLING IN A DSM FROM STEREO SATELLITE IMAGES IN URBAN AREAS

    Directory of Open Access Journals (Sweden)

    Z. Gharib Bafghi

    2016-06-01

    Full Text Available Digital Surface Models (DSM derived from stereo-pair satellite images are the main sources for many Geo-Informatics applications like 3D change detection, object classification and recognition. However since occlusion especially in urban scenes result in some deficiencies in the stereo matching phase, these DSMs contain some voids. In order to fill the voids a range of algorithms have been proposed, mainly including interpolation alone or along with auxiliary DSM. In this paper an algorithm for void filling in DSM from stereo satellite images has been developed. Unlike common previous approaches we didn’t use any external DSM to fill the voids. Our proposed algorithm uses only the original images and the unfilled DSM itself. First a neighborhood around every void in the unfilled DSM and its corresponding area in multispectral image is defined. Then it is analysed to extract both spectral and geometric texture and accordingly to assign labels to each cell in the voids. This step contains three phases comprising shadow detection, height thresholding and image segmentation. Thus every cell in void has a label and is filled by the median value of its co-labelled neighbors. The results for datasets from WorldView-2 and IKONOS are shown and discussed.

  11. Code Tracking Algorithms for Mitigating Multipath Effects in Fading Channels for Satellite-Based Positioning

    Directory of Open Access Journals (Sweden)

    Markku Renfors

    2007-12-01

    Full Text Available The ever-increasing public interest in location and positioning services has originated a demand for higher performance global navigation satellite systems (GNSSs. In order to achieve this incremental performance, the estimation of line-of-sight (LOS delay with high accuracy is a prerequisite for all GNSSs. The delay lock loops (DLLs and their enhanced variants (i.e., feedback code tracking loops are the structures of choice for the commercial GNSS receivers, but their performance in severe multipath scenarios is still rather limited. In addition, the new satellite positioning system proposals specify the use of a new modulation, the binary offset carrier (BOC modulation, which triggers a new challenge in the code tracking stage. Therefore, in order to meet this emerging challenge and to improve the accuracy of the delay estimation in severe multipath scenarios, this paper analyzes feedback as well as feedforward code tracking algorithms and proposes the peak tracking (PT methods, which are combinations of both feedback and feedforward structures and utilize the inherent advantages of both structures. We propose and analyze here two variants of PT algorithm: PT with second-order differentiation (Diff2, and PT with Teager Kaiser (TK operator, which will be denoted herein as PT(Diff2 and PT(TK, respectively. In addition to the proposal of the PT methods, the authors propose also an improved early-late-slope (IELS multipath elimination technique which is shown to provide very good mean-time-to-lose-lock (MTLL performance. An implementation of a noncoherent multipath estimating delay locked loop (MEDLL structure is also presented. We also incorporate here an extensive review of the existing feedback and feedforward delay estimation algorithms for direct sequence code division multiple access (DS-CDMA signals in satellite fading channels, by taking into account the impact of binary phase shift keying (BPSK as well as the newly proposed BOC modulation

  12. Impact of Missing Passive Microwave Sensors on Multi-Satellite Precipitation Retrieval Algorithm

    Directory of Open Access Journals (Sweden)

    Bin Yong

    2015-01-01

    Full Text Available The impact of one or two missing passive microwave (PMW input sensors on the end product of multi-satellite precipitation products is an interesting but obscure issue for both algorithm developers and data users. On 28 January 2013, the Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA products were reproduced and re-released by National Aeronautics and Space Administration (NASA Goddard Space Flight Center because the Advanced Microwave Sounding Unit-B (AMSU-B and the Special Sensor Microwave Imager-Sounder-F16 (SSMIS-F16 input data were unintentionally disregarded in the prior retrieval. Thus, this study investigates the sensitivity of TMPA algorithm results to missing PMW sensors by intercomparing the “early” and “late” Version-7 TMPA real-time (TMPA-RT precipitation estimates (i.e., without and with AMSU-B, SSMIS-F16 sensors with an independent high-density gauge network of 200 tipping-bucket rain gauges over the Chinese Jinghe river basin (45,421 km2. The retrieval counts and retrieval frequency of various PMW and Infrared (IR sensors incorporated into the TMPA system were also analyzed to identify and diagnose the impacts of sensor availability on the TMPA-RT retrieval accuracy. Results show that the incorporation of AMSU-B and SSMIS-F16 has substantially reduced systematic errors. The improvement exhibits rather strong seasonal and topographic dependencies. Our analyses suggest that one or two single PMW sensors might play a key role in affecting the end product of current combined microwave-infrared precipitation estimates. This finding supports algorithm developers’ current endeavor in spatiotemporally incorporating as many PMW sensors as possible in the multi-satellite precipitation retrieval system called Integrated Multi-satellitE Retrievals for Global Precipitation Measurement mission (IMERG. This study also recommends users of satellite precipitation products to switch to the newest Version-7 TMPA datasets and

  13. Orbit computation of the TELECOM-2D satellite with a Genetic Algorithm

    Science.gov (United States)

    Deleflie, Florent; Coulot, David; Vienne, Alain; Decosta, Romain; Richard, Pascal; Lasri, Mohammed Amjad

    2014-07-01

    In order to test a preliminary orbit determination method, we fit an orbit of the geostationary satellite TELECOM-2D, as if we did not know any a priori information on its trajectory. The method is based on a genetic algorithm coupled to an analytical propagator of the trajectory, that is used over a couple of days, and that uses a whole set of altazimutal data that are acquired by the tracking network made up of the two TAROT telescopes. The adjusted orbit is then compared to a numerical reference. The method is described, and the results are analyzed, as a step towards an operational method of preliminary orbit determination for uncatalogued objects.

  14. Numerical arc segmentation algorithm for a radio conference - A software tool for communication satellite systems planning

    Science.gov (United States)

    Whyte, W. A.; Heyward, A. O.; Ponchak, D. S.; Spence, R. L.; Zuzek, J. E.

    1988-01-01

    A detailed description of a Numerical Arc Segmentation Algorithm for a Radio Conference (NASARC) software package for communication satellite systems planning is presented. This software provides a method of generating predetermined arc segments for use in the development of an allotment planning procedure to be carried out at the 1988 World Administrative Radio Conference (WARC - 88) on the use of the GEO and the planning of space services utilizing GEO. The features of the NASARC software package are described, and detailed information is given about the function of each of the four NASARC program modules. The results of a sample world scenario are presented and discussed.

  15. Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD.

    Science.gov (United States)

    Bhandari, A K; Soni, V; Kumar, A; Singh, G K

    2014-07-01

    This paper presents a new contrast enhancement approach which is based on Cuckoo Search (CS) algorithm and DWT-SVD for quality improvement of the low contrast satellite images. The input image is decomposed into the four frequency subbands through Discrete Wavelet Transform (DWT), and CS algorithm used to optimize each subband of DWT and then obtains the singular value matrix of the low-low thresholded subband image and finally, it reconstructs the enhanced image by applying IDWT. The singular value matrix employed intensity information of the particular image, and any modification in the singular values changes the intensity of the given image. The experimental results show superiority of the proposed method performance in terms of PSNR, MSE, Mean and Standard Deviation over conventional and state-of-the-art techniques. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  16. Target Matching Recognition for Satellite Images Based on the Improved FREAK Algorithm

    Directory of Open Access Journals (Sweden)

    Yantong Chen

    2016-01-01

    Full Text Available Satellite remote sensing image target matching recognition exhibits poor robustness and accuracy because of the unfit feature extractor and large data quantity. To address this problem, we propose a new feature extraction algorithm for fast target matching recognition that comprises an improved feature from accelerated segment test (FAST feature detector and a binary fast retina key point (FREAK feature descriptor. To improve robustness, we extend the FAST feature detector by applying scale space theory and then transform the feature vector acquired by the FREAK descriptor from decimal into binary. We reduce the quantity of data in the computer and improve matching accuracy by using the binary space. Simulation test results show that our algorithm outperforms other relevant methods in terms of robustness and accuracy.

  17. Power Allocation Algorithm for IDMA-based Multi-Beam Satellite Communication Systems

    Directory of Open Access Journals (Sweden)

    Gongliang Liu

    2012-08-01

    Full Text Available Rain attenuation is one of the most dominant impairment factors that degrade the performance of satellite communications at Ka band and above. In order to solve the technical bottlenecks in the existing Ka-band satellite communication schemes, the authors has introduced the emerging Interleave Division Multiple Access (IDMA technology into multi-beam satellite communication systems, and consequently, a novel power allocation algorithm is proposed for the emerging and promising system in this paper. The main goal of the proposed scheme is to provide sufficient transmission quality to as many mobiles as possible, even for the users suffering heavy rain attenuation. Analysis and simulation results show that compared to the traditional power allocation schemes, the proposed scheme can guarantee high power efficiency even in heavy rain attenuation conditions, illustrating the high efficiency of the Chip-by-Chip (CBC Multi-user Detection (MUD technique in IDMA. Furthermore, in virtue of the Signal to Interference plus Noise Ratio (SINR evolution technique, the proposed scheme can make accurate estimation of available resource on considering the effect of MUD, leading to low outage probability.

  18. Fuzzy Classification of Ocean Color Satellite Data for Bio-optical Algorithm Constituent Retrievals

    Science.gov (United States)

    Campbell, Janet W.

    1998-01-01

    The ocean has been traditionally viewed as a 2 class system. Morel and Prieur (1977) classified ocean water according to the dominant absorbent particle suspended in the water column. Case 1 is described as having a high concentration of phytoplankton (and detritus) relative to other particles. Conversely, case 2 is described as having inorganic particles such as suspended sediments in high concentrations. Little work has gone into the problem of mixing bio-optical models for these different water types. An approach is put forth here to blend bio-optical algorithms based on a fuzzy classification scheme. This scheme involves two procedures. First, a clustering procedure identifies classes and builds class statistics from in-situ optical measurements. Next, a classification procedure assigns satellite pixels partial memberships to these classes based on their ocean color reflectance signature. These membership assignments can be used as the basis for a weighting retrievals from class-specific bio-optical algorithms. This technique is demonstrated with in-situ optical measurements and an image from the SeaWiFS ocean color satellite.

  19. Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

    Science.gov (United States)

    Mitra, Sunanda; Pemmaraju, Surya

    1992-01-01

    Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

  20. Optimization design of satellite separation systems based on Multi-Island Genetic Algorithm

    Science.gov (United States)

    Hu, Xingzhi; Chen, Xiaoqian; Zhao, Yong; Yao, Wen

    2014-03-01

    The separation systems are crucial for the launch of satellites. With respect to the existing design issues of satellite separation systems, an optimization design approach based on Multi-Island Genetic Algorithm is proposed, and a hierarchical optimization of system mass and separation angular velocity is designed. Multi-Island Genetic Algorithm is studied for the problem and the optimization parameters are discussed. Dynamic analysis of ADAMS used to validate the designs is integrated with iSIGHT. Then the optimization method is employed for a typical problem using the helical compression spring mechanism, and the corresponding objective functions are derived. It turns out that the mass of compression spring catapult is decreased by 30.7% after optimization and the angular velocity can be minimized considering spring stiffness errors. Moreover, ground tests and on-orbit flight indicate that the error of separation speed is controlled within 1% and the angular velocity is reduced by nearly 90%, which proves the design result and the optimization approach.

  1. Coral Reef environment reconstruction using small drones, new generation photogrammetry algorithms and satellite imagery

    Science.gov (United States)

    Elisa, Casella; Rovere, Alessio; Harris, Daniel; Parravicini, Valeriano

    2016-04-01

    Surveys based on Remotely Piloted Aircraft Systems (RPAS), together with new-generation Structure from Motion (SfM) and Multi-View Stereo (MVS) reconstruction algorithms have been employed to reconstruct the shallow bathymetry of the inner lagoon of a coral reef in Moorea, French Polinesia. This technique has already been used with a high rate of success on coastal environments (e.g. sandy beaches and rocky shorelines) reaching accuracy of the final Digital Elevation Model in the order of few centimeters. The application of such techniques to reconstruct shallow underwater environments is, though, still little reported. We then used the bathymetric dataset obtained from aerial pictures as ground-truth for relative bathymetry obtained from satellite imagery (WorldView-2) of a larger area within the same study site. The first results of our work suggest that RPAS coupled with SfM and MVS algorithms can be used to reconstruct shallow water environments with favorable weather conditions, and can be employed to ground-truth to satellite imagery.

  2. Adaptive Predistortions Based on Neural Networks Associated with Levenberg-Marquardt Algorithm for Satellite Down Links

    Directory of Open Access Journals (Sweden)

    Roviras Daniel

    2008-01-01

    Full Text Available Abstract This paper presents adaptive predistortion techniques based on a feed-forward neural network (NN to linearize power amplifiers such as those used in satellite communications. Indeed, it presents the suitable NN structures which give the best performances for three satellite down links. The first link is a stationary memoryless travelling wave tube amplifier (TWTA, the second one is a nonstationary memoryless TWT amplifier while the third is an amplifier with memory modeled by a memoryless amplifier followed by a linear filter. Equally important, it puts forward the studies concerning the application of different NN training algorithms in order to determine the most prefermant for adaptive predistortions. This comparison examined through computer simulation for 64 carriers and 16-QAM OFDM system, with a Saleh's TWT amplifier, is based on some quality measure (mean square error, the required training time to reach a particular quality level, and computation complexity. The chosen adaptive predistortions (NN structures associated with an adaptive algorithm have a low complexity, fast convergence, and best performance.

  3. 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.

  4. Hail detection algorithm for the Global Precipitation Measuring mission core satellite sensors

    Science.gov (United States)

    Mroz, Kamil; Battaglia, Alessandro; Lang, Timothy J.; Tanelli, Simone; Cecil, Daniel J.; Tridon, Frederic

    2017-04-01

    By exploiting an abundant number of extreme storms observed simultaneously by the Global Precipitation Measurement (GPM) mission core satellite's suite of sensors and by the ground-based S-band Next-Generation Radar (NEXRAD) network over continental US, proxies for the identification of hail are developed based on the GPM core satellite observables. The full capabilities of the GPM observatory are tested by analyzing more than twenty observables and adopting the hydrometeor classification based on ground-based polarimetric measurements as truth. The proxies have been tested using the Critical Success Index (CSI) as a verification measure. The hail detection algorithm based on the mean Ku reflectivity in the mixed-phase layer performs the best, out of all considered proxies (CSI of 45%). Outside the Dual frequency Precipitation Radar (DPR) swath, the Polarization Corrected Temperature at 18.7 GHz shows the greatest potential for hail detection among all GMI channels (CSI of 26% at a threshold value of 261 K). When dual variable proxies are considered, the combination involving the mixed-phase reflectivity values at both Ku and Ka-bands outperforms all the other proxies, with a CSI of 49%. The best-performing radar-radiometer algorithm is based on the mixed-phase reflectivity at Ku-band and on the brightness temperature (TB) at 10.7 GHz (CSI of 46%). When only radiometric data are available, the algorithm based on the TBs at 36.6 and 166 GHz is the most efficient, with a CSI of 27.5%.

  5. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    Directory of Open Access Journals (Sweden)

    Marc Wieland

    2014-03-01

    Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

  6. Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data

    Directory of Open Access Journals (Sweden)

    Ugur Avdan

    2016-01-01

    Full Text Available Land surface temperature is an important factor in many areas, such as global climate change, hydrological, geo-/biophysical, and urban land use/land cover. As the latest launched satellite from the LANDSAT family, LANDSAT 8 has opened new possibilities for understanding the events on the Earth with remote sensing. This study presents an algorithm for the automatic mapping of land surface temperature from LANDSAT 8 data. The tool was developed using the LANDSAT 8 thermal infrared sensor Band 10 data. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, for the first case, the standard deviation was 2.4°C, and for the second case, it was 2.7°C. For future studies, the tool should be refined with in situ measurements of land surface temperature.

  7. Vegetation Height Estimation Near Power transmission poles Via satellite Stereo Images using 3D Depth Estimation Algorithms

    Science.gov (United States)

    Qayyum, A.; Malik, A. S.; Saad, M. N. M.; Iqbal, M.; Abdullah, F.; Rahseed, W.; Abdullah, T. A. R. B. T.; Ramli, A. Q.

    2015-04-01

    Monitoring vegetation encroachment under overhead high voltage power line is a challenging problem for electricity distribution companies. Absence of proper monitoring could result in damage to the power lines and consequently cause blackout. This will affect electric power supply to industries, businesses, and daily life. Therefore, to avoid the blackouts, it is mandatory to monitor the vegetation/trees near power transmission lines. Unfortunately, the existing approaches are more time consuming and expensive. In this paper, we have proposed a novel approach to monitor the vegetation/trees near or under the power transmission poles using satellite stereo images, which were acquired using Pleiades satellites. The 3D depth of vegetation has been measured near power transmission lines using stereo algorithms. The area of interest scanned by Pleiades satellite sensors is 100 square kilometer. Our dataset covers power transmission poles in a state called Sabah in East Malaysia, encompassing a total of 52 poles in the area of 100 km. We have compared the results of Pleiades satellite stereo images using dynamic programming and Graph-Cut algorithms, consequently comparing satellites' imaging sensors and Depth-estimation Algorithms. Our results show that Graph-Cut Algorithm performs better than dynamic programming (DP) in terms of accuracy and speed.

  8. Geostationary Communications Satellites as Sensors for the Space Weather Environment: Telemetry Event Identification Algorithms

    Science.gov (United States)

    Carlton, A.; Cahoy, K.

    2015-12-01

    Reliability of geostationary communication satellites (GEO ComSats) is critical to many industries worldwide. The space radiation environment poses a significant threat and manufacturers and operators expend considerable effort to maintain reliability for users. Knowledge of the space radiation environment at the orbital location of a satellite is of critical importance for diagnosing and resolving issues resulting from space weather, for optimizing cost and reliability, and for space situational awareness. For decades, operators and manufacturers have collected large amounts of telemetry from geostationary (GEO) communications satellites to monitor system health and performance, yet this data is rarely mined for scientific purposes. The goal of this work is to acquire and analyze archived data from commercial operators using new algorithms that can detect when a space weather (or non-space weather) event of interest has occurred or is in progress. We have developed algorithms, collectively called SEER (System Event Evaluation Routine), to statistically analyze power amplifier current and temperature telemetry by identifying deviations from nominal operations or other events and trends of interest. This paper focuses on our work in progress, which currently includes methods for detection of jumps ("spikes", outliers) and step changes (changes in the local mean) in the telemetry. We then examine available space weather data from the NOAA GOES and the NOAA-computed Kp index and sunspot numbers to see what role, if any, it might have played. By combining the results of the algorithm for many components, the spacecraft can be used as a "sensor" for the space radiation environment. Similar events occurring at one time across many component telemetry streams may be indicative of a space radiation event or system-wide health and safety concern. Using SEER on representative datasets of telemetry from Inmarsat and Intelsat, we find events that occur across all or many of

  9. Design of a Four-Element, Hollow-Cube Corner Retroreflector for Satellites by use of a Genetic Algorithm.

    Science.gov (United States)

    Minato, A; Sugimoto, N

    1998-01-20

    A four-element retroreflector was designed for satellite laser ranging and Earth-satellite-Earth laser long-path absorption measurement of the atmosphere. The retroreflector consists of four symmetrically located corner retroreflectors. Each retroreflector element has curved mirrors and tuned dihedral angles to correct velocity aberrations. A genetic algorithm was employed to optimize dihedral angles of each element and the directions of the four elements. The optimized four-element retroreflector has high reflectance with a reasonably broad angular coverage. It is also shown that the genetic algorithm is effective for optimizing optics with many parameters.

  10. Advancements of in-flight mass moment of inertia and structural deflection algorithms for satellite attitude simulators

    Science.gov (United States)

    Wright, Jonathan W.

    Experimental satellite attitude simulators have long been used to test and analyze control algorithms in order to drive down risk before implementation on an operational satellite. Ideally, the dynamic response of a terrestrial-based experimental satellite attitude simulator would be similar to that of an on-orbit satellite. Unfortunately, gravitational disturbance torques and poorly characterized moments of inertia introduce uncertainty into the system dynamics leading to questionable attitude control algorithm experimental results. This research consists of three distinct, but related contributions to the field of developing robust satellite attitude simulators. In the first part of this research, existing approaches to estimate mass moments and products of inertia are evaluated followed by a proposition and evaluation of a new approach that increases both the accuracy and precision of these estimates using typical on-board satellite sensors. Next, in order to better simulate the micro-torque environment of space, a new approach to mass balancing satellite attitude simulator is presented, experimentally evaluated, and verified. Finally, in the third area of research, we capitalize on the platform improvements to analyze a control moment gyroscope (CMG) singularity avoidance steering law. Several successful experiments were conducted with the CMG array at near-singular configurations. An evaluation process was implemented to verify that the platform remained near the desired test momentum, showing that the first two components of this research were effective in allowing us to conduct singularity avoidance experiments in a representative space-like test environment.

  11. Development of a Reduction Algorithm of GEO Satellite Optical Observation Data for Optical Wide Field Patrol (OWL)

    Science.gov (United States)

    Park, Sun-youp; Choi, Jin; Jo, Jung Hyun; Son, Ju Young; Park, Yung-Sik; Yim, Hong-Suh; Moon, Hong-Kyu; Bae, Young-Ho; Choi, Young-Jun; Park, Jang-Hyun

    2015-09-01

    An algorithm to automatically extract coordinate and time information from optical observation data of geostationary orbit satellites (GEO satellites) or geosynchronous orbit satellites (GOS satellites) is developed. The optical wide-field patrol system is capable of automatic observation using a pre-arranged schedule. Therefore, if this type of automatic analysis algorithm is available, daily unmanned monitoring of GEO satellites can be possible. For data acquisition for development, the COMS1 satellite was observed with 1-s exposure time and 1-m interval. The images were grouped and processed in terms of ¡°action¡±, and each action was composed of six or nine successive images. First, a reference image with the best quality in one action was selected. Next, the rest of the images in the action were geometrically transformed to fit in the horizontal coordinate system (expressed in azimuthal angle and elevation) of the reference image. Then, these images were median-combined to retain only the possible non-moving GEO candidates. By reverting the coordinate transformation of the positions of these GEO satellite candidates, the final coordinates could be calculated.

  12. The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution

    Science.gov (United States)

    Beirle, Steffen; Hörmann, Christoph; Jöckel, Patrick; Liu, Song; Penning de Vries, Marloes; Pozzer, Andrea; Sihler, Holger; Valks, Pieter; Wagner, Thomas

    2016-07-01

    The STRatospheric Estimation Algorithm from Mainz (STREAM) determines stratospheric columns of NO2 which are needed for the retrieval of tropospheric columns from satellite observations. It is based on the total column measurements over clean, remote regions as well as over clouded scenes where the tropospheric column is effectively shielded. The contribution of individual satellite measurements to the stratospheric estimate is controlled by various weighting factors. STREAM is a flexible and robust algorithm and does not require input from chemical transport models. It was developed as a verification algorithm for the upcoming satellite instrument TROPOMI, as a complement to the operational stratospheric correction based on data assimilation. STREAM was successfully applied to the UV/vis satellite instruments GOME 1/2, SCIAMACHY, and OMI. It overcomes some of the artifacts of previous algorithms, as it is capable of reproducing gradients of stratospheric NO2, e.g., related to the polar vortex, and reduces interpolation errors over continents. Based on synthetic input data, the uncertainty of STREAM was quantified as about 0.1-0.2 × 1015 molecules cm-2, in accordance with the typical deviations between stratospheric estimates from different algorithms compared in this study.

  13. A Comparison of Different Regression Algorithms for Downscaling Monthly Satellite-Based Precipitation over North China

    Directory of Open Access Journals (Sweden)

    Wenlong Jing

    2016-10-01

    Full Text Available Environmental monitoring of Earth from space has provided invaluable information for understanding land–atmosphere water and energy exchanges. However, the use of satellite-based precipitation observations in hydrologic and environmental applications is often limited by their coarse spatial resolutions. In this study, we propose a downscaling approach based on precipitation–land surface characteristics. Daytime land surface temperature, nighttime land surface temperature, and day–night land surface temperature differences were introduced as variables in addition to the Normalized Difference Vegetation Index (NDVI, the Digital Elevation Model (DEM, and geolocation (longitude, latitude. Four machine learning regression algorithms, the classification and regression tree (CART, the k-nearest neighbors (k-NN, the support vector machine (SVM, and random forests (RF, were implemented to downscale monthly TRMM 3B43 V7 precipitation data from 25 km to 1 km over North China for the purpose of comparison of algorithm performance. The downscaled results were validated based on observations from meteorological stations and were also compared to a previous downscaling algorithm. According to the validation results, the RF-based model produced the results with the highest accuracy. It was followed by SVM, CART, and k-NN, but the accuracy of the downscaled results using SVM relied greatly on residual correction. The downscaled results were well correlated with the observations during the year, but the accuracies were relatively lower in July to September. Downscaling errors increase as monthly total precipitation increases, but the RF model was less affected by this proportional effect between errors and observation compared with the other algorithms. The variable importances of the land surface temperature (LST feature variables were higher than those of NDVI, which indicates the significance of considering the precipitation–land surface temperature

  14. 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.

  15. Estimate Landslide Volume with Genetic Algorithms and Image Similarity Method from Single Satellite Image

    Science.gov (United States)

    Yu, Ting-To

    2013-04-01

    It is important to acquire the volume of landslide in short period of time. For hazard mitigation and also emergency response purpose, the traditional method takes much longer time than expected. Due to the weather limit, traffic accessibility and many regulations of law, it take months to handle these process before the actual carry out of filed work. Remote sensing imagery can get the data as long as the visibility allowed, which happened only few day after the event. While traditional photometry requires a stereo pairs images to produce the post event DEM for calculating the change of volume. Usually have to wait weeks or even months for gathering such data, LiDAR or ground GPS measurement might take even longer period of time with much higher cost. In this study we use one post event satellite image and pre-event DTM to compare the similarity between these by alter the DTM with genetic algorithms. The outcome of smartest guess from GAs shall remove or add exact values of height at each location, which been converted into shadow relief viewgraph to compare with satellite image. Once the similarity threshold been make then the guessing work stop. It takes only few hours to finish the entire task, the computed accuracy is around 70% by comparing to the high resolution LiDAR survey at a landslide, southern Taiwan. With extra GCPs, the estimate accuracy can improve to 85% and also within few hours after the receiving of satellite image. Data of this demonstration case is a 5 m DTM at 2005, 2M resolution FormoSat optical image at 2009 and 5M LiDAR at 2010. The GAs and image similarity code is developed on Matlab at windows PC.

  16. Numerical arc segmentation algorithm for a radio conference: A software tool for communication satellite systems planning

    Science.gov (United States)

    Whyte, W. A.; Heyward, A. O.; Ponchak, D. S.; Spence, R. L.; Zuzek, J. E.

    1988-01-01

    The Numerical Arc Segmentation Algorithm for a Radio Conference (NASARC) provides a method of generating predetermined arc segments for use in the development of an allotment planning procedure to be carried out at the 1988 World Administrative Radio Conference (WARC) on the Use of the Geostationary Satellite Orbit and the Planning of Space Services Utilizing It. Through careful selection of the predetermined arc (PDA) for each administration, flexibility can be increased in terms of choice of system technical characteristics and specific orbit location while reducing the need for coordination among administrations. The NASARC software determines pairwise compatibility between all possible service areas at discrete arc locations. NASARC then exhaustively enumerates groups of administrations whose satellites can be closely located in orbit, and finds the arc segment over which each such compatible group exists. From the set of all possible compatible groupings, groups and their associated arc segments are selected using a heuristic procedure such that a PDA is identified for each administration. Various aspects of the NASARC concept and how the software accomplishes specific features of allotment planning are discussed.

  17. Evaluation of three satellite-based latent heat flux algorithms over forest ecosystems using eddy covariance data.

    Science.gov (United States)

    Yao, Yunjun; Zhang, Yuhu; Zhao, Shaohua; Li, Xianglan; Jia, Kun

    2015-06-01

    We have evaluated the performance of three satellite-based latent heat flux (LE) algorithms over forest ecosystems using observed data from 40 flux towers distributed across the world on all continents. These are the revised remote sensing-based Penman-Monteith LE (RRS-PM) algorithm, the modified satellite-based Priestley-Taylor LE (MS-PT) algorithm, and the semi-empirical Penman LE (UMD-SEMI) algorithm. Sensitivity analysis illustrates that both energy and vegetation terms has the highest sensitivity compared with other input variables. The validation results show that three algorithms demonstrate substantial differences in algorithm performance for estimating daily LE variations among five forest ecosystem biomes. Based on the average Nash-Sutcliffe efficiency and root-mean-squared error (RMSE), the MS-PT algorithm has high performance over both deciduous broadleaf forest (DBF) (0.81, 25.4 W/m(2)) and mixed forest (MF) (0.62, 25.3 W/m(2)) sites, the RRS-PM algorithm has high performance over evergreen broadleaf forest (EBF) (0.4, 28.1 W/m(2)) sites, and the UMD-SEMI algorithm has high performance over both deciduous needleleaf forest (DNF) (0.78, 17.1 W/m(2)) and evergreen needleleaf forest (ENF) (0.51, 28.1 W/m(2)) sites. Perhaps the lower uncertainties in the required forcing data for the MS-PT algorithm, the complicated algorithm structure for the RRS-PM algorithm, and the calibrated coefficients of the UMD-SEMI algorithm based on ground-measured data may explain these differences.

  18. Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

    OpenAIRE

    Fei Song; Shiyin Qin

    2014-01-01

    This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywhe...

  19. Advanced Oil Spill Detection Algorithms For Satellite Based Maritime Environment Monitoring

    Science.gov (United States)

    Radius, Andrea; Azevedo, Rui; Sapage, Tania; Carmo, Paulo

    2013-12-01

    During the last years, the increasing pollution occurrence and the alarming deterioration of the environmental health conditions of the sea, lead to the need of global monitoring capabilities, namely for marine environment management in terms of oil spill detection and indication of the suspected polluter. The sensitivity of Synthetic Aperture Radar (SAR) to the different phenomena on the sea, especially for oil spill and vessel detection, makes it a key instrument for global pollution monitoring. The SAR performances in maritime pollution monitoring are being operationally explored by a set of service providers on behalf of the European Maritime Safety Agency (EMSA), which has launched in 2007 the CleanSeaNet (CSN) project - a pan-European satellite based oil monitoring service. EDISOFT, which is from the beginning a service provider for CSN, is continuously investing in R&D activities that will ultimately lead to better algorithms and better performance on oil spill detection from SAR imagery. This strategy is being pursued through EDISOFT participation in the FP7 EC Sea-U project and in the Automatic Oil Spill Detection (AOSD) ESA project. The Sea-U project has the aim to improve the current state of oil spill detection algorithms, through the informative content maximization obtained with data fusion, the exploitation of different type of data/ sensors and the development of advanced image processing, segmentation and classification techniques. The AOSD project is closely related to the operational segment, because it is focused on the automation of the oil spill detection processing chain, integrating auxiliary data, like wind information, together with image and geometry analysis techniques. The synergy between these different objectives (R&D versus operational) allowed EDISOFT to develop oil spill detection software, that combines the operational automatic aspect, obtained through dedicated integration of the processing chain in the existing open source NEST

  20. 2D Flood Modelling Using Advanced Terrain Analysis Techniques And A Fully Continuous DEM-Based Rainfall-Runoff Algorithm

    Science.gov (United States)

    Nardi, F.; Grimaldi, S.; Petroselli, A.

    2012-12-01

    Remotely sensed Digital Elevation Models (DEMs), largely available at high resolution, and advanced terrain analysis techniques built in Geographic Information Systems (GIS), provide unique opportunities for DEM-based hydrologic and hydraulic modelling in data-scarce river basins paving the way for flood mapping at the global scale. This research is based on the implementation of a fully continuous hydrologic-hydraulic modelling optimized for ungauged basins with limited river flow measurements. The proposed procedure is characterized by a rainfall generator that feeds a continuous rainfall-runoff model producing flow time series that are routed along the channel using a bidimensional hydraulic model for the detailed representation of the inundation process. The main advantage of the proposed approach is the characterization of the entire physical process during hydrologic extreme events of channel runoff generation, propagation, and overland flow within the floodplain domain. This physically-based model neglects the need for synthetic design hyetograph and hydrograph estimation that constitute the main source of subjective analysis and uncertainty of standard methods for flood mapping. Selected case studies show results and performances of the proposed procedure as respect to standard event-based approaches.

  1. 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.

  2. Sensitivity Analysis and Calibration of a Rainfall-runoff Model with the Combined Use of EPA-SWMM and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Del Giudice Giuseppe

    2016-10-01

    Full Text Available An integrated Visual Basic Application interface is described that allows for sensitivity analysis, calibration and routing of hydraulichydrological models. The routine consists in the combination of three freeware tools performing hydrological modelling, hydraulic modelling and calibration. With such an approach, calibration is made possible even if information about sewers geometrical features is incomplete. Model parameters involve storage coefficient, time of concentration, runoff coefficient, initial abstraction and Manning coefficient; literature formulas are considered and manipulated to obtain novel expressions and variation ranges. A sensitivity analysis with a local method is performed to obtain information about collinearity among parameters and a ranking of influence. The least important parameters are given a fixed value, and for the remaining ones calibration is performed by means of a genetic algorithm implemented in GANetXL. Single-event calibration is performed with a selection of six rainfall events, which are chosen so to avoid non-uniform rainfall distribution; results are then successfully validated with a sequence of four events.

  3. Sensitivity Analysis and Calibration of a Rainfall-Runoff Model with the Combined Use of EPA-SWMM and Genetic Algorithm

    Science.gov (United States)

    Del Giudice, Giuseppe; Padulano, Roberta

    2016-10-01

    An integrated Visual Basic Application interface is described that allows for sensitivity analysis, calibration and routing of hydraulichydrological models. The routine consists in the combination of three freeware tools performing hydrological modelling, hydraulic modelling and calibration. With such an approach, calibration is made possible even if information about sewers geometrical features is incomplete. Model parameters involve storage coefficient, time of concentration, runoff coefficient, initial abstraction and Manning coefficient; literature formulas are considered and manipulated to obtain novel expressions and variation ranges. A sensitivity analysis with a local method is performed to obtain information about collinearity among parameters and a ranking of influence. The least important parameters are given a fixed value, and for the remaining ones calibration is performed by means of a genetic algorithm implemented in GANetXL. Single-event calibration is performed with a selection of six rainfall events, which are chosen so to avoid non-uniform rainfall distribution; results are then successfully validated with a sequence of four events.

  4. A mission-oriented orbit design method of remote sensing satellite for region monitoring mission based on evolutionary algorithm

    Science.gov (United States)

    Shen, Xin; Zhang, Jing; Yao, Huang

    2015-12-01

    Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can't satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users' demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.

  5. Low-cost Citizen Science Balloon Platform for Measuring Air Pollutants to Improve Satellite Retrieval Algorithms

    Science.gov (United States)

    Potosnak, M. J.; Beck-Winchatz, B.; Ritter, P.

    2016-12-01

    High-altitude balloons (HABs) are an engaging platform for citizen science and formal and informal STEM education. However, the logistics of launching, chasing and recovering a payload on a 1200 g or 1500 g balloon can be daunting for many novice school groups and citizen scientists, and the cost can be prohibitive. In addition, there are many interesting scientific applications that do not require reaching the stratosphere, including measuring atmospheric pollutants in the planetary boundary layer. With a large number of citizen scientist flights, these data can be used to constrain satellite retrieval algorithms. In this poster presentation, we discuss a novel approach based on small (30 g) balloons that are cheap and easy to handle, and low-cost tracking devices (SPOT trackers for hikers) that do not require a radio license. Our scientific goal is to measure air quality in the lower troposphere. For example, particulate matter (PM) is an air pollutant that varies on small spatial scales and has sources in rural areas like biomass burning and farming practices such as tilling. Our HAB platform test flight incorporates an optical PM sensor, an integrated single board computer that records the PM sensor signal in addition to flight parameters (pressure, location and altitude), and a low-cost tracking system. Our goal is for the entire platform to cost less than $500. While the datasets generated by these flights are typically small, integrating a network of flight data from citizen scientists into a form usable for comparison to satellite data will require big data techniques.

  6. Shoreline to Height (S2H): an algorithm to monitor reservoirs' water height from satellite images. A flood risk management application

    Science.gov (United States)

    Cenci, Luca; Boni, Giorgio; Pulvirenti, Luca; Gabellani, Simone; Gardella, Fabio; Squicciarino, Giuseppe; Pierdicca, Nazzareno; Benedetto, Catia

    2016-04-01

    In a reservoir, water level monitoring is important for emergency management purposes. This information can be used to estimate the degree of filling of the water body, thus helping decision makers in flood control operations. Furthermore, if assimilated in hydrological models and coupled with rainfall forecasts, this information can be used for flood forecast and early warning. In many cases, water level is not known (e.g. data-scarce environments), or not shared by operators. Remote sensing may allow overcoming these limitations, enabling its estimation. The objective of this work is to present the Shoreline to Height (S2H) algorithm, developed to retrieve the height of the water stored in reservoirs from satellite images. To this aim, some auxiliary data are needed: a DEM and the maximum/minimum height that can be reached by the water. In data-scarce environments, these information can be easily obtained on the Internet (e.g. free, worldwide DEM and design data for artificial reservoirs). S2H was tested with different satellite data, both optical and SAR (Landsat and Cosmo SkyMed®-CSK®) in order to assess the impact of different sensors on the final estimates. The study area was the Place-Moulin Lake (Valle d'Aosta-VdA, Italy), where it is present a monitoring network that can provide reliable ground-truths for validating the algorithm and assessing its accuracy. When the algorithm was developed, it was assumed to be in absence of any "official"-auxiliary data. Therefore, two DEMs (SRTM 1 arc-second and ASTER GDEM) were used to evaluate their performances. The maximum/minimum water height values were found on the website of VdA Region. The S2H is based on three steps: i) satellite data preprocessing (Landsat: atmospheric correction; CSK®: geocoding and speckle filtering); ii) water mask generation (using a thresholding and region growing algorithm) and shoreline extraction; iii) retrieval of the shoreline height according to the reference DEMs (adopting a

  7. Dynamic Routing Algorithm for Satellite Network Based on Ant Colony Algorithm%基于蚁群算法的卫星网动态路由算法

    Institute of Scientific and Technical Information of China (English)

    马海滨; 王汝传; 饶元

    2011-01-01

    卫星网络路由应当具有使用较小的通信开销和处理能力计算出最优路径,并能够适应卫星网络拓扑结构动态变化等特点,这与蚁群算法的特征相匹配,能很好地解决这一问题.以此为背景,提出了一种新型的基于蚁群算法的卫星网动态路由算法(DRAS-ACA),并在NS2网络仿真平台上实现了该路由算法,使用gnuplot分析了仿真结果.%Satellite network routing should have the use of smaller capacity and communication overhead to calculate the optimal path, and be able to adapt to the satellite network topology changes, and other characteristics. The Ant Colony Algorithm should be a good appraach to solve this problem. In this paper, a dynamic routing algorithm for satellite network based on ant colony algorithm (DRAS-ACA) was presented and simulated on NS2 platform,and we also analyzed the simulation results with gnuplot.

  8. An analytic algorithm for global coverage of the revisiting orbit and its application to the CFOSAT satellite

    Science.gov (United States)

    Xu, Ming; Huang, Li

    2014-08-01

    This paper addresses a new analytic algorithm for global coverage of the revisiting orbit and its application to the mission revisiting the Earth within long periods of time, such as Chinese-French Oceanic Satellite (abbr., CFOSAT). In the first, it is presented that the traditional design methodology of the revisiting orbit for some imaging satellites only on the single (ascending or descending) pass, and the repeating orbit is employed to perform the global coverage within short periods of time. However, the selection of the repeating orbit is essentially to yield the suboptimum from the rare measure of rational numbers of passes per day, which will lose lots of available revisiting orbits. Thus, an innovative design scheme is proposed to check both rational and irrational passes per day to acquire the relationship between the coverage percentage and the altitude. To improve the traditional imaging only on the single pass, the proposed algorithm is mapping every pass into its ascending and descending nodes on the specified latitude circle, and then is accumulating the projected width on the circle by the field of view of the satellite. The ergodic geometry of coverage percentage produced from the algorithm is affecting the final scheme, such as the optimal one owning the largest percentage, and the balance one possessing the less gradient in its vicinity, and is guiding to heuristic design for the station-keeping control strategies. The application of CFOSAT validates the feasibility of the algorithm.

  9. 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.

  10. Development of Ray Tracing Algorithms for Scanning Plane and Transverse Plane Analysis for Satellite Multibeam Application

    Directory of Open Access Journals (Sweden)

    N. H. Abd Rahman

    2014-01-01

    Full Text Available Reflector antennas have been widely used in many areas. In the implementation of parabolic reflector antenna for broadcasting satellite applications, it is essential for the spacecraft antenna to provide precise contoured beam to effectively serve the required region. For this purpose, combinations of more than one beam are required. Therefore, a tool utilizing ray tracing method is developed to calculate precise off-axis beams for multibeam antenna system. In the multibeam system, each beam will be fed from different feed positions to allow the main beam to be radiated at the exact direction on the coverage area. Thus, detailed study on caustics of a parabolic reflector antenna is performed and presented in this paper, which is to investigate the behaviour of the rays and its relation to various antenna parameters. In order to produce accurate data for the analysis, the caustic behaviours are investigated in two distinctive modes: scanning plane and transverse plane. This paper presents the detailed discussions on the derivation of the ray tracing algorithms, the establishment of the equations of caustic loci, and the verification of the method through calculation of radiation pattern.

  11. 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.

  12. Seeking an optimal algorithm for a new satellite-based Sea Ice Drift Climate Data Record : Motivations, plans and initial results from the ESA CCI Sea Ice project

    DEFF Research Database (Denmark)

    Lavergne, T.; Dybkjær, Gorm; Girard-Ardhuin, Fanny

    relevant satellite and “ground-truth” data, building the Round-Robin Data Package for testing the algorithms, and finally selection of the most promising algorithm(s) for processing of a new sea ice drift climate dataset. Specific efforts are dedicated to the definition of per-grid-cell uncertainties...

  13. Seeking an optimal algorithm for a new satellite-based Sea Ice Drift Climate Data Record : Motivations, plans and initial results from the ESA CCI Sea Ice project

    DEFF Research Database (Denmark)

    Lavergne, T.; Dybkjær, Gorm; Girard-Ardhuin, Fanny

    relevant satellite and “ground-truth” data, building the Round-Robin Data Package for testing the algorithms, and finally selection of the most promising algorithm(s) for processing of a new sea ice drift climate dataset. Specific efforts are dedicated to the definition of per-grid-cell uncertainties...

  14. Testing and Adapting a Daytime Four Band Satellite Ash Detection Algorithm for Eruptions in Alaska and the Kamchatka Peninsula, Russia

    Science.gov (United States)

    Andrup-Henriksen, G.; Skoog, R. A.

    2007-12-01

    Volcanic ash is detectable from satellite remote sensing due to the differences in spectral signatures compared to meteorological clouds. Recently a new global daytime ash detection algorithm was developed at University of Madison, Wisconsin. The algorithm is based on four spectral bands with the central wavelengths 0.65, 3.75, 11 and 12 micrometers that are common on weather satellite sensors including MODIS, AVHRR, GOES and MTSAT. The initial development of the algorithm was primarily based on MODIS data with global coverage. We have tested it using three years of AVHRR data in Alaska and the Kamchatka Peninsula, Russia. All the AVHRR data have been manually analyzed and recorded into an observational database during the daily monitoring performed by the remote sensing group at the Alaska Volcano Observatory (AVO). By taking the manual observations as accurate we were able to examine the accuracy of the four-channel algorithm for daytime data. The results were also compared to the current automated ash alarm used by AVO, based on the reverse absorption technique, also known as the split window method, with a threshold of -1.7K. This comparison indicates that the four- banded technique has a higher sensitivity to volcanic ash, but a greater number of false alarms. The algorithm was modified to achieve a false alarm rate comparable to current ash alarm while still maintaining increased sensitivity.

  15. 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

    , and the V37 or V21 channel becomes the top responder to surface rain as the amount of hydrometeors in the atmospheric column reaches very high values. Additionally, it is found that land surface type and 2 m air temperature have significant skills in characterizing rain cloud types, so that the V19-V37 channel is more sensitive to surface rainfall for more vegetated warm surface, while the V85 channel is more sensitive to cold bare land. This finding implies that the above two parameters may be used to prioritize satellite observations at different channels, so that the channel that has the best rainfall sensitivity under a given condition receives the highest weight in retrieval algorithms.

  16. 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...

  17. A global aerosol classification algorithm incorporating multiple satellite data sets of aerosol and trace gas abundances

    Directory of Open Access Journals (Sweden)

    M. J. M. Penning de Vries

    2015-09-01

    Full Text Available Detecting the optical properties of aerosols using passive satellite-borne measurements alone is a difficult task due to the broadband effect of aerosols on the measured spectra and the influences of surface and cloud reflection. We present another approach to determine aerosol type, namely by studying the relationship of aerosol optical depth (AOD with trace gas abundance, aerosol absorption, and mean aerosol size. Our new Global Aerosol Classification Algorithm, GACA, examines relationships between aerosol properties (AOD and extinction Ångström exponent from the Moderate Resolution Imaging Spectroradiometer (MODIS, UV Aerosol Index from the second Global Ozone Monitoring Experiment, GOME-2 and trace gas column densities (NO2, HCHO, SO2 from GOME-2, and CO from MOPITT, the Measurements of Pollution in the Troposphere instrument on a monthly mean basis. First, aerosol types are separated based on size (Ångström exponent and absorption (UV Aerosol Index, then the dominating sources are identified based on mean trace gas columns and their correlation with AOD. In this way, global maps of dominant aerosol type and main source type are constructed for each season and compared with maps of aerosol composition from the global MACC (Monitoring Atmospheric Composition and Climate model. Although GACA cannot correctly characterize transported or mixed aerosols, GACA and MACC show good agreement regarding the global seasonal cycle, particularly for urban/industrial aerosols. The seasonal cycles of both aerosol type and source are also studied in more detail for selected 5° × 5° regions. Again, good agreement between GACA and MACC is found for all regions, but some systematic differences become apparent: the variability of aerosol composition (yearly and/or seasonal is often not well captured by MACC, the amount of mineral dust outside of the dust belt appears to be overestimated, and the abundance of secondary organic aerosols is underestimated in

  18. A global aerosol classification algorithm incorporating multiple satellite data sets of aerosol and trace gas abundances

    Directory of Open Access Journals (Sweden)

    M. J. M. Penning de Vries

    2015-05-01

    Full Text Available Detecting the optical properties of aerosols using passive satellite-borne measurements alone is a difficult task due to the broad-band effect of aerosols on the measured spectra and the influences of surface and cloud reflection. We present another approach to determine aerosol type, namely by studying the relationship of aerosol optical depth (AOD with trace gas abundance, aerosol absorption, and mean aerosol size. Our new Global Aerosol Classification Algorithm, GACA, examines relationships between aerosol properties (AOD and extinction Ångström exponent from the Moderate Resolution Imaging Spectroradiometer (MODIS, UV Aerosol Index from the second Global Ozone Monitoring Experiment, GOME-2 and trace gas column densities (NO2, HCHO, SO2 from GOME-2, and CO from MOPITT, the Measurements of Pollution in the Troposphere instrument on a monthly mean basis. First, aerosol types are separated based on size (Ångström exponent and absorption (UV Aerosol Index, then the dominating sources are identified based on mean trace gas columns and their correlation with AOD. In this way, global maps of dominant aerosol type and main source type are constructed for each season and compared with maps of aerosol composition from the global MACC (Monitoring Atmospheric Composition and Climate model. Although GACA cannot correctly characterize transported or mixed aerosols, GACA and MACC show good agreement regarding the global seasonal cycle, particularly for urban/industrial aerosols. The seasonal cycles of both aerosol type and source are also studied in more detail for selected 5° × 5° regions. Again, good agreement between GACA and MACC is found for all regions, but some systematic differences become apparent: the variability of aerosol composition (yearly and/or seasonal is often not well captured by MACC, the amount of mineral dust outside of the dust belt appears to be overestimated, and the abundance of secondary organic aerosols is underestimated

  19. 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...

  20. Development of hybrid fog detection algorithm (FDA) using satellite and ground observation data for nighttime

    Science.gov (United States)

    Kim, So-Hyeong; Han, Ji-Hae; Suh, Myoung-Seok

    2017-04-01

    In this study, we developed a hybrid fog detection algorithm (FDA) using AHI/Himawari-8 satellite and ground observation data for nighttime. In order to detect fog at nighttime, Dual Channel Difference (DCD) method based on the emissivity difference between SWIR and IR1 is most widely used. DCD is good at discriminating fog from other things (middle/high clouds, clear sea and land). However, it is difficult to distinguish fog from low clouds. In order to separate the low clouds from the pixels that satisfy the thresholds of fog in the DCD test, we conducted supplementary tests such as normalized local standard derivation (NLSD) of BT11 and the difference of fog top temperature (BT11) and air temperature (Ta) from NWP data (SST from OSTIA data). These tests are based on the larger homogeneity of fog top than low cloud tops and the similarity of fog top temperature and Ta (SST). Threshold values for the three tests were optimized through ROC analysis for the selected fog cases. In addition, considering the spatial continuity of fog, post-processing was performed to detect the missed pixels, in particular, at edge of fog or sub-pixel size fog. The final fog detection results are presented by fog probability (0 100 %). Validation was conducted by comparing fog detection probability with the ground observed visibility data from KMA. The validation results showed that POD and FAR are ranged from 0.70 0.94 and 0.45 0.72, respectively. The quantitative validation and visual inspection indicate that current FDA has a tendency to over-detect the fog. So, more works which reducing the FAR is needed. In the future, we will also validate sea fog using CALIPSO data.

  1. Satellite range scheduling with the priority constraint: An improved genetic algorithm using a station ID encoding method

    Directory of Open Access Journals (Sweden)

    Li Yuqing

    2015-06-01

    Full Text Available Satellite range scheduling with the priority constraint is one of the most important problems in the field of satellite operation. This paper proposes a station coding based genetic algorithm to solve this problem, which adopts a new chromosome encoding method that arranges tasks according to the ground station ID. The new encoding method contributes to reducing the complexity in conflict checking and resolving, and helps to improve the ability to find optimal resolutions. Three different selection operators are designed to match the new encoding strategy, namely random selection, greedy selection, and roulette selection. To demonstrate the benefits of the improved genetic algorithm, a basic genetic algorithm is designed in which two cross operators are presented, a single-point crossover and a multi-point crossover. For the purpose of algorithm test and analysis, a problem-generating program is designed, which can simulate problems by modeling features encountered in real-world problems. Based on the problem generator, computational results and analysis are made and illustrated for the scheduling of multiple ground stations.

  2. Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Fei Song

    2014-01-01

    Full Text Available This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywheel is activated to counteract the fault effect and ensure that the satellite is working safely and reliably. The active disturbance rejection approach is employed to design the controller, which handles input information with tracking differentiator, estimates system uncertainties with extended state observer, and generates control variables by state feedback and compensation. The designed active disturbance rejection controller is robust to both internal dynamics and external disturbances. The bandwidth parameter of extended state observer is optimized by the artificial bee colony algorithm so as to improve the performance of attitude control system. A series of simulation experiment results demonstrate the performance superiorities of the proposed robust fault-tolerant control algorithm.

  3. Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis)

    OpenAIRE

    Gustavo A. Carvalho; Minnett, Peter J.; Fleming, Lora E; Banzon, Viva F.; Baringer, Warner

    2010-01-01

    In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlor...

  4. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Science.gov (United States)

    Dubovik, O.; Herman, M.; Holdak, A.; Lapyonok, T.; Tanré, D.; Deuzé, J. L.; Ducos, F.; Sinyuk, A.; Lopatin, A.

    2011-05-01

    The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation. The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index). In order to achieve reliable retrieval from PARASOL observations even over very reflective

  5. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Directory of Open Access Journals (Sweden)

    O. Dubovik

    2011-05-01

    Full Text Available The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns that is not common in satellite observations. The POLDER imager on board the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

    The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index. In order to achieve reliable retrieval from PARASOL observations

  6. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

    Directory of Open Access Journals (Sweden)

    O. Dubovik

    2010-11-01

    Full Text Available The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns that is not common in satellite observations. The POLDER imager on board of the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of the all available angular observations of total and polarized radiances obtained by POLDER sensor in the window spectral channels where absorption by gaseous is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed on retrieval of extended set of parameters affecting measured radiation.

    The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index. In order to achieve

  7. Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration

    Directory of Open Access Journals (Sweden)

    Yunjun Yao

    2014-01-01

    Full Text Available Satellite-based vegetation indices (VIs and Apparent Thermal Inertia (ATI derived from temperature change provide valuable information for estimating evapotranspiration (LE and detecting the onset and severity of drought. The modified satellite-based Priestley-Taylor (MS-PT algorithm that we developed earlier, coupling both VI and ATI, is validated based on observed data from 40 flux towers distributed across the world on all continents. The validation results illustrate that the daily LE can be estimated with the Root Mean Square Error (RMSE varying from 10.7 W/m2 to 87.6 W/m2, and with the square of correlation coefficient (R2 from 0.41 to 0.89 (p < 0.01. Compared with the Priestley-Taylor-based LE (PT-JPL algorithm, the MS-PT algorithm improves the LE estimates at most flux tower sites. Importantly, the MS-PT algorithm is also satisfactory in reproducing the inter-annual variability at flux tower sites with at least five years of data. The R2 between measured and predicted annual LE anomalies is 0.42 (p = 0.02. The MS-PT algorithm is then applied to detect the variations of long-term terrestrial LE over Three-North Shelter Forest Region of China and to monitor global land surface drought. The MS-PT algorithm described here demonstrates the ability to map regional terrestrial LE and identify global soil moisture stress, without requiring precipitation information.

  8. Design of Satellite Attitude Control Algorithm Based on the SDRE Method Using Gas Jets and Reaction Wheels

    Directory of Open Access Journals (Sweden)

    Luiz C. G. de Souza

    2013-01-01

    Full Text Available An experimental attitude control algorithm design using prototypes can minimize space mission costs by reducing the number of errors transmitted to the next phase of the project. The Space Mechanics and Control Division (DMC of INPE is constructing a 3D simulator to supply the conditions for implementing and testing satellite control hardware and software. Satellite large angle maneuver makes the plant highly nonlinear and if the parameters of the system are not well determined, the plant can also present some level of uncertainty. As a result, controller designed by a linear control technique can have its performance and robustness degraded. In this paper the standard LQR linear controller and the SDRE controller associated with an SDRE filter are applied to design a controller for a nonlinear plant. The plant is similar to the DMC 3D satellite simulator where the unstructured uncertainties of the system are represented by process and measurements noise. In the sequel the State-Dependent Riccati Equation (SDRE method is used to design and test an attitude control algorithm based on gas jets and reaction wheel torques to perform large angle maneuver in three axes. The SDRE controller design takes into account the effects of the plant nonlinearities and system noise which represents uncertainty. The SDRE controller performance and robustness are tested during the transition phase from angular velocity reductions to normal mode of operation with stringent pointing accuracy using a switching control algorithm based on minimum system energy. This work serves to validate the numerical simulator model and to verify the functionality of the control algorithm designed by the SDRE method.

  9. A Distributed Cooperative Dynamic Task Planning Algorithm for Multiple Satellites Based on Multi-agent Hybrid Learning

    Institute of Scientific and Technical Information of China (English)

    WANG Chong; LI Jun; JING Ning; WANG Jun; CHEN Hao

    2011-01-01

    Traditionally,heuristic re-planning algorithms are used to tackle the problem of dynamic task planning for multiple satellites.However,the traditional heuristic strategies depend on the concrete tasks,which often affect the result's optimality.Noticing that the historical information of cooperative task planning will impact the latter planning results,we propose a hybrid learning algorithrn for dynamic multi-satellite task planning,which is based on the multi-agent reinforcement learning of policy iteration and the transfer learning.The reinforcement learning strategy of each satellite is described with neural networks.The policy neural network individuals with the best topological structure and weights are found by applying co-evolutionary search iteratively.To avoid the failure of the historical learning caused by the randomly occurring observation requests,a novel approach is proposed to balance the quality and efficiency of the task planning,which converts the historical leaming strategy to the current initial learning strategy by applying the transfer learning algorithm.The simulations and analysis show the feasibility and adaptability of the proposed approach especially for the situation with randomly occurring observation requests.

  10. Satellite cell heterogeneity revealed by G-Tool, an open algorithm to quantify myogenesis through colony-forming assays

    Directory of Open Access Journals (Sweden)

    Ippolito Joseph

    2012-06-01

    Full Text Available Abstract Background Muscle growth and repair is accomplished by the satellite cell pool, a self-renewing population of myogenic progenitors. Functional heterogeneity within the satellite cell compartment and changes in potential with experimental intervention can be revealed by in vitro colony-forming cell (CFC assays, however large numbers of colonies need to be assayed to give meaningful data, and manually quantifying nuclei and scoring markers of differentiation is experimentally limiting. Methods We present G-Tool, a multiplatform (Java open-source algorithm that analyzes an ensemble of fluorescent micrographs of satellite cell-derived colonies to provide quantitative and statistically meaningful metrics of myogenic potential, including proliferation capacity and propensity to differentiate. Results We demonstrate the utility of G-Tool in two applications: first, we quantify the response of satellite cells to oxygen concentration. Compared to 3% oxygen which approximates tissue levels, we find that 21% oxygen, the ambient level, markedly limits the proliferative potential of transit amplifying progeny but at the same time inhibits the rate of terminal myogenic differentiation. We also test whether satellite cells from different muscles have intrinsic differences that can be read out in vitro. Compared to masseter, dorsi, forelimb and hindlimb muscles, we find that the diaphragm satellite cells have significantly increased proliferative potential and a reduced propensity to spontaneously differentiate. These features may be related to the unique always-active status of the diaphragm. Conclusions G-Tool facilitates consistent and reproducible CFC analysis between experiments and individuals. It is released under an open-source license that enables further development by interested members of the community.

  11. 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

  12. A robust TEC depletion detector algorithm for satellite based navigation in Indian zone and depletion analysis for GAGAN

    Science.gov (United States)

    Dashora, Nirvikar

    2012-07-01

    require an immediate solution to attack this problem. Hence, an alternative approach is chosen in which TEC-depletions are ignored for GIVE estimation. This approach requires further attention to accommodate it in the processing software for a near real time solution for the concerned user in Indian zone. But, nonetheless, as a prime concern, to precluding a particular satellite-link affected by TEC depletion, a reference receiver or user requires an algorithm that can compute the TEC and detect the depletion in TEC in near real time. To answer it, a novel TEC depletion detector algorithm and software has been developed which can be used for any SBAS in India. The algorithm is initially tested for recorded data from ground based dual frequency GPS receivers of GAGAN project. Data from 18-20 stations with 30 second sampling interval was obtained for year 2004 and 2005. The algorithm has been tuned to Indian ionosphere and show a great success in detecting TEC depletions with minimum false alarm. This is because of a specific property of this algorithm that it rejects the smooth fall in TEC in post sunset ionosphere. The depletions in TEC are characterized by a sudden fall and immediate recovery in level of TEC for a given line of sight. Since our algorithm extracts only such signatures and hence minimize the false alarms it may reduce burden on operational systems. We present this algorithm in detail. Another important facet of this algorithm is about its scientific use in automatic analysis of large amount of continuous GPS data. We have analyzed the aforementioned data by a MATLAB based script and obtained significant statistical results. The temporal duration and depth of TEC depletions is obtained for all over Indian region which provide a new insight over the phenomenon called EPBs and TEC depletions.

  13. Using Lagrangian-based process studies to test satellite algorithms of vertical carbon flux in the eastern North Pacific Ocean

    Science.gov (United States)

    Stukel, M. R.; Kahru, M.; Benitez-Nelson, C. R.; Décima, M.; Goericke, R.; Landry, M. R.; Ohman, M. D.

    2015-11-01

    The biological carbon pump is responsible for the transport of ˜5-20 Pg C yr-1 from the surface into the deep ocean but its variability is poorly understood due to an incomplete mechanistic understanding of the complex underlying planktonic processes. In fact, algorithms designed to estimate carbon export from satellite products incorporate fundamentally different assumptions about the relationships between plankton biomass, productivity, and export efficiency. To test the alternate formulations of export efficiency in remote-sensing algorithms formulated by Dunne et al. (2005), Laws et al. (2011), Henson et al. (2011), and Siegel et al. (2014), we have compiled in situ measurements (temperature, chlorophyll, primary production, phytoplankton biomass and size structure, grazing rates, net chlorophyll change, and carbon export) made during Lagrangian process studies on seven cruises in the California Current Ecosystem and Costa Rica Dome. A food-web based approach formulated by Siegel et al. (2014) performs as well or better than other empirical formulations, while simultaneously providing reasonable estimates of protozoan and mesozooplankton grazing rates. By tuning the Siegel et al. (2014) algorithm to match in situ grazing rates more accurately, we also obtain better in situ carbon export measurements. Adequate representations of food-web relationships and grazing dynamics are therefore crucial to improving the accuracy of export predictions made from satellite-derived products. Nevertheless, considerable unexplained variance in export remains and must be explored before we can reliably use remote sensing products to assess the impact of climate change on biologically mediated carbon sequestration.

  14. Algorithm for Recovery of Integrated Water Vapor Content in the Atmosphere over Land Surfaces Based on Satellite Spectroradiometer Data

    Science.gov (United States)

    Lisenko, S. A.

    2017-05-01

    An algorithm is proposed for making charts of the distribution of water vapor in the atmosphere based on multispectral images of the earth by the Ocean and Land Color Instrument (OLCI) on board of the European research satellite Sentinel-3. The algorithm is based on multiple regression fits of the spectral brightness coefficients at the upper boundary of the atmosphere, the geometric parameters of the satellite location (solar and viewing angles), and the total water vapor content in the atmosphere. A regression equation is derived from experimental data on the variation in the optical characteristics of the atmosphere and underlying surface, together with Monte-Carlo calculations of the radiative transfer characteristics. The equation includes the brightness coefficients in the near IR channels of the OLCI for the absorption bands of water vapor and oxygen, as well as for the transparency windows of the atmosphere. Together these make it possible to eliminate the effect of the reflection spectrum of the underlying surface and air pressure on the accuracy of the measurements. The algorithm is tested using data from a prototype OLCI, the medium resolution imaging spectrometer (MERIS). A sample chart of the distribution of water vapor in the atmosphere over Eastern Europe is constructed without using subsatellite data and digital models of the surface relief. The water vapor contents in the atmosphere determined using MERIS images and data provided by earthbound measurements with the aerosol robotic network (AERONET) are compared with a mean square deviation of 1.24 kg/m2.

  15. An Image Matching Algorithm Integrating Global SRTM and Image Segmentation for Multi-Source Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xiao Ling

    2016-08-01

    Full Text Available This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC, which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3, Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.

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

    Science.gov (United States)

    Seltzer, S. M.

    1976-01-01

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

  17. An Empirical Orthogonal Function-Based Algorithm for Estimating Terrestrial Latent Heat Flux from Eddy Covariance, Meteorological and Satellite Observations.

    Science.gov (United States)

    Feng, Fei; Li, Xianglan; Yao, Yunjun; Liang, Shunlin; Chen, Jiquan; Zhao, Xiang; Jia, Kun; Pintér, Krisztina; McCaughey, J Harry

    2016-01-01

    Accurate estimation of latent heat flux (LE) based on remote sensing data is critical in characterizing terrestrial ecosystems and modeling land surface processes. Many LE products were released during the past few decades, but their quality might not meet the requirements in terms of data consistency and estimation accuracy. Merging multiple algorithms could be an effective way to improve the quality of existing LE products. In this paper, we present a data integration method based on modified empirical orthogonal function (EOF) analysis to integrate the Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16) and the Priestley-Taylor LE algorithm of Jet Propulsion Laboratory (PT-JPL) estimate. Twenty-two eddy covariance (EC) sites with LE observation were chosen to evaluate our algorithm, showing that the proposed EOF fusion method was capable of integrating the two satellite data sets with improved consistency and reduced uncertainties. Further efforts were needed to evaluate and improve the proposed algorithm at larger spatial scales and time periods, and over different land cover types.

  18. Developing the science product algorithm testbed for Chinese next-generation geostationary meteorological satellites: Fengyun-4 series

    Science.gov (United States)

    Min, Min; Wu, Chunqiang; Li, Chuan; Liu, Hui; Xu, Na; Wu, Xiao; Chen, Lin; Wang, Fu; Sun, Fenglin; Qin, Danyu; Wang, Xi; Li, Bo; Zheng, Zhaojun; Cao, Guangzhen; Dong, Lixin

    2017-08-01

    Fengyun-4A (FY-4A), the first of the Chinese next-generation geostationary meteorological satellites, launched in 2016, offers several advances over the FY-2: more spectral bands, faster imaging, and infrared hyperspectral measurements. To support the major objective of developing the prototypes of FY-4 science algorithms, two science product algorithm testbeds for imagers and sounders have been developed by the scientists in the FY-4 Algorithm Working Group (AWG). Both testbeds, written in FORTRAN and C programming languages for Linux or UNIX systems, have been tested successfully by using Intel/g compilers. Some important FY-4 science products, including cloud mask, cloud properties, and temperature profiles, have been retrieved successfully through using a proxy imager, Himawari-8/Advanced Himawari Imager (AHI), and sounder data, obtained from the Atmospheric InfraRed Sounder, thus demonstrating their robustness. In addition, in early 2016, the FY-4 AWG was developed based on the imager testbed—a near real-time processing system for Himawari-8/AHI data for use by Chinese weather forecasters. Consequently, robust and flexible science product algorithm testbeds have provided essential and productive tools for popularizing FY-4 data and developing substantial improvements in FY-4 products.

  19. 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,.

  20. Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance

    Directory of Open Access Journals (Sweden)

    Chen Zeng

    2016-12-01

    Full Text Available Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO. However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution, simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy.

  1. An Enhanced Satellite-Based Algorithm for Detecting and Tracking Dust Outbreaks by Means of SEVIRI Data

    Directory of Open Access Journals (Sweden)

    Francesco Marchese

    2017-05-01

    Full Text Available Dust outbreaks are meteorological phenomena of great interest for scientists and authorities (because of their impact on the climate, environment, and human activities, which may be detected, monitored, and characterized from space using different methods and procedures. Among the recent dust detection algorithms, the RSTDUST multi-temporal technique has provided good results in different geographic areas (e.g., Mediterranean basin; Arabian Peninsula, exhibiting a better performance than traditional split window methods, in spite of some limitations. In this study, we present an optimized configuration of this technique, which better exploits data provided by Spinning Enhanced Visible and Infrared Imager (SEVIRI aboard Meteosat Second Generation (MSG satellites to address those issues (e.g., sensitivity reduction over arid and semi-arid regions; dependence on some meteorological clouds. Three massive dust events affecting Europe and the Mediterranean basin in May 2008/2010 are analysed in this work, using information provided by some independent and well-established aerosol products to assess the achieved results. The study shows that the proposed algorithm, christened eRSTDUST (i.e., enhanced RSTDUST, which provides qualitative information about dust outbreaks, is capable of increasing the trade-off between reliability and sensitivity. The results encourage further experimentations of this method in other periods of the year, also exploiting data provided by different satellite sensors, for better evaluating the advantages arising from the use of this dust detection technique in operational scenarios.

  2. Extracting impervious surfaces from multi-source satellite imagery based on unified conceptual model by decision tree algorithm

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Extraction of impervious surfaces is one of the necessary processes in urban change detection.This paper derived a unified conceptual model (UCM) from the vegetation-impervious surface-soil (VIS) model to make the extraction more effective and accurate.UCM uses the decision tree algorithm with indices of spectrum and texture,etc.In this model,we found both dependent and independent indices for multi-source satellite imagery according to their similarity and dissimilarity.The purpose of the indices is to remove the other land-use and land-cover types (e.g.,vegetation and soil) from the imagery,and delineate the impervious surfaces as the result.UCM has the same steps conducted by decision tree algorithm.The Landsat-5 TM image (30 m) and the Satellite Probatoire d’Observation de la Terre (SPOT-4) image (20 m) from Chaoyang District (Beijing) in 2007 were used in this paper.The results show that the overall accuracy in Landsat-5 TM image is 88%,while 86.75% in SPOT-4 image.It is an appropriate method to meet the demand of urban change detection.

  3. Multi-objective entropy evolutionary algorithm for marine oil spill detection using cosmo-skymed satellite data

    Directory of Open Access Journals (Sweden)

    M. Marghany

    2015-06-01

    Full Text Available Oil spill pollution has a substantial role in damaging the marine ecosystem. Oil spill that floats on top of water, as well as decreasing the fauna populations, affects the food chain in the ecosystem. In fact, oil spill is reducing the sunlight penetrates the water, limiting the photosynthesis of marine plants and phytoplankton. Moreover, marine mammals for instance, disclosed to oil spills their insulating capacities are reduced, and so making them more vulnerable to temperature variations and much less buoyant in the seawater. This study has demonstrated a design tool for oil spill detection in SAR satellite data using optimization of Entropy based Multi-Objective Evolutionary Algorithm (E-MMGA which based on Pareto optimal solutions. The study also shows that optimization entropy based Multi-Objective Evolutionary Algorithm provides an accurate pattern of oil slick in SAR data. This shown by 85 % for oil spill, 10 % look-alike and 5 % for sea roughness using the receiver-operational characteristics (ROC curve. The E-MMGA also shows excellent performance in SAR data. In conclusion, E-MMGA can be used as optimization for entropy to perform an automatic detection of oil spill in SAR satellite data.

  4. Experimental Demonstration of an Algorithm to Detect the Presence of a Parasitic Satellite

    Science.gov (United States)

    2003-03-01

    1-9 ACTEX · · · Advanced Controls Technology Experiment . . . . . . . . 2-2 ETS-VI · · · Engineering Test Satellite-VI...Technology Experiment ( ACTEX ), Stetson’s on-orbit ID work on NOAA-2 [33], and Wertz and Lee’s operational MOI estimation of the Cassini spacecraft. 2.1.2

  5. Cloud classification from satellite data using a fuzzy sets algorithm: A polar example

    Science.gov (United States)

    Key, J. R.; Maslanik, J. A.; Barry, R. G.

    1988-01-01

    Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine likely areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

  6. Cloud classification from satellite data using a fuzzy sets algorithm - A polar example

    Science.gov (United States)

    Key, J. R.; Maslanik, J. A.; Barry, R. G.

    1989-01-01

    Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine like areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

  7. Cloud classification from satellite data using a fuzzy sets algorithm - A polar example

    Science.gov (United States)

    Key, J. R.; Maslanik, J. A.; Barry, R. G.

    1989-01-01

    Where spatial boundaries between phenomena are diffuse, classification methods which construct mutually exclusive clusters seem inappropriate. The Fuzzy c-means (FCM) algorithm assigns each observation to all clusters, with membership values as a function of distance to the cluster center. The FCM algorithm is applied to AVHRR data for the purpose of classifying polar clouds and surfaces. Careful analysis of the fuzzy sets can provide information on which spectral channels are best suited to the classification of particular features, and can help determine like areas of misclassification. General agreement in the resulting classes and cloud fraction was found between the FCM algorithm, a manual classification, and an unsupervised maximum likelihood classifier.

  8. A New Algorithm for the Satellite-Based Retrieval of Solar Surface Irradiance in Spectral Bands

    Directory of Open Access Journals (Sweden)

    Annette Hammer

    2012-03-01

    Full Text Available Accurate solar surface irradiance data is a prerequisite for an efficient planning and operation of solar energy systems. Further, it is essential for climate monitoring and analysis. Recently, the demand on information about spectrally resolved solar surface irradiance has grown. As surface measurements are rare, satellite derived information with high accuracy might fill this gap. This paper describes a new approach for the retrieval of spectrally resolved solar surface irradiance from satellite data. The method combines a eigenvector-hybrid look-up table approach for the clear sky case with satellite derived cloud transmission (Heliosat method. The eigenvector LUT approach is already used to retrieve the broadband solar surface irradiance of data sets provided by the Climate Monitoring Satellite Application Facility (CM-SAF. This paper describes the extension of this approach to wavelength bands and the combination with spectrally resolved cloud transmission values derived with radiative transfer corrections of the broadband cloud transmission. Thus, the new approach is based on radiative transfer modeling and enables the use of extended information about the atmospheric state, among others, to resolve the effect of water vapor and ozone absorption bands. The method is validated with spectrally resolved measurements from two sites in Europe and by comparison with radiative transfer calculations. The validation results demonstrate the ability of the method to retrieve accurate spectrally resolved irradiance from satellites. The accuracy is in the range of the uncertainty of surface measurements, with exception of the UV and NIR ( ≥ 1200 nm part of the spectrum, where higher deviations occur.

  9. Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

    Science.gov (United States)

    Minnis, P.; Sun-Mack, S.; Bedka, K. M.; Yost, C. R.; Trepte, Q. Z.; Smith, W. L., Jr.; Painemal, D.; Chen, Y.; Palikonda, R.; Dong, X.; Xi, B.

    2016-01-01

    Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

  10. A DHIP Algorithm for SAR Satellite Imaging Planning%SAR卫星成像任务规划的DHIP方法

    Institute of Scientific and Technical Information of China (English)

    朱小满; 王钧; 李军; 景宁

    2011-01-01

    The emergence of earth observing satellite with Synthetic Aperture Radar (SAR) onboard provides a significant instrument to obtain geo-space information. This paper studies rightly on the SAR satellite imaging planning problem. Firstly, the general imaging process of SAR satellite is described to illustrate that the methods pertinent to optical satellite imaging planning are no longer suitable for the problem of a SAR satellite imaging planning. Secondly, the main influential constraints of SAR satellite are induced. Based on that, an approach called DHIP (Double Hierarchy Insert Planning) is proposed and described detailedly. The main idea of this method is to form an optimized scheme by tentatively inserting every candidate imaging request through two hierarchies, which are the hierarchy of SAR opening and closing, and that of photographing, by a checking while constructing method. The final experimental results show that the DHIP algorithm works fast and is able to get a satisfying scheme under general circumstances.%合成孔径雷达(SAR)卫星的出现为获取地球空间信息提供了重要手段,本文研究的即是SAR卫星成像任务规划问题.首先描述了SAR成像卫星的一般工作流程,说明针对可见光卫星进行成像任务规划的方法不再适用于SAR成像卫星任务规划;然后归纳了影响SAR卫星成像的主要约束.在此基础上,提出了双层插入规划(DHIP)方法,该方法将待规划任务在星载SAR开关机信息元组级和成像信息元组级两个层级上逐次进行试探性插入,采用边构造边检测的方法获得该问题的优化解.实验结果表明,该方法计算速度快,可以有效解决SAR卫星成像任务规划问题.

  11. Discrepant estimates of primary and export production from satellite algorithms, a biogeochemical model, and geochemical tracer measurements in the North Pacific Ocean

    Science.gov (United States)

    Palevsky, Hilary I.; Quay, Paul D.; Nicholson, David P.

    2016-08-01

    Estimates of primary and export production (PP and EP) based on satellite remote sensing algorithms and global biogeochemical models are widely used to provide year-round global coverage not available from direct observations. However, observational data to validate these approaches are limited. We find that no single satellite algorithm or model can reproduce seasonal and annual geochemically determined PP, export efficiency (EP/PP), and EP rates throughout the North Pacific basin, based on comparisons throughout the full annual cycle at time series stations in the subarctic and subtropical gyres and basin-wide regions sampled by container ship transects. The high-latitude regions show large PP discrepancies in winter and spring and strong effects of deep winter mixed layers on annual EP that cannot be accounted for in current satellite-based approaches. These results underscore the need to evaluate satellite- and model-based estimates using multiple productivity parameters measured over broad ocean regions throughout the annual cycle.

  12. Novel Algorithms for Retrieval of Hydrology and Ice Regimes of Middle-sized Inland Water Bodies from Satellite Altimetry

    Science.gov (United States)

    Troitskaya, Y. I.; Rybushkina, G. V.; Kuznetsova, A. M.; Baidakov, G. A.; Soustova, I.

    2014-12-01

    A novel method of regional adaptive re-tracking based on constructing a theoretical model describing the formation of telemetric waveforms by reflection from the piecewise constant model surface corresponding to the geography of the region is considered. The algorithm includes four consecutive steps: a) constructing a local piecewise model of a reflecting surface in the neighbourhood of the reservoir; b) solving a direct problem by calculating the reflected waveforms within the framework of the model; c) imposing restrictions and validity criteria for the algorithm based on waveform modelling; d) solving the inverse problem by retrieving a tracking point by the improved threshold algorithm. The results obtained on the basis of standard algorithm and method for adaptive re-tracking at Rybinsk , Gorky, Kuibyshev, Saratov and Volgograd reservoirs and middle-sized lakes of Russia: Chany, Segozero, Hanko, Onego, Beloye are compared to each other and to the field data of hydrological stations in reservoirs and lakes. The possibility of determination of significant wave height (SWH) in the lakes through a two-step adaptive retracking is investigated. Comparing results of retracting of SGDR data and ground measurements shows, that retrieving wave parameters in medium sized water bodies still meets difficulties. The direction of improvement of the existing algorithm is associated with comprehensive use of altimetry data, field studies and numerical modeling of high resolution. A simple method for timing of water freezing and ice break-up in lakes based on analysis of along-track dependencies of brightness temperatures at 18.7 and 34 GHz registered by microwave radiometer of altimetry satellite Jason-2. Comparison with in situ data of Russian Register of hydraulic structures on the example of reservoirs of the Volga River and the Don River confirms ability of the proposed method to determine quantitatively the freezing and break-up times for middle-sized inland water bodies.

  13. Validation of Two MODIS Aerosols Algorithms with SKYNET and Prospects for Future Climate Satellites Such as the GCOM-C/SGLI

    Directory of Open Access Journals (Sweden)

    Jules R. Dim

    2013-01-01

    Full Text Available Potential improvements of aerosols algorithms for future climate-oriented satellites such as the coming Global Change Observation Mission Climate/Second generation Global Imager (GCOM-C/SGLI are discussed based on a validation study of three years’ (2008–2010 daily aerosols properties, that is, the aerosol optical thickness (AOT and the Ångström exponent (AE retrieved from two MODIS algorithms. The ground-truth data used for this validation study are aerosols measurements from 3 SKYNET ground sites. The results obtained show a good agreement between the ground-truth data AOT and that of one of the satellites’ algorithms, then a systematic overestimation (around 0.2 by the other satellites’ algorithm. The examination of the AE shows a clear underestimation (by around 0.2–0.3 by both satellites’ algorithms. The uncertainties explaining these ground-satellites’ algorithms discrepancies are examined: the cloud contamination affects differently the aerosols properties (AOT and AE of both satellites’ algorithms due to the retrieval scale differences between these algorithms. The deviation of the real part of the refractive index values assumed by the satellites’ algorithms from that of the ground tends to decrease the accuracy of the AOT of both satellites’ algorithms. The asymmetry factor (AF of the ground tends to increase the AE ground-satellites discrepancies as well.

  14. A Leo Satellite Navigation Algorithm Based on GPS and Magnetometer Data

    Science.gov (United States)

    Deutschmann, Julie; Harman, Rick; Bar-Itzhack, Itzhack

    2001-01-01

    The Global Positioning System (GPS) has become a standard method for low cost onboard satellite orbit determination. The use of a GPS receiver as an attitude and rate sensor has also been developed in the recent past. Additionally, focus has been given to attitude and orbit estimation using the magnetometer, a low cost, reliable sensor. Combining measurements from both GPS and a magnetometer can provide a robust navigation system that takes advantage of the estimation qualities of both measurements. Ultimately, a low cost, accurate navigation system can result, potentially eliminating the need for more costly sensors, including gyroscopes. This work presents the development of a technique to eliminate numerical differentiation of the GPS phase measurements and also compares the use of one versus two GPS satellites.

  15. Ozone ProfilE Retrieval Algorithm for nadir-looking satellite instruments in the UV-VIS

    Directory of Open Access Journals (Sweden)

    J. C. A. van Peet

    2013-10-01

    Full Text Available For the retrieval of the vertical distribution of ozone in the atmosphere the Ozone ProfilE Retrieval Algorithm (OPERA has been further developed. The new version (1.26 of OPERA is capable of retrieving ozone profiles from UV-VIS observations of most nadir looking satellite instruments like GOME, SCIAMACHY, OMI and GOME-2. The set-up of OPERA is described and results are presented for GOME and GOME-2 observations. The retrieved ozone profiles are globally compared to ozone sondes for the year 1997 and 2008. Relative differences between GOME/GOME-2 and ozone sondes are within the limits as specified by the user requirements from the Climate Change Initiative (CCI program of ESA. To demonstrate the performance of the algorithm under extreme circumstances the 2009 Antarctic ozone hole season was investigated in more detail using GOME-2 ozone profiles and lidar data, which showed an unusual persistence of the vortex over the Río Gallegos observing station (51° S, 69.3° W. By applying OPERA to multiple instruments a timeseries of ozone profiles from 1996 to 2013 from a single robust algorithm can be created.

  16. SeaWiFS Technical Report Series. Volume 42; Satellite Primary Productivity Data and Algorithm Development: A Science Plan for Mission to Planet Earth

    Science.gov (United States)

    Falkowski, Paul G.; Behrenfeld, Michael J.; Esaias, Wayne E.; Balch, William; Campbell, Janet W.; Iverson, Richard L.; Kiefer, Dale A.; Morel, Andre; Yoder, James A.; Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor)

    1998-01-01

    Two issues regarding primary productivity, as it pertains to the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Program and the National Aeronautics and Space Administration (NASA) Mission to Planet Earth (MTPE) are presented in this volume. Chapter 1 describes the development of a science plan for deriving primary production for the world ocean using satellite measurements, by the Ocean Primary Productivity Working Group (OPPWG). Chapter 2 presents discussions by the same group, of algorithm classification, algorithm parameterization and data availability, algorithm testing and validation, and the benefits of a consensus primary productivity algorithm.

  17. A geostationary longitude acquisition planning algorithm. [for maneuver planning of geosynchronous satellites

    Science.gov (United States)

    Petruzzo, C. J.; Bryant, W. C., Jr.; Nickerson, K. G.

    1977-01-01

    The paper is concerned with the phase of the geosynchronous mission termed station acquisition, which involves the maneuvering of a spacecraft to its geostationary longitude by means of the spacecraft propulsion system. An algorithm which assists in maneuver planning is described, and examples of its use are presented. The algorithm can be applied when sequences of more than three maneuvers are to be expected. While, in general, three maneuvers are sufficient to achieve the desired end conditions when orbital mechanics are the only consideration, operational considerations may add constraints resulting in an increased number of maneuvers required.

  18. 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.

  19. A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

    Science.gov (United States)

    Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

    2016-06-01

    There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

  20. LEO星座网络动态源路由算法%Dynamic Source Routing Algorithm for LEO Satellite Networks

    Institute of Scientific and Technical Information of China (English)

    万鹏; 曹志刚; 王京林

    2007-01-01

    近年来,在低轨(LEO)卫星星座通信网络中采用网际协议(IP)路由算法的研究已经取得了一系列进展,文章论述了LEO星座通信网络的特点、拓扑结构和虚拟节点策略.在此基础上提出了基于泛洪路由的LEO星座动态源路由算法DSR-LSN(Dynamic Source Routing algorithm in LEO Satellite Networks),星座网络仿真表明,DSR-LSN算法具有网络路由状态稳定性好、时延小的优点.

  1. Estimation of net surface shortwave radiation over the tropical Indian Ocean using geostationary satellite observations: Algorithm and validation

    Science.gov (United States)

    Shahi, Naveen R.; Thapliyal, Pradeep K.; Sharma, Rashmi; Pal, Pradip K.; Sarkar, Abhijit

    2011-09-01

    This paper presents the development of a methodology to estimate the net surface shortwave radiation (SWR) over tropical oceans using half-hourly geostationary satellite estimates of outgoing longwave radiation (OLR). The collocated data set of SWR measured at 13 buoy locations over the Indian Ocean and a Meteosat-derived OLR for the period of 2002-2009 have been used to derive an empirical relationship. The information from the solar zenith angle that determines the amount of solar radiation received at a particular location is used to normalize the SWR to nadir observation in order to make the empirical relationship location independent. As the relationship between SWR and OLR is valid mostly over the warm-pool regions, the present study restricts SWR estimation in the tropical Indian Ocean domain (30°E-110°E, 30°S-30°N). The SWR estimates are validated with an independent collocated data set and subsequently compared with the SWR estimates from the Global Energy and Water Cycle Experiment-Surface Radiation Budget V3.0 (GEWEX-SRB), International Satellite Cloud Climatology Project-Flux Data (ISCCP-FD), and National Centers for Environmental Prediction (NCEP) reanalysis for the year 2007. The present algorithm provides significantly better accuracy of SWR estimates, with a root-mean-square error of 27.3 W m-2 as compared with the values of 32.7, 37.5, and 59.6 W m-2 obtained from GEWEX-SRB, ISCCP-FD, and NCEP, respectively. The present algorithm also provides consistently better SWR compared with other available products under different sky conditions and seasons over Indian Ocean warm-pool regions.

  2. 最大熵算法在气象雨量预测中的应用分析%Application of Maximum Entropy Algorithm Meteorological Rainfall Prediction

    Institute of Scientific and Technical Information of China (English)

    王海燕

    2014-01-01

    将最大熵原理的计算方法应用到气象雨量预测中,通过有效的仿真实验能够证明最大熵方法在气象雨量预测中的可行性。%The calculation of the maximum entropy principle is applied to the weather forecast rainfall through effective simulation experiment to prove the feasibility of the maximum entropy method of meteorological rainfall prediction.

  3. Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

    Science.gov (United States)

    Marghany, Maged

    2016-10-01

    In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiveroperating characteristic (ROC) curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

  4. Automatic Mexico Gulf Oil Spill Detection from Radarsat-2 SAR Satellite Data Using Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Marghany Maged

    2016-10-01

    Full Text Available In this work, a genetic algorithm is exploited for automatic detection of oil spills of small and large size. The route is achieved using arrays of RADARSAT-2 SAR ScanSAR Narrow single beam data obtained in the Gulf of Mexico. The study shows that genetic algorithm has automatically segmented the dark spot patches related to small and large oil spill pixels. This conclusion is confirmed by the receiver-operating characteristic (ROC curve and ground data which have been documented. The ROC curve indicates that the existence of oil slick footprints can be identified with the area under the curve between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. The small oil spill sizes represented 30% of the discriminated oil spill pixels in ROC curve. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills of either small or large size and the ScanSAR Narrow single beam mode serves as an excellent sensor for oil spill patterns detection and surveying in the Gulf of Mexico.

  5. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations

    Science.gov (United States)

    We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop si...

  6. Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations

    Science.gov (United States)

    We analyzed 10 established and 4 new satellite reflectance algorithms for estimating chlorophyll-a (Chl-a) in a temperate reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense water truth collected within one hour of image acquisition to develop si...

  7. A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

    Directory of Open Access Journals (Sweden)

    Byongjun Hwang

    2017-07-01

    Full Text Available In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover

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

    Science.gov (United States)

    Adler, Robert; Hong, Yang; Huffman, George

    2007-01-01

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

  9. User-oriented data acquisition chain task planning algorithm for operationally responsive space satellite

    Institute of Scientific and Technical Information of China (English)

    Hao Chen; Jun Li; Ning Jing

    2016-01-01

    With the development of operational y responsive space (ORS) and on-board processing techniques, the end users can receive the observation data from the ORS satel ite directly. To satisfy the demand for reducing the requirements-tasking-effects cycle from one day to hours, the various resources of the whole data acquisition chain (including satel ites, ground stations, data processing centers, users, etc.) should be taken into an overal consideration, and the traditional batch task planning mode should be transformed into the user-oriented task planning mode. Con-sidering there are many approaches for data acquisition due to the new techniques of ORS satel ite, the data acquisition chain task planning problem for ORS satel ite can be seen as the multi-modal route planning problem. Thereby, a framework is presented using label-constrained shortest path technique with the conflict resolution. To apply this framework to solve the ORS satel ite task planning problem, the preprocessing and the conflict resolution strategies are discussed in detail. Based on the above work, the user-oriented data acquisition chain task planning algorithm for ORS satel ite is proposed. The exact solution can be obtained in polynomial time using the proposed algorithm. The simulation experiments validate the feasibility and the adaptability of the pro-posed approach.

  10. 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

  11. 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

  12. Improving a DWT-based compression algorithm for high image-quality requirement of satellite images

    Science.gov (United States)

    Thiebaut, Carole; Latry, Christophe; Camarero, Roberto; Cazanave, Grégory

    2011-10-01

    Past and current optical Earth observation systems designed by CNES are using a fixed-rate data compression processing performed at a high-rate in a pushbroom mode (also called scan-based mode). This process generates fixed-length data to the mass memory and data downlink is performed at a fixed rate too. Because of on-board memory limitations and high data rate processing needs, the rate allocation procedure is performed over a small image area called a "segment". For both PLEIADES compression algorithm and CCSDS Image Data Compression recommendation, this rate allocation is realised by truncating to the desired rate a hierarchical bitstream of coded and quantized wavelet coefficients for each segment. Because the quantisation induced by truncation of the bit planes description is the same for the whole segment, some parts of the segment have a poor image quality. These artefacts generally occur in low energy areas within a segment of higher level of energy. In order to locally correct these areas, CNES has studied "exceptional processing" targeted for DWT-based compression algorithms. According to a criteria computed for each part of the segment (called block), the wavelet coefficients can be amplified before bit-plane encoding. As usual Region of Interest handling, these multiplied coefficients will be processed earlier by the encoder than in the nominal case (without exceptional processing). The image quality improvement brought by the exceptional processing has been confirmed by visual image analysis and fidelity criteria. The complexity of the proposed improvement for on-board application has also been analysed.

  13. 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.

  14. A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE for Satellite-Based Actual Evapotranspiration Estimation

    Directory of Open Access Journals (Sweden)

    Hua Zhang

    2016-09-01

    Full Text Available The estimation of spatially-variable actual evapotranspiration (AET is a critical challenge to regional water resources management. We propose a new remote sensing method, the Triangle Algorithm with Variable Edges (TAVE, to generate daily AET estimates based on satellite-derived land surface temperature and the vegetation index NDVI. The TAVE captures heterogeneity in AET across elevation zones and permits variability in determining local values of wet and dry end-member classes (known as edges. Compared to traditional triangle methods, TAVE introduces three unique features: (i the discretization of the domain as overlapping elevation zones; (ii a variable wet edge that is a function of elevation zone; and (iii variable values of a combined-effect parameter (that accounts for aerodynamic and surface resistance, vapor pressure gradient, and soil moisture availability along both wet and dry edges. With these features, TAVE effectively addresses the combined influence of terrain and water stress on semi-arid environment AET estimates. We demonstrate the effectiveness of this method in one of the driest countries in the world—Jordan, and compare it to a traditional triangle method (TA and a global AET product (MOD16 over different land use types. In irrigated agricultural lands, TAVE matched the results of the single crop coefficient model (−3%, in contrast to substantial overestimation by TA (+234% and underestimation by MOD16 (−50%. In forested (non-irrigated, water consuming regions, TA and MOD16 produced AET average deviations 15.5 times and −3.5 times of those based on TAVE. As TAVE has a simple structure and low data requirements, it provides an efficient means to satisfy the increasing need for evapotranspiration estimation in data-scarce semi-arid regions. This study constitutes a much needed step towards the satellite-based quantification of agricultural water consumption in Jordan.

  15. Retrieval algorithm for densities of mesospheric and lower thermospheric metal and ion species from satellite borne limb emission signals

    Science.gov (United States)

    Langowski, M.; Sinnhuber, M.; Aikin, A. C.; von Savigny, C.; Burrows, J. P.

    2013-05-01

    Meteoroids bombard the earth's atmosphere during its orbit around the sun, depositing a highly varying and significant amount of matter into the thermosphere and mesosphere. The strength of the material source needs to be characterized and its impact on atmospheric chemistry assessed. In this study an algorithm for the retrieval of metal and metal ion number densities for a two-dimensional (latitude, altitude) grid is described and explained. Dayglow emission spectra of the mesosphere and lower thermosphere are used, which are obtained by passive satellite remote sensing with the SCIAMACHY instrument on Envisat. The limb scans cover the tangent altitude range from 50 to 150 km. Metals and metal ions are strong emitters in this region and form sharply peaked layers with a FWHM of several 10 km in the mesosphere and lower thermosphere with peak altitudes between 90 to 110 km. The emission signal is first separated from the background signal, arising from Rayleigh and Raman scattering of solar radiation by air molecules. A forward radiative transfer model calculating the slant column density (SCD) from a given vertical distribution was developed. This non-linear model is inverted in an iterative procedure to yield the vertical profiles for the emitting species. Several constraints are applied to the solution, for numerical stability reasons and to get physically reasonable solutions. The algorithm is applied to SCIAMACHY limb-emission observations for the retrieval of Mg and Mg+ using emission signatures at 285.2 and 279.6/280.4 nm, respectively. Results are presented for these three lines as well as error estimations and sensitivity tests on different constraint strength and different separation approaches for the background signal.

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

    Institute of Scientific and Technical Information of China (English)

    蒋卫国; 侯鹏; 朱晓华; 曹广真; 刘小曼; 曹入尹

    2011-01-01

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

  17. Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

    Science.gov (United States)

    Adler, Robert; Hong, Yang; Huffman, George

    2007-01-01

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

  18. 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

  19. 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.

  20. Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis)

    Science.gov (United States)

    Carvalho, Gustavo A.; Minnett, Peter J.; Fleming, Lora E.; Banzon, Viva F.; Baringer, Warner

    2010-01-01

    In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods – July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104 cells l−1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs. PMID:21037979

  1. Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis).

    Science.gov (United States)

    Carvalho, Gustavo A; Minnett, Peter J; Fleming, Lora E; Banzon, Viva F; Baringer, Warner

    2010-06-01

    In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods - July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×10(4) cells l(-1) defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs.

  2. 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.

  3. A Beam Tracking Algorithm Based on Satellite Beacon Signals for Phased Array in Mobile Satellite Communications%一种基于信标的移动卫通相控阵波束跟踪算法

    Institute of Scientific and Technical Information of China (English)

    陈鹏; 张慧

    2012-01-01

    In this paper a beam tracking algorithm based on satellite beacon signals is proposed and realized. The method is suitable for all kinds of phased array type mobile satellite communication antennas. It overcomes the difficulty of detecting the extremely weak satellite beacon signals and then the tracking performance is greatly improved. The highlight of the algorithm is the beam tracking process can be run without the help of gyroscopes and thus improves the survivability in the extreme environments. The algorithm was implemented and verified in a Ku band phased array mobile satellite antenna.%提出并实现了一种利用卫星信标信号来实施基于相控阵天线的波束跟踪算法。该方法适用于采用相控阵天线技术的各种卫星“动中通”天线,克服了卫星信标信号强度弱,检测困难的弱点,提高了跟踪信噪比,同时采用了软件无线电方式解调可以提供最大的灵活性。跟踪算法的最大优点是没有任何陀螺仪的辅助,极大地提高了天线在各种极端运动环境下的适应能力。算法最终在自行研制的Ku波段相控阵移动卫星天线系统上获得验证。

  4. Lessons Learned from the Deployment and Integration of a Microwave Sounder Based Tropical Cyclone Intensity and Surface Wind Estimation Algorithm into NOAA/NESDIS Satellite Product Operations

    Science.gov (United States)

    Longmore, S. P.; Knaff, J. A.; Schumacher, A.; Dostalek, J.; DeMaria, R.; Chirokova, G.; Demaria, M.; Powell, D. C.; Sigmund, A.; Yu, W.

    2014-12-01

    The Colorado State University (CSU) Cooperative Institute for Research in the Atmosphere (CIRA) has recently deployed a tropical cyclone (TC) intensity and surface wind radii estimation algorithm that utilizes Suomi National Polar-orbiting Partnership (S-NPP) satellite Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit (AMSU) from the NOAA18, NOAA19 and METOPA polar orbiting satellites for testing, integration and operations for the Product System Development and Implementation (PSDI) projects at NOAA's National Environmental Satellite, Data, and Information Service (NESDIS). This presentation discusses the evolution of the CIRA NPP/AMSU TC algorithms internally at CIRA and its migration and integration into the NOAA Data Exploitation (NDE) development and testing frameworks. The discussion will focus on 1) the development cycle of internal NPP/AMSU TC algorithms components by scientists and software engineers, 2) the exchange of these components into the NPP/AMSU TC software systems using the subversion version control system and other exchange methods, 3) testing, debugging and integration of the NPP/AMSU TC systems both at CIRA/NESDIS and 4) the update cycle of new releases through continuous integration. Lastly, a discussion of the methods that were effective and those that need revision will be detailed for the next iteration of the NPP/AMSU TC system.

  5. Long-term analysis of aerosol optical depth over Northeast Asia using a satellite-based measurement: MI Yonsei Aerosol Retrieval Algorithm (YAER)

    Science.gov (United States)

    Kim, Mijin; Kim, Jhoon; Yoon, Jongmin; Chung, Chu-Yong; Chung, Sung-Rae

    2017-04-01

    In 2010, the Korean geostationary earth orbit (GEO) satellite, the Communication, Ocean, and Meteorological Satellite (COMS), was launched including the Meteorological Imager (MI). The MI measures atmospheric condition over Northeast Asia (NEA) using a single visible channel centered at 0.675 μm and four IR channels at 3.75, 6.75, 10.8, 12.0 μm. The visible measurement can also be utilized for the retrieval of aerosol optical properties (AOPs). Since the GEO satellite measurement has an advantage for continuous monitoring of AOPs, we can analyze the spatiotemporal variation of the aerosol using the MI observations over NEA. Therefore, we developed an algorithm to retrieve aerosol optical depth (AOD) using the visible observation of MI, and named as MI Yonsei Aerosol Retrieval Algorithm (YAER). In this study, we investigated the accuracy of MI YAER AOD by comparing the values with the long-term products of AERONET sun-photometer. The result showed that the MI AODs were significantly overestimated than the AERONET values over bright surface in low AOD case. Because the MI visible channel centered at red color range, contribution of aerosol signal to the measured reflectance is relatively lower than the surface contribution. Therefore, the AOD error in low AOD case over bright surface can be a fundamental limitation of the algorithm. Meanwhile, an assumption of background aerosol optical depth (BAOD) could result in the retrieval uncertainty, also. To estimate the surface reflectance by considering polluted air condition over the NEA, we estimated the BAOD from the MODIS dark target (DT) aerosol products by pixel. The satellite-based AOD retrieval, however, largely depends on the accuracy of the surface reflectance estimation especially in low AOD case, and thus, the BAOD could include the uncertainty in surface reflectance estimation of the satellite-based retrieval. Therefore, we re-estimated the BAOD using the ground-based sun-photometer measurement, and

  6. 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

  7. 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

  8. Improving radar rainfall estimation by merging point rainfall measurements within a model combination framework

    Science.gov (United States)

    Hasan, Mohammad Mahadi; Sharma, Ashish; Mariethoz, Gregoire; Johnson, Fiona; Seed, Alan

    2016-11-01

    While the value of correcting raw radar rainfall estimates using simultaneous ground rainfall observations is well known, approaches that use the complete record of both gauge and radar measurements to provide improved rainfall estimates are much less common. We present here two new approaches for estimating radar rainfall that are designed to address known limitations in radar rainfall products by using a relatively long history of radar reflectivity and ground rainfall observations. The first of these two approaches is a radar rainfall estimation algorithm that is nonparametric by construction. Compared to the traditional gauge adjusted parametric relationship between reflectivity (Z) and ground rainfall (R), the suggested new approach is based on a nonparametric radar rainfall estimation method (NPR) derived using the conditional probability distribution of reflectivity and gauge rainfall. The NPR method is applied to the densely gauged Sydney Terrey Hills radar network, where it reduces the RMSE in rainfall estimates by 10%, with improvements observed at 90% of the gauges. The second of the two approaches is a method to merge radar and spatially interpolated gauge measurements. The two sources of information are combined using a dynamic combinatorial algorithm with weights that vary in both space and time. The weight for any specific period is calculated based on the error covariance matrix that is formulated from the radar and spatially interpolated rainfall errors of similar reflectivity periods in a cross-validation setting. The combination method reduces the RMSE by about 20% compared to the traditional Z-R relationship method, and improves estimates compared to spatially interpolated point measurements in sparsely gauged areas.

  9. 基于OPNET的卫星路由查找算法仿真分析%Simulation Analysis of Satellite Routing Lookup Algorithm Based on OPNET

    Institute of Scientific and Technical Information of China (English)

    邓全才; 张连连; 孙志田

    2015-01-01

    为了更加直观的比较线性表算法、Trie tree算法以及 Hash算法在卫星路由查找的性能,通过 OPNET平台进行建模仿真。实验结果表明,三种算法路由查询次数相同。如果以访问次数为标准,选择Trie tree算法为宜。如果以查询深度为标准,选择 Trie tree算法为宜。如果以响应时间为标准,由于 Hash算法不稳定,选择线性表算法和 Trie tree算法为宜。因此实验结论为,Trie tree算法总体性能最佳,但算法实现比较复杂,Hash算法不稳定,但对规则的增减比较容易,线性表算法易于实现,但访问次数较高。%For a more intuitive comparison of the Linear list algorithm,Trie tree algorithm and Hash al-gorithm performance in the satellite route lookup,OPNET platform is used for modeling and sim-ulation.The experimental results show that Experimental results show that the three algorithms the number of route query is the same.If the number of visits as a standard,select the Trie tree al-gorithm is appropriate.If the query depth as a standard,select the Trie tree algorithm is appropri-ate.If the response time as a standard.If the response time for the standard,the Hash algorithm is not stable,the selection of linear table algorithm and Trie tree algorithm is appropriate.There-fore,the experimental conclusions is that Trie tree algorithm is the best overall performance,but the algorithm is more complex,Hash algorithm is not stable,but the rules change easier,Linear list is easy to achieve,but the algorithm has a high number of visits.

  10. Adaptive re-tracking algorithm for retrieval of water level variations and wave heights from satellite altimetry data for middle-sized inland water bodies

    Science.gov (United States)

    Troitskaya, Yuliya; Lebedev, Sergey; Soustova, Irina; Rybushkina, Galina; Papko, Vladislav; Baidakov, Georgy; Panyutin, Andrey

    One of the recent applications of satellite altimetry originally designed for measurements of the sea level [1] is associated with remote investigation of the water level of inland waters: lakes, rivers, reservoirs [2-7]. The altimetry data re-tracking algorithms developed for open ocean conditions (e.g. Ocean-1,2) [1] often cannot be used in these cases, since the radar return is significantly contaminated by reflection from the land. The problem of minimization of errors in the water level retrieval for inland waters from altimetry measurements can be resolved by re-tracking satellite altimetry data. Recently, special re-tracking algorithms have been actively developed for re-processing altimetry data in the coastal zone when reflection from land strongly affects echo shapes: threshold re-tracking, The other methods of re-tracking (threshold re-tracking, beta-re-tracking, improved threshold re-tracking) were developed in [9-11]. The latest development in this field is PISTACH product [12], in which retracking bases on the classification of typical forms of telemetric waveforms in the coastal zones and inland water bodies. In this paper a novel method of regional adaptive re-tracking based on constructing a theoretical model describing the formation of telemetric waveforms by reflection from the piecewise constant model surface corresponding to the geography of the region is considered. It was proposed in [13, 14], where the algorithm for assessing water level in inland water bodies and in the coastal zone of the ocean with an error of about 10-15 cm was constructed. The algorithm includes four consecutive steps: - constructing a local piecewise model of a reflecting surface in the neighbourhood of the reservoir; - solving a direct problem by calculating the reflected waveforms within the framework of the model; - imposing restrictions and validity criteria for the algorithm based on waveform modelling; - solving the inverse problem by retrieving a tracking point

  11. 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.

  12. Classification of textures in satellite image with Gabor filters and a multi layer perceptron with back propagation algorithm obtaining high accuracy

    Directory of Open Access Journals (Sweden)

    Adriano Beluco, Paulo M. Engel, Alexandre Beluco

    2015-01-01

    Full Text Available The classification of images, in many cases, is applied to identify an alphanumeric string, a facial expression or any other characteristic. In the case of satellite images is necessary to classify all the pixels of the image. This article describes a supervised classification method for remote sensing images that integrates the importance of attributes in selecting features with the efficiency of artificial neural networks in the classification process, resulting in high accuracy for real images. The method consists of a texture segmentation based on Gabor filtering followed by an image classification itself with an application of a multi layer artificial neural network with a back propagation algorithm. The method was first applied to a synthetic image, like training, and then applied to a satellite image. Some results of experiments are presented in detail and discussed. The application of the method to the synthetic image resulted in the identification of 89.05% of the pixels of the image, while applying to the satellite image resulted in the identification of 85.15% of the pixels. The result for the satellite image can be considered a result of high accuracy.

  13. 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

  14. Resolving SSM/I-Ship Radar Rainfall Discrepancies from AIP-3

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The third algorithm intercomparison project (AIP-3) involved rain estimates from more than 50satellite rainfall algorithms and ground radar measurements within the Intensive Flux Array (IFA) over the equatorial western Pacific warm pool region during the Tropical Ocean Global Atmosphere coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Early results indicated that there was a systematic bias between rainrates from satellite passive microwave and ground radar measurements. The mean rainrate from radar measurements is about 50% underestimated compared to that from passive microwave-based retrieval algorithms. This paper is designed to analyze rain patterns from the Florida State University rain retrieval algorithm and radar measurements to understand physically the rain discrepancies. Results show that there is a clear range-dependent bias associated with the radar measurements.However, this range-dependent systematical bias is almost eliminated with the corrected radar rainrates.Results suggest that the effects from radar attenuation correction, calibration and beam filling are the major sources of rain discrepancies. This study demonstrates that rain retrievals based on satellite measurements from passive microwave radiometers such as the Special Sensor of Microwave Imager (SSM/I)are reliable, while rain estimates from ground radar measurements are correctable.

  15. Comparison of ground-based FTIR and Brewer O3 total column with data from two different IASI algorithms and from OMI and GOME-2 satellite instruments

    Directory of Open Access Journals (Sweden)

    T. Blumenstock

    2011-03-01

    Full Text Available An intercomparison of ozone total column measurements derived from various platforms is presented in this work. Satellite data from Infrared Atmospheric Sounding Interferometer (IASI, Ozone Monitoring Instrument (OMI and Global Ozone Monitoring Experiment (GOME-2 are compared with data from two ground-based spectrometers (Fourier Transform Infrared spectrometer FTIR and Brewer, located at the Network for Detection of Atmospheric Composition Change (NDACC super-site of Izaña (Tenerife, measured during a campaign from March to June 2009. These ground-based observing systems have already been demonstrated to perform consistent, precise and accurate ozone total column measurements. An excellent agreement between ground-based and OMI/GOME-2 data is observed. Results from two different algorithms for deriving IASI ozone total column are also compared: the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT/ESA operational algorithm and the LISA (Laboratoire Inter-universitaire des Systèmes Atmosphériques algorithm. A better agreement was found with LISA's analytical approach based on an altitude-dependent Tikhonov-Philips regularization: correlations are 0.94 and 0.89 compared to FTIR and Brewer, respectively; while the operational IASI ozone columns (based on neural network analysis show correlations of 0.90 and 0.85, respectively, compared to the O3 columns obtained from FTIR and Brewer.

  16. A new iterative algorithm for geolocating a known altitude target using TDOA and FDOA measurements in the presence of satellite location uncertainty

    Institute of Scientific and Technical Information of China (English)

    Cao Yalu; Peng Li; Li Jinzhou; Yang Le; Guo Fucheng

    2015-01-01

    This paper considers the problem of geolocating a target on the Earth surface whose altitude is known previously using the target signal time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements obtained at satellites. The number of satellites available for the geolocation task is more than sufficient and their locations are subject to random errors. This paper derives the constrained Crame´ r-Rao lower bound (CCRLB) of the target position, and on the basis of the CCRLB analysis, an approximately efficient constrained maximum likelihood estimator (CMLE) for geolocating the target is established. A new iterative algorithm for solving the CMLE is then proposed, where the updated target position estimate is shown to be the globally optimal solu-tion to a generalized trust region sub-problem (GTRS) which can be found via a simple bisection search. First-order mean square error (MSE) analysis is conducted to quantify the performance degradation when the known target altitude is assumed to be precise but indeed has an unknown but deterministic error. Computer simulations are used to compare the performance of the proposed iterative geolocation technique with those of two benchmark algorithms. They verify the approximate efficiency of the proposed algorithm and the validity of the MSE analysis.

  17. A new iterative algorithm for geolocating a known altitude target using TDOA and FDOA measurements in the presence of satellite location uncertainty

    Directory of Open Access Journals (Sweden)

    Cao Yalu

    2015-10-01

    Full Text Available This paper considers the problem of geolocating a target on the Earth surface whose altitude is known previously using the target signal time difference of arrival (TDOA and frequency difference of arrival (FDOA measurements obtained at satellites. The number of satellites available for the geolocation task is more than sufficient and their locations are subject to random errors. This paper derives the constrained Cramér-Rao lower bound (CCRLB of the target position, and on the basis of the CCRLB analysis, an approximately efficient constrained maximum likelihood estimator (CMLE for geolocating the target is established. A new iterative algorithm for solving the CMLE is then proposed, where the updated target position estimate is shown to be the globally optimal solution to a generalized trust region sub-problem (GTRS which can be found via a simple bisection search. First-order mean square error (MSE analysis is conducted to quantify the performance degradation when the known target altitude is assumed to be precise but indeed has an unknown but deterministic error. Computer simulations are used to compare the performance of the proposed iterative geolocation technique with those of two benchmark algorithms. They verify the approximate efficiency of the proposed algorithm and the validity of the MSE analysis.

  18. Global clear-sky surface skin temperature from multiple satellites using a single-channel algorithm with angular anisotropy corrections

    Science.gov (United States)

    Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

    2017-01-01

    Surface skin temperature (Ts) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve Ts over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of Ts over the diurnal cycle in non-polar regions, while polar Ts retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed Ts, along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly Ts observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived Ts data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, Ts validation with established references is essential, as is proper evaluation of Ts sensitivity to atmospheric correction source.This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based Ts product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve satellite LST retrievals. Application of the anisotropic correction

  19. Global Clear-Sky Surface Skin Temperature from Multiple Satellites Using a Single-Channel Algorithm with Angular Anisotropy Corrections

    Science.gov (United States)

    Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

    2017-01-01

    Surface skin temperature (T(sub s)) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve T(sub s) over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of T(sub s) over the diurnal cycle in non-polar regions, while polar T(sub s) retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed T(sub s), along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly T(sub s) observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived T(sub s) data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, T(sub s) validation with established references is essential, as is proper evaluation of T(sub s) sensitivity to atmospheric correction source. This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based T(sub s) product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve

  20. 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%.

  1. 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.

  2. Long-term evaluation of three satellite ocean color algorithms for identifying harmful algal blooms (Karenia brevis) along the west coast of Florida: A matchup assessment.

    Science.gov (United States)

    Carvalho, Gustavo A; Minnett, Peter J; Banzon, Viva F; Baringer, Warner; Heil, Cynthia A

    2011-01-17

    We present a simple algorithm to identify Karenia brevis blooms in the Gulf of Mexico along the west coast of Florida in satellite imagery. It is based on an empirical analysis of collocated matchups of satellite and in situ measurements. The results of this Empirical Approach is compared to those of a Bio-optical Technique - taken from the published literature - and the Operational Method currently implemented by the NOAA Harmful Algal Bloom Forecasting System for K. brevis blooms. These three algorithms are evaluated using a multi-year MODIS data set (from July, 2002 to October, 2006) and a long-term in situ database. Matchup pairs, consisting of remotely-sensed ocean color parameters and near-coincident field measurements of K. brevis concentration, are used to assess the accuracy of the algorithms. Fair evaluation of the algorithms was only possible in the central west Florida shelf (i.e. between 25.75°N and 28.25°N) during the boreal Summer and Fall months (i.e. July to December) due to the availability of valid cloud-free matchups. Even though the predictive values of the three algorithms are similar, the statistical measure of success in red tide identification (defined as cell counts in excess of 1.5 × 10(4) cells L(-1)) varied considerably (sensitivity-Empirical: 86%; Bio-optical: 77%; Operational: 26%), as did their effectiveness in identifying non-bloom cases (specificity-Empirical: 53%; Bio-optical: 65%; Operational: 84%). As the Operational Method had an elevated frequency of false-negative cases (i.e. presented low accuracy in detecting known red tides), and because of the considerable overlap between the optical characteristics of the red tide and non-bloom population, only the other two algorithms underwent a procedure for further inspecting possible detection improvements. Both optimized versions of the Empirical and Bio-optical algorithms performed similarly, being equally specific and sensitive (~70% for both) and showing low levels of

  3. Rainfall measurement from the opportunistic use of an Earth–space link in the Ku band

    Directory of Open Access Journals (Sweden)

    L. Barthès

    2013-08-01

    Full Text Available The present study deals with the development of a low-cost microwave device devoted to the measurement of average rain rates observed along Earth–satellite links, the latter being characterized by a tropospheric path length of a few kilometres. The ground-based power measurements, which are made using the Ku-band television transmissions from several different geostationary satellites, are based on the principle that the atmospheric attenuation produced by rain encountered along each transmission path can be used to determine the path-averaged rain rate. This kind of device could be very useful in hilly areas where radar data are not available or in urban areas where such devices could be directly placed in homes by using residential TV antenna. The major difficulty encountered with this technique is that of retrieving rainfall characteristics in the presence of many other causes of received signal fluctuation, produced by atmospheric scintillation, variations in atmospheric composition (water vapour concentration, cloud water content or satellite transmission parameters (variations in emitted power, satellite pointing. In order to conduct a feasibility study with such a device, a measurement campaign was carried out over a period of five months close to Paris. The present paper proposes an algorithm based on an artificial neural network, used to identify dry and rainy periods and to model received signal variability resulting from effects not related to rain. When the altitude of the rain layer is taken into account, the rain attenuation can be inverted to obtain the path-averaged rain rate. The rainfall rates obtained from this process are compared with co-located rain gauges and radar measurements taken throughout the full duration of the campaign, and the most significant rainfall events are analysed.

  4. About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm

    Directory of Open Access Journals (Sweden)

    François Peyret

    2013-01-01

    Full Text Available Reliable GPS positioning in city environment is a key issue: actually, signals are prone to multipath, with poor satellite geometry in many streets. Using a 3D urban model to forecast satellite visibility in urban contexts in order to improve GPS localization is the main topic of the present article. A virtual image processing that detects and eliminates possible faulty measurements is the core of this method. This image is generated using the position estimated a priori by the navigation process itself, under road constraints. This position is then updated by measurements to line-of-sight satellites only. This closed-loop real-time processing has shown very first promising full-scale test results.

  5. 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.

  6. Investigation of Lake Water Salinity by Using Four-Band Salinity Algorithm on WorldView-2 Satellite Image for a Saline Industrial Lake

    Science.gov (United States)

    Budakoǧlu, Murat; Karaman, Muhittin; Damla Uça Avcı, Z.; Kumral, Mustafa; Geredeli (Yılmaz), Serpil

    2014-05-01

    Salinity of a lake is an important characteristic since, these are potentially industrial lakes and the degree of salinity can significantly be used for determination of mineral resources and for the production management. In the literature, there are many studies of using satellite data for salinity related lake studies such as determination of salinity distribution and detection of potential freshwater sources in less salt concentrated regions. As the study area Lake Acigol, located in Denizli (Turkey) was selected. With it's saline environment, it's the major sodium sulphate production resource of Turkey. In this study, remote sensing data and data from a field study was used and correlated. Remote sensing is an efficient tool to monitor and analyze lake properties by using it complementary to field data. Worldview-2 satellite data was used in this study which consists of 8 bands. At the same time with the satellite data acquisition, a field study was conducted to collect the salinity values in 17 points of the laker with using YSI 556 Multiparametre for measurements. The values were measured as salinity amount in grams per kilogram solution and obtained as ppt unit. It was observed that the values vary from 34 ppt - 40.1 ppt and the average is 38.056 ppt. In Thalassic serie, the lake was in mixoeuhaline state in the time of issue. As a first step, ATCOR correction was performed on satellite image for atmospheric correction. There were some clouds on the lake field, hence it was decided to continue the study by using the 12 sampling points which were clear on the image. Then, for each sampling point, a spectral value was obtained by calculating the average at a 11*11 neighborhood. The relation between the spectral reflectance values and the salinity was investigated. The 4-band algorithm, which was used for determination of chlorophyll-a distribution in highly turbid coastal environment by Wei (2012) was applied. Salinity α (Λi-1 / Λj-1) * (Λk-1 / Λm-1) (i

  7. Algorithm developing of gross primary production from its capacity and a canopy conductance index using flux and global observing satellite data

    Science.gov (United States)

    Muramatsu, Kanako; Furumi, Shinobu; Daigo, Motomasa

    2015-10-01

    We plan to estimate gross primary production (GPP) using the SGLI sensor on-board the GCOM-C1 satellite after it is launched in 2017 by the Japan Aerospace Exploration Agency, as we have developed a GPP estimation algorithm that uses SGLI sensor data. The characteristics of this GPP estimation method correspond to photosynthesis. The rate of plant photosynthesis depends on the plant's photosynthesis capacity and the degree to which photosynthesis is suppressed. The photosynthesis capacity depends on the chlorophyll content of leaves, which is a plant physiological parameter, and the degree of suppression of photosynthesis depends on weather conditions. The framework of the estimation method to determine the light-response curve parameters was developed using ux and satellite data in a previous study[1]. We estimated one of the light-response curve parameters based on the linear relationship between GPP capacity at 2000 (μmolm-2s-1) of photosynthetically active radiation and a chlorophyll index (CIgreen [2;3] ). The relationship was determined for seven plant functional types. Decreases in the photosynthetic rate are controlled by stomatal opening and closing. Leaf stomatal conductance is maximal during the morning and decreases in the afternoon. We focused on daily changes in leaf stomatal conductance. We used open shrub flux data and MODIS reflectance data to develop an algorithm for a canopy. We first evaluated the daily changes in GPP capacity estimated from CIgreen and photosynthesis active radiation using light response curves, and GPP observed during a flux experiment. Next, we estimated the canopy conductance using flux data and a big-leaf model using the Penman-Monteith equation[4]. We estimated GPP by multiplying GPP capacity by the normalized canopy conductance at 10:30, the time of satellite observations. The results showed that the estimated daily change in GPP was almost the same as the observed GPP. From this result, we defined a normalized canopy

  8. Characteristics and Diurnal Cycle of GPM Rainfall Estimates over the Central Amazon Region

    Directory of Open Access Journals (Sweden)

    Rômulo Oliveira

    2016-06-01

    Full Text Available Studies that investigate and evaluate the quality, limitations and uncertainties of satellite rainfall estimates are fundamental to assure the correct and successful use of these products in applications, such as climate studies, hydrological modeling and natural hazard monitoring. Over regions of the globe that lack in situ observations, such studies are only possible through intensive field measurement campaigns, which provide a range of high quality ground measurements, e.g., CHUVA (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GlobAl Precipitation Measurement and GoAmazon (Observations and Modeling of the Green Ocean Amazon over the Brazilian Amazon during 2014/2015. This study aims to assess the characteristics of Global Precipitation Measurement (GPM satellite-based precipitation estimates in representing the diurnal cycle over the Brazilian Amazon. The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG and the Goddard Profiling Algorithm—Version 2014 (GPROF2014 algorithms are evaluated against ground-based radar observations. Specifically, the S-band weather radar from the Amazon Protection National System (SIPAM, is first validated against the X-band CHUVA radar and then used as a reference to evaluate GPM precipitation. Results showed satisfactory agreement between S-band SIPAM radar and both IMERG and GPROF2014 algorithms. However, during the wet season, IMERG, which uses the GPROF2014 rainfall retrieval from the GPM Microwave Imager (GMI sensor, significantly overestimates the frequency of heavy rainfall volumes around 00:00–04:00 UTC and 15:00–18:00 UTC. This overestimation is particularly evident over the Negro, Solimões and Amazon rivers due to the poorly-calibrated algorithm over water surfaces. On the other hand, during the dry season, the IMERG product underestimates mean precipitation in comparison to the S-band SIPAM

  9. 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.

  10. 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

  11. Incorporation of an evolutionary algorithm to estimate transfer-functions for a parameter regionalization scheme of a rainfall-runoff model

    Science.gov (United States)

    Klotz, Daniel; Herrnegger, Mathew; Schulz, Karsten

    2016-04-01

    This contribution presents a framework, which enables the use of an Evolutionary Algorithm (EA) for the calibration and regionalization of the hydrological model COSEROreg. COSEROreg uses an updated version of the HBV-type model COSERO (Kling et al. 2014) for the modelling of hydrological processes and is embedded in a parameter regionalization scheme based on Samaniego et al. (2010). The latter uses subscale-information to estimate model via a-priori chosen transfer functions (often derived from pedotransfer functions). However, the transferability of the regionalization scheme to different model-concepts and the integration of new forms of subscale information is not straightforward. (i) The usefulness of (new) single sub-scale information layers is unknown beforehand. (ii) Additionally, the establishment of functional relationships between these (possibly meaningless) sub-scale information layers and the distributed model parameters remain a central challenge in the implementation of a regionalization procedure. The proposed method theoretically provides a framework to overcome this challenge. The implementation of the EA encompasses the following procedure: First, a formal grammar is specified (Ryan et al., 1998). The construction of the grammar thereby defines the set of possible transfer functions and also allows to incorporate hydrological domain knowledge into the search itself. The EA iterates over the given space by combining parameterized basic functions (e.g. linear- or exponential functions) and sub-scale information layers into transfer functions, which are then used in COSEROreg. However, a pre-selection model is applied beforehand to sort out unfeasible proposals by the EA and to reduce the necessary model runs. A second optimization routine is used to optimize the parameters of the transfer functions proposed by the EA. This concept, namely using two nested optimization loops, is inspired by the idea of Lamarckian Evolution and Baldwin Effect

  12. A real-time algorithm for integrating differential satellite and inertial navigation information during helicopter approach. M.S. Thesis

    Science.gov (United States)

    Hoang, TY

    1994-01-01

    A real-time, high-rate precision navigation Kalman filter algorithm is developed and analyzed. This Navigation algorithm blends various navigation data collected during terminal area approach of an instrumented helicopter. Navigation data collected include helicopter position and velocity from a global position system in differential mode (DGPS) as well as helicopter velocity and attitude from an inertial navigation system (INS). The goal of the Navigation algorithm is to increase the DGPS accuracy while producing navigational data at the 64 Hertz INS update rate. It is important to note that while the data was post flight processed, the Navigation algorithm was designed for real-time analysis. The design of the Navigation algorithm resulted in a nine-state Kalman filter. The Kalman filter's state matrix contains position, velocity, and velocity bias components. The filter updates positional readings with DGPS position, INS velocity, and velocity bias information. In addition, the filter incorporates a sporadic data rejection scheme. This relatively simple model met and exceeded the ten meter absolute positional requirement. The Navigation algorithm results were compared with truth data derived from a laser tracker. The helicopter flight profile included terminal glideslope angles of 3, 6, and 9 degrees. Two flight segments extracted during each terminal approach were used to evaluate the Navigation algorithm. The first segment recorded small dynamic maneuver in the lateral plane while motion in the vertical plane was recorded by the second segment. The longitudinal, lateral, and vertical averaged positional accuracies for all three glideslope approaches are as follows (mean plus or minus two standard deviations in meters): longitudinal (-0.03 plus or minus 1.41), lateral (-1.29 plus or minus 2.36), and vertical (-0.76 plus or minus 2.05).

  13. 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

  14. 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).

  15. 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.

  16. Research and Application of GEO Satellite Spot-beam Covering Algorithm%GEO卫星点波束覆盖算法的研究与应用

    Institute of Scientific and Technical Information of China (English)

    董彦磊; 汪春霆; 孙巍

    2016-01-01

    GEO卫星点波束覆盖范围准确计算在实际工程应用中需求日益迫切,针对GEO卫星点波束覆盖特点,提出点波束平面覆盖和点波束球面覆盖计算方法。点波束平面覆盖计算是将地球看成一个平面利用平面几何公式计算点波束覆盖范围,点波束球面覆盖计算是将地球看成一个球体利用球面立体几何公式计算点波束覆盖范围。通过仿真、分析与比较,当点波束半功率角θ3dB较小时平面覆盖计算和球面覆盖计算精度都较高,当半功率角θ3dB较大时平面覆盖计算偏差明显增大,球面覆盖计算精度一直保持在较高水平。%Accurately calculating GEO satellite spot-beam coverage is demanded increasingly in the actual engineering applications.In view ofthe features of spot-beam coverage,this paper presents the algorithm of spot-beam plane coverage and spot-beam spherical coverage.The algorithm of spot-beam plane coverage takes the Earth as a flat to calculate spot-beam coverage with plane geometry formulas,and the algorithm of spot-beam sphere coverage takes the Earth as a sphere to calculate spot-beam coverage with three-dimensional geometry formulas.Through simulation,analysis and comparison,when the half-power angle of spot-beam is smaller,both plane coverage algorithm and spot-beam spherical coverage algorithm have high accuracy of calculation. When the half-power angle of spot-beam is bigger,the calculated deviation of spot-beam plane coverage algorithm increases significantly,however the calculation accuracy of spot-beam spherical coverage algorithm maintains at a high level.

  17. Country-wide rainfall maps from cellular communication networks

    Science.gov (United States)

    Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

    2013-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. Here we show how one cellular telecommunication network can be used to retrieve the space-time dynamics of rainfall for an entire country. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (2400) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both

  18. Applicability of data mining algorithms in the identification of beach features/patterns on high-resolution satellite data

    Science.gov (United States)

    Teodoro, Ana C.

    2015-01-01

    The available beach classification algorithms and sediment budget models are mainly based on in situ parameters, usually unavailable for several coastal areas. A morphological analysis using remotely sensed data is a valid alternative. This study focuses on the application of data mining techniques, particularly decision trees (DTs) and artificial neural networks (ANNs) to an IKONOS-2 image in order to identify beach features/patterns in a stretch of the northwest coast of Portugal. Based on knowledge of the coastal features, five classes were defined. In the identification of beach features/patterns, the ANN algorithm presented an overall accuracy of 98.6% and a kappa coefficient of 0.97. The best DTs algorithm (with pruning) presents an overall accuracy of 98.2% and a kappa coefficient of 0.97. The results obtained through the ANN and DTs were in agreement. However, the ANN presented a classification more sensitive to rip currents. The use of ANNs and DTs for beach classification from remotely sensed data resulted in an increased classification accuracy when compared with traditional classification methods. The association of remotely sensed high-spatial resolution data and data mining algorithms is an effective methodology with which to identify beach features/patterns.

  19. Advancements of In-Flight Mass Moment of Inertia and Structural Deflection Algorithms for Satellite Attitude Simulators

    Science.gov (United States)

    2015-03-26

    on the air-bearing satellite attitude simulator at Shenyang University of Technology. Additionally, Chesi et al., [3] advanced the EKF developed by Kim...in a disturbance torque. The data for hrw about the test axis is then used to calculate the coefficients Arw and Brw that best fit the equation hrw...oscillation; and m, b, D, and E are coefficients that best fit the 51 0 10 20 30 40 50 −0.4 −0.3 −0.2 −0.1 0 0.1 0.2 0.3 0.4 time (s) A ng ul ar M om en

  20. A New Traffic Flow Prediction Algorithm for Satellite Communication Network%一种新的卫星通信网流量预测算法*

    Institute of Scientific and Technical Information of China (English)

    秦红祥; 杨飞

    2013-01-01

      在通信网络的设计中,使用基于流量预测的网络规划已成为LTE发展的必然趋势。与地面网络不同,卫星网络由于受资源受限和拓扑时变的不利影响,其流量预测算法必须能兼顾精度和效率,这令传统的地面网络预测方法已不再适用。为了解决以上问题,提出了一种新的基于小波回声状态网络的流量预测算法,该算法通过小波多尺度分解的信号处理方法屏蔽了网络流量的噪声,而后结合了无反馈的回声状态网络联合进行预测。仿真证明,新算法相比传统算法能大幅提升网络流量的预测精度和运行效率,为卫星网络的流量规划提供了强有力的决策支持。%In the design of a communication network,it has become an inevitable trend with LET development to use traffic flow prediction method for network planning. Due to suffer from the constrained resource and change-able topology,the traffic flow prediction algorithm of the satellite networks which is different from terrestrial net-works,should fully take into account the accuracy and efficiency,so the traditional prediction methods for ter-restrial networks are no longer fit for application. In order to resolve this problem,a new traffic flow prediction algorithm based on wavelet and echo state networks is proposed in this paper. The new algorithm uses the signal processing method based on multi-scale decomposition of wavelet to shield the noise of the network traffic,and it combines with the non-feedback echo state network to predict. The simulation results show that the new algorithm can greatly improve the prediction accuracy and running efficiency of network traffic compared with traditional al-gorithms,so it provides a more scientific decision support for satellite communication network traffic planning.

  1. Development of Fast Error Compensation Algorithm for Integrated Inertial-Satellite Navigation System of Small-size Unmanned Aerial Vehicles in Complex Environment

    Directory of Open Access Journals (Sweden)

    A. V. Fomichev

    2015-01-01

    Full Text Available In accordance with the structural features of small-size unmanned aerial vehicle (UAV, and considering the feasibility of this project, the article studies an integrated inertial-satellite navigation system (INS. The INS algorithm development is based on the method of indirect filtration and principle of loosely coupled combination of output data on UAV positions and velocity. Data on position and velocity are provided from the strapdown inertial navigation system (SINS and satellite navigation system (GPS. A difference between the output flows of measuring data on position and velocity provided from the SINS and GPS is used to evaluate SINS errors by means of the basic algorithm of Kalman filtering. Then the outputs of SINS are revised. The INS possesses the following advantages: a simpler mathematical model of Kalman filtering, high reliability, two independently operating navigation systems, and high redundancy of available navigation information.But in case of loosely coupled scheme, INS can meet the challenge of high precision and reliability of navigation only when the SINS and GPS operating conditions are normal all the time. The proposed INS is used with UAV moving in complex environment due to obstacles available, severe natural climatic conditions, etc. This case expects that it is impossible for UAV to receive successful GPS-signals frequently. In order to solve this problem, was developed an algorithm for rapid compensation for errors of INS information, which could effectively solve the problem of failure of the navigation system in case there are no GPS-signals .Since it is almost impossible to obtain the data of the real trajectory in practice, in the course of simulation in accordance with the kinematic model of the UAV and the complex environment of the terrain, the flight path generator is used to produce the flight path. The errors of positions and velocities are considered as an indicator of the INS effectiveness. The results

  2. 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

  3. Priority-based active queue management algorithm for satellite networks%一种基于优先级的卫星网络AQM算法

    Institute of Scientific and Technical Information of China (English)

    孙力娟; 谢慧婷; 肖甫; 叶晓国; 王汝传

    2011-01-01

    针对卫星网络大带宽、长时延、高误码等特点,结合控制理论,提出了一种基于优先级的卫星网络主动队列管理(active queue management,AQM)算法.首先,借鉴控制理论中比例-积分-微分(propertional-integral-derivative,PID)控制器设计方法计算总的报文丢弃概率;然后,针对IN和OUT两种不同优先级报文定义不同的丢弃概率,以实现不同优先级业务流量的区分服务.仿真实验表明,相对于低优先级流量,高优先级业务在保持高吞吐量的同时具有较低的报文丢失率,且整体队列长度抖动小,从而实现高优先级流量报文的有效保护.%Aimming at the characteristics of high bandwidth, long delay and high bit error ratio in satellite networks, a satellite network active queue management (AQM) algorithm based on prioity, which is integrated with control theory, is proposed. Firistly, based on the designing of the propertional-integral-derivative (PID) controller in control theory, a total probability of dropped messages is defined. Then, to differentiate between IN and OUT flows with different priorities, different probabilities of dropped messages are designed as well. Simulation results show that, compared with the case of flow with low priority, the proposed algorithm can effectively protect high priority flow by means of achieving a higher throughput with smaller jitter and low probability of dropped messages.

  4. 自适应遗传算法的数据中继卫星光网络资源调度算法%Scheduling algorithm for data relay satellite optical network based on self-adaptive genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    赵卫虎; 赵静; 赵尚弘; 李勇军; 董毅; 李轩

    2015-01-01

    According to the resources, missions and restraints of the data relay satellite optical network, a scheduling algorithm based on improved self-adaptive genetic algorithm was put forwarded. Considering the multi-relay satellite, multi-window, multi-optical-antenna and multi-mission PRI, the model was established. The missions were scheduled by the scheduling operates: the ascertainment of current mission scheduling time and the refreshment of latter mission time-window. The whole weight of the scheduled missions was set as the cost value and the scheduling schemes were optimized by the self-adaptive genetic algorithm. The simulation scene including 3 relay satellites, 12 user satellites, 6 antennas and 60 missions, the result reveals that the algorithm obtains satisfactory results in both time and optimization which is suitable in multi-user, multi-mission and multi-optical-antenna recourse scheduling.%以数据中继卫星光网络系统资源、任务和约束条件为参量,以任务对资源的选择为优化对象,提出了一种基于自适应遗传算法的数据中继卫星光网络资源调度算法。综合考虑多中继星、多时间窗口、多光学天线以及任务优先级要求,建立调度模型;采用“当前任务调度时间的确定”和“后续任务可见时间窗口的更新”的调度操作,对不同资源的任务集合进行调度安排并实现了可见时间窗口的动态更新,获得调度任务的总权值并将其作为参量计算适应度值,最后通过改进的自适应遗传算法对不同调度方案进行寻优。以3颗中继星、12颗用户星,6个光天线,60个任务为条件设置了仿真场景,仿真结果表明该算法在收敛速度、调度效率方面具有优势,适应于多任务、多天线的数据中继卫星光网络系统资源调度。

  5. Utilization of a genetic algorithm for the automatic detection of oil spill from RADARSAT-2 SAR satellite data.

    Science.gov (United States)

    Marghany, Maged

    2014-12-15

    In this work, a genetic algorithm is applied for the automatic detection of oil spills. The procedure is implemented using sequences from RADARSAT-2 SAR ScanSAR Narrow single-beam data acquired in the Gulf of Mexico. The study demonstrates that the implementation of crossover allows for the generation of an accurate oil spill pattern. This conclusion is confirmed by the receiver-operating characteristic (ROC) curve. The ROC curve indicates that the existence of oil slick footprints can be identified using the area between the ROC curve and the no-discrimination line of 90%, which is greater than that of other surrounding environmental features. In conclusion, the genetic algorithm can be used as a tool for the automatic detection of oil spills, and the ScanSAR Narrow single-beam mode serves as an excellent sensor for oil spill detection and survey.

  6. The inter-comparison of major satellite aerosol retrieval algorithms using simulated intensity and polarization characteristics of reflected light

    Directory of Open Access Journals (Sweden)

    A. A. Kokhanovsky

    2010-07-01

    Full Text Available Remote sensing of aerosol from space is a challenging and typically underdetermined retrieval task, requiring many assumptions to be made with respect to the aerosol and surface models. Therefore, the quality of a priori information plays a central role in any retrieval process (apart from the cloud screening procedure and the forward radiative transfer model, which to be most accurate should include the treatment of light polarization and molecular-aerosol coupling. In this paper the performance of various algorithms with respect to the of spectral aerosol optical thickness determination from optical spaceborne measurements is studied. The algorithms are based on various types of measurements (spectral, angular, polarization, or some combination of these. It is confirmed that multiangular spectropolarimetric measurements provide more powerful constraints compared to spectral intensity measurements alone, particularly those acquired at a single view angle and which rely on a priori assumptions regarding the particle phase function in the retrieval process.

  7. Performance of operational satellite bio-optical algorithms in different water types in the southeastern Arabian Sea

    Directory of Open Access Journals (Sweden)

    P. Minu

    2016-10-01

    Full Text Available The in situ remote sensing reflectance (Rrs and optically active substances (OAS measured using hyperspectral radiometer, were used for optical classification of coastal waters in the southeastern Arabian Sea. The spectral Rrs showed three distinct water types, that were associated with the variability in OAS such as chlorophyll-a (chl-a, chromophoric dissolved organic matter (CDOM and volume scattering function at 650 nm (β650. The water types were classified as Type-I, Type-II and Type-III respectively for the three Rrs spectra. The Type-I waters showed the peak Rrs in the blue band (470 nm, whereas in the case of Type-II and III waters the peak Rrs was at 560 and 570 nm respectively. The shifting of the peak Rrs at the longer wavelength was due to an increase in concentration of OAS. Further, we evaluated six bio-optical algorithms (OC3C, OC4O, OC4, OC4E, OC3M and OC4O2 used operationally to retrieve chl-a from Coastal Zone Colour Scanner (CZCS, Ocean Colour Temperature Scanner (OCTS, Sea-viewing Wide Field-of-view Sensor (SeaWiFS, MEdium Resolution Imaging Spectrometer (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS and Ocean Colour Monitor (OCM2. For chl-a concentration greater than 1.0 mg m−3, algorithms based on the reference band ratios 488/510/520 nm to 547/550/555/560/565 nm have to be considered. The assessment of algorithms showed better performance of OC3M and OC4. All the algorithms exhibited better performance in Type-I waters. However, the performance was poor in Type-II and Type-III waters which could be attributed to the significant co-variance of chl-a with CDOM.

  8. Estimation of stratospheric NO2 from nadir-viewing satellites: The MPI-C TROPOMI verification algorithm

    Science.gov (United States)

    Beirle, Steffen; Wagner, Thomas

    2015-04-01

    The retrieval of tropospheric column densities of NO2 requires the subtraction of the stratospheric fraction from the total columns derived by DOAS. Here we present a modified reference sector method, which estimates the stratosphere over "clean" regions, as well as over clouded scenarios in which the tropospheric column is shielded. The selection of "clean" pixels is realized gradually by assingning weighting factors to the individual ground pixels, instead of applying binary flags. Global stratospheric fields are then compiled by "weighted convolution". In a second iteration, unphysical negative tropospheric residues are suppressed by adjusting the weights respectively. This algorithm is foreseen as "verification algorithm" for the upcoming TROPOMI on S5p. We show the resulting stratospheric estimates and tropospheric residues for a test data set based on OMI observations. The dependencies on the a-priori settings (definition of weighting factors and convolution kernels) are discussed, and the results are compared to other products, in particular to DOMINO v.2 (based on assimilation, similar to the TROPOMI prototype algorithm) and the NASA standard product (based on a similar reference-region-type approach).

  9. Satellite Based Assessment of the NSRDB Site Irradiances and Time Series from NASA and SUNY/Albany Algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Stackhouse, P. W., Jr.; Zhang, T.; Chandler, W. S.; Whitlock, C. H.; Hoell, J. M.; Westberg, D. J.; Perez, R.; Wilcox, S.

    2008-01-01

    In April, 2007, the National Solar Radiation Database (NSRDB) of the National Renewable Energy Laboratory was updated for the period from 1991 to 2005. NSRDB includes monthly averaged summary statistics from 221 Class I sites spanning the entire time period with least uncertainty. In 2008, the NASA GEWEX Surface Radiation Budget (SRB) project updated its satellite-derived solar surface irradiance to Release 3.0. This dataset spans July 1983 to June 2006 at a 1ox1o resolution. In this paper, we compare the NSRDB data monthly average summary statistics to NASA SRB data that has been validated favorably against the BSRN, SURFRAD, WRDC and GEBA datasets. The SRB-NSRDB comparison reveals reasonably good agreement of the two datasets.

  10. A Fast and Sensitive New Satellite SO2 Retrieval Algorithm based on Principal Component Analysis: Application to the Ozone Monitoring Instrument

    Science.gov (United States)

    Li, Can; Joiner, Joanna; Krotkov, A.; Bhartia, Pawan K.

    2013-01-01

    We describe a new algorithm to retrieve SO2 from satellite-measured hyperspectral radiances. We employ the principal component analysis technique in regions with no significant SO2 to capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering and ozone absorption) and measurement artifacts. We use the resulting principal components and SO2 Jacobians calculated with a radiative transfer model to directly estimate SO2 vertical column density in one step. Application to the Ozone Monitoring Instrument (OMI) radiance spectra in 310.5-340 nm demonstrates that this approach can greatly reduce biases in the operational OMI product and decrease the noise by a factor of 2, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing longterm, consistent SO2 records for air quality and climate research.

  11. 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.

  12. 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.

  13. 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.

  14. Sensitivity of Satellite-Based Skin Temperature to Different Surface Emissivity and NWP Reanalysis Sources Demonstrated Using a Single-Channel, Viewing-Angle-Corrected Retrieval Algorithm

    Science.gov (United States)

    Scarino, B. R.; Minnis, P.; Yost, C. R.; Chee, T.; Palikonda, R.

    2015-12-01

    Single-channel algorithms for satellite thermal-infrared- (TIR-) derived land and sea surface skin temperature (LST and SST) are advantageous in that they can be easily applied to a variety of satellite sensors. They can also accommodate decade-spanning instrument series, particularly for periods when split-window capabilities are not available. However, the benefit of one unified retrieval methodology for all sensors comes at the cost of critical sensitivity to surface emissivity (ɛs) and atmospheric transmittance estimation. It has been demonstrated that as little as 0.01 variance in ɛs can amount to more than a 0.5-K adjustment in retrieved LST values. Atmospheric transmittance requires calculations that employ vertical profiles of temperature and humidity from numerical weather prediction (NWP) models. Selection of a given NWP model can significantly affect LST and SST agreement relative to their respective validation sources. Thus, it is necessary to understand the accuracies of the retrievals for various NWP models to ensure the best LST/SST retrievals. The sensitivities of the single-channel retrievals to surface emittance and NWP profiles are investigated using NASA Langley historic land and ocean clear-sky skin temperature (Ts) values derived from high-resolution 11-μm TIR brightness temperature measured from geostationary satellites (GEOSat) and Advanced Very High Resolution Radiometers (AVHRR). It is shown that mean GEOSat-derived, anisotropy-corrected LST can vary by up to ±0.8 K depending on whether CERES or MODIS ɛs sources are used. Furthermore, the use of either NOAA Global Forecast System (GFS) or NASA Goddard Modern-Era Retrospective Analysis for Research and Applications (MERRA) for the radiative transfer model initial atmospheric state can account for more than 0.5-K variation in mean Ts. The results are compared to measurements from the Surface Radiation Budget Network (SURFRAD), an Atmospheric Radiation Measurement (ARM) Program ground

  15. 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...

  16. Comparison of the TRMM Precipitation Radar rainfall estimation with ground-based disdrometer and radar measurements in South Greece

    Science.gov (United States)

    Ioannidou, Melina P.; Kalogiros, John A.; Stavrakis, Adrian K.

    2016-11-01

    The performance of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) rainfall estimation algorithm is assessed, locally, in Crete island, south Greece, using data from a 2D-video disdrometer and a ground-based, X-band, polarimetric radar. A three-parameter, normalized Gamma drop size distribution is fitted to the disdrometer rain spectra; the latter are classified in stratiform and convective rain types characterized by different relations between distribution parameters. The method of moments estimates more accurately the distribution parameters than the best fit technique, which exhibits better agreement with and is more biased by the observed droplet distribution at large diameter values. Power laws between the radar reflectivity factor (Z) and the rainfall rate (R) are derived from the disdrometer data. A significant diversity of the prefactor and the exponent of the estimated power laws is observed, depending on the scattering model and the regression technique. The Z-R relationships derived from the disdrometer data are compared to those obtained from TRMM-PR data. Generally, the power laws estimated from the two datasets are different. Specifically, the greater prefactor found for the disdrometer data suggests an overestimation of rainfall rate by the TRMM-PR algorithm for light and moderate stratiform rain, which was the main rain type in the disdrometer dataset. Finally, contemporary data from the TRMM-PR and a ground-based, X-band, polarimetric radar are analyzed. Comparison of the corresponding surface rain rates for a rain event with convective characteristics indicates a large variability of R in a single TRMM-PR footprint, which typically comprises several hundreds of radar pixels. Thus, the coarse spatial resolution of TRMM-PR may lead to miss of significant high local peaks of convective rain. Also, it was found that the high temporal variability of convective rain may introduce significant errors in the estimation of bias of

  17. Meteosat SEVIRI Fire Radiative Power (FRP products from the Land Surface Analysis Satellite Applications Facility (LSA SAF – Part 1: Algorithms, product contents and analysis

    Directory of Open Access Journals (Sweden)

    M. J. Wooster

    2015-06-01

    Full Text Available Characterising changes in landscape scale fire activity at very high temporal resolution is best achieved using thermal observations of actively burning fires made from geostationary Earth observation (EO satellites. Over the last decade or more, a series of research and/or operational "active fire" products have been developed from these types of geostationary observations, often with the aim of supporting the generation of data related to biomass burning fuel consumption and trace gas and aerosol emission fields. The Fire Radiative Power (FRP products generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF from data collected by the Meteosat Second Generation (MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI are one such set of products, and are freely available in both near real-time and archived form. Every 15 min, the algorithms used to generate these products identify and map the location of new SEVIRI observations containing actively burning fires, and characterise their individual rates of radiative energy release (fire radiative power; FRP that is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL product contains the highest spatial resolution FRP dataset, delivered for all of Europe, northern and southern Africa, and part of South America at a spatial resolution of 3 km (decreasing away from the west African sub-satellite point at the full 15 min temporal resolution. The FRP-GRID product is an hourly summary of the FRP-PIXEL data, produced at a 5° grid cell size and including simple bias adjustments for meteorological cloud cover and for the regional underestimation of FRP caused, primarily, by the non-detection of low FRP fire pixels at SEVIRI's relatively coarse pixel size. Here we describe the enhanced geostationary Fire Thermal Anomaly (FTA algorithm used to detect the SEVIRI active fire pixels, and detail methods used to deliver atmospherically corrected FRP

  18. 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.

  19. Inversion methods for satellite studies of the Earth Radiation Budget - Development of algorithms for the ERBE mission

    Science.gov (United States)

    Smith, G. L.; Green, R. N.; Avis, L. M.; Suttles, J. T.; Wielicki, B. A.; Raschke, E.; Davies, R.

    1986-01-01

    The Earth Radiation Budget Experiment carries a three-channel scanning radiometer and a set of nadir-looking wide and medium field-of-view instruments for measuring the radiation emitted from earth and the solar radiation reflected from earth. This paper describes the algorithms which are used to compute the radiant exitances at a reference level ('top of the atmosphere') from these measurements. Methods used to analyze data from previous radiation budget experiments are reviewed, and the rationale for the present algorithms is developed. The scanner data are converted to radiances by use of spectral factors, which account for imperfect spectral response of the optics. These radiances are converted to radiant exitances at the reference level by use of directional models, which account for anisotropy of the radiation as it leaves the earth. The spectral factors and directional models are selected on the basis of the scene, which is identified on the basis of the location and the long-wave and shortwave radiances. These individual results are averaged over 2.5 x 2.5 deg regions. Data from the wide and medium field-of-view instruments are analyzed by use of the traditional shape factor method and also by use of a numerical filter, which permits resolution enhancement along the orbit track.

  20. Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

    Science.gov (United States)

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

    2000-01-01

    Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

  1. Rainfall measurement from opportunistic use of earth-space link in Ku Band

    Directory of Open Access Journals (Sweden)

    L. Barthès

    2013-02-01

    Full Text Available The present study deals with the development of a low cost microwave device devoted to measure average rain rate observed along earth – satellite links. The principle is to use rain atmospheric attenuation along Earth – space links in Ku-band to deduce the path averaged rain rate. These links are characterized by a path length of a few km through the troposphere. Ground based power measurements are carried out by receiving TV channels from different geostationary satellites in Ku-band.

    The major difficulty in this study is to retrieve rain characteristics among many fluctuations of the received signal which are due to atmospheric scintillations, changes in the composition of the atmosphere (water vapour concentration, cloud water content or satellite features (variation of the emitted power, satellite motions. In order to perform a feasibility study of such a device, a measurement campaign has been performed for five months near Paris. This paper proposes an algorithm based on an artificial neural network to identify drought and rainy periods and to suppress the variability of the received signal due to no-rain effects. Taking into account the height of the rain layer, rain attenuation is then inverted to obtain path averaged rain rate. Obtained rainfall rates are compared with co-located rain gauges and radar measurements on the whole experiment period, then the most significant rainy events are analyzed.

  2. Countrywide rainfall maps from a commercial cellular telecommunication network

    Science.gov (United States)

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

    2012-12-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information. Many countries do not have continuously operating weather radars, and have no or few rain gauges. A new development is rainfall estimation from microwave links of commercial cellular telecommunication networks. Such networks cover large parts of the land surface of the earth and have a high density, especially in urban areas. The estimation of rainfall using commercial microwave links could therefore become a valuable source of information. The data produced by microwave links is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (1500) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both calibration and validation are done using gauge-adjusted radar data

  3. Single-source surface energy balance algorithms to estimate evapotranspiration from satellite-based remotely sensed data

    Science.gov (United States)

    Bhattarai, Nishan

    The flow of water and energy fluxes at the Earth's surface and within the climate system is difficult to quantify. Recent advances in remote sensing technologies have provided scientists with a useful means to improve characterization of these complex processes. However, many challenges remain that limit our ability to optimize remote sensing data in determining evapotranspiration (ET) and energy fluxes. For example, periodic cloud cover limits the operational use of remotely sensed data from passive sensors in monitoring seasonal fluxes. Additionally, there are many remote sensing-based single-source surface energy balance (SEB) models, but no clear guidance on which one to use in a particular application. Two widely used models---surface energy balance algorithm for land (SEBAL) and mapping ET at high resolution with internalized calibration (METRIC)---need substantial human-intervention that limits their applicability in broad-scale studies. This dissertation addressed some of these challenges by proposing novel ways to optimize available resources within the SEB-based ET modeling framework. A simple regression-based Landsat-Moderate Resolution Imaging Spectroradiometer (MODIS) fusion model was developed to integrate Landsat spatial and MODIS temporal characteristics in calculating ET. The fusion model produced reliable estimates of seasonal ET at moderate spatial resolution while mitigating the impact that cloud cover can have on image availability. The dissertation also evaluated five commonly used remote sensing-based single-source SEB models and found the surface energy balance system (SEBS) may be the best overall model for use in humid subtropical climates. The study also determined that model accuracy varies with land cover type, for example, all models worked well for wet marsh conditions, but the SEBAL and simplified surface energy balance index (S-SEBI) models worked better than the alternatives for grass cover. A new automated approach based on

  4. Algorithm for Satellite Detection Capability Based on Fuzzy AHP Assessment%基于模糊层次分析法的卫星探测效能评估算法

    Institute of Scientific and Technical Information of China (English)

    王玉菊; 岳丽军

    2012-01-01

    Taking remote sensing satellites as an example, performance assessment techniques of satellite detection were studied. First, a satellite-based practical detection capability assessment hierarchy was established, and then the integrating use of motion simulation, probability theory, and continuous Markov chain and Monte Carlo methods, the corresponding algorithm model was established for assessment of satellite detection of individual targets. Then, based on fuzzy analytic hierarchy process, satellite-ship target of evaluation index weights was determined. The final adoption of an application example verifies superiority of the algorithm in the program's priority selection.%以遥感卫星为例研究了卫星探测效能评估技术。首先建立基于实用化的卫星探测能力评估递阶层次结构,接着综合运用运动仿真、概率论、连续马尔科夫链和蒙特卡罗法等方法对卫星探测评估中的单项指标建立相应的算法模型,然后基于模糊层次分析法确定卫星探测舰船目标的各评价指标权重,最后通过一个应用实例验证该算法在方案选优中的优越性。

  5. 元任务插入的多星成像侦察任务聚类启发式算法%Heuristic Clustering Algorithm of Multiple Satellite Imaging Reconnaissance Tasks Based on Atomic Task Insertion

    Institute of Scientific and Technical Information of China (English)

    徐培德; 王建江; 许语拉

    2012-01-01

    At the time of multiple satellites execute reconnaissance tasks in cooperation, Clustering of multiple satellite imaging reconnaissance tasks is able to improve integrated Reconnaissance efficiency of multiple satellites. Based on satellite imaging reconnaissance atomic tasks clustering relations and restriction conditions,this paper establishes mathematics programming model of multiple satellite imaging reconnaissance tasks clustering, then it presents heuristic clustering algorithm based on atomic task insertion to solve the model. Finally the algorithm is validated by an example.%在多颗卫星协同执行侦察任务时,多星成像侦察任务聚类能够提高多颗卫星的整体侦察效率.根据卫星成像侦察元任务之间的聚类关系及约束条件,建立了数学规划模型,并提出了模型求解的基于元任务插入的启发式聚类算法,最后结合实例验证了算法的有效性.

  6. Retrieval algorithm for densities of mesospheric and lower thermospheric metal atom and ion species from satellite-borne limb emission signals

    Science.gov (United States)

    Langowski, M.; Sinnhuber, M.; Aikin, A. C.; von Savigny, C.; Burrows, J. P.

    2014-01-01

    Meteoroids bombard Earth's atmosphere during its orbit around the Sun, depositing a highly varying and significant amount of matter into the thermosphere and mesosphere. The strength of the material source needs to be characterized and its impact on atmospheric chemistry assessed. In this study an algorithm for the retrieval of metal atom and ion number densities for a two-dimensional (latitude, altitude) grid is described and explained. Dayglow emission spectra of the mesosphere and lower thermosphere are used, which are obtained by passive satellite remote sensing with the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument on board Envisat. The limb scans cover the tangent altitude range from 50 to 150 km. Metal atoms and ions are strong emitters in this region and form sharply peaked layers with a FWHM (full width at half maximum) of several 10 km in the mesosphere and lower thermosphere measuring peak altitudes between 90 to 110 km. The emission signal is first separated from the background signal, arising from Rayleigh and Raman scattering of solar radiation by air molecules. A forward radiative transfer model calculating the slant column density (SCD) from a given vertical distribution was developed. This nonlinear model is inverted in an iterative procedure to yield the vertical profiles for the emitting species. Several constraints are applied to the solution for numerical stability reasons and to get physically reasonable solutions. The algorithm is applied to SCIAMACHY limb-emission observations for the retrieval of Mg and Mg+ using emission signatures at 285.2 and 279.6/280.4 nm, respectively. Results are presented for these three lines as well as error estimations and sensitivity tests on different constraint strength and different separation approaches for the background signal.

  7. 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.

  8. Peculiarities of stochastic regime of Arctic ice cover time evolution over 1987-2014 from microwave satellite sounding on the basis of NASA team 2 algorithm

    Science.gov (United States)

    Raev, M. D.; Sharkov, E. A.; Tikhonov, V. V.; Repina, I. A.; Komarova, N. Yu.

    2015-12-01

    The GLOBAL-RT database (DB) is composed of long-term radio heat multichannel observation data received from DMSP F08-F17 satellites; it is permanently supplemented with new data on the Earth's exploration from the space department of the Space Research Institute, Russian Academy of Sciences. Arctic ice-cover areas for regions higher than 60° N latitude were calculated using the DB polar version and NASA Team 2 algorithm, which is widely used in foreign scientific literature. According to the analysis of variability of Arctic ice cover during 1987-2014, 2 months were selected when the Arctic ice cover was maximal (February) and minimal (September), and the average ice cover area was calculated for these months. Confidence intervals of the average values are in the 95-98% limits. Several approximations are derived for the time dependences of the ice-cover maximum and minimum over the period under study. Regression dependences were calculated for polynomials from the first degree (linear) to sextic. It was ascertained that the minimal root-mean-square error of deviation from the approximated curve sharply decreased for the biquadratic polynomial and then varied insignificantly: from 0.5593 for the polynomial of third degree to 0.4560 for the biquadratic polynomial. Hence, the commonly used strictly linear regression with a negative time gradient for the September Arctic ice cover minimum over 30 years should be considered incorrect.

  9. RECOGNITION ALGORITHM OF ANCIENT DWELLINGS BASED ON SATELLITE IMAGES%基于卫星图像的古民居识别算法

    Institute of Scientific and Technical Information of China (English)

    杨帆; 沈来信; 王雪飞

    2016-01-01

    We study the determination of village images from satellite maps according to the scope of longitude and latitude.The dwelling objects are extracted by using rectangular algorithm based on greyscale feature and shape feature of dwellings.For those misrecognised dwellings objects,it is needed to further extract internal texture features of the object for discrimination.We use statistics value of grey-level co-occurrence matrix (GLCM)to represent the feature of every dwelling object,and form the eigenvector of dwellings image.GMLVQ classification algorithm is used to classify the extracted dwellings objects and thus the exclusion of non-dwellings can be achieved. Experiments show that the extraction rate of dwellings is up to 76.1% when the appropriate parameters are selected,such as the length and width of the rectangle,and the related threshold.Using the eigenvector classification algorithm generated based on the elastic mesh and GLCM,the correct recognition rate of dwellings is higher than 88.9%.%根据经纬度范围从卫星地图中确定村落图像,根据民居灰度值特征与形状特征,使用矩形法抽取出民居目标,对于误识别的民居目标,需要进一步提取内部纹理特征加以区分。使用灰度共生矩阵的统计值表征每个民居目标的特征,并组成民居图像的特征向量。使用 GMLVQ 分类算法对抽取民居目标进行分类,实现非民居的排除。实验表明,选取适当的矩形长宽及相关阈值等参数,民居目标抽取率达76.1%;使用基于弹性网格和 GLCM生成的特征向量的分类算法,民居目标的正确识别率超过88.9%。

  10. Generalized Split-Window Algorithm for Estimate of Land Surface Temperature from Chinese Geostationary FengYun Meteorological Satellite (FY-2C Data

    Directory of Open Access Journals (Sweden)

    Jun Xia

    2008-02-01

    Full Text Available On the basis of the radiative transfer theory, this paper addressed the estimate ofLand Surface Temperature (LST from the Chinese first operational geostationarymeteorological satellite-FengYun-2C (FY-2C data in two thermal infrared channels (IR1,10.3-11.3 μ m and IR2, 11.5-12.5 μ m , using the Generalized Split-Window (GSWalgorithm proposed by Wan and Dozier (1996. The coefficients in the GSW algorithmcorresponding to a series of overlapping ranging of the mean emissivity, the atmosphericWater Vapor Content (WVC, and the LST were derived using a statistical regressionmethod from the numerical values simulated with an accurate atmospheric radiativetransfer model MODTRAN 4 over a wide range of atmospheric and surface conditions.The simulation analysis showed that the LST could be estimated by the GSW algorithmwith the Root Mean Square Error (RMSE less than 1 K for the sub-ranges with theViewing Zenith Angle (VZA less than 30° or for the sub-rangs with VZA less than 60°and the atmospheric WVC less than 3.5 g/cm2 provided that the Land Surface Emissivities(LSEs are known. In order to determine the range for the optimum coefficients of theGSW algorithm, the LSEs could be derived from the data in MODIS channels 31 and 32 provided by MODIS/Terra LST product MOD11B1, or be estimated either according tothe land surface classification or using the method proposed by Jiang et al. (2006; and theWVC could be obtained from MODIS total precipitable water product MOD05, or beretrieved using Li et al.’ method (2003. The sensitivity and error analyses in term of theuncertainty of the LSE and WVC as well as the instrumental noise were performed. Inaddition, in order to compare the different formulations of the split-window algorithms,several recently proposed split-window algorithms were used to estimate the LST with thesame simulated FY-2C data. The result of the intercomparsion showed that most of thealgorithms give

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

    Science.gov (United States)

    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.

  12. Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes in Morocco

    Directory of Open Access Journals (Sweden)

    Adam Milewski

    2015-05-01

    Full Text Available TRMM Multi-satellite Precipitation Analysis (TMPA satellite precipitation products have been utilized to quantify, forecast, or understand precipitation patterns, climate change, hydrologic models, and drought in numerous scientific investigations. The TMPA products recently went through a series of algorithm developments to enhance the accuracy and reliability of high-quality precipitation measurements, particularly in low rainfall environments and complex terrain. In this study, we evaluated four TMPA products (3B42: V6, V7temp, V7, RTV7 against 125 rain gauges in Northern Morocco to assess the accuracy of TMPA products in various regimes, examine the performance metrics of new algorithm developments, and assess the impact of the processing error in 2012. Results show that the research products outperform the real-time products in all environments within Morocco, and the newest algorithm development (3B42 V7 outperforms the previous version (V6, particularly in low rainfall and high-elevation environments. TMPA products continue to overestimate precipitation in arid environments and underestimate it in high-elevation areas. Lastly, the temporary processing error resulted in little bias except in arid environments. These results corroborate findings from previous studies, provide scientific data for the Middle East, highlight the difficulty of using TMPA products in varying conditions, and present preliminary research for future algorithm development for the GPM mission.

  13. 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...

  14. 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

  15. A hybrid framework for verification of satellite precipitation products

    Science.gov (United States)

    Li, J.; Hsu, K.; AghaKouchak, A.; Sorooshian, S.

    2011-12-01

    Advances in satellite technology have led to the development of many remote-sensing algorithms to estimate precipitation at quasi-global scales. A number of satellite precipitation products are provided at high spatial and temporal resolutions that are suitable for short-term hydrologic applications. Several coordinated validation activities have been established to evaluate the accuracy of satellite precipitation. Traditional verification measures summarize pixel-to-pixel differences between observation and estimates. Object-based verification methods, however, extend pixel based validation to address errors related to spatial patterns and storm structure, such as the shape, volume, and distribution of precipitation rain-objects. In this investigation, a 2D watershed segmentation technique is used to identify rain storm objects and is further adopted in a hybrid verification framework to diagnose the storm-scale rainfall objects from both satellite-based precipitation estimates and ground observations (radar estimates). Five key scores are identified in the objective-based verification framework, including false alarm ratio, missing ratio, maximum of total interest, equal weight and weighted summation of total interest. These scores indicate the performance of satellite estimates with features extracted from the segmented storm objects. The proposed object-based verification framework was used to evaluate PERSIANN, PERSIANN-CCS, CMORPH, 3B42RT against NOAA stage IV MPE multi-sensor composite rain analysis. All estimates are evaluated at 0.25°x0.25° daily-scale in summer 2008 over the continental United States (CONUS). The five final scores for each precipitation product are compared with the median of maximum interest (MMI) of the Method for Object-Based Diagnostic Evaluation (MODE). The results show PERSIANN and CMORPH outperform 3B42RT and PERSIANN-CCS. Different satellite products presented distinct features of precipitation. For example, the sizes of

  16. 一种基于多Agent强化学习的多星协同任务规划算法%An Algorithm of Cooperative Multiple Satellites Mission Planning Based on Multi-agent Reinforcement Learning

    Institute of Scientific and Technical Information of China (English)

    王冲; 景宁; 李军; 王钧; 陈浩

    2011-01-01

    在分析任务特点和卫星约束的基础上给出了多星协同任务规划问题的数学模型.引入约束惩罚算子和多星联合惩罚算子对卫星Agent原始的效用值增益函数进行改进,在此基础上提出了一种多卫星Agent强化学习算法以求解多星协同任务分配策略,设计了基于黑板结构的多星交互方式以降低学习交互过程中的通信代价.通过仿真实验及分析证明该方法能够有效解决多星协同任务规划问题.%A multi-satellite cooperative planning problem model was given considering the characteristics of the task requests and satellite constraints. Then the original performance function of each satellite agent was modified by introducing both the constraint punishing operator and the multi-satellite joint punishing operator. Next, a multi-satellite reinforcement learning algorithm (MUSARLA)was proposed to derive the coordinated task allocation strategy. Furethermore, the interaction among multiple satellites was designed based on blackboard architecture to reduce the communication cost while learning. Fimally, simulated experiments are carried out which verified the effectiveness of the proposed algorithm.

  17. Estimation of oceanic rainfall using passive and active measurements from SeaWinds spaceborne microwave sensor

    Science.gov (United States)

    Ahmad, Khalil Ali

    The Ku band microwave remote sensor, SeaWinds, was developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Two identical SeaWinds instruments were launched into space. The first was flown onboard NASA QuikSCAT satellite which has been orbiting the Earth since June 1999, and the second instrument flew onboard the Japanese Advanced Earth Observing Satellite II (ADEOS-II) from December 2002 till October 2003 when an irrecoverable solar panel failure caused a premature end to the ADEOS-II satellite mission. SeaWinds operates at a frequency of 13.4 GHz, and was originally designed to measure the speed and direction of the ocean surface wind vector by relating the normalized radar backscatter measurements to the near surface wind vector through a geophysical model function (GMF). In addition to the backscatter measurement capability, SeaWinds simultaneously measures the polarized radiometric emission from the surface and atmosphere, utilizing a ground signal processing algorithm known as the QuikSCAT/ SeaWinds Radiometer (QRad/SRad). This dissertation presents the development and validation of a mathematical inversion algorithm that combines the simultaneous active radar backscatter and the passive microwave brightness temperatures observed by the SeaWinds sensor to retrieve the oceanic rainfall. The retrieval algorithm is statistically based, and has been developed using collocated measurements from SeaWinds, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rates, and Numerical Weather Prediction (NWP) wind fields from the National Centers for Environmental Prediction (NCEP). The oceanic rain is retrieved on a spacecraft wind vector cell (WVC) measurement grid that has a spatial resolution of 25 km. To evaluate the accuracy of the retrievals, examples of the passive-only, as well as the combined active/passive rain estimates from SeaWinds are presented, and comparisons are made with the standard

  18. 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

  19. 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

  20. 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...

  1. Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea

    Science.gov (United States)

    Yoon, Sunkwon; Jang, Sangmin; Park, Kyungwon

    2017-04-01

    Extreme weather due to changing climate is a main source of water-related disasters such as flooding and inundation and its damage will be accelerated somewhere in world wide. To prevent the water-related disasters and mitigate their damage in urban areas in future, we developed a multi-sensor based real-time discharge forecasting system using remotely sensed data such as radar and satellite. We used Communication, Ocean and Meteorological Satellite (COMS) and Korea Meteorological Agency (KMA) weather radar for quantitative precipitation estimation. The Automatic Weather System (AWS) and McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) were used for verification of rainfall accuracy. The optimal Z-R relation was applied the Tropical Z-R relationship (Z=32R1.65), it has been confirmed that the accuracy is improved in the extreme rainfall events. In addition, the performance of blended multi-sensor combining rainfall was improved in 60mm/h rainfall and more strong heavy rainfall events. Moreover, we adjusted to forecast the urban discharge using Storm Water Management Model (SWMM). Several statistical methods have been used for assessment of model simulation between observed and simulated discharge. In terms of the correlation coefficient and r-squared discharge between observed and forecasted were highly correlated. Based on this study, we captured a possibility of real-time urban discharge forecasting system using remotely sensed data and its utilization for real-time flood warning. Acknowledgement This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.

  2. Web Based Rapid Mapping of Disaster Areas using Satellite Images, Web Processing Service, Web Mapping Service, Frequency Based Change Detection Algorithm and J-iView

    Science.gov (United States)

    Bandibas, J. C.; Takarada, S.

    2013-12-01

    Timely identification of areas affected by natural disasters is very important for a successful rescue and effective emergency relief efforts. This research focuses on the development of a cost effective and efficient system of identifying areas affected by natural disasters, and the efficient distribution of the information. The developed system is composed of 3 modules which are the Web Processing Service (WPS), Web Map Service (WMS) and the user interface provided by J-iView (fig. 1). WPS is an online system that provides computation, storage and data access services. In this study, the WPS module provides online access of the software implementing the developed frequency based change detection algorithm for the identification of areas affected by natural disasters. It also sends requests to WMS servers to get the remotely sensed data to be used in the computation. WMS is a standard protocol that provides a simple HTTP interface for requesting geo-registered map images from one or more geospatial databases. In this research, the WMS component provides remote access of the satellite images which are used as inputs for land cover change detection. The user interface in this system is provided by J-iView, which is an online mapping system developed at the Geological Survey of Japan (GSJ). The 3 modules are seamlessly integrated into a single package using J-iView, which could rapidly generate a map of disaster areas that is instantaneously viewable online. The developed system was tested using ASTER images covering the areas damaged by the March 11, 2011 tsunami in northeastern Japan. The developed system efficiently generated a map showing areas devastated by the tsunami. Based on the initial results of the study, the developed system proved to be a useful tool for emergency workers to quickly identify areas affected by natural disasters.

  3. 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

  4. 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.

  5. Variational Assimilation of GPS Precipitable Water Vapor and Hourly Rainfall Observations for a Meso-β Scale Heavy Precipitation Event During the 2002 Mei-Yu Season

    Institute of Scientific and Technical Information of China (English)

    ZHANG Meng; NI Yunqi; ZHANG Fuqing

    2007-01-01

    Recent advances in Global Positioning System (GPS) remote sensing technology allow for a direct estimation of the precipitable water vapor (PWV) from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational (4DVAR) data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavy precipitation was induced by a sequence of meso-β-scale convective systems (MCS) along the mei-yu front in China.The experiments with GPS-PWV assimilation successfully simulated the evolution of the observed MCS cluster and also eliminated the erroneous rainfall systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.

  6. 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.

  7. 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...

  8. 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.

  9. An alternative approach to characterize time series data: Case study on Malaysian rainfall data

    Energy Technology Data Exchange (ETDEWEB)

    Radhakrishnan, P. [Faculty of Information Science and Technology, Multimedia University, Melaka 75450 (Malaysia)] e-mail: radha.krishnan@mmu.edu.my; Dinesh, S. [Faculty of Engineering and Technology, Multimedia University, Melaka 75450 (Malaysia)

    2006-01-01

    This paper focuses on the characterization of time series rainfall data to understand the behavior in the Malaysian rainfall data. An analysis of the rainfall behavior of different time periods is also conducted. The rainfall data is rounded. A bar with a width of 12 pixels is drawn for each day in the data. The length of the bars drawn is equal to the corresponding rainfall value. Each bar is separated by a space of 2 pixels. Bars for data from different year are stored in different rows. Morphological opening is performed on the barcode image obtained, using line kernels of increasing length. Connected component-labeling algorithm is implemented on the resulting images to identify the individual bar codes and to compute the number of bars remaining after the opening process. A daily rainfall record for the duration of 30 years, obtained from the Melaka Meteorological Station, is analyzed. The results provide characterization of behavior in daily rainfall data.

  10. 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.

  11. A Comparison of Machine Learning Algorithms for Mapping of Complex Surface-Mined and Agricultural Landscapes Using ZiYuan-3 Stereo Satellite Imagery

    Directory of Open Access Journals (Sweden)

    Xianju Li

    2016-06-01

    Full Text Available Land cover mapping (LCM in complex surface-mined and agricultural landscapes could contribute greatly to regulating mine exploitation and protecting mine geo-environments. However, there are some special and spectrally similar land covers in these landscapes which increase the difficulty in LCM when employing high spatial resolution images. There is currently no research on these mixed complex landscapes. The present study focused on LCM in such a mixed complex landscape located in Wuhan City, China. A procedure combining ZiYuan-3 (ZY-3 stereo satellite imagery, the feature selection (FS method, and machine learning algorithms (MLAs (random forest, RF; support vector machine, SVM; artificial neural network, ANN was proposed and first examined for both LCM of surface-mined and agricultural landscapes (MSMAL and classification of surface-mined land (CSML, respectively. The mean and standard deviation filters of spectral bands and topographic features derived from ZY-3 stereo images were newly introduced. Comparisons of three MLAs, including their sensitivities to FS and whether FS resulted in significant influences, were conducted for the first time in the present study. The following conclusions are drawn. Textures were of little use, and the novel features contributed to improve classification accuracy. Regarding the influence of FS: FS substantially reduced feature set (by 68% for MSMAL and 87% for CSML, and often improved classification accuracies (with an average value of 4.48% for MSMAL using three MLAs, and 11.39% for CSML using RF and SVM; FS showed statistically significant improvements except for ANN-based MSMAL; SVM was most sensitive to FS, followed by ANN and RF. Regarding comparisons of MLAs: for MSMAL based on feature subset, RF achieved the greatest overall accuracy of 77.57%, followed by SVM and ANN; for CSML, SVM had the highest accuracies (87.34%, followed by RF and ANN; based on the feature subsets, significant differences were

  12. Estimation of Real-Time Flood Risk on Roads Based on Rainfall Calculated by the Revised Method of Missing Rainfall

    Directory of Open Access Journals (Sweden)

    Eunmi Kim

    2014-09-01

    Full Text Available Recently, flood damage by frequent localized downpours in cities is on the increase on account of abnormal climate phenomena and the growth of impermeable areas due to urbanization. This study suggests a method to estimate real-time flood risk on roads for drivers based on the accumulated rainfall. The amount of rainfall of a road link, which is an intensive type, is calculated by using the revised method of missing rainfall in meteorology, because the rainfall is not measured on roads directly. To process in real time with a computer, we use the inverse distance weighting (IDW method, which is a suitable method in the computing system and is commonly used in relation to precipitation due to its simplicity. With real-time accumulated rainfall, the flooding history, rainfall range causing flooding from previous rainfall information and frequency probability of precipitation are used to determine the flood risk on roads. The result of simulation using the suggested algorithms shows the high concordance rate between actual flooded areas in the past and flooded areas derived from the simulation for the research region in Busan, Korea.

  13. Assessment of Satellite-based Precipitation Products (TRMM) in Hydrologic Modeling: Case Studies from Northern Morocco

    Science.gov (United States)

    EL kadiri, R.; Milewski, A.; Durham, M.

    2012-12-01

    Precipitation is the most important forcing parameter in hydrological modeling, yet it is largely unknown in the arid Middle East. We assessed the magnitude, probability of detection, and false alarm rates of various rainfall satellite products (e.g., TRMM, RFE2.0) compared to in situ gauge data (~79 stations) across the Our Er Rbia, Sebou, and Melouya Watersheds in Northern Morocco. Precipitation over the area is relatively high with an average of ~400mm/year according to TRMM (1998-2008). The existing gauges indicate that the average annual precipitation across the Tadla and Coastal Plains region is 260mm/year and 390mm/year across the Atlas Mountains. Following the assessment of satellite products against in situ gauge data, we evaluated the effects (e.g., runoff and recharge amounts) of using satellite driven hydrologic models using SWAT. Specifically, we performed a four-fold exercise: (1) The first stage focused on the analysis of the rainfall products; (2) the second stage involved the construction of a rainfall-runoff model using gauge data; (3) the third stage entailed the calibration of the model against flow gauges and/or dams storage variability, and (4) model simulation using satellite based rainfall products using the calibrated parameters from the initial simulation. Results suggest the TRMM V7 has a much better correlation with the field data over the Oum Er Rbia watershed. The Correlation E (Nash-Suncliffe coefficient) has a positive value of 0.5, while the correlation coefficient of TRMM V6 vs. gauges data is a negative value of -0.25. This first order evaluation of the TRMM V7 shows the new algorithm has partially overcame the underestimation effect in the semi-arid environments. However, more research needs to be done to increase the usability of TRMM V7 in hydrologic models. Low correlations are most likely a result of the following: (1) snow at the high elevations in the Oum Er Rbia watershed, (2) the ocean effect on TRMM measurements along

  14. Toward a Global Map of Raindrop Size Distributions. Part 1; Rain-Type Classification and Its Implications for Validating Global Rainfall Products

    Science.gov (United States)

    L'Ecuyer, Tristan S.; Kummerow, Christian; Berg,Wesley

    2004-01-01

    Variability in the global distribution of precipitation is recognized as a key element in assessing the impact of climate change for life on earth. The response of precipitation to climate forcings is, however, poorly understood because of discrepancies in the magnitude and sign of climatic trends in satellite-based rainfall estimates. Quantifying and ultimately removing these biases is critical for studying the response of the hydrologic cycle to climate change. In addition, estimates of random errors owing to variability in algorithm assumptions on local spatial and temporal scales are critical for establishing how strongly their products should be weighted in data assimilation or model validation applications and for assigning a level of confidence to climate trends diagnosed from the data. This paper explores the potential for refining assumed drop size distributions (DSDs) in global radar rainfall algorithms by establishing a link between satellite observables and information gleaned from regional validation experiments where polarimetric radar, Doppler radar, and disdrometer measurements can be used to infer raindrop size distributions. By virtue of the limited information available in the satellite retrieval framework, the current method deviates from approaches adopted in the ground-based radar community that attempt to relate microphysical processes and resultant DSDs to local meteorological conditions. Instead, the technique exploits the fact that different microphysical pathways for rainfall production are likely to lead to differences in both the DSD of the resulting raindrops and the three-dimensional structure of associated radar reflectivity profiles. Objective rain-type classification based on the complete three-dimensional structure of observed reflectivity profiles is found to partially mitigate random and systematic errors in DSDs implied by differential reflectivity measurements. In particular, it is shown that vertical and horizontal

  15. 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...

  16. How reliable are satellite precipitation estimates for driving hydrological models: a verification study over the Mediterranean area

    Science.gov (United States)

    Camici, Stefania; Ciabatta, Luca; Massari, Christian; Brocca, Luca

    2017-04-01

    , TMPA 3B42-RT, CMORPH, PERSIANN and a new soil moisture-derived rainfall datasets obtained through the application of SM2RAIN algorithm (Brocca et al., 2014) to ASCAT (Advanced SCATterometer) soil moisture product are used in the analysis. The performances obtained with SRPs are compared with those obtained by using ground data during the 6-year period from 2010 to 2015. In addition, the performance obtained by an integration of the above mentioned SRPs is also investigated to see whether merged rainfall observations are able to improve flood simulation. Preliminary analysis were also carried out by using the IMERG early run product of GPM mission. The results highlight that SRPs should be used with caution for rainfall-runoff modelling in the Mediterranean region. Bias correction and model recalibration are necessary steps, even though not always sufficient to achieve satisfactory performances. Indeed, some of the products provide unreliable outcomes, mainly in smaller basins (<500 km2) that, however, represent the main target for flood modelling in the Mediterranean area. The better performances are obtained by integrating different SRPs, and particularly by merging TMPA 3B42-RT and SM2RAIN-ASCAT products. The promising results of the integrated product are expected to increase the confidence on the use of SRPs in hydrological modeling, even in challenging areas as the Mediterranean. REFERENCES Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research, 119(9), 5128-5141, doi:10.1002/2014JD021489. Masseroni, D., Cislaghi, A., Camici, S., Massari, C., Brocca, L. (2017). A reliable rainfall-runoff model for flood forecasting: review and application to a semiurbanized watershed at high flood risk in Italy. Hydrology Research, in press, doi:10.2166/nh.2016.037.

  17. Evaluation of SCaMPR Satellite QPEs for Operational Hydrologic Prediction

    Science.gov (United States)

    LEE, H.; Zhang, Y.; Seo, D.; Kitzmiller, D. H.; Kuligowski, R. J.; Corby, R.

    2011-12-01

    National Weather Service (NWS) River Forecast Centers (RFCs) use rain gauge or radar-gauge multi-sensor quantitative precipitation estimates (QPEs) as the primary rainfall input to their operational hydrologic models. In areas with poor radar and rain gauge coverage, satellite-based QPEs are a potential alternative. In this work, we evaluated the utility of satellite-based QPEs produced via the Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) algorithm for operational hydrologic modeling for a set of basins in Texas and Louisiana for the period of 2000-7. First, we assessed the relative accuracy of two sets of SCaMPR QPEs versus gauge-only QPE, with operational multi-sensor QPEs as the reference. One set used only operational polar orbiting satellite microwave input as the predictors, the other included Tropical Rainfall Measuring Mission (TRMM) rain rates in the calibration process. We then performed hydrologic simulations using these QPEs and evaluated the simulations. Results indicated that a) SCaMPR QPEs showed better/worse skill than the gauge-only QPEs in resolving heavy precipitation at 1-h/24-h time intervals in terms of Critical Success Index (CSI); b) SCaMPR QPEs underperformed gauge-only QPEs in simulating flood events; and c) ingesting TRMM rainfall rates helped enhance the hydrologic utility of SCaMPR QPE, by mitigating the positive bias of SCaMPR QPEs, elevating the detection rates of heavy rainfall, and improving the simulation of flood discharge. Our findings suggest that the superior performance of gauge-only QPEs versus SCaMPR in hydrologic simulations is tied to its better accuracy at 24-h scale. The implication of the scale dependence in the relative performance of SCaMPR QPEs to their potential hydrologic utility is discussed.

  18. Probabilistic forecasts based on radar rainfall uncertainty

    Science.gov (United States)

    Liguori, S.; Rico-Ramirez, M. A.

    2012-04-01

    The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at

  19. A SELF-ADAPTIVE WEIGHT-BASED ROUTING ALGORITHM IN LEO SATELLITE NETWORK%LEO卫星网络中一种自适应权值路由算法

    Institute of Scientific and Technical Information of China (English)

    江玉洁; 姚晔; 梁旭文

    2013-01-01

    针对LEO卫星网络拓扑动态时变的特点,提出一种自适应权值路由算法.该算法综合考虑了路由的时延和切换频率,既能保证低代价路由的选择优先权,又兼顾了网络流量的平衡.采用地面离线计算方式,简化了星上路由计算.另外,采用节点实时状态与权值路由表相结合的方式选择分组路径,使其对网络实时状态具备一定的自适应性.通过仿真分析证明,该算法在应对拥塞时的时延和时延抖动方面的性能表现良好.%According to the characteristics of LEO satellite network in its topology dynamic time-variant, we propose a novel self-adaptive weights-based routing algorithm. The algorithm takes in to account comprehensively the routing delays and handover frequency and balances between the selection priority of low-cost routing and the equilibrium of networks traffic. With the help of off-line computing on the ground, we simplify the computing complexity of the routing in the satellite. Besides, the algorithm selects the packet path by combining the node real-time status with weighted routing table, this makes the algorithm has self-adaptive property to certain extent on real-time status of the network. From the simulation analyses it is proved that the algorithm performs well in tackling with the delay and its jitters when congestion happened in the network.

  20. 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…

  1. Turkish Cloud-Radiation Database (CRD) and Its Application with CDR Bayesian Probability Algorithm

    Science.gov (United States)

    Oztopal, A.; Mugnai, A.; Casella, D.; Formenton, M.; Sano, P.; Sonmez, I.; Sen, Z.; Hsaf Team

    2010-12-01

    ABSTRACT It is rather a very difficult task to determine ground rainfall amounts from few Special Sensor Microwave Imager/Sounder (SSMI/S) channels. Although ground rainfall cannot be observed from the space directly, but knowledge about the cloud physics helps to estimate the amound of ground rainfall. SSMI/S includes so much information about the atmospheric structure, however it cannot provide cloud micro-physical structural information. In such a situation, in the rainfall algorithm, besides the SSMI/S data, it is necessary to incorporate cloud micro-physical properties from an external data source. These properties can be obtained quite simply by the help of Cloud Resolving Model (CRM). Later, in addition to all available data, also micro-physical properties obtained from Radiative Transfer Model (RTM) help to determine the SSMI/S brightness temperatures (Brightness temperatures - TBs), which can then be correlated with Cloud-Radiation Database (CRD) data generation. SSMI/S satellite data and CDR provide a common basis for rainfall prediction procedure through CDR Bayesian probability algorithm, which combines the two sets of data in a scientific manner. The first applications of this algorithm, which is being used up today, is due to various researchers. In this work, in order to establish a reflection of available data processing CDR CRM University of Wisconsin - Non-hydrostatic Modeling System (UW-NMS) model is employed, which is first developed by Prof. Gregory J. Tripoli. It is also used by Turkish Meteorological Service by benefiting from radar network data, and finally 14 simulations are realized in this study. Moreover, one case study is fulfilled by using a 3X3 spatial filtering, and then radar data and result of CDR Bayesian probability algorithm are compared with each other. On 9 September 2009 at 03:40 GMT rainfall event on comparatively flat area matches far better with the retrieval values and hence the spatial rainfall occurrence extent and

  2. 基于改进的NSGA-Ⅱ的卫星星座构型分层优化策略%Layered optimization strategy of satellite constellation configuration by improved NSGA-Ⅱ algorithm

    Institute of Scientific and Technical Information of China (English)

    常辉; 胡修林

    2013-01-01

    For the huge computing cost of integrated design method of Satellite constellation system, layered optimization strategy of satellite constellation configuration was proposed. The core of new strategy is improved non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) in which the non-dominated sorting algorithm was improved. New non-dominated sorting algorithm combines the advantages of Jensen's recursive method and Zheng's fast sorting method and its robustness is better than the recursive method and fast sorting method. The computational complexity of improved NSGA-II algorithm is O(MNlogN) and much smaller than the original NSGA-Ⅱ algorithm's O(MN2). Finally, the new optimization strategy was used to design the configuration of a regional navigation satellite constellation which was simulated by Matlab and the Satellite Tool Kit (STK). The simulation result indicated that the position dilution of precision (PDOP) mean value of the regional navigation satellite constellation achieves 2. 73. And using new optimization strategy the computing cost was reduced to 13. 3% of the computing cost by the original optimization strategy, which laid a good foundation for the practicability of integrated design method of satellite constellation system.%针对卫星星座系统一体化设计方法运算开销庞大的缺陷,提出了卫星星座构型分层优化策略,其核心是改进了非支配排序算法的非劣性分层遗传算法(NSGA-Ⅱ).新的非支配排序算法结合了Jensen的递归方法和快速排序法的优点,其鲁棒性优于递归方法和快速排序法,改进的NS-GA Ⅱ算法其计算复杂度O(MNlogN)也远小于原NSGA-Ⅱ算法的O(MN2).最后,将新的优化策略用于区域导航卫星星座构型的优化设计,并利用Matlab和Satellite Tool Kit (STK)对星座进行了仿真.仿真结果表明,设计的导航星座位置定位精度平均值达到2.73,采用新的优化策略的运算开销为采用原优化策略的13.3%,大大降

  3. 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.

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. Depiction of global drought by reanalysis and real-time satellite precipitation products

    Science.gov (United States)

    Wood, Eric; Zhan, Wang

    2017-04-01

    Reanalysis precipitation is routinely used as a surrogate of observations due to its high spatial and temporal resolution and global coverage, and thus widely used in hydrologic and agricultural applications. The resultant product is largely dependent on the accuracy of reanalysis precipitation datasets. With advances in satellite remote sensing technology, the latest generation of reanalysis systems starts to include real time satellite precipitation estimates as inputs to their assimilation system. In this presentation, reanalysis precipitations datasets and real-time satellite rainfall products are used for the depiction of global drought events by comparing them against an observational reference dataset, namely the Princeton Global Forcing (PGF) dataset, during the period of March 2000 to December 2012. The selected reanalyses are the Climate Forecast System Reanalysis (CFSR), ERA-Interim, and the Modern-Era Retrospective Analysis for Research and Applications, version 1 (MERRA) and 2 (MERRA-2). Three real-time satellite precipitation estimates; namely the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42RT, the Climate Prediction Center (CPC) morphing algorithm (CMORPH) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) are included in the study. Our results show that all datasets depict Sub-Saharan African drought events with limited skill, as opposed to mid latitude regions. Reanalyses and satellite real-time precipitation datasets have comparative skill in the low latitudes. Specific drought events are analyzed that demonstrate the drought depiction from the various datasets. In North America, Asia and Europe, drought events are better replicated and inter-dataset variability is significantly smaller. Overall, temporal characteristics of identified drought events are better estimated than their spatial extent.

  10. 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.

  11. 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.

  12. 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).

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. Inter-satellite links for satellite autonomous integrity monitoring

    Science.gov (United States)

    Rodríguez-Pérez, Irma; García-Serrano, Cristina; Catalán Catalán, Carlos; García, Alvaro Mozo; Tavella, Patrizia; Galleani, Lorenzo; Amarillo, Francisco

    2011-01-01

    A new integrity monitoring mechanisms to be implemented on-board on a GNSS taking advantage of inter-satellite links has been introduced. This is based on accurate range and Doppler measurements not affected neither by atmospheric delays nor ground local degradation (multipath and interference). By a linear combination of the Inter-Satellite Links Observables, appropriate observables for both satellite orbits and clock monitoring are obtained and by the proposed algorithms it is possible to reduce the time-to-alarm and the probability of undetected satellite anomalies.Several test cases have been run to assess the performances of the new orbit and clock monitoring algorithms in front of a complete scenario (satellite-to-satellite and satellite-to-ground links) and in a satellite-only scenario. The results of this experimentation campaign demonstrate that the Orbit Monitoring Algorithm is able to detect orbital feared events when the position error at the worst user location is still under acceptable limits. For instance, an unplanned manoeuvre in the along-track direction is detected (with a probability of false alarm equals to 5 × 10-9) when the position error at the worst user location is 18 cm. The experimentation also reveals that the clock monitoring algorithm is able to detect phase jumps, frequency jumps and instability degradation on the clocks but the latency of detection as well as the detection performances strongly depends on the noise added by the clock measurement system.

  18. 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

  19. Estimation of the soil temperature from the AVHRR-NOAA satellite data applying split window algorithms; Estimacion de la temperatura de suelo desde datos satelitales AVHRR-NOAA aplicando algoritmos de split window

    Energy Technology Data Exchange (ETDEWEB)

    Parra, J.C.; Acevedo, P.S. [Depto. de Ciencias Fisicas, Universidad de la Frontera, Casilla 54-D, Temuco (Chile); Sobrino, J.A. [Dep. de Termodinamica, Universidad de Valencia, 46100 Burjassot, Valencia (Spain); Morales, L.J. [Dep. de Fisica, Universidad Tecnologica Metropolitana, Casilla 9845, Santiago (Chile)

    2006-07-01

    Four algorithms based on the technique of split-window, to estimate the land surface temperature starting from the data provided by the sensor Advanced Very High Resolution radiometer (AVHRR), on board the series of satellites of the National Oceanic and Atmospheric Administration (NOAA), are carried out. These algorithms consider corrections for atmospheric characteristics and emissivity of the different surfaces of the land. Fourteen images AVHRR-NOAA corresponding to the months of October of 2003, and January of 2004 were used. Simultaneously, measurements of soil temperature in the Carillanca hydro-meteorological station were collected in the Region of La Araucana, Chile (38 deg 41 min S; 72 deg 25 min W). Of all the used algorithms, the best results correspond to the model proposed by Sobrino and Raussoni (2000), with a media and standard deviation corresponding to the difference among the temperature of floor measure in situ and the estimated for this algorithm, of -0.06 and 2.11 K, respectively. (Author)

  20. 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.

  1. Spatial Disaggregation of Areal Rainfall Using Two Different Artificial Neural Networks Models

    Directory of Open Access Journals (Sweden)

    Sungwon Kim

    2015-06-01

    Full Text Available The objective of this study is to develop artificial neural network (ANN models, including multilayer perceptron (MLP and Kohonen self-organizing feature map (KSOFM, for spatial disaggregation of areal rainfall in the Wi-stream catchment, an International Hydrological Program (IHP representative catchment, in South Korea. A three-layer MLP model, using three training algorithms, was used to estimate areal rainfall. The Levenberg–Marquardt training algorithm was found to be more sensitive to the number of hidden nodes than were the conjugate gradient and quickprop training algorithms using the MLP model. Results showed that the networks structures of 11-5-1 (conjugate gradient and quickprop and 11-3-1 (Levenberg-Marquardt were the best for estimating areal rainfall using the MLP model. The networks structures of 1-5-11 (conjugate gradient and quickprop and 1-3-11 (Levenberg–Marquardt, which are the inverse networks for estimating areal rainfall using the best MLP model, were identified for spatial disaggregation of areal rainfall using the MLP model. The KSOFM model was compared with the MLP model for spatial disaggregation of areal rainfall. The MLP and KSOFM models could disaggregate areal rainfall into individual point rainfall with spatial concepts.

  2. 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...

  3. Modelling Ecuador's rainfall distribution according to geographical characteristics.

    Science.gov (United States)

    Tobar, Vladimiro; Wyseure, Guido

    2017-04-01

    It is known that rainfall is affected by terrain characteristics and some studies had focussed on its distribution over complex terrain. Ecuador's temporal and spatial rainfall distribution is affected by its location on the ITCZ, the marine currents in the Pacific, the Amazon rainforest, and the Andes mountain range. Although all these factors are important, we think that the latter one may hold a key for modelling spatial and temporal distribution of rainfall. The study considered 30 years of monthly data from 319 rainfall stations having at least 10 years of data available. The relatively low density of stations and their location in accessible sites near to main roads or rivers, leave large and important areas ungauged, making it not appropriate to rely on traditional interpolation techniques to estimate regional rainfall for water balance. The aim of this research was to come up with a useful model for seasonal rainfall distribution in Ecuador based on geographical characteristics to allow its spatial generalization. The target for modelling was the seasonal rainfall, characterized by nine percentiles for each one of the 12 months of the year that results in 108 response variables, later on reduced to four principal components comprising 94% of the total variability. Predictor variables for the model were: geographic coordinates, elevation, main wind effects from the Amazon and Coast, Valley and Hill indexes, and average and maximum elevation above the selected rainfall station to the east and to the west, for each one of 18 directions (50-135°, by 5°) adding up to 79 predictors. A multiple linear regression model by the Elastic-net algorithm with cross-validation was applied for each one of the PC as response to select the most important ones from the 79 predictor variables. The Elastic-net algorithm deals well with collinearity problems, while allowing variable selection in a blended approach between the Ridge and Lasso regression. The model fitting

  4. 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.

  5. 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

  6. 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.

  7. Application and analysis of formation satellites cluster orbit transfer based on genetic algorithm%遗传算法在编队卫星群轨道机动中的应用分析

    Institute of Scientific and Technical Information of China (English)

    李京生; 邓忠民

    2009-01-01

    Orbit transfer of formation satellites was a potential way for future spacecrafts. The Lambert maneuver problem of formation satellites with initial and target positions was studied. Relative motion model including central orbit elements and perturbation was set up using Gim-Alfriend matrix, and an impulse thrust control strategy for coordinated formation keeping on transfer orbit was designed. Genetic algorithm (GA) was applied to optimize the maneuver of formation satellites, with the goal to minimize the total fuel consumption, or weighted index which concerns the fuel consumption and time duration. Factors affecting fuel consumption were analyzed. Simulation results indicate that GA is available to solve the maneuver problem of formation satellites.%卫星群机动是航天器发展的一个方向.针对编队卫星群的Lambert机动问题,采用Gim-Alfriend矩阵建立了包含中心轨道根数和摄动项的群卫星的相对运动模型,设计了转移轨道上的卫星群队形协同保持的脉冲控制策略.应用遗传算法对编队卫星群轨道机动问题进行了优化,优化指标分别为卫星群协同变轨过程中总燃料消耗最少或燃料均衡分配最小.分析了群机动过程中燃料消耗的影响因素.算例结果表明遗传算法可以很好地应用于编队卫星群机动问题.

  8. Day 1 and Beyond for Multi-satellite Retrievals in GPM (Invited)

    Science.gov (United States)

    Huffman, G. J.; Bolvin, D.; Braithwaite, D.; Hsu, K.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

    2013-12-01

    Merged multi-satellite estimates of precipitation constitute one of the key goals of the Global Precipitation Measurement (GPM) mission. These allow users access to quasi-global precipitation estimates at relatively fine time/space scales without detailed knowledge of satellites, sensors, or algorithms. The Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm will provide the at-launch combined-satellite precipitation dataset being produced by the U.S. GPM Science Team. This talk will review IMERG's development as a unified U.S. algorithm that takes advantage of strengths in three current U.S. algorithms, namely the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). The goal is to provide a long-term, fine-scale record of global precipitation from the entire constellation of precipitation-relevant satellite sensors, with input from surface precipitation gauges as feasible. The record will begin January 1998 corresponding with the start of the TRMM and extend as GPM records additional data. Although homogeneity is considered desirable, the use of diverse and evolving data sources works against the strict long-term homogeneity that characterizes a Climate Data Record (CDR). We plan to compute multiple runs at different latencies (most likely around 4 hours, 12 hours, and 2 months after observation time) to address the needs of different groups of users. We will describe the current focus of bringing up the Day-1 IMERG in the Precipitation Processing System using TRMM-based calibration until the GPM sensor algorithms finish check-out in 2014, and then transition to GPM-based calibration after that. However, at the same time we are looking ahead to the next challenges for Day 2 and beyond. This talk will briefly

  9. 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...

  10. A Method to Retrieve Rainfall Rate Over Land from TRMM Microwave Imager Observations

    Science.gov (United States)

    Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    Over tropical land regions, rain rate maxima in mesoscale convective systems revealed by the Precipitation Radar (PR) flown on the Tropical Rainfall Measuring Mission (TRMM) satellite are found to correspond to thunderstorms, i.e., Cbs. These Cbs are reflected as minima in the 85 GHz brightness temperature, T85, observed by the TRMM Microwave Imager (TMI) radiometer. Because the magnitude of TMI observations do not discriminate satisfactorily convective and stratiform rain, we developed here a different TMI discrimination method. In this method, two types of Cbs, strong and weak, are inferred from the Laplacian of T85 at minima. Then, to retrieve rain rate, where T85 is less than 270 K, a weak (background) rain rate is deduced using T85 observations. Furthermore, over a circular area of 10 km radius centered at the location of each T85 minimum, an additional Cb component of rain rate is added to the background rain rate. This Cb component of rain rate is estimated with the help of (T19-T37) and T85 observations. Initially, our algorithm is calibrated with the PR rain rate measurements from 20 MCS rain events. After calibration, this method is applied to TMI data taken from several tropical land regions. With the help of the PR observations, we show that the spatial distribution and intensity of rain rate over land estimated from our algorithm are better than those given by the current TMI-Version-5 Algorithm. For this reason, our algorithm may be used to improve the current state of rain retrievals on land.

  11. 使用物理方法反演中国陆地雨强和水凝物垂直结构%The retrieval of the rainfall intensity and the vertical structure of hydrometers over land in China using the physical algorithm

    Institute of Scientific and Technical Information of China (English)

    王小兰; 程明虎; 马启明; 张乐坚

    2011-01-01

    使用MM5模式模拟了11个降水个例,获得中国陆地的降水廓线,由蒙特卡罗辐射传输模式计算其上行辐射亮温,构成初始云一辐射数据库.采用对照表方法从中获得Db_ml和Db_m2两个数据集,作为GPROF反演算法的先验数据集.对2007年7月的3次强降水过程的地面雨强进行反演,与微波成像仪(TMI)及NESDIS、GSCAT、PCT-SI 3种经验算法反演的雨强比较,发现Db_m2参与反演的地面雨强和TMI的反演结果比较接近,效果明显优于Dbee_ml获得的反演结果,甚至优于3种经验算法的反演结果.使用测雨雷达、地面S波段雷达反演的雨强分别检验上述各算法反演雨强的综合效果,表明Db_m2和TMI反演的结果综合效果较好,经验算法中以PCT-SI综合指数法效果比较好.数据集Db_m2参与反演的可降水在垂直分布和含量上与TMI反演的结果非常一致,与地面雷达反演的液态水含量也较接近;而云水、云冰和可降冰与TMI反演结果在垂直高度分布上较接近,含量上高于TMI的结果.使用数据集Db_m1反演的4种水凝物垂直结构与使用Db_m2的结果在垂直分布上基本一致,可降水含量略低一些,云水含量有时偏低.综上,研究使用数据集Db_m1和Db_m2对地面雨强的反演具有一定的准确性,反演的水凝物结构与TMI反演的结果有相近之处,可作为发展适用于中国的由微波亮温反演地面雨强和水凝物廓线的一种物理方法.%In order to construct the cloud-radiation database , 11 precipitating systems were simulated by the MM5 to obtain the rainfall profiles whose upwelling radiative brightness temperatures were computed by the Monte-Carlo radiative transfer model. Then as the priori databases, the Db_ml and Db_m2 were extracted from the cloud-radiation database by using check list. The rain rates of three precipitation systems during July 2007 were retrieved by importing Db_ml and Db_m2 to the GPROF algorithm respectively

  12. 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.

  13. 改进的NSGA-Ⅱ算法及其在星座优化设计中的应用%Improved NSGA-Ⅱ algorithm and its application in optimization of satellite constellation

    Institute of Scientific and Technical Information of China (English)

    肖宝秋; 刘洋; 戴光明

    2012-01-01

    针对NSGA-Ⅱ算法中的模拟二进制交叉(SBX)算子以及NSGA-Ⅱ在收敛速度及多样性保持方面性能的不足,将反向学习机制(OBL)应用到NSGA-Ⅱ的初始化和进化过程中,并引入一种改进的算术交叉算子.ZDT系列测试函数在收敛性和多样性两个方面的评价结果表明,改进的NSGA-Ⅱ算法在收敛速度、收敛性和多样性上优于NSGA-Ⅱ算法.将改进的NSGA-Ⅱ算法应用于卫星星座优化设计中,仿真结果表明改进的算法在卫星星座优化设计中比较有效.%In order to overcome the shortages of Simulated Binary Crossover(SBX) operator, convergence speed and population diversity of NSGA-Ⅱ, this paper applies the opposition-based learning mechanism to the initialization and evolution process of NSGA-Ⅱ algorithm. In addition, the paper introduces an improved arithmetic crossover operator as well. The convergence and diversity of the proposed algorithm on the series of ZDT test bench-marks are evaluated and the results show that the improved NSGA-Ⅱ algorithm is better than the traditional NSGA-II on converge speed, convergence and diversity. The paper applies the proposed algorithm to the optimization of satellite constellation design and the results indicate that the improved algorithm is very effective on this application.

  14. A distributed model for slope stability analysis using radar detected rainfall intensity

    Science.gov (United States)

    Leoni, L.; Rossi, G.; Catani, F.

    2009-04-01

    The term shallow landslides is widely used in literature to describe a slope movement of limited size that mainly develops in soils up to a maximum of a few meters. Shallow landslides are usually triggered by heavy rainfall because, as the water starts to infiltrate in the soil, the pore-water pressure increases so that the shear strength of the soil is reduced leading to slope failure. We have developed a distributed hydrological-geotechnical model for the forecasting of the temporal and spatial distribution of shallow landslides to be used as a warning system for civil protection purpose. The model uses radar detected rainfall intensity as the input for the hydrological simulation of the infiltration. Using the rainfall pattern detected by the radar is in fact possible to dynamically control the redistribution of groundwater pressure associated with transient infiltration of rain so as to infer the slope stability of the studied area. The model deals with both saturated and unsaturated conditions taking into account the effect of soil suction when the soil is not completely saturated. Two pilot sites have been chosen to develop and test this model: the Armea basin (Liguria, Italy) and the Ischia Island (Campania, Italy). In recent years several severe rainstorms have occurred in both these areas. In at least two cases these have triggered numerous shallow landslides that have caused victims and damaged roads, buildings and agricultural activities. In its current stage, the basic basin-scale model applied for predicting the probable location of shallow landslides involves several stand-alone components. The solution suggested by Iverson for the Richards equation is used to estimate the transient groundwater pressure head distribution according to radar detected rainfall intensity. A soil depth prediction scheme and a limit-equilibrium infinite slope stability algorithm are used to calculate the distributed factor of safety (FS) at different depths and to record

  15. 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

  16. Comparison of ground-based FTIR and Brewer O3 total column with data from two different IASI algorithms and from OMI and GOME-2 satellite instruments

    OpenAIRE

    Blumenstock, T.; J.-M. Flaud; P. Chelin; Eremenko, M.; A. Redondas; Hase, F.; Schneider, M; C. Viatte; Orphal, J

    2011-01-01

    An intercomparison of ozone total column measurements derived from various platforms is presented in this work. Satellite data from Infrared Atmospheric Sounding Interferometer (IASI), Ozone Monitoring Instrument (OMI) and Global Ozone Monitoring Experiment (GOME-2) are compared with data from two ground-based spectrometers (Fourier Transform Infrared spectrometer FTIR and Brewer), located at the Network for Detection of Atmospheric Composition Change (NDACC) super-site of Izaña (Tenerife), m...

  17. Application and Research of PID Algorithm in Shipborne Satellite Communications System%船载卫星通信系统中PID算法的应用与探究

    Institute of Scientific and Technical Information of China (English)

    万冰

    2015-01-01

    In shipborne satellite communications system,how to use azimuth,pitch,roll angle error value of DC motors to adjust the an-tenna stance in order to achieve real-time antenna pointing stability is the most important problem. The algorithm of DC motors’ control will directly affect the work performance of the communication system,so the study of its control algorithm becomes very important. PID algorithm is simple,adaptable and robust,which is very suitable for shipborne satellite communications system. However,the PID algo-rithm is prone to integration saturation and weak immunity situation. Based on the above-described problems,propose some improved al-gorithms,including integral separation,integral limit,incomplete integration and incomplete differential. The improved algorithms can not only prevent too much overshoot,but also accelerate response speed,improving control accuracy and immunity performance.%在船载卫星通信系统中,最重要的问题就是利用方位、俯仰、横摇的角度误差值控制直流电机实时调整天线姿态,使天线波束中心始终准确地对准卫星。直流电机控制算法的优劣将直接影响到船载卫星通信系统的工作性能,因此对船载卫星通信系统中控制算法的研究就显得非常重要。 PID算法原理简单,适应性强,鲁棒性好,非常适合应用于船载卫星通信系统;但它也容易出现积分饱和、抗干扰性差的问题。文中基于上述问题,提出积分分离、积分限幅、不完全积分和不完全微分的改进型PID算法,它不但可以防止产生太大超调,而且加快了响应速度,提高了控制精度和抗干扰能力。

  18. Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

    Science.gov (United States)

    Wolff, David B.; Fisher, Brad L.

    2011-01-01

    Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations a