WorldWideScience

Sample records for satellite precipitation radar

  1. Performance of the Dual-frequency Precipitation Radar on the GPM core satellite

    Science.gov (United States)

    Iguchi, Toshio; Seto, Shinta; Awaka, Jun; Meneghini, Robert; Kubota, Takuji; Oki, Riko; Chandra, Venkatchalam; Kawamoto, Nozomi

    2016-04-01

    The GPM core satellite was launched on February 28, 2014. This paper describes some of the results of precipitation measurements with the Dual-Frequency Precipitation Radar (DPR) on the GPM core satellite. The DPR, which was developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT), consists of two radars: Ku-band precipitation radar (KuPR) and Ka-band radar (KaPR). The performance of the DPR is evaluated by comparing the level 2 products with the corresponding TRMM/PR data and surface rain measurements. The scanning geometry and footprint size of KuPR and those of PR are nearly identical. The major differences between them are the sensitivity, visiting frequency, and the rain retrieval algorithm. KuPR's sensitivity is twice as good as PR. The increase of sensitivity reduces the cases of missing light rain. Since relatively light rain prevails in Japan, the difference in sensitivity may cause a few percentage points in the bias. Comparisons of the rain estimates by GPM/DPR with AMeDAS rain gauge data over Japan show that annual KuPR's estimates over Japan agree quite well with the rain gauge estimates although the monthly or local statistics of these two kinds of data scatter substantially. KuPR's esimates are closer to the gauge estimates than the TRMM/PR. Possible sources of the differences that include sampling errors, sensitivity, and the algorithm are examined.

  2. Assimilation of radar precipitation and satellite data into a NWP model using a physical initialisation scheme

    Science.gov (United States)

    Milan, M.; Schüttemeyer, D.; Venema, V.; Simmer, C.

    2009-04-01

    We implemented a PI (Physical Initialization) method in the non hydrostatic limited-area model COSMO (version 4.2) of the DWD (German Meteorological Service). The goal is the improvement of quantitative rain nowcasting with a high resolution NWP model. Input radar data is a DWD product: the national radar composite for 16 radars with a spatial resolution of one kilometer and a time resolution of 5 minutes. The conversion from reflectivity to rain rate is already made by DWD. This data is interpolated on the LM grid ( 2.8 × 2.8 km resolution) in order to calculate the analysed precipitation rate which depends on the observed precipitation and the model precipitation. The PIB (Physical Initialization Bonn) takes as input the radar based precipitation product and a cloud top height field retrieved from satellite observations, in our case we are using the SAFNWC products generated from Meteosat Second Generation data by DWD. During the assimilation window PIB adjusts the vertical wind, humidity, cloud water and cloud ice in order to force the model state towards the measurements. The most distinctive feature of the algorithm is the adjustment of the vertical wind profile in the framework of a simple precipitation scheme. The PIB assumes that the rain rate is proportional to the vertical humidity flux at cloud base and the vertical wind is adapted according to the conversion efficiency of saturated water vapor into rain water at the cloud base. This parameter is dynamically adjusted by the comparison between the model precipitation and the radar precipitation. The model is tested in convective cases over Germany, an identical twin experiment is used in order to demonstrate the consistency of PIB with the physics of the NWP model. In the tests which we have already performed this method has improved the forecast of the precipitation patterns, as well as the dynamics of the events. These improvements are found both during the assimilation window and for the first hours

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

    Science.gov (United States)

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

    2016-04-01

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

  4. Simulation of Ship-Track versus Satellite-Sensor Differences in Oceanic Precipitation Using an Island-Based Radar

    Directory of Open Access Journals (Sweden)

    Jörg Burdanowitz

    2017-06-01

    Full Text Available The point-to-area problem strongly complicates the validation of satellite-based precipitation estimates, using surface-based point measurements. We simulate the limited spatial representation of light-to-moderate oceanic precipitation rates along ship tracks with respect to areal passive microwave satellite estimates using data from a subtropical island-based radar. The radar data serves to estimate the discrepancy between point-like and areal precipitation measurements. From the spatial discrepancy, two statistical adjustments are derived so that along-track precipitation ship data better represent areal precipitation estimates from satellite sensors. The first statistical adjustment uses the average duration of a precipitation event as seen along a ship track, and the second adjustment uses the median-normalized along-track precipitation rate. Both statistical adjustments combined reduce the root mean squared error by 0.24 mm h − 1 (55% compared to the unadjusted average track of 60 radar pixels in length corresponding to a typical ship speed of 24–34 km h − 1 depending on track orientation. Beyond along-track averaging, the statistical adjustments represent an important step towards a more accurate validation of precipitation derived from passive microwave satellite sensors using point-like along-track surface precipitation reference data.

  5. Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.

    2006-01-01

    Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal

  6. Evaluating Frontal Precipitation with a Spectral Microphysics Mesoscale Model and a Satellite Simulator as Compared to Radar and Radiometer Observations

    Science.gov (United States)

    Han, M.; Braun, S. A.; Matsui, T.; Iguchi, T.; Williams, C. R.

    2013-12-01

    The Advanced Microwave Scanning Radiometer for EOS (AMSR-E) onboard NASA Aqua satellite and a ground-based precipitation profiling radar sampled a frontal precipitation event in the US west coast on 30 to 31 December 2005. Simulations with bulk microphysics schemes in the Weather Research and Forecast (WRF) model have been evaluated with those remote sensing data. In the current study, we continue similar work to evaluate a spectral bin microphysics (SBM) scheme, HUCM, in the WRF model. The Goddard-Satellite Data Simulation Unit (G-SDSU) is used to simulate quantities observed by the radar and radiometer. With advanced representation of cloud and precipitation microphysics processes, the HUCM scheme predicts distributions of 7 hydrometeor species as storms evolve. In this study, the simulation with HUCM well captured the structure of the precipitation and its microphysics characteristics. In addition, it improved total precipitation ice mass simulation and corrected, to a certain extent, the large low bias of ice scattering signature in the bulk scheme simulations. However, the radar reflectivity simulations with the HUCM scheme were not improved as compared to the bulk schemes. We conducted investigations to understand how microphysical processes and properties, such as snow break up parameter and particle fall velocities would influence precipitation size distribution and spectrum of water paths, and further modify radar and/or radiometer simulations. Influence by ice nuclei is going to be examined as well.

  7. 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

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

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    L. Milani

    2015-01-01

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

  10. Improving Quantitative Precipitation Estimation via Data Fusion of High-Resolution Ground-based Radar Network and CMORPH Satellite-based Product

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    Cifelli, R.; Chen, H.; Chandrasekar, V.; Xie, P.

    2015-12-01

    A large number of precipitation products at multi-scales have been developed based upon satellite, radar, and/or rain gauge observations. However, how to produce optimal rainfall estimation for a given region is still challenging due to the spatial and temporal sampling difference of different sensors. In this study, we develop a data fusion mechanism to improve regional quantitative precipitation estimation (QPE) by utilizing satellite-based CMORPH product, ground radar measurements, as well as numerical model simulations. The CMORPH global precipitation product is essentially derived based on retrievals from passive microwave measurements and infrared observations onboard satellites (Joyce et al. 2004). The fine spatial-temporal resolution of 0.05o Lat/Lon and 30-min is appropriate for regional hydrologic and climate studies. However, it is inadequate for localized hydrometeorological applications such as urban flash flood forecasting. Via fusion of the Regional CMORPH product and local precipitation sensors, the high-resolution QPE performance can be improved. The area of interest is the Dallas-Fort Worth (DFW) Metroplex, which is the largest land-locked metropolitan area in the U.S. In addition to an NWS dual-polarization S-band WSR-88DP radar (i.e., KFWS radar), DFW hosts the high-resolution dual-polarization X-band radar network developed by the center for Collaborative Adaptive Sensing of the Atmosphere (CASA). This talk will present a general framework of precipitation data fusion based on satellite and ground observations. The detailed prototype architecture of using regional rainfall instruments to improve regional CMORPH precipitation product via multi-scale fusion techniques will also be discussed. Particularly, the temporal and spatial fusion algorithms developed for the DFW Metroplex will be described, which utilizes CMORPH product, S-band WSR-88DP, and X-band CASA radar measurements. In order to investigate the uncertainties associated with each

  11. A multi-source precipitation approach to fill gaps over a radar precipitation field

    Science.gov (United States)

    Tesfagiorgis, K. B.; Mahani, S. E.; Khanbilvardi, R.

    2012-12-01

    Satellite Precipitation Estimates (SPEs) may be the only available source of information for operational hydrologic and flash flood prediction due to spatial limitations of radar and gauge products. The present work develops an approach to seamlessly blend satellite, radar, climatological and gauge precipitation products to fill gaps over ground-based radar precipitation fields. To mix different precipitation products, the bias of any of the products relative to each other should be removed. For bias correction, the study used an ensemble-based method which aims to estimate spatially varying multiplicative biases in SPEs using a radar rainfall product. Bias factors were calculated for a randomly selected sample of rainy pixels in the study area. Spatial fields of estimated bias were generated taking into account spatial variation and random errors in the sampled values. A weighted Successive Correction Method (SCM) is proposed to make the merging between error corrected satellite and radar rainfall estimates. In addition to SCM, we use a Bayesian spatial method for merging the gap free radar with rain gauges, climatological rainfall sources and SPEs. We demonstrate the method using SPE Hydro-Estimator (HE), radar- based Stage-II, a climatological product PRISM and rain gauge dataset for several rain events from 2006 to 2008 over three different geographical locations of the United States. Results show that: the SCM method in combination with the Bayesian spatial model produced a precipitation product in good agreement with independent measurements. The study implies that using the available radar pixels surrounding the gap area, rain gauge, PRISM and satellite products, a radar like product is achievable over radar gap areas that benefits the scientific community.

  12. Analysis of long term trends of precipitation estimates acquired using radar network in Turkey

    Science.gov (United States)

    Tugrul Yilmaz, M.; Yucel, Ismail; Kamil Yilmaz, Koray

    2016-04-01

    Precipitation estimates, a vital input in many hydrological and agricultural studies, can be obtained using many different platforms (ground station-, radar-, model-, satellite-based). Satellite- and model-based estimates are spatially continuous datasets, however they lack the high resolution information many applications often require. Station-based values are actual precipitation observations, however they suffer from their nature that they are point data. These datasets may be interpolated however such end-products may have large errors over remote locations with different climate/topography/etc than the areas stations are installed. Radars have the particular advantage of having high spatial resolution information over land even though accuracy of radar-based precipitation estimates depends on the Z-R relationship, mountain blockage, target distance from the radar, spurious echoes resulting from anomalous propagation of the radar beam, bright band contamination and ground clutter. A viable method to obtain spatially and temporally high resolution consistent precipitation information is merging radar and station data to take advantage of each retrieval platform. An optimally merged product is particularly important in Turkey where complex topography exerts strong controls on the precipitation regime and in turn hampers observation efforts. There are currently 10 (additional 7 are planned) weather radars over Turkey obtaining precipitation information since 2007. This study aims to optimally merge radar precipitation data with station based observations to introduce a station-radar blended precipitation product. This study was supported by TUBITAK fund # 114Y676.

  13. Radar-Derived Quantitative Precipitation Estimation Based on Precipitation Classification

    Directory of Open Access Journals (Sweden)

    Lili Yang

    2016-01-01

    Full Text Available A method for improving radar-derived quantitative precipitation estimation is proposed. Tropical vertical profiles of reflectivity (VPRs are first determined from multiple VPRs. Upon identifying a tropical VPR, the event can be further classified as either tropical-stratiform or tropical-convective rainfall by a fuzzy logic (FL algorithm. Based on the precipitation-type fields, the reflectivity values are converted into rainfall rate using a Z-R relationship. In order to evaluate the performance of this rainfall classification scheme, three experiments were conducted using three months of data and two study cases. In Experiment I, the Weather Surveillance Radar-1988 Doppler (WSR-88D default Z-R relationship was applied. In Experiment II, the precipitation regime was separated into convective and stratiform rainfall using the FL algorithm, and corresponding Z-R relationships were used. In Experiment III, the precipitation regime was separated into convective, stratiform, and tropical rainfall, and the corresponding Z-R relationships were applied. The results show that the rainfall rates obtained from all three experiments match closely with the gauge observations, although Experiment II could solve the underestimation, when compared to Experiment I. Experiment III significantly reduced this underestimation and generated the most accurate radar estimates of rain rate among the three experiments.

  14. Satellite radar for monitoring forest resources

    Science.gov (United States)

    Hoffer, Roger M.; Lee, Kyu-Sung

    1990-01-01

    An evaluation is made of the computer analysis results of a study which used Seasat satellite radar data obtained in 1978 and Shuttle Imaging Radar-B data obtained in 1984. The change-detection procedures employed demonstrate that deforestation and reforestation activities can be effectively monitored on the basis of radar data gathered at satellite altitudes. The computer-processing techniques applied to the data encompassed (1) overlay display, (2) ratios, (3) differences, (4) principal-component analysis, and (5) classification; of these, overlay display is noted to quickly and easily yield a qualitative display of the multidate data.

  15. Tropical convective systems life cycle characteristics from geostationary satellite and precipitating estimates derived from TRMM and ground weather radar observations for the West African and South American regions

    Science.gov (United States)

    Fiolleau, T.; Roca, R.; Angelis, F. C.; Viltard, N.

    2012-12-01

    In the tropics most of the rainfall comes in the form of individual storm events embedded in the synoptic circulations (e.g., monsoons). Understanding the rainfall and its variability hence requires to document these highly contributing tropical convective systems (MCS). Our knowledge of the MCS life cycle, from a physical point of view mainly arises from individual observational campaigns heavily based on ground radar observations. While this large part of observations enabled the creation of conceptual models of MCS life cycle, it nevertheless does not reach any statistically significant integrated perspective yet. To overcome this limitation, a composite technique, that will serve as a Day-1 algorithm for the Megha-Tropiques mission, is considered in this study. this method is based on a collocation in space and time of the level-2 rainfall estimates (BRAIN) derived from the TMI radiometer onboard TRMM with the cloud systems identified by a new MCS tracking algorithm called TOOCAN and based on a 3-dimensional segmentation (image + time) of the geostationary IR imagery. To complete this study, a similar method is also developed collocating the cloud systems with the precipitating features derived from the ground weather radar which has been deployed during the CHUVA campaign over several Brazilian regions from 2010 up to now. A comparison of the MCSs life cycle is then performed for the 2010-2012 summer seasons over the West African, and South American regions. On the whole region of study, the results show that the temporal evolution of the cold cloud shield associated to MCSs describes a symmetry between the growth and the decay phases. It is also shown that the parameters of the conceptual model of MCSs are strongly correlated, reducing thereby the problem to a single degree of freedom. At the system scale, over both land and oceanic regions, rainfall is described by an increase at the beginning (the first third) of the life cycle and then smoothly decreases

  16. Haystack Ultrawideband Satellite Imaging Radar

    Science.gov (United States)

    2014-09-01

    enable long-range imaging. In 2013, a major upgrade to the facility was completed, adding a millimeter - wave W-band radar capability to Haystack’s X...diameter antenna was completely rebuilt to provide a 100 μm root-mean-square (rms) surface accuracy to support operation at the 3 mm wave - length (W...electromagnetic wave propagation through the troposphere. − The signal processing system lev- eraged Lincoln Laboratory‘s Radar Open Systems

  17. Monitoring civil infrastructure using satellite radar interferometry

    NARCIS (Netherlands)

    Chang, L.

    2015-01-01

    Satellite radar interferometry (InSAR) is a precise and efficient technique to monitor deformation on Earth with millimeter precision. Most InSAR applications focus on geophysical phenomena, such as earthquakes, volcanoes, or subsidence. Monitoring civil infrastructure with InSAR is relatively new,

  18. Investigating Satellite Microwave observations of Precipitation in Different Climate Regimes

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    Wang, N.; Ferraro, R. R.

    2013-12-01

    Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperature characteristics similar to precipitation Ongoing work by GPM microwave radiometer team is constructing databases through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The original data sets will focus on stratification by emissivity class, surface temperature and total perceptible water. We'll perform sensitivity studies to determine the potential role of ancillary data (e.g., land surface temperature, snow cover/water equivalent, etc.) to improve precipitation estimation over land in different climate regimes, including rain and snow. In other words, what information outside of the radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

  19. Simulation of Space-borne Radar Observation from High Resolution Cloud Model - for GPM Dual frequency Precipitation Radar -

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    Kim, H.; Meneghini, R.; Jones, J.; Liao, L.

    2011-12-01

    A comprehensive space-borne radar simulator has been developed to support active microwave sensor satellite missions. The two major objectives of this study are: 1) to develop a radar simulator optimized for the Dual-frequency Precipitation Radar (KuPR and KaPR) on the Global Precipitation Measurement Mission satellite (GPM-DPR) and 2) to generate the synthetic test datasets for DPR algorithm development. This simulator consists of two modules: a DPR scanning configuration module and a forward module that generates atmospheric and surface radar observations. To generate realistic DPR test data, the scanning configuration module specifies the technical characteristics of DPR sensor and emulates the scanning geometry of the DPR with a inner swath of about 120 km, which contains matched-beam data from both frequencies, and an outer swath from 120 to 245 km over which only Ku-band data will be acquired. The second module is a forward model used to compute radar observables (reflectivity, attenuation and polarimetric variables) from input model variables including temperature, pressure and water content (rain water, cloud water, cloud ice, snow, graupel and water vapor) over the radar resolution volume. Presently, the input data to the simulator come from the Goddard Cumulus Ensemble (GCE) and Weather Research and Forecast (WRF) models where a constant mass density is assumed for each species with a particle size distribution given by an exponential distribution with fixed intercept parameter (N0) and a slope parameter (Λ) determined from the equivalent water content. Although the model data do not presently contain mixed phase hydrometeors, the Yokoyama-Tanaka melting model is used along with the Bruggeman effective dielectric constant to replace rain and snow particles, where both are present, with mixed phase particles while preserving the snow/water fraction. For testing one of the DPR retrieval algorithms, the Surface Reference Technique (SRT), the simulator uses

  20. Regional Bias of Satellite Precipitation Estimates

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    Modrick, T. M.; Georgakakos, K. P.; Spencer, C. R.

    2012-12-01

    Satellite-based estimates of precipitation have improved the spatial availability of precipitation data particularly for regions with limited gauge networks due to limited accessibility or infrastructure. Understanding the quality and reliability of satellite precipitation estimates is important, especially when the estimates are utilitized for real-time hydrologic forecasting and for fast-responding phenomena. In partnership with the World Meteorological Organization (WMO), the U.S. Agency of International Development (USAID) and the National Ocean and Atmospheric Administration (NOAA), the Hydrologic Research Center has begun implementation of real-time flash flood warning systems for diverse regions around the world. As part of this effort, bias characteristics of satellite precipitation have been examined in these various regions, such includes portions of Southeastern Asia, Southeastern Europe, the Middle East, Central America, and the southern half of the African continent. The work has focused on the Global Hydro-Estimator (GHE) precipitation product from NOAA/NESDIS. These real-time systems utilize the GHE given low latency times of this product. This presentation focuses on the characterization of precipitation bias as compared to in-situ gauge records, and the regional variations or similarities. Additional analysis is currently underway considering regional bias for other satellite precipitation products (e.g., CMORPH) for comparison with the GHE results.

  1. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  2. Bistatic synthetic aperture radar using two satellites

    Science.gov (United States)

    Tomiyasu, K.

    1978-01-01

    The paper demonstrates the feasibility of a bistatic synthetic aperture radar (BISAR) utilizing two satellites. The proposed BISAR assumes that the direction of the two narrow antenna beams are programmed to coincide over the desired area to be imaged. Functionally, the transmitter and receiver portions can be interchanged between the two satellites. The two satellites may be in one orbit plane or two different orbits such as geosynchronous and low-earth orbits. The pulse repetition frequency and imaging geometry are constrained by contours of isodops and isodels. With two images of the same area viewed from different angles, it is possible in principle to derive three-dimensional stereo images. Applications of BISAR include topography, water resource management, and soil moisture determination.. Advantages of BISAR over a monostatic SAR are mentioned, including lower transmitter power and greater ranges in incidence angle and coverage.

  3. 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

  4. Evaluation of clouds and precipitation in the ECHAM5 general circulation model using CALIPSO and CloudSat satellite data

    OpenAIRE

    Nam, Christine C. W.; Quaas, Johannes

    2015-01-01

    Observations from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat satellites are used to evaluate clouds and precipitation in the ECHAM5 general circulation model. Active lidar and radar instruments on board CALIPSO and CloudSat allow the vertical distribution of clouds and their optical properties to be studied on a global scale. To evaluate the clouds modeled by ECHAM5 with CALIPSO and CloudSat, the lidar and radar satellite simulators of the Cloud ...

  5. A global satellite-assisted precipitation climatology

    Science.gov (United States)

    Funk, C.; Verdin, A.; Michaelsen, J.; Peterson, P.; Pedreros, D.; Husak, G.

    2015-10-01

    Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high-resolution (0.05°) global precipitation climatologies that perform reasonably well in data-sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate

  6. A global satellite assisted precipitation climatology

    Directory of Open Access Journals (Sweden)

    C. Funk

    2015-05-01

    Full Text Available Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05° global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology

  7. A global satellite assisted precipitation climatology

    Science.gov (United States)

    Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

    2015-01-01

    Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate

  8. Precipitation Estimation Using Combined Radar/Radiometer Measurements Within the GPM Framework

    Science.gov (United States)

    Hou, Arthur

    2012-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. The GPM mission centers upon the deployment of a Core Observatory in a 65o non-Sun-synchronous orbit to serve as a physics observatory and a transfer standard for intersatellite calibration of constellation radiometers. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles needed for improving precipitation retrievals from microwave sensors. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1

  9. Observing convection with satellite, radar, and lightning measurements

    Science.gov (United States)

    Hamann, Ulrich; Nisi, Luca; Clementi, Lorenzo; Ventura, Jordi Figueras i.; Gabella, Marco; Hering, Alessandro M.; Sideris, Ioannis; Trefalt, Simona; Germann, Urs

    2015-04-01

    Heavy precipitation, hail, and wind gusts are the fundamental meteorological hazards associated with strong convection and thunderstorms. The thread is particularly severe in mountainous areas, e.g. it is estimated that on average between 50% and 80% of all weather-related damage in Switzerland is caused by strong thunderstorms (Hilker et al., 2010). Intense atmospheric convection is governed by processes that range from the synoptic to the microphysical scale and are considered to be one of the most challenging and difficult weather phenomena to predict. Even though numerical weather prediction models have some skills to predict convection, in general the exact location of the convective initialization and its propagation cannot be forecasted by these models with sufficient precision. Hence, there is a strong interest to improve the short-term forecast by using statistical, object oriented and/or heuristic nowcasting methods. MeteoSwiss has developed several operational nowcasting systems for this purpose such as TRT (Hering, 2008) and COALITION (Nisi, 2014). In this contribution we analyze the typical development of convection using measurements of the Swiss C-band Dual Polarization Doppler weather radar network, the MSG SEVIRI satellite, and the Météorage lighting network. The observations are complemented with the analysis and forecasts of the COSMO model. Special attention is given to the typical evolutionary stages like the pre-convective environment, convective initiation, cloud top glaciation, start, maximum, and end of precipitation and lightning activity. The pre-convective environment is examined using instability indices derived from SEVIRI observations and the COSMO forecasts. During the early development satellite observations are used to observe the rise of the cloud top, the growth of the cloud droplet or crystals, and the glaciation of the cloud top. SEVIRI brightness temperatures, channel differences, and temporal trends as suggested by

  10. Radar Observations and Simulation of the Melting Layer of Precipitation

    NARCIS (Netherlands)

    Klaassen, Wim

    1988-01-01

    The melting layer in precipitation is physically modeled and compared with high resolution Doppler radar data. The model includes a new formulation of the dielectric properties and can handle all ice particles with densities ranging from pure snow to hail. The air temperature is calculated from the

  11. Radar Observations and Simulation of the Melting Layer of Precipitation

    NARCIS (Netherlands)

    Klaassen, Wim

    1988-01-01

    The melting layer in precipitation is physically modeled and compared with high resolution Doppler radar data. The model includes a new formulation of the dielectric properties and can handle all ice particles with densities ranging from pure snow to hail. The air temperature is calculated from the

  12. Measurements of Cumulonimbus Clouds using quantitative satellite and radar data

    Science.gov (United States)

    Negri, A. J.; Reynolds, D. W.; Maddox, R. A.

    1977-01-01

    Results are reported for a preliminary study of SMS-2 digital brightness and IR data obtained at frequent 5-7.5 min intervals. The clouds studied were over the Central and Great Plains in midlatitudes and thus were typical of an environment much different from that of the tropical oceans. The satellite data are compared to radar data for both a severe weather event and weak thundershower activity of the type which might be a target for weather modification efforts. The relative importance of short time interval satellite data is shown for both cases, and possible relationships between the two types of data are presented. It is concluded that (1) using a threshold technique for visible reflected brightness, precipitating vs. nonprecipitating clouds can be discriminated; (2) brightness is well related to cloud size and shape; and (3) satellite-derived growth rates may be a significant parameter to be used in determining storm severity, especially if rapid time sequence data are used during the development phase of the storm.

  13. Satellite Monitoring for REDD: Radar vs. Optical

    Science.gov (United States)

    Mitchard, E. T.; Saatchi, S. S.; Ryan, C.; Woollen, E.; Goodman, L. E.; Williams, M.; Gerard, F.; Starkey, M.; Meir, P.

    2010-12-01

    The proposed REDD (Reducing Emissions from Deforestation and Degradation) protocol will only succeed in reducing emissions if deforestation and degradation can be accurately monitored. Ground surveys are prohibitively expensive over large areas, so satellite monitoring will be essential for independently monitoring deforestation and degradation rates, and thus calculating payments. In addition, remote sensing will be needed for developing historical baselines. It is clear that different methodologies will be needed for different project areas, scales and threat types. In addition different methodologies are needed depending on the capabilities of the countries in question: in the context of Africa for example, in-country monitoring tends to be at a basic level, yet for REDD it is important that countries are able to do their own monitoring, so simple methods must be developed and tested. In this paper we present change detection results for different remote sensing methodologies for potential REDD projects in Cameroon and Mozambique. We have shown previously that a good relationship exists between aboveground biomass (AGB) and L-band radar backscatter (Mitchard et al. 2009). The errors in estimation of absolute biomass were still relatively high, in the region of ±25 %. However, it is suspected that some of these errors are intransient, being due to the structure of the landscape and vegetation within a site, and so it has been predicted that errors in change detection are smaller than those for absolute estimation. We present evidence from these sites that this is indeed correct, using ALOS PALSAR L-band radar data from 2007, 2008 and 2009. Optical satellite data is widely used for monitoring deforestation, for example the excellent system run by INPE in Brazil. However, while optical data is good at detecting deforestation occurring progressively in large clear-fell blocks, as in the Amazon, it is less good at detecting small-scale deforestation or degradation

  14. A Generalized Statistical Uncertainty Model for Satellite Precipitation Products

    Science.gov (United States)

    Sarachi, S.

    2013-12-01

    A mixture model of Generalized Normal Distribution and Gamma distribution (GND-G) is used to model the joint probability distribution of satellite-based and stage IV radar rainfall under a given spatial and temporal resolution (e.g. 1°x1° and daily rainfall). The distribution parameters of GND-G are extended across various rainfall rates and spatial and temporal resolutions. In the study, GND-G is used to describe the uncertainty of the estimates from Precipitation Estimation from Remote Sensing Information using Artificial Neural Network algorithm (PERSIANN). The stage IV-based multi-sensor precipitation estimates (MPE) are used as reference measurements .The study area for constructing the uncertainty model covers a 15°×15°box of 0.25°×0.25° cells over the eastern United States for summer 2004 to 2009. Cells are aggregated in space and time to obtain data with different resolutions for the construction of the model's parameter space. Result shows that comparing to the other statistical uncertainty models, GND-G fits better than the other models, such as Gaussian and Gamma distributions, to the reference precipitation data. The impact of precipitation uncertainty to the stream flow is further demonstrated by Monte Carlo simulation of precipitation forcing in the hydrologic model. The NWS DMIP2 basins over Illinois River basin south of Siloam is selected in this case study. The data covers the time period of 2006 to 2008.The uncertainty range of stream flow from precipitation of GND-G distributions calculated and will be discussed.

  15. Validation of TRMM Precipitation Radar Through Comparison of its Multi-Year Measurements to Ground-Based Radar

    Science.gov (United States)

    Liao, Liang; Meneghini, Robert

    2010-01-01

    A procedure to accurately resample spaceborne and ground-based radar data is described, and then applied to the measurements taken from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and the ground-based Weather Surveillance Radar-1988 Doppler (WSR-88D or WSR) for the validation of the PR measurements and estimates. Through comparisons with the well-calibrated, non-attenuated WSR at Melbourne, Florida for the period 1998-2007, the calibration of the Precipitation Radar (PR) aboard the TRMM satellite is checked using measurements near the storm top. Analysis of the results indicates that the PR, after taking into account differences in radar reflectivity factors between the PR and WSR, has a small positive bias of 0.8 dB relative to the WSR, implying a soundness of the PR calibration in view of the uncertainties involved in the comparisons. Comparisons between the PR and WSR reflectivities are also made near the surface for evaluation of the attenuation-correction procedures used in the PR algorithms. It is found that the PR attenuation is accurately corrected in stratiform rain but is underestimated in convective rain, particularly in heavy rain. Tests of the PR estimates of rainfall rate are conducted through comparisons in the overlap area between the TRMM overpass and WSR scan. Analyses of the data are made both on a conditional basis, in which the instantaneous rain rates are compared only at those pixels where both the PR and WSR detect rain, and an unconditional basis, in which the area-averaged rain rates are estimated independently for the PR and WSR. Results of the conditional rain comparisons show that the PR-derived rain is about 9% greater and 19% less than the WSR estimates for stratiform and convective storms, respectively. Overall, the PR tends to underestimate the conditional mean rain rate by 8% for all rain categories, a finding that conforms to the results of the area-averaged rain (unconditional) comparisons.

  16. PoPSat: The Polar Precipitation Satellite Mission

    Science.gov (United States)

    Binder, Matthias J.; Agten, Dries; Arago-Higueras, Nadia; Borderies, Mary; Diaz-Schümmer, Carlos; Jamali, Maryam; Jimenez-Lluva, David; Kiefer, Joshua; Larsson, Anna; Lopez-Gilabert, Lola; Mione, Michele; Mould, Toby JD; Pavesi, Sara; Roth, Georg; Tomicic, Maja

    2017-04-01

    The terrestrial water cycle is one of many unique regulatory systems on planet Earth. It is directly responsible for sustaining biological life on land and human populations by ensuring sustained crop yields. However, this delicate balanced system continues to be influenced significantly by a changing climate, which has had drastic impacts particularly on the polar regions. Precipitation is a key process in the weather and climate system, due to its storage, transport and release of latent heat in the atmosphere. It has been extensively investigated in low latitudes, in which detailed models have been established for weather prediction. However, a gap has been left in higher latitudes above 65°, which show the strongest response to climate changes and where increasing precipitations have been foreseen in the future. In order to establish a global perspective of atmospheric processes, space observation of high-latitude areas is crucial to produce globally consistent data. The increasing demand for those data has driven a critical need to devise a mission which fills the gaps in current climate models. The authors propose the Polar Precipitation Satellite (PoPSat), an innovative satellite mission to provide enhanced observation of light and medium precipitation, focusing on snowfall and light rain in high latitudes. PoPSat is the first mission aimed to provide high resolution 3D structural information about snow and light precipitation systems and cloud structure in the covered areas. The satellite is equipped with a dual band (Ka and W band) phased-array radar. These antennas provide a horizontal resolution of 2 km and 4 km respectively which will exceed all other observations made to date at high-latitudes, while providing the additional capability to monitor snowfall. The data gathered will be compatible and complementary with measurements made during previous missions. PoPSat has been designed to fly on a sun-synchronous, dawn-dusk orbit at 460 km. This orbit

  17. 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

  18. Combination of radar and daily precipitation data to estimate meaningful sub-daily point precipitation extremes

    Science.gov (United States)

    Bárdossy, András; Pegram, Geoffrey

    2017-01-01

    The use of radar measurements for the space time estimation of precipitation has for many decades been a central topic in hydro-meteorology. In this paper we are interested specifically in daily and sub-daily extreme values of precipitation at gauged or ungauged locations which are important for design. The purpose of the paper is to develop a methodology to combine daily precipitation observations and radar measurements to estimate sub-daily extremes at point locations. Radar data corrected using precipitation-reflectivity relationships lead to biased estimations of extremes. Different possibilities of correcting systematic errors using the daily observations are investigated. Observed gauged daily amounts are interpolated to unsampled points and subsequently disaggregated using the sub-daily values obtained by the radar. Different corrections based on the spatial variability and the subdaily entropy of scaled rainfall distributions are used to provide unbiased corrections of short duration extremes. Additionally a statistical procedure not based on a matching day by day correction is tested. In this last procedure as we are only interested in rare extremes, low to medium values of rainfall depth were neglected leaving a small number of L days of ranked daily maxima in each set per year, whose sum typically comprises about 50% of each annual rainfall total. The sum of these L day maxima is first iterpolated using a Kriging procedure. Subsequently this sum is disaggregated to daily values using a nearest neighbour procedure. The daily sums are then disaggregated by using the relative values of the biggest L radar based days. Of course, the timings of radar and gauge maxima can be different, so the method presented here uses radar for disaggregating daily gauge totals down to 15 min intervals in order to extract the maxima of sub-hourly through to daily rainfall. The methodologies were tested in South Africa, where an S-band radar operated relatively continuously at

  19. North and northeast Greenland ice discharge from satellite radar interferometry

    DEFF Research Database (Denmark)

    Rignot, E.J.; Gogineni, S.P.; Krabill, W.B.

    1997-01-01

    Ice discharge from north and northeast Greenland calculated from satellite radar interferometry data of 14 outlet glaciers is 3.5 times that estimated from iceberg production. The satellite estimates, obtained at the grounding line of the outlet glaciers, differ from those obtained at the glacier...

  20. Space time disaggregation of precipitation using daily precipitation and radar observations.

    Science.gov (United States)

    Bàrdossy, Andràs; Pegram, Geoffrey

    2016-04-01

    Radar measurements provide useful information on the spatial and temporal distribution of precipitation. Unfortunately the measurements are often erroneous and biased. Traditional raingauge based observations offer point values. The purpose of this contribution is to investigate the possibility of combining high frequency pluviometer rainfall observations, daily data and radar measurements to obtain sets of possible realizations of the "real" space-time distribution of precipitation. The stochastic model uses space-time copulas, and simulates realizations using a random mixing approach. The method does not intend to provide a single best estimate, but instead to generate many realizations of precipitation fields using the stochastic model. The realizations reflect the different sources of information and represent the corresponding uncertainty. Different levels of information derived from considering radar data are investigated starting with the use of (i) radar zeros only, then (ii) intensity classes and (iii) rank based combinations. The methods are tested and compared on selected events recorded by a dense radar network in South-West Germany, which has been carefully bias corrected.

  1. Current status of the dual-frequency precipitation radar on the global precipitation measurement core spacecraft and the new version of GPM standard products

    Science.gov (United States)

    Furukawa, K.; Nio, T.; Konishi, T.; Masaki, T.; Kubota, T.; Oki, R.; Iguchi, T.

    2016-10-01

    The Dual-frequency Precipitation Radar (DPR) on the Global Precipitation Measurement (GPM) core satellite was developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT). The objective of the GPM mission is to observe global precipitation more frequently and accurately. The GPM core satellite is a joint product of National Aeronautics and Space Administration (NASA), JAXA and NICT. NASA developed the satellite bus and the GPM Microwave Imager (GMI), and JAXA and NICT developed the DPR. The inclination of the GPM core satellite is 65 degrees, and the nominal flight altitude is 407 km. The non-sunsynchronous circular orbit is necessary for measuring the diurnal change of rainfall. The DPR consists of two radars, which are Ku-band precipitation radar (KuPR) and Ka-band precipitation radar (KaPR). GPM core observatory was successfully launched by H2A launch vehicle on Feb. 28, 2014. DPR keeps its performances on orbit after launch. DPR products were released to the public on Sep. 2, 2014. JAXA is continuing DPR trend monitoring, calibration and validation operations to confirm that DPR keeps its function and performance on orbit. JAXA have started to provide new version (Version 4) of GPM standard products on March 3, 2016. Various improvements of the DPR algorithm were implemented in the Version 4 product. Moreover, the latent heat product based on the Spectral Latent Heating (SLH) algorithm is available since Version 4 product. Current orbital operation status of the GPM/DPR and highlights of the Version 4 product are reported.

  2. Assimilation of radar quantitative precipitation estimations in the Canadian Precipitation Analysis (CaPA)

    Science.gov (United States)

    Fortin, Vincent; Roy, Guy; Donaldson, Norman; Mahidjiba, Ahmed

    2015-12-01

    The Canadian Precipitation Analysis (CaPA) is a data analysis system used operationally at the Canadian Meteorological Center (CMC) since April 2011 to produce gridded 6-h and 24-h precipitation accumulations in near real-time on a regular grid covering all of North America. The current resolution of the product is 10-km. Due to the low density of the observational network in most of Canada, the system relies on a background field provided by the Regional Deterministic Prediction System (RDPS) of Environment Canada, which is a short-term weather forecasting system for North America. For this reason, the North American configuration of CaPA is known as the Regional Deterministic Precipitation Analysis (RDPA). Early in the development of the CaPA system, weather radar reflectivity was identified as a very promising additional data source for the precipitation analysis, but necessary quality control procedures and bias-correction algorithms were lacking for the radar data. After three years of development and testing, a new version of CaPA-RDPA system was implemented in November 2014 at CMC. This version is able to assimilate radar quantitative precipitation estimates (QPEs) from all 31 operational Canadian weather radars. The radar QPE is used as an observation source and not as a background field, and is subject to a strict quality control procedure, like any other observation source. The November 2014 upgrade to CaPA-RDPA was implemented at the same time as an upgrade to the RDPS system, which brought minor changes to the skill and bias of CaPA-RDPA. This paper uses the frequency bias indicator (FBI), the equitable threat score (ETS) and the departure from the partial mean (DPM) in order to assess the improvements to CaPA-RDPA brought by the assimilation of radar QPE. Verification focuses on the 6-h accumulations, and is done against a network of 65 synoptic stations (approximately two stations per radar) that were withheld from the station data assimilated by Ca

  3. Interdisciplinary Earth Science Applications Using Satellite Radar Altimetry

    Science.gov (United States)

    Kuo, C.; Shum, C.; Lee, H.; Dai, C.; Yi, Y.

    2012-12-01

    Satellite altimetry was conceived as a space geodetic concept for ocean surface topography mapping in the NASA-sponsored 1969 Williamstown, MA Conference, and was tested as part of the passive and active radar payload (S192), along with a radiometer and a scatterometer, on Skylab-1 in May 14, 1973. Since then, numerous radar and laser satellite altimetry missions orbiting/flying-by the Earth, Mars, Mercury, Titan and the Moon have been launched, evolving from the original scientific objective of marine gravity field mapping to a geodetic tool to address interdisciplinary Earth and planetary sciences. The accuracy of the radar altimeter has improved from 0.9 m RMS for the S-192 Skylab Ku-band compressed-pulse altimeter, to 2 cm RMS (2 second average) for the dual-frequency pulse-limited radar altimetry and associated sensors onboard TOPEX/POSEIDON. Satellite altimetry has evolved into a unique cross-disciplinary geodetic tool in addressing contemporary Earth science problems including sea-level rise, large-scale general ocean circulation, ice-sheet mass balance, terrestrial hydrology, and bathymetry. Here we provide a concise review and describe specific results on the additional recent innovative and unconventional applications of interdisciplinary science research using satellite radar altimetry, including geodynamics, land subsidence, snow depth, wetland and cold region hydrology.

  4. Radar-Derived Characteristics of Precipitation in South East Queensland

    Energy Technology Data Exchange (ETDEWEB)

    Peter, Justin R; May, Peter T; Potts, Rodney J; Collis, Scott M.; Manton, Michael J; Wilson, Louise

    2015-10-01

    Statistics of radar-retrievals of precipitation are presented. A K-means clustering algorithm is applied to an historical record of radiosonde measurements which identified three major synoptic regimes; a dry, stable regime with mainly westerly winds prevalent during winter, a moist south easterly trade wind regime and a moist northerly regime both prevalent during summer. These are referred to as westerly, trade wind and northerly regimes, respectively. Cell statistics are calculated using an objective cell identification and tracking methodology on data obtained from a nearby S-band radar. Cell statistics are investigated for the entire radar observational period and also during sub-periods corresponding to the three major synoptic regimes. The statistics investigated are cell initiation location, area, rainrate, volume, height, height of the maximum reflectivity, volume greater than 40 dBZ and storm speed and direction. Cells are found predominantly along the elevated topography. The cell statistics reveal that storms which form in the dry, stable westerly regime are of comparable size to the deep cells which form in the northerly regime, larger than those in the trade regime and, furthermore, have the largest rainrate. However, they occur less frequently and have shorter lifetimes than cells in the other regimes. Diurnal statistics of precipitation area and rainrate exhibit early morning and mid afternoon peaks, although the areal coverage lags the rainrate by several hours indicative of a transition from convective to stratiform precipitation. The probability distributions of cell area, rainrate, volume, height and height of the maximum re ectivity are found to follow lognormal distributions.

  5. On the use of Cloud Profiling Radar to detect solid precipitation over Antarctica at different scales

    Science.gov (United States)

    Milani, Lisa; Kulie, Mark S.; Casella, Daniele; D'Adderio, Leo Pio; Dietrich, Stefano; L'Ecuyer, Tristan S.; Panegrossi, Giulia; Porcù, Federico; Sanò, Paolo; Wood, Norman B.

    2016-04-01

    Precipitation is a key geophysical parameter in understanding the Antarctic climate. However, the particular environmental conditions of the Continent make it difficult to measure directly solid precipitation rate and accumulation from either ground based instruments or passive space-borne sensors. A significant improvement in the study of solid precipitation over Antarctica is possible by using active space-borne instruments: the Cloud Profiling Radar (CPR), a nadir-pointing 94 GHz radar, on board the low earth orbit CloudSat satellite. Five years (2006-2011) of CPR data and products over Antarctica are analyzed to investigate the characteristics of solid precipitation. The aim of this work is twofold: 1) to compare a global snowfall rate retrieval algorithm (Kulie and Bennartz, 2009) with the official CloudSat product (2C-SNOW-PROFILE) over the Antarctic environment, evaluating the sensitivity of the estimated snow fields to: ground clutter, choice of reflectivity-snowfall rate relationship (Z-S), presence of melting snow/liquid precipitation; 2) to provide snow fall rates and accumulation at different scales over Antarctica, evaluating the impact of background physiography and seasonal cycle on the precipitation distribution. Further comparisons are also performed with ERA-Interim snowfall fields and point-like snow stack height measurements by acoustic depth gauges. Results show that the difference between the Kulie and Bennartz (2009) algorithm and the 2C-SNOW-PROFILE product is mainly due to the choice of the Z-S relationship. Furthermore, despite the CPR limited temporal and spatial sampling capabilities, CPR is able to evidence precipitation characteristics difficult to study from conventional ground-based instruments, at spatial and temporal scales of interest for the study of the hydrological cycle over Antarctica. This is of particular relevance given that the CPR follow-on mission on EarthCare will ensure a long-term coverage.

  6. North and northeast Greenland ice discharge from satellite radar interferometry

    DEFF Research Database (Denmark)

    Rignot, E.J.; Gogineni, S.P.; Krabill, W.B.

    1997-01-01

    Ice discharge from north and northeast Greenland calculated from satellite radar interferometry data of 14 outlet glaciers is 3.5 times that estimated from iceberg production. The satellite estimates, obtained at the grounding line of the outlet glaciers, differ from those obtained at the glacier...... front, because basal melting is extensive at the underside of the floating glacier sections. The results suggest that the north and northeast parts of the Greenland ice sheet may be thinning and contributing positively to sea-level rise.......Ice discharge from north and northeast Greenland calculated from satellite radar interferometry data of 14 outlet glaciers is 3.5 times that estimated from iceberg production. The satellite estimates, obtained at the grounding line of the outlet glaciers, differ from those obtained at the glacier...

  7. Quantitative precipitation estimation in complex orography using quasi-vertical profiles of dual polarization radar variables

    Science.gov (United States)

    Montopoli, Mario; Roberto, Nicoletta; Adirosi, Elisa; Gorgucci, Eugenio; Baldini, Luca

    2017-04-01

    Weather radars are nowadays a unique tool to estimate quantitatively the rain precipitation near the surface. This is an important task for a plenty of applications. For example, to feed hydrological models, mitigate the impact of severe storms at the ground using radar information in modern warning tools as well as aid the validation studies of satellite-based rain products. With respect to the latter application, several ground validation studies of the Global Precipitation Mission (GPM) products have recently highlighted the importance of accurate QPE from ground-based weather radars. To date, a plenty of works analyzed the performance of various QPE algorithms making use of actual and synthetic experiments, possibly trained by measurement of particle size distributions and electromagnetic models. Most of these studies support the use of dual polarization variables not only to ensure a good level of radar data quality but also as a direct input in the rain estimation equations. Among others, one of the most important limiting factors in radar QPE accuracy is the vertical variability of particle size distribution that affects at different levels, all the radar variables acquired as well as rain rates. This is particularly impactful in mountainous areas where the altitudes of the radar sampling is likely several hundred of meters above the surface. In this work, we analyze the impact of the vertical profile variations of rain precipitation on several dual polarization radar QPE algorithms when they are tested a in complex orography scenario. So far, in weather radar studies, more emphasis has been given to the extrapolation strategies that make use of the signature of the vertical profiles in terms of radar co-polar reflectivity. This may limit the use of the radar vertical profiles when dual polarization QPE algorithms are considered because in that case all the radar variables used in the rain estimation process should be consistently extrapolated at the surface

  8. Mobile Three Frequency Radar as Research Platform for Precipitation Profiling

    Science.gov (United States)

    Schmidt, Walter; Rautiainen, Kimmo; Harri, Ari-Matti

    2014-05-01

    Precipitation profiling at the frequency bands of Ku, Ka and W bands are becoming increasingly popular in the studies of atmospheric microphysics. Ever since the introduction of Ku / Ka pair of frequencies for the Global Precipitation Measurement mission (GPM) and the success of W band in Cloudsat, the interest in precipitation profiling using these frequencies has increased. The profiling observations will also serve as ground validation instruments for several space missions such as GPM and EarthCARE [1]. In order to get better information to retrieve ice microphysics as well as to enhance sensitivity, we need to move from the standard S- and C-band weather radars to higher frequencies [2]. As was recently shown, the use of multi- frequency profiling yields important additional information compared to single-frequency radar mapping [3]. During the past four years a consortium of research, academic and private industries in Finland has been developing a flexible low-cost mobile three-band radar system for precipitation profiling. The feasibility of the concept is being demonstrated by implementing the Ku- and Ka-band part of the system. The antenna structure with antennas for Ku-, Ka- and W-band is completed allowing the pointing of all three antenna systems into the same direction during an azimuth and elevation scan. Using a freely programmable digital waveform generator and decoding electronics for the received data, the implementation of different wave form generation, compression and decoding schemes and their influence on the radar performance in the different bands can be evaluated and optimized. The modular design allows the connection of different transmitter control and receiver decoding units to any of the three band front-end electronics to evaluate the performance of different approaches in the various bands simultaneously. A real-time analysis software supports the data interpretation and system optimization during field tests. Via mobile internet

  9. Next-Generation Satellite Precipitation Products for Understanding Global and Regional Water Variability

    Science.gov (United States)

    Hou, Arthur Y.

    2011-01-01

    A major challenge in understanding the space-time variability of continental water fluxes is the lack of accurate precipitation estimates over complex terrains. While satellite precipitation observations can be used to complement ground-based data to obtain improved estimates, space-based and ground-based estimates come with their own sets of uncertainties, which must be understood and characterized. Quantitative estimation of uncertainties in these products also provides a necessary foundation for merging satellite and ground-based precipitation measurements within a rigorous statistical framework. Global Precipitation Measurement (GPM) is an international satellite mission that will provide next-generation global precipitation data products for research and applications. It consists of a constellation of microwave sensors provided by NASA, JAXA, CNES, ISRO, EUMETSAT, DOD, NOAA, NPP, and JPSS. At the heart of the mission is the GPM Core Observatory provided by NASA and JAXA to be launched in 2013. The GPM Core, which will carry the first space-borne dual-frequency radar and a state-of-the-art multi-frequency radiometer, is designed to set new reference standards for precipitation measurements from space, which can then be used to unify and refine precipitation retrievals from all constellation sensors. The next-generation constellation-based satellite precipitation estimates will be characterized by intercalibrated radiometric measurements and physical-based retrievals using a common observation-derived hydrometeor database. For pre-launch algorithm development and post-launch product evaluation, NASA supports an extensive ground validation (GV) program in cooperation with domestic and international partners to improve (1) physics of remote-sensing algorithms through a series of focused field campaigns, (2) characterization of uncertainties in satellite and ground-based precipitation products over selected GV testbeds, and (3) modeling of atmospheric processes and

  10. Simultaneous Radar and Satellite Data Storm-Scale Assimilation Using an Ensemble Kalman Filter Approach for 24 May 2011

    Science.gov (United States)

    Jones, Thomas A.; Stensrud, David; Wicker, Louis; Minnis, Patrick; Palikonda, Rabindra

    2015-01-01

    Assimilating high-resolution radar reflectivity and radial velocity into convection-permitting numerical weather prediction models has proven to be an important tool for improving forecast skill of convection. The use of satellite data for the application is much less well understood, only recently receiving significant attention. Since both radar and satellite data provide independent information, combing these two sources of data in a robust manner potentially represents the future of high-resolution data assimilation. This research combines Geostationary Operational Environmental Satellite 13 (GOES-13) cloud water path (CWP) retrievals with Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity to examine the impacts of assimilating each for a severe weather event occurring in Oklahoma on 24 May 2011. Data are assimilated into a 3-km model using an ensemble adjustment Kalman filter approach with 36 members over a 2-h assimilation window between 1800 and 2000 UTC. Forecasts are then generated for 90 min at 5-min intervals starting at 1930 and 2000 UTC. Results show that both satellite and radar data are able to initiate convection, but that assimilating both spins up a storm much faster. Assimilating CWP also performs well at suppressing spurious precipitation and cloud cover in the model as well as capturing the anvil characteristics of developed storms. Radar data are most effective at resolving the 3D characteristics of the core convection. Assimilating both satellite and radar data generally resulted in the best model analysis and most skillful forecast for this event.

  11. Simultaneous Radar and Satellite Data Storm-Scale Assimilation Using an Ensemble Kalman Filter Approach for 24 May 2011

    Science.gov (United States)

    Jones, Thomas A.; Stensrud, David; Wicker, Louis; Minnis, Patrick; Palikonda, Rabindra

    2015-01-01

    Assimilating high-resolution radar reflectivity and radial velocity into convection-permitting numerical weather prediction models has proven to be an important tool for improving forecast skill of convection. The use of satellite data for the application is much less well understood, only recently receiving significant attention. Since both radar and satellite data provide independent information, combing these two sources of data in a robust manner potentially represents the future of high-resolution data assimilation. This research combines Geostationary Operational Environmental Satellite 13 (GOES-13) cloud water path (CWP) retrievals with Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity to examine the impacts of assimilating each for a severe weather event occurring in Oklahoma on 24 May 2011. Data are assimilated into a 3-km model using an ensemble adjustment Kalman filter approach with 36 members over a 2-h assimilation window between 1800 and 2000 UTC. Forecasts are then generated for 90 min at 5-min intervals starting at 1930 and 2000 UTC. Results show that both satellite and radar data are able to initiate convection, but that assimilating both spins up a storm much faster. Assimilating CWP also performs well at suppressing spurious precipitation and cloud cover in the model as well as capturing the anvil characteristics of developed storms. Radar data are most effective at resolving the 3D characteristics of the core convection. Assimilating both satellite and radar data generally resulted in the best model analysis and most skillful forecast for this event.

  12. Detecting weather radar clutter using satellite-based nowcasting products

    DEFF Research Database (Denmark)

    Jensen, Thomas B.S.; Gill, Rashpal S.; Overgaard, Søren

    2006-01-01

    for the detecting and removal of clutter. Naturally, the improved spatio-temporal resolution of the Meteosat Second Generation sensors, coupled with its increased number of spectral bands, is expected to yield even better detection accuracies. Weather radar data from three C-band Doppler weather radars...... Application Facility' of EUMETSAT and is based on multispectral images from the SEVIRI sensor of the Meteosat-8 platform. Of special interest is the 'Precipitating Clouds' product, which uses the spectral information coupled with surface temperatures from Numerical Weather Predictions to assign probabilities...... by the resolution of the radar data. Subsequently, a supervised classifier was developed based on training data selected by a weather radar expert. Results of classification of data from several different meteorological events are shown. Cases of widespread sea clutter caused by anomalous propagation are especially...

  13. An interactive system for compositing digital radar and satellite data

    Science.gov (United States)

    Heymsfield, G. M.; Ghosh, K. K.; Chen, L. C.

    1983-01-01

    This paper describes an approach for compositing digital radar data and GOES satellite data for meteorological analysis. The processing is performed on a user-oriented image processing system, and is designed to be used in the research mode. It has a capability to construct PPIs and three-dimensional CAPPIs using conventional as well as Doppler data, and to composite other types of data. In the remapping of radar data to satellite coordinates, two steps are necessary. First, PPI or CAPPI images are remapped onto a latitude-longitude projection. Then, the radar data are projected into satellite coordinates. The exact spherical trigonometric equations, and the approximations derived for simplifying the computations are given. The use of these approximations appears justified for most meteorological applications. The largest errors in the remapping procedure result from the satellite viewing angle parallax, which varies according to the cloud top height. The horizontal positional error due to this is of the order of the error in the assumed cloud height in mid-latitudes. Examples of PPI and CAPPI data composited with satellite data are given for Hurricane Frederic on 13 September 1979 and for a squall line on 2 May 1979 in Oklahoma.

  14. Combining Satellite Microwave Radiometer and Radar Observations to Estimate Atmospheric Latent Heating Profiles

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.; Shie, Chung-Lin; L'Ecuyer, Tristan S.; Tao, Wei-Kuo

    2009-01-01

    In this study, satellite passive microwave sensor observations from the TRMM Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q1-QR) in regions of precipitation. The TMI heating algorithm (TRAIN) is calibrated, or "trained" using relatively accurate estimates of heating based upon spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based upon a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically-integrated condensation and surface precipitation. Estimates of Q1-QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q1 produced by combining TMI Q1-QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q1 from two field campaigns, although the satellite estimates exhibit heating profile structure with sharper and more intense heating peaks than the rawinsonde estimates. 2

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

    Science.gov (United States)

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

    2010-05-01

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

  16. Comparison of Precipitation Observations from a Prototype Space-based Cloud Radar and Ground-based Radars

    Institute of Scientific and Technical Information of China (English)

    LIU Liping; ZHANG Zhiqiang; YU Danru; YANG Hu; ZHAO Chonghui; ZHONG Lingzhi

    2012-01-01

    A prototype space-based cloud radar has been developed and was installed on an airplane to observe a precipitation system over Tianjin,China in July 2010.Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype. A cross-comparison algorithm between different wavelengths,spatial resolutions and platform radars is presented.The reflectivity biases,correlation coefficients and standard deviations between the radars are analyzed.The equivalent reflectivity bias between the S- and Ka-band radars were simulated with a given raindrop size distribution.The results indicated that reflectivity bias between the S- and Ka-band radars due to scattering properties was less than 5 dB,and for weak precipitation the bias was negligible. The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity,but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter.The measured reflectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar (SA radar),and 13.7 dB stronger than that by the ground-based cloud radar.The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar.This study could provide a method for the quantitative examination of the observation ability for space-based radars.

  17. Monitoring coastal inundation with Synthetic Aperture Radar satellite data

    Science.gov (United States)

    Suzuoki, Yukihiro; Rangoonwala, Amina; Ramsey, Elijah W.

    2011-01-01

    Maps representing the presence and absence of surface inundation in the Louisiana coastal zone were created from available satellite scenes acquired by the Japanese Aerospace Exploration Agency's Advanced Land Observing Satellite and by the European Space Agency's Envisat from late 2006 through summer 2009. Detection of aboveground surface flooding relied on the well-documented and distinct signature of decreased backscatter in Synthetic Aperture Radar (SAR), which is indicative of inundated marsh in the Gulf of Mexico. Even though decreases in backscatter were distinctive, the multiplicity of possible interactions between changing flood depths and canopy height yielded complex SAR-based representations of the marshes.

  18. Making Satellite Precipitation Data Work for the Developing World

    Science.gov (United States)

    Gebregiorgis, A. S.; Hossain, F.

    2013-12-01

    The traditional approach to measuring precipitation by placing a probe on the ground will likely never be adequate or affordable in most parts of the world. Fortunately, satellites today provide a continuous global bird's-eye view (above ground) at any given location.However, the usefulness of such precipitation products for hydrological applications depends on their error characteristics and how intelligently we can harness the implications of uncertainty for surface hydrology. Satellite precipitation data is most useful where there exists little to none conventional measurements. As a result, the conventional method of comparing satellite estimate against in-situ records to 'harness' the uncertainty is unrealistic and impractical. As a community tasked with the job of making satellite precipitation 'work' for applications in most parts of the world, there is now a need think outside the box. The manuscript aims to describe a method that will 'truly' work in the developing world. The proposed manuscript aims to provide a broad view summary of our work on making hydrologically merged precipitation data work in the Middle East, Europe, Asia and Mediterranean regions. The aim will be to appeal to a broad range of water managers, climate decision makers and policy and planners in the developing world. The merged precipitation data has already been created for 2002-2010 and will be made freely available to BAMS readers through our ftp site. Globally selected study regions for developing and validating error variance regression model and satellite rainfall products merging scheme

  19. South African Weather Service operational satellite based precipitation estimation technique: applications and improvements

    Directory of Open Access Journals (Sweden)

    E. de Coning

    2010-11-01

    Full Text Available Extreme weather related to heavy or more frequent precipitation events seem to be a likely possibility for the future of our planet. While precipitation measurements can be done by means of rain gauges, the obvious disadvantages of point measurements are driving meteorologists towards remotely sensed precipitation methods. In South Africa more sophisticated and expensive nowcasting technology such as radar and lightning networks are available, supported by a fairly dense rain gauge network of about 1500 gauges. In the rest of southern Africa rainfall measurements are more difficult to obtain. The availability of the local version of the Unified Model and the Meteosat Second Generation satellite data make these products ideal components of precipitation measurement in data sparse regions such as Africa. In this article the local version of the Hydroestimator (originally from NOAA/NESDIS is discussed as well as its applications for precipitation measurement in this region. Hourly accumulations of the Hydroestimator are currently used as a satellite based precipitation estimator for the South African Flash Flood Guidance system. However, the Hydroestimator is by no means a perfect representation of the real rainfall. In this study the Hydroestimator and the stratiform rainfall field from the Unified Model are both bias corrected and then combined into a new precipitation field which can feed into the South African Flash Flood Guidance system. This new product should provide a more accurate and comprehensive input to the Flash Flood Guidance systems in South Africa as well as southern Africa. In this way the southern African region where data is sparse and very few radars are available can have access to more accurate flash flood guidance.

  20. Evaluation of Satellite Precipitation and Hydrological Model Predictions for Flood Events Over The Guadalupe River Basin, Texas

    Science.gov (United States)

    Sharif, H. O.; Furl, C.

    2016-12-01

    In this study, we evaluate the quality of several satellite precipitation products in comparison to gauge corrected ground based radar estimaties for moderate to high magnitude events across the Guadalupe River system in south Texas. The analysis is conducted across four partially nested watersheds (200-10,000 km2) such that scale effects can also be examined. Additionally, the precipitation data sets are used as input to the fully-distributed, physics-based Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to examine rainfall error propagation through the hydrologic model predictions. Both gauge corrected and uncorrected satellite products are used encompassing a variety of latent delivery times, spatial resolutions, and temporal resolutions. Satellite precipitation datasets used in the study include various products from GPM, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) system, the NOAA CPC Morphing Technique (CMORPH), and the Tropical Rainfall Measuring Mission (TRMM).

  1. Combining C- and X-band Weather Radars for Improving Precipitation Estimates over Urban Areas

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk

    The topic of this thesis is weather radar precipitation measurements. Measuring the spatial and temporal variations of the precipitation by weather radars has significant advantages compared to point measurements from rain gauges within urban drainage applications. Knowledge on how the rainfall...... of future system state. Accurate and reliable weather radar measurements are, therefore, important for future developments and achievements within urban drainage. This PhD study investigates two types of weather radars. Both systems are in operational use in Denmark today. A network of meteorological C......-band weather radars provides a basic coverage of almost the entire country. In addition, the larger cities are also covered by small Local Area Weather Radars (LAWR). Whereas the large C-band network is operated and owned by the Danish Meteorological Institute (DMI), the smaller urban radars are operated...

  2. High-resolution satellite-gauge merged precipitation climatologies of the Tropical Andes

    Science.gov (United States)

    Manz, Bastian; Buytaert, Wouter; Zulkafli, Zed; Lavado, Waldo; Willems, Bram; Robles, Luis Alberto; Rodríguez-Sánchez, Juan-Pablo

    2016-02-01

    Satellite precipitation products are becoming increasingly useful to complement rain gauge networks in regions where these are too sparse to capture spatial precipitation patterns, such as in the Tropical Andes. The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (TPR) was active for 17 years (1998-2014) and has generated one of the longest single-sensor, high-resolution, and high-accuracy rainfall records. In this study, high-resolution (5 km) gridded mean monthly climatological precipitation is derived from the raw orbital TPR data (TRMM 2A25) and merged with 723 rain gauges using multiple satellite-gauge (S-G) merging approaches. The resulting precipitation products are evaluated by cross validation and catchment water balances (runoff ratios) for 50 catchments across the Tropical Andes. Results show that the TPR captures major synoptic and seasonal precipitation patterns and also accurately defines orographic gradients but underestimates absolute monthly rainfall rates. The S-G merged products presented in this study constitute an improved source of climatological rainfall data, outperforming the gridded TPR product as well as a rain gauge-only product based on ordinary Kriging. Among the S-G merging methods, performance of inverse distance interpolation of satellite-gauge residuals was similar to that of geostatistical methods, which were more sensitive to gauge network density. High uncertainty and low performance of the merged precipitation products predominantly affected regions with low and intermittent precipitation regimes (e.g., Peruvian Pacific coast) and is likely linked to the low TPR sampling frequency. All S-G merged products presented in this study are available in the public domain.

  3. Evaluating cloud precipitation efficiency with satellite retrievals of water isotopologues

    Science.gov (United States)

    Bailey, A.; Noone, D. C.; Wood, R.

    2015-12-01

    The efficiency with which clouds precipitate is believed to influence climate by modifying cloud lifetime and, ultimately, cloud amount. Aerosols can influence this linkage by reducing the effective radii of cloud droplets and suppressing precipitation. This relationship, however, is not unidirectional. Cloud precipitation efficiency can also regulate particle concentrations, since precipitation effectively scavenges aerosols from the atmosphere. One challenge in studying how aerosols, clouds, and precipitation processes interrelate is that observational constraints are difficult to attain. This work evaluates the ability of isotope ratios in water vapor to quantify cloud precipitation efficiency across the tropical and subtropical oceans. Theory suggests isotope ratios will record the precipitation efficiency of a convective plume, since heavier isotopologues precipitate preferentially; and a recent analysis of in situ measurements from the Mauna Loa Observatory (MLO, Hawaii, USA) verifies this to be the case. The challenge now lies in understanding whether satellite retrievals of isotope ratios in water vapor are sensitive enough to track precipitation efficiency globally. To answer this question, vertical profiles of the D/H ratio derived from NASA's Tropospheric Emission Spectrometer (TES) are first compared with the MLO in situ measurements. A qualitative match indicates the satellite retrievals can distinguish high from low precipitation efficiency convection. To expand the analysis geographically, TES profiles between 40°S and 40°N are compared with estimates of precipitation efficiency derived from the Tropical Rainfall Measuring Mission (TRMM) and ECMWF's ERA-Interim. Retrievals are binned by lower-tropospheric humidity and by vertical velocity in order to minimize large-scale thermodynamical influences. Co-located cloud retrievals provide the context necessary to evaluate the utility of these new estimates in elucidating cloud feedbacks on climate.

  4. Ku/Ka/W-band Antenna for Electronically-Scanned Cloud and Precipitation Radar Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Development of the key antenna technologies for Tri-band (Ku/Ka/W), scanning precipitation and cloud radar is a required milestone in preparation for one or more...

  5. A Novel Low-Cost Dual-Wavelength Precipitation Radar Sensor Network Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Remote Sensing Solutions, Inc. (RSS) has developed a novel, practical design that will produce a low-cost precipitation radar / radiometer sensor. Operating in a...

  6. Improving Weather Radar Precipitation Estimates by Combining two Types of Radars

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2014-01-01

    the two radar types achieves a radar product with both long range and high temporal resolution. It is validated that the blended radar product performs better than the individual radars based on ground observations from laser disdrometers. However, the data combination is challenged by lower performance...

  7. Estimating the vertical structure of intense Mediterranean precipitation using two X-band weather radar systems

    NARCIS (Netherlands)

    Berne, A.D.; Delrieu, G.; Andrieu, H.

    2005-01-01

    The present study aims at a preliminary approach of multiradar compositing applied to the estimation of the vertical structure of precipitation¿an important issue for radar rainfall measurement and prediction. During the HYDROMET Integrated Radar Experiment (HIRE¿98), the vertical profile of

  8. 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

  9. Stratiform and Convective Precipitation Observed by Multiple Radars during the DYNAMO/AMIE Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Min; Kollias, Pavlos; Feng, Zhe; Zhang, Chidong; Long, Charles N.; Kalesse, Heike; Chandra, Arunchandra; Kumar, Vickal; Protat, Alain

    2014-11-01

    The motivation for this research is to develop a precipitation classification and rain rate estimation method using cloud radar-only measurements for Atmospheric Radiation Measurement (ARM) long-term cloud observation analysis, which are crucial and unique for studying cloud lifecycle and precipitation features under different weather and climate regimes. Based on simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two precipitation radars (NCAR S-PolKa and Texas A&M University SMART-R), and surface precipitation during the DYNAMO/AMIE field campaign, a new cloud radar-only based precipitation classification and rain rate estimation method has been developed and evaluated. The resulting precipitation classification is equivalent to those collocated SMART-R and S-PolKa observations. Both cloud and precipitation radars detected about 5% precipitation occurrence during this period. The convective (stratiform) precipitation fraction is about 18% (82%). The 2-day collocated disdrometer observations show an increased number concentration of large raindrops in convective rain compared to dominant concentration of small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also show two distinct structures for convective and stratiform rain. These indicate that the method produces physically consistent results for two types of rain. The cloud radar-only rainfall estimation is developed based on the gradient of accumulative radar reflectivity below 1 km, near-surface Ze, and collocated surface rainfall (R) measurement. The parameterization is compared with the Z-R exponential relation. The relative difference between estimated and surface measured rainfall rate shows that the two-parameter relation can improve rainfall estimation.

  10. Recovering of Precipitating Electrons Spectra on the Incoherent Scattering Radar Data.

    Science.gov (United States)

    Lyakhov, A.; Smirnova, N.; Osepian, A.

    2001-12-01

    Precipitating electrons are the main ionization source in the polar ionosphere. They determine practically all important electrodynamical properties of an ionosphere. So, the form of the spectrum and its time history allows to identify the zone of the precipitating particles source in magnitosphere in different substorm phases. It's worthwhile to note that quantitative estimations of the full energy flow is important for estimation of energy balance in atmosphere, and effects, caused by invasions of the high-energy particles must be taken into account in the study of the middle atmosphere chemistry. Incoherent radars are unique and powerful source for the observation and measurements of an ionosphere electrodynamic parameters. In principle, it is possible to determine the energy spectrum of precipitating electrons on their data. From mathematical point of view the problem of spectrum recovering is a linear integral Fredholm equation of the 1st kind, which is the classical ill-posed problem. The kernel of this integral equation defines the function of the electron energy losses in the atmosphere. Up to date a number of methods have been developed for the reconstruction of spectrum with energies Erestore effectively the precipitating spectra even when altitude electron density profile is noisy. The comparison of least-squares, Tikhonov regularization and adaptive optimal algorithms is presented for model problems and for satellite data as well. New model is given for α eff(h) determination in various geophysical conditions. The possibility of real-time spectra recovering, which, in turn, is based on the concept of dynamical regularization, is discussed.

  11. The validation service of the hydrological SAF geostationary and polar satellite precipitation products

    Science.gov (United States)

    Puca, S.; Porcu, F.; Rinollo, A.; Vulpiani, G.; Baguis, P.; Balabanova, S.; Campione, E.; Ertürk, A.; Gabellani, S.; Iwanski, R.; Jurašek, M.; Kaňák, J.; Kerényi, J.; Koshinchanov, G.; Kozinarova, G.; Krahe, P.; Lapeta, B.; Lábó, E.; Milani, L.; Okon, L'.; Öztopal, A.; Pagliara, P.; Pignone, F.; Rachimow, C.; Rebora, N.; Roulin, E.; Sönmez, I.; Toniazzo, A.; Biron, D.; Casella, D.; Cattani, E.; Dietrich, S.; Di Paola, F.; Laviola, S.; Levizzani, V.; Melfi, D.; Mugnai, A.; Panegrossi, G.; Petracca, M.; Sanò, P.; Zauli, F.; Rosci, P.; De Leonibus, L.; Agosta, E.; Gattari, F.

    2014-04-01

    The development phase (DP) of the EUMETSAT Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF) led to the design and implementation of several precipitation products, after 5 yr (2005-2010) of activity. Presently, five precipitation estimation algorithms based on data from passive microwave and infrared sensors, on board geostationary and sun-synchronous platforms, function in operational mode at the H-SAF hosting institute to provide near real-time precipitation products at different spatial and temporal resolutions. In order to evaluate the precipitation product accuracy, a validation activity has been established since the beginning of the project. A Precipitation Product Validation Group (PPVG) works in parallel with the development of the estimation algorithms with two aims: to provide the algorithm developers with indications to refine algorithms and products, and to evaluate the error structure to be associated with the operational products. In this paper, the framework of the PPVG is presented: (a) the characteristics of the ground reference data available to H-SAF (i.e. radar and rain gauge networks), (b) the agreed upon validation strategy settled among the eight European countries participating in the PPVG, and (c) the steps of the validation procedures. The quality of the reference data is discussed, and the efforts for its improvement are outlined, with special emphasis on the definition of a ground radar quality map and on the implementation of a suitable rain gauge interpolation algorithm. The work done during the H-SAF development phase has led the PPVG to converge into a common validation procedure among the members, taking advantage of the experience acquired by each one of them in the validation of H-SAF products. The methodology is presented here, indicating the main steps of the validation procedure (ground data quality control, spatial interpolation, up-scaling of radar data vs. satellite grid

  12. Spatial correlation of radar and gauge precipitation data in high temporal resolution

    Directory of Open Access Journals (Sweden)

    J. Brommundt

    2007-01-01

    Full Text Available A multi-sites precipitation time series generator for engineering designs is currently being developed. The objective is to generate several time series' simultaneously with correct inter-station relationships. Therefore, a model to estimate correlation between stations for arbitrary points in a project area is needed, using rain gauge data as well as radar data. Two methods are applied to compare the spatial behaviour of precipitation in both the rain gauge data and the radar data. The first approach is to calculate precipitation intensities from radar reflectivity and use it as gauge data. The results show that the spatial structure in both data sets is similar, but cross correlation varies too much to use radar derived spatial correlation to describe gauge inter-station relationship. Thus, a second approach was tested to account for the differences in the spatial correlation associated to the distribution. Using the indicator time series, cross correlations for different quantiles were calculated from both the rain gauge and radar data. This approach shows that cross correlation varies depending on the chosen quantile. In the lower quantiles, the correlation is very similar in rain gauge and radar data, hence a transfer is possible. This insight is useful to derive cross correlations of rain gauges from radar images. Correlation data for rain gauges thus obtained contains all the information about heterogeneity and anisotropy of the spatial structure of rainfall, which is in the radar data.

  13. Improving high-resolution quantitative precipitation estimation via fusion of multiple radar-based precipitation products

    Science.gov (United States)

    Rafieeinasab, Arezoo; Norouzi, Amir; Seo, Dong-Jun; Nelson, Brian

    2015-12-01

    For monitoring and prediction of water-related hazards in urban areas such as flash flooding, high-resolution hydrologic and hydraulic modeling is necessary. Because of large sensitivity and scale dependence of rainfall-runoff models to errors in quantitative precipitation estimates (QPE), it is very important that the accuracy of QPE be improved in high-resolution hydrologic modeling to the greatest extent possible. With the availability of multiple radar-based precipitation products in many areas, one may now consider fusing them to produce more accurate high-resolution QPE for a wide spectrum of applications. In this work, we formulate and comparatively evaluate four relatively simple procedures for such fusion based on Fisher estimation and its conditional bias-penalized variant: Direct Estimation (DE), Bias Correction (BC), Reduced-Dimension Bias Correction (RBC) and Simple Estimation (SE). They are applied to fuse the Multisensor Precipitation Estimator (MPE) and radar-only Next Generation QPE (Q2) products at the 15-min 1-km resolution (Experiment 1), and the MPE and Collaborative Adaptive Sensing of the Atmosphere (CASA) QPE products at the 15-min 500-m resolution (Experiment 2). The resulting fused estimates are evaluated using the 15-min rain gauge observations from the City of Grand Prairie in the Dallas-Fort Worth Metroplex (DFW) in north Texas. The main criterion used for evaluation is that the fused QPE improves over the ingredient QPEs at their native spatial resolutions, and that, at the higher resolution, the fused QPE improves not only over the ingredient higher-resolution QPE but also over the ingredient lower-resolution QPE trivially disaggregated using the ingredient high-resolution QPE. All four procedures assume that the ingredient QPEs are unbiased, which is not likely to hold true in reality even if real-time bias correction is in operation. To test robustness under more realistic conditions, the fusion procedures were evaluated with and

  14. X-band radar field campaign data analysis for orographic/warm-rain precipitation processes

    Science.gov (United States)

    Porcacchia, Leonardo; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Anagnostou, Marios N.; Anagnostou, Emmanouil N.; Bousquet, Olivier; Cheong, Boon-Leng; Maggioni, Viviana; Hong, Yang

    2016-04-01

    Accurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to hazards such as flash floods, shallow landslides, and debris flows. It is usually hard to obtain reliable weather radar information in mountainous areas, due to difficulties connected to non-meteorological scattering and the elevation of the study sites. Such regions are particularly interested by orographic/warm-rain precipitation processes, characterized by no ice phase in the cloud and prevailing concentration of small drops in the drop size distribution. Field campaigns are able to provide complete and solid datasets in mountainous regions, thanks to mobile radars and the complementary information provided by rain gauges and disdrometers. This study analyzes datasets collected during the Hymex, IPHEX, and Colorado field campaigns in mountainous areas in Italy, France, North Carolina, and Colorado. Mobile X-band radars from the NOAA National Severe Storm Laboratory and the Advanced Radar Research Center at the University of Oklahoma are utilized. The X-band dual polarimetric radar data are corrected for attenuation through the SCOP algorithm, and evaluated against disdrometer and rain-gauge data. Warm-rain events are identified by looking at the Gorgucci, Cao-Zhang, and Kumjian-Ryzhkov parameter spaces relating polarimetric radar variables to precipitation development processes in the cloud and rain size distributions. A conceptual model for the vertical profile of precipitation and microphysical structure of the cloud is also derived, to be contrasted against other typical convective and stratiform profiles.

  15. A Multi-Frequency Wide-Swath Spaceborne Cloud and Precipitation Imaging Radar

    Science.gov (United States)

    Li, Lihua; Racette, Paul; Heymsfield, Gary; McLinden, Matthew; Venkatesh, Vijay; Coon, Michael; Perrine, Martin; Park, Richard; Cooley, Michael; Stenger, Pete; hide

    2016-01-01

    Microwave and millimeter-wave radars have proven their effectiveness in cloud and precipitation observations. The NASA Earth Science Decadal Survey (DS) Aerosol, Cloud and Ecosystems (ACE) mission calls for a dual-frequency cloud radar (W band 94 GHz and Ka-band 35 GHz) for global measurements of cloud microphysical properties. Recently, there have been discussions of utilizing a tri-frequency (KuKaW-band) radar for a combined ACE and Global Precipitation Measurement (GPM) follow-on mission that has evolved into the Cloud and Precipitation Process Mission (CaPPM) concept. In this presentation we will give an overview of the technology development efforts at the NASA Goddard Space Flight Center (GSFC) and at Northrop Grumman Electronic Systems (NGES) through projects funded by the NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP). Our primary objective of this research is to advance the key enabling technologies for a tri-frequency (KuKaW-band) shared-aperture spaceborne imaging radar to provide unprecedented, simultaneous multi-frequency measurements that will enhance understanding of the effects of clouds and precipitation and their interaction on Earth climate change. Research effort has been focused on concept design and trade studies of the tri-frequency radar; investigating architectures that provide tri-band shared-aperture capability; advancing the development of the Ka band active electronically scanned array (AESA) transmitreceive (TR) module, and development of the advanced radar backend electronics.

  16. ER-2 Airborne Radars Data during Iphex - a New 4-Frequency Look at Precipitation.

    Science.gov (United States)

    Heymsfield, G. M.; Tian, L.; McLinden, M.; Li, L.; Cervantes, J.; Venkatesh, V.; Coon, M.

    2014-12-01

    The Integrated Precipitation and Hydrology Experiment (IPHEx) field campaign was conducted in the Southeast U.S. from 15 May to 30 June 2014 in support of Global Precipitation Mission (GPM) ground validation. The NASA ER-2 flew in this campaign as a GPM simulator with radars and radiometers that covered the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) frequencies. The main goal for the ER-2 high spatial and temporal resolution data sets to be used for GPM algorithm validation and improvement. Goddard Space Flight Center provided 3 nadir-pointing radars that covered X- through W-band. The High-altitude Wind and Rain Airborne Profiler (HIWRAP) provided Ku and Ka-band measurements that are similar to GPM's DPR. In addition, the W-band Cloud Radar System (CRS) and ER-2 X-band Radar (EXRAD) were on board. The 4 frequencies provide opportunity for developing consistent retrieval algorithms as well as to expand the dynamic range (i.e., particle size) of the retrievals. There were a total of 15 science flights during IPHEx that measured a variety of land-based and oceanic precipitation, with may convective, stratiform, and cloud targets. This presentation will provide preliminary observations and analyses from the IPHEx ER-2 radars. It will discuss planned retrieval algorithms and data analyses.

  17. 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%.

  18. 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

  19. Hydrologic evaluation of a Generalized Statistical Uncertainty Model for Satellite Precipitation Products

    Science.gov (United States)

    Sarachi, S.; Hsu, K. L.; Sorooshian, S.

    2014-12-01

    Development of satellite based precipitation retrieval algorithms and using them in hydroclimatic studies have been of great interest to hydrologists. It is important to understand the uncertainty associated with precipitation products and how they further contribute to the variability in stream flow simulation. In this study a mixture model of Generalized Normal Distribution and Gamma distribution (GND-G) is used to model the joint probability distribution of satellite-based (PERSIANN) and stage IV radar rainfall. The study area for constructing the uncertainty model covers a 15°×15°box of 0.25°×0.25° cells over the eastern United States for summer 2004 to 2009. Cells are aggregated in space and time to obtain data with different resolutions for the construction of the model's parameter space. This uncertainty model is evaluated using data from National Weather Service (NWS) Distributed Hydrologic Model Intercomparison Project - Phase 2 (DMIP 2) basin over Illinois River basin south of Siloam, OK. This data covers the time period of 2006 to 2008.The uncertainty range of precipitation is estimated. The impact of precipitation uncertainty to the stream flow estimation is demonstrated by Monte Carlo simulation of precipitation forcing in the Sacramento Soil Moisture Accounting (SAC-SMA) model. The results show that using precipitation along with its uncertainty distribution as forcing to SAC-SMA make it possible to have an estimation of the uncertainty associated with the stream flow simulation ( in this case study %90 confidence interval is used). The mean of this stream flow confidence interval is compared to the reference stream flow for evaluation of the model and the results show that this method helps to better estimate the variability of the stream flow simulation along with its statistics e.g. percent bias and root mean squared error.

  20. The new approach of polarimetric attenuation correction for improving radar quantitative precipitation estimation(QPE)

    Science.gov (United States)

    Gu, Ji-Young; Suk, Mi-Kyung; Nam, Kyung-Yeub; Ko, Jeong-Seok; Ryzhkov, Alexander

    2016-04-01

    To obtain high-quality radar quantitative precipitation estimation data, reliable radar calibration and efficient attenuation correction are very important. Because microwave radiation at shorter wavelength experiences strong attenuation in precipitation, accounting for this attenuation is the essential work at shorter wavelength radar. In this study, the performance of different attenuation/differential attenuation correction schemes at C band is tested for two strong rain events which occurred in central Oklahoma. And also, a new attenuation correction scheme (combination of self-consistency and hot-spot concept methodology) that separates relative contributions of strong convective cells and the rest of the storm to the path-integrated total and differential attenuation is among the algorithms explored. A quantitative use of weather radar measurement such as rainfall estimation relies on the reliable attenuation correction. We examined the impact of attenuation correction on estimates of rainfall in heavy rain events by using cross-checking with S-band radar measurements which are much less affected by attenuation and compared the storm rain totals obtained from the corrected Z and KDP and rain gages in these cases. This new approach can be utilized at shorter wavelength radars efficiently. Therefore, it is very useful to Weather Radar Center of Korea Meteorological Administration preparing X-band research dual Pol radar network.

  1. Weather from 250 Miles Up: Visualizing Precipitation Satellite Data (and Other Weather Applications) Using CesiumJS

    Science.gov (United States)

    Lammers, Matt

    2017-01-01

    Geospatial weather visualization remains predominately a two-dimensional endeavor. Even popular advanced tools like the Nullschool Earth display 2-dimensional fields on a 3-dimensional globe. Yet much of the observational data and model output contains detailed three-dimensional fields. In 2014, NASA and JAXA (Japanese Space Agency) launched the Global Precipitation Measurement (GPM) satellite. Its two instruments, the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) observe much of the Earth's atmosphere between 65 degrees North Latitude and 65 degrees South Latitude. As part of the analysis and visualization tools developed by the Precipitation Processing System (PPS) Group at NASA Goddard, a series of CesiumJS [Using Cesium Markup Language (CZML), JavaScript (JS) and JavaScript Object Notation (JSON)] -based globe viewers have been developed to improve data acquisition decision making and to enhance scientific investigation of the satellite data. Other demos have also been built to illustrate the capabilities of CesiumJS in presenting atmospheric data, including model forecasts of hurricanes, observed surface radar data, and gridded analyses of global precipitation. This talk will present these websites and the various workflows used to convert binary satellite and model data into a form easily integrated with CesiumJS.

  2. Linking oil production to surface subsidence from satellite radar interferometry

    Science.gov (United States)

    Xu, Haibin; Dvorkin, Jack; Nur, Amos

    Land subsidence over the Belridge and Lost Hills oil fields, Southern California, was measured using spaceborne interferometric synthetic aperture radar (InSAR). During the 105-day period between 11/5/95 and 2/17/96, the subsidence in the center of the Lost Hills field reached 15 cm. We assume that this surface subsidence resulted from the vertical shrinkage of the reservoir, which in turn was due to oil production and the resulting pore pressure drop. We model this mechanical effect using an elastic deformation theoretical solution with input constants taken from relevant experiments. The modeled surface deformation matches the InSAR measured values. This result indicates that it is possible, in principle, to monitor hydrocarbon production using satellite-based measurements of earth deformation.

  3. Earthquake Monitoring in Australia Using Satellite Radar Interferometry

    Institute of Scientific and Technical Information of China (English)

    Ge Lin-lin; E. Cheng; D. Polonska; C. Rizos; C. Collins; C. Smith

    2003-01-01

    Are there any earthquakes in Australia? Although most Australians are not as familiar with earthquakes as citizens in countries such as Japan, there are some quakes on the Australian continent every year. Differential Synthetic Aperture Radar Interferometry (DInSAR) has been widely used in recent years for monitoring crustal deformation due to earthquakes, volcanoes, underground mining, oil extraction,and so on. Hence the follow-on question is, can repeat-pass satellite DInSAR be used in Australian regions to monitor earthquakes? Nine ERS-1 and ERS-2 radar images of the Burakin region in Western Australia were used to form the InSAR pairs.Twenty-two InSAR pairs were formed and were used to study the temporal decorrelation characteristics in the Burakin area. It was found that good coherence could be maintained all over the full scene for a pair spanning 211 d. The repeat cycles of RADARSAT and ERS (all C-band SAR missions) are 24 and 35 drespectively, Furthermore it is easier to maintain good coherence in L-band SAR images (e.g. the JERS-1 mission has a 44 d repeat cycle). Therefore the authors are confident that repeat-pass differential InSAR can be used to monitor ground deformation due to earthquakes in the Burakin region.

  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. The scavenging of air pollutants by precipitation, and its estimation with the aid of weather radar

    Science.gov (United States)

    Jylha, Kirsti Tellervo

    2000-09-01

    Precipitation cleanses the air by capturing airborne pollutants and depositing them onto the ground. The efficiency of this process may be expressed by the fractional depletion rate of pollutant concentrations in the air, designated as the scavenging coefficient. It depends on the size distribution of the raindrops and snow crystals and is thereby related to quantities estimated by weather radar, namely, the radar reflectivity factor and the precipitation rate. On the other hand, there are no universal relationships between the scavenging coefficient and these two quantities; the relationships vary depending on the properties of the precipitation and pollutants. In the present thesis, a few estimates for them were derived theoretically and empirically, using in the latter case observations made in Finland either after the Chernobyl nuclear accident or during a wintertime case study near a coal-fired power plant. The greatest advantage in the use of weather radar in assessing precipitation scavenging arises from the fact that radar estimates the spatial distributions of precipitation in real time with a good spatial and temporal resolution. Radar software usually used to create displays of the precipitation rate can easily be modified to show distributions of the scavenging coefficient. Such images can provide valuable information about the areas where a substantial portion of the pollutants is deposited onto the ground or, alternatively, remains airborne. Based on the movement of the precipitation areas, it is also possible to make short-term forecasts of those areas most likely to be exposed to wet deposition. A network of radars may hence form an important part of a real-time monitoring and warning system that can be immediately effective in the event of an accidental releases of hazardous materials into the air.

  6. Marine parameters from synergy of optical and radar satellite data

    Science.gov (United States)

    Lehner, S.; Hoja, D.; Schulz-Stellenfleth, J.

    In 2001 the European Space Agency ESA will launch the earth observation satellite ENVISAT. It will carry several instruments that provide new opportunities to measure oceanographic variables. Together, they represent the main measurement techniques of satellite oceanography, and complement each other in an ideal manner. These instruments are to be used in synergy to: Improve the analysis of measured wind and ocean wave fields, and thereby improve weather forecasting at weather centers; Determine the extent and variables of sea ice and develop a five-day sea ice prediction model, to support maritime shipping and offshore activities; Monitor and map sediment and suspended matter transport in coastal regions, especially in areas with large river estuaries, which greatly affects shipping lanes, harbors, and dredging activities; Monitor hydrobiological and bio-geochemical variables related to water quality in coastal regions and large inland waters, which affects ecology, coastal development, aquaculture, drinking water supplies, and tourism. To prepare the oceanographic community to make best use of the ENVISAT sensors in the pre-launch phase, existing algorithms to derive marine parameters are used and validated using data from the ERS SAR, the ERS RA, SeaWiFS and IRS MOS sensors now in operation. Derived products are used to address problems that can best be tackled using the synergy of radar and optical data, such as the effect of surface slicks on radar wind measurements, of sea state on ocean color, of wind and waves on the resuspension of suspended matter, and of wind and waves on sea ice variables.

  7. Precipitation retrieval from satellite within EUMETSAT's H-SAF

    Science.gov (United States)

    Mugnai, A.; Dietrich, S.; Levizzani, V.; Casella, D.; Cattani, E.; di Paola, F.; Formenton, M.; Laviola, S.; Sanò, P.

    2010-09-01

    The EUMETSAT Satellite Application Facility on support to Operational Hydrology and Water Management (H-SAF) was established by the EUMETSAT Council on July 3, 2005 and started activity at the official date of September 1, 2005. The Italian Meteorological Service serves as "Host Institute" on behalf of 12 European countries. The Project Plan focuses on the generation of the following products for the European and Mediterranean regions: • instantaneous and accumulated precipitation, including liquid/solid discrimination; • soil moisture in the surface layer and in the roots region; • snow parameters such as effective cover, wet/dry discrimination and water equivalent. In addition to products development and generation, the project includes a products validation programme and a hydrological validation programme. The development programme duration is 5 years, ending on August 31, 2010. A follow-on Continuous Development and Operations Phase (CDOP) will start in September 2010 to provide long-term perspective (2010-2017) to the initiative. Precipitation products are being generated according to algorithms developed by CNR-ISAC in collaboration with the international community, by exploiting the following satellites and instruments: • MW conically-scanning radiometers (SSM/I and SSMIS) on LEO satellites (DMSP); • MW cross-track scanning radiometers (AMSU-A and AMSU-B / MHS) on LEO operational satellites (NOAA and MetOp); • VIS/IR imagers (SEVIRI) on GEO satellites (MSG). These products are generated routinely at the Italian Centro Nazionale di Meteorologia e Climatologia Aeronautica (CNMCA), which is responsible of operational product generation and dissemination. Whilst precipitation products continue to be developed and improved, major focus is now on product validation. Products are generated in a pre-operational fashion, with a delay of few minutes to few hours from observation, depending on product and satellite data access. Access to products is

  8. Precipitation Type Specific Radar Reflectivity-Rain Rate Relationships for Warsaw, Poland

    Science.gov (United States)

    Licznar, Paweł; Krajewski, Witold F.

    2016-10-01

    Implementation of weather radar precipitation estimates into hydrology, especially urban hydrology practice in Poland, requires the introduction of more precise radar reflectivity versus rain rate (Z-R) relationships accounting for drop size distribution (DSD) specific for different precipitation phases. We explored the development of precipitation type dependent Z-R relationship on the basis of approximately two years of DSD recordings at high temporal resolution of ten seconds. We divided the recorded data into four separate precipitation-type groups: rain, snow, rain-with-snow, and hail. The Z-R relationships for rain and rainwith- snow showed a strong resemblance to the well-known Marshall- Palmer Z-R power-type relationship for rain. In the case of snowfall, we found that both the multiplication factor and the exponent coefficients in the Z-R formula have smaller values than for rain. In contrast, for hail precipitation these parameters are higher than for rain, especially the multiplication factor.

  9. CLUJ-NAPOCA PRECIPITATION FORECAST USING WSR-98D DOPPLER RADAR

    Directory of Open Access Journals (Sweden)

    Narcis MAIER

    2011-11-01

    Full Text Available CLUJ-NAPOCA precipitation forecast using WSR-98D Doppler radar. Forecasting inundations requires accurate spatial and temporal estimation of rainfalls in an area. Depending on the Z-R relationship (reflectivity-precipitation rate, the thresholds, maximum reflectivity data processing, VIL, cloud height or speed, provided by the WSR-98D affects the estimated precipitation used in the prediction of inundations. How much precipitation receives a watershed during an extreme event and what response will result depends on the basin hydrographic characteristics. A study of summer weather events between the years 2004-2008 and a new method in establishing relations between the radar estimated and recorded precipitations led to the determination of new relations between them which will balance the connections between them.

  10. Meteorological radar methods for validating space observations of precipitation

    Science.gov (United States)

    Thiele, Otto W.

    1991-01-01

    Meteorological approaches to verification of space measurements of rainfall are examined; validation of Tropical Rainfall Measuring Mission (TRMM) observations is expected to depend significantly on ground-based radars. Two methods of comparison are initially contemplated. TRMM rainfall data over time periods of a month for large areas (500 x 500 km) are averaged and compared with similarly averaged ground truth measurements. Both the rainfall and height distribution data from TRMM are compared with the instantaneous values observed at one or more 'ground truth' stations and from airborne radar and radiometers as available.

  11. Satellite Observations of Spatial and Interannual Variability of Lightning and Radar Reflectivity

    Science.gov (United States)

    Durden, S. L.; Meagher, J. P.; Haddad, Z. S.

    2004-01-01

    The authors use satellite data to examine the relationship between lightning and upper-level radar reflectivity. They find correlations between average flash rates and upper-level reflectivities over both land and ocean, although both flash rates and reflectivities are much lower over ocean than land. Analysis of the data using Empirical Orthogonal Functions (EOFs) shows similar EOFs for averaged lightning and reflectivity. In contrast, the EOFs of the anomalies of lightning and reflectivity have different spatial patterns; however, both have principal component time series that are correlated with the Southern Oscillation Index and, hence, El Nino. Differences in behavior of the lightning and reflectivity anomaly EOFs and principal components suggest that El Nino plays a smaller role in lightning anomaly than precipitation anomaly.

  12. Application of Multi-Scale Tracking Radar Echoes Scheme in Quantitative Precipitation Nowcasting

    Institute of Scientific and Technical Information of China (English)

    WANG Gaili; WONG Waikin; LIU Liping; WANG Hongyan

    2013-01-01

    A new radar echo tracking algorithm known as multi-scale tracking radar echoes by cross-correlation (MTREC) was developed in this study to analyze movements of radar echoes at different spatial scales.Movement of radar echoes,particularly associated with convective storms,exhibits different characteristics at various spatial scales as a result of complex interactions among meteorological systems leading to the formation of convective storms.For the null echo region,the usual correlation technique produces zero or a very small magnitude of motion vectors.To mitigate these constraints,MTREC uses the tracking radar echoes by correlation (TREC) technique with a large "box" to determine the systematic movement driven by steering wind,and MTREC applies the TREC technique with a small "box" to estimate small-scale internal motion vectors.Eventually,the MTREC vectors are obtained by synthesizing the systematic motion and the small scale internal motion.Performance of the MTREC technique was compared with TREC technique using case studies:the Khanun typhoon on 11 September 2005 observed by Wenzhou radar and a squall-line system on 23 June 2011 detected by Beijing radar.The results demonstrate that more spatially smoothed and continuous vector fields can be generated by the MTREC technique,which leads to improvements in tracking the entire radar reflectivity pattern.The new multi-scale tracking scheme was applied to study its impact on the performance of quantitative precipitation nowcasting.The location and intensity of heavy precipitation at a 1-h lead time was more consistent with quantitative precipitation estimates using radar and rain gauges.

  13. Classification of daily precipitation patterns on the basis of radar-derived precipitation rates for Saxony, Germany

    Energy Technology Data Exchange (ETDEWEB)

    Kronenberg, Rico; Franke, Johannes; Bernhofer, Christian [Technische Univ. Dresden (Germany). Inst. fuer Hydrologie und Meteorologie

    2012-10-15

    We present a radar-based climatology of precipitation fields summarised into characteristic daily precipitation patterns. These patterns were derived by temporal classification, applying a neural network and data from Saxony during the period from 2004 to 2010. The properties of the dataset (RADOLAN rw-product) are discussed in detail and reviewed with respect to their adequacy for the intended application. The analysis showed a systematic dependence of the precipitation error on the altitude and aggregation period. Accordingly, for future applications of the considered radar product, we recommend the use of a maximal aggregation time step of 24 hours. The classification reveals significant precipitation patterns. Comparison of the qualitative features exhibited by the precipitation patterns, such as the synoptic scale flow direction, pressure distribution and atmospheric humidity, showed general trends as well as distinct spatial and atmospheric properties in dependence of the incidence rate. The lowest statistical qualities were shown by the patterns with the most distinct spatial characteristics due to a low incidence rate and high standard deviations. Nevertheless, the applied method led to a robust classification and the derived patterns appropriately summarized the mean daily precipitation behaviour in Saxony. (orig.)

  14. 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

  15. Study on the Algorithm to Retrieve Precipitation with X-Band Synthetic Aperture Radar

    Institute of Scientific and Technical Information of China (English)

    XIE Yanan; HUAN Jianping; TAO Yang

    2010-01-01

    In order to obtain the global precipitation distribution data,this paper investigates the precipitation distribution model,the normalized radar cross-section model,and the retrieval algorithm with X-band synthetic aperture radar(X-SAR).A new retrieval algorithm based on the surface-scattering reference attenuation is developed to retrieve the rain rate above the ground surface.This new algorithm needs no statistical work load and has more extensive applications.Calculations using the new algorithm for three cases verify that the rainfall is retrieved with high precision,which proves the capability of the algorithm.

  16. Utilizing Satellite-derived Precipitation Products in Hydrometeorological Applications

    Science.gov (United States)

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

    2012-12-01

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

  17. Forecast of muddy floods using high-resolution radar precipitation forcasting data and erosion modelling

    Science.gov (United States)

    Hänsel, Phoebe; Schindewolf, Marcus; Schmidt, Jürgen

    2016-04-01

    In the federal province of Saxony, Eastern Germany, almost 60 % of the agricultural land is endangered by erosion processes, mainly caused by heavy rainfall events. Beside the primary impact of soil loss and decreasing soil fertility, erosion can cause significant effects if transported sediments are entering downslope settlements, infrastructure or traffic routes. Available radar precipitation data are closing the gap between the conventional rainfall point measurements and enable the nationwide rainfall distribution with high spatial and temporal resolution. By means of the radar precipitation data of the German Weather Service (DWD), high-resolution radar-based rainfall data totals up to 5 minute time steps are possible. The radar data are visualised in a grid-based hourly precipitation map. In particular, the daily and hourly precipitation maps help to identify regions with heavy rainfall and possible erosion events. In case of an erosion event on agricultural land, these areas are mapped with an unmanned airborne vehicle (UAV). The camera-equipped UAV delivers high-resolution images of the erosion event, that allow the generation of high-resolution orthophotos. By the application of the high-resolution radar precipitation data as an input for the process-based soil loss and deposition model EROSION 3D, these images are for validation purposes. Future research is focused on large scale soil erosion modelling with the help of the radar forecasting product and an automatic identification of sediment pass over points. The study will end up with an user friendly muddy flood warning tool, which allows the local authorities to initiate immediate measures in order to prevent severe damages in settlements, infrastructure or traffic routes.

  18. Using TRMM and GPM precipitation radar for calibration of weather radars in the Philippines

    Science.gov (United States)

    Crisologo, Irene; Bookhagen, Bodo; Smith, Taylor; Heistermann, Maik

    2016-04-01

    Torrential and sustained rainfall from tropical cyclones, monsoons, and thunderstorms frequently impact the Philippines. In order to predict, assess, and measure storm impact, it is imperative to have a reliable and accurate monitoring system in place. In 2011, the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA) established a weather radar network of ten radar devices, eight of which are single-polarization S-band radars and two dual-polarization C-band radars. Because of a low-density hydrometeorological monitoring networks in the Philippines, calibration of weather radars becomes a challenging, but important task. In this study, we explore the potential of scrutinizing the calibration of ground radars by using the observations from the Tropical Rainfall Measuring Mission (TRMM). For this purpose, we compare different TRMM level 1 and 2 orbital products from overpasses over the Philippines, and compare these products to reflectivities observed by the Philippine ground radars. Differences in spatial resolution are addressed by computing adequate zonal statistics of the local radar bins located within the corresponding TRMM cell in space and time. The wradlib package (Heistermann et al. 2013; Heistermann et al. 2015) is used to process the data from the Subic S-band single-polarization weather radar. These data will be analyzed in conjunction with TRMM data for June to August 2012, three months of the wet season. This period includes the enhanced monsoon of 2012, locally called Habagat 2012, which brought sustained intense rainfall and massive floods in several parts of the country including the most populated city of Metro Manila. References Heistermann, M., Jacobi, S., Pfaff, T. (2013): Technical Note: An open source library for processing weather radar data (wradlib). Hydrol. Earth Syst. Sci., 17, 863-871, doi: 10.5194/hess-17-863-2013. Heistermann, M., S. Collis, M. J. Dixon, S. Giangrande, J. J. Helmus, B. Kelley, J

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

    Science.gov (United States)

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

    2012-12-01

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

  20. Definition and impact of a quality index for radar-based reference measurements in the H-SAF precipitation product validation

    Science.gov (United States)

    Rinollo, A.; Vulpiani, G.; Puca, S.; Pagliara, P.; Kaňák, J.; Lábó, E.; Okon, L'.; Roulin, E.; Baguis, P.; Cattani, E.; Laviola, S.; Levizzani, V.

    2013-10-01

    The EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) provides rainfall estimations based on infrared and microwave satellite sensors on board polar and geostationary satellites. The validation of these satellite estimations is performed by the H-SAF Precipitation Product Validation Group (PPVG). A common validation methodology has been defined inside the PPVG in order to make validation results from several institutes comparable and understandable. The validation of the PR-OBS-3 (blended infrared-microwave (IR-MW) instantaneous rainfall estimation) product using radar-based rainfall estimations as ground reference is described herein. A network of C-band and Ka-band radars throughout Europe ensures a wide area coverage with different orographic configurations and climatological regimes, but the definition of a quality control protocol for obtaining consistent ground precipitation fields across several countries is required. Among the hydro-meteorological community, the evaluation of the data quality is a quite consolidated practice, even though a unique definition of a common evaluation methodology between different countries and institutions has not been set up yet. Inside H-SAF, the first definition of the quality index of the radar rainfall observations has been introduced at the Italian Civil Protection Department (DPC). In the evaluation of the DPC quality index, several parameters are considered, some measured by the radar itself (static clutter map, range distance, radial velocity, texture of differential reflectivity, texture of co-polar correlation coefficient and texture of differential phase shift) and some obtained by external sources (digital elevation model, freezing layer height). In some cases, corrections were applied for clutter and beam blocking. The DPC quality index was calculated and applied to some relevant meteorological events reported by a radar test site in Italy. The precipitation

  1. Precipitation accumulation analysis – assimilation of radar-gauge measurements and validation of different methods

    Directory of Open Access Journals (Sweden)

    E. Gregow

    2013-10-01

    Full Text Available We investigate the appropriateness of four different methods to produce precipitation accumulation fields using radar data alone or combined with precipitation gauge data. These methods were validated for high-latitude weather conditions of Finland. The reference method uses radar reflectivity only, while three assimilation methods are used to blend radar and surface observations together, namely the linear analysis regression, the Barnes objective analysis and a new method based on a combination of the regression and Barnes techniques (RandB. The Local Analysis and Prediction System (LAPS is used as a platform to calculate the four different hourly accumulation products over a 6-month period covering summer 2011. The performance of each method is verified against both dependent and independent observations (i.e. observations that are or are not included, respectively, into the precipitation accumulation analysis. The newly developed RandB method performs best according to our results. Applying the regression or Barnes assimilation analysis separately still yields better results for the accumulation products compared to precipitation accumulation derived from radar data alone.

  2. Precipitation accumulation analysis – assimilation of radar-gauge measurements and validation of different methods

    Directory of Open Access Journals (Sweden)

    H. Hohti

    2013-02-01

    Full Text Available We investigate the appropriateness of four different methods used for combining radar data with precipitation gauge data to produce precipitation accumulation fields. These methods were validated for high-latitudes weather conditions of Finland. The reference method uses radar reflectivity only, while three assimilation methods are used to blend radar and surface observations together, namely: the linear analysis regression, the Barnes objective analysis and a new method based on a combination of the regression and Barnes techniques (RandB. The Local Analysis and Prediction System (LAPS is used as platform to calculate the four different hourly accumulation products over a 6-months period covering summer 2011. The performance of each method is verified against both dependent and independent observations (i.e. observations that are or are not included, respectively, into the precipitation accumulation analysis. The new developed RandB-method performs best according to our results. Applying the regression- or Barnes assimilation analysis separately still yields better results for the accumulation products compared to precipitation accumulation derived from radar data alone.

  3. How Well Can We Estimate Error Variance of Satellite Precipitation Data Around the World?

    Science.gov (United States)

    Gebregiorgis, A. S.; Hossain, F.

    2014-12-01

    The traditional approach to measuring precipitation by placing a probe on the ground will likely never be adequate or affordable in most parts of the world. Fortunately, satellites today provide a continuous global bird's-eye view (above ground) at any given location. However, the usefulness of such precipitation products for hydrological applications depends on their error characteristics. Thus, providing error information associated with existing satellite precipitation estimates is crucial to advancing applications in hydrologic modeling. In this study, we present a method of estimating satellite precipitation error variance using regression model for three satellite precipitation products (3B42RT, CMORPH, and PERSIANN-CCS) using easily available geophysical features and satellite precipitation rate. The goal of this work is to explore how well the method works around the world in diverse geophysical settings. Topography, climate, and seasons are considered as the governing factors to segregate the satellite precipitation uncertainty and fit a nonlinear regression equation as function of satellite precipitation rate. The error variance models were tested on USA, Asia, Middle East, and Mediterranean region. Rain-gauge based precipitation product was used to validate the errors variance of satellite precipitation products. Our study attests that transferability of model estimators (which help to estimate the error variance) from one region to another is practically possible by leveraging the similarity in geophysical features. Therefore, the quantitative picture of satellite precipitation error over ungauged regions can be discerned even in the absence of ground truth data.

  4. JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

    Science.gov (United States)

    Folmer, M. J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J. M.; Nelson, J. A., Jr.; Goldberg, M.

    2016-12-01

    The National Oceanic and Atmospheric Administration (NOAA) Satellite Proving Ground (PG) for Marine, Precipitation, and Satellite Analysis (MPS) has been demonstrating and evaluating Suomi National Polar-orbiting Partnership (S-NPP) products along with other polar-orbiting satellite platforms in preparation for the Joint Polar Satellite System - 1 (JPSS-1) launch in March 2017. The first S-NPP imagery was made available to the MPS PG during the evolution of Hurricane Sandy in October 2012 and has since been popular in operations. Since this event the MPS PG Satellite Liaison has been working with forecasters on ways to integrate single-channel and multispectral imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Advanced Very High Resolution Radiometer (AVHRR)into operations to complement numerical weather prediction and geostationary satellite savvy National Weather Service (NWS) National Centers. Additional unique products have been introduced to operations to address specific forecast challenges, including the Cooperative Institute for Research in the Atmosphere (CIRA) Layered Precipitable Water, the National Environmental Satellite, Data, and Information Service (NESDIS) Snowfall Rate product, NOAA Unique Combined Atmospheric Processing System (NUCAPS) Soundings, ozone products from the Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS), and Infrared Atmospheric Sounding Interferometer (IASI). In addition, new satellite domains have been created to provide forecasters at the NWS Ocean Prediction Center and Weather Prediction Center with better quality imagery at high latitudes. This has led to research projects that are addressing forecast challenges such as tropical to extratropical transition and explosive cyclogenesis. This presentation will provide examples of how the MPS PG has been introducing and integrating

  5. Analysis of satellite precipitation over East Africa during last decades

    Science.gov (United States)

    Cattani, Elsa; Wenhaji Ndomeni, Claudine; Merino, Andrés; Levizzani, Vincenzo

    2016-04-01

    Daily accumulated precipitation time series from satellite retrieval algorithms (e.g., ARC2 and TAMSAT) are exploited to extract the spatial and temporal variability of East Africa (EA - 5°S-20°N, 28°E-52°E) precipitation during last decades (1983-2013). The Empirical Orthogonal Function (EOF) analysis is applied to precipitation time series to investigate the spatial and temporal variability in particular for October-November-December referred to as the short rain season. Moreover, the connection among EA's precipitation, sea surface temperature, and soil moisture is analyzed through the correlation with the dominant EOF modes of variability. Preliminary results concern the first two EOF's modes for the ARC2 data set. EOF1 is characterized by an inter-annual variability and a positive correlation between precipitation and El Niño, positive Indian Ocean Dipole mode, and soil moisture, while EOF2 shows a dipole structure of spatial variability associated with a longer scale temporal variability. This second dominant mode is mostly linked to sea surface temperature variations in the North Atlantic Ocean. Further analyses are carried out by computing the time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml), i.e. RX1day, RX5day, CDD, CDD, CWD, SDII, PRCPTOT, R10, R20. The purpose is to identify the occurrenes of extreme events (droughts and floods) and extract precipitation temporal variation by trend analysis (Mann-Kendall technique). Results for the ARC2 data set demonstrate the existence of a dipole spatial pattern in the linear trend of the time series of PRCPTOT (annual precipitation considering days with a rain rate > 1 mm) and SDII (average precipitation on wet days over a year). A negative trend is mainly present over West Ethiopia and Sudan, whereas a positive trend is exhibited over East Ethiopia and Somalia. CDD (maximum number of consecutive dry days) and

  6. Remote sensing satellite formation for bistatic synthetic aperture radar observation

    Science.gov (United States)

    D'Errico, Marco; Moccia, Antonio

    2001-12-01

    In recent years the Italian Space Agency has been proceeding to the definition and launch of small missions. In this ambit, the BISSAT mission was proposed and selected along with five other missions for a competitive Phase A study. BISSAT mission concept consists in flying a passive SAR on board a small satellite, which observes the area illuminated by an active SAR, operating on an already existing large platform. Several scientific applications of bistatic measurements can be envisaged: improvement of image classification and pattern recognition, derivation of medium-resolution digital elevation models, velocity measurements, measurements of sea-wave spectra. BISSAT payload is developed on the basis of the X-band SAR of the COSMO/SkyMed mission, while BISSAT bus is based on an upgrade of MITA. Orbit design has been performed, leading to the same orbit parameters apart from the ascending node right ascension (5.24 degree(s) shift) and the time of the passage on the ascending node (1.17s shift). A minimum distance at the passage of the orbit crossing point of about 42 km (5.7s) is computed. To maintain adequate swath overlap along the orbit, attitude maneuver or antenna electronic steering must be envisaged and traded-off taking into account radar performance and cost of hardware upgrade.

  7. A general interactive system for compositing digital radar and satellite data

    Science.gov (United States)

    Ghosh, K. K.; Chen, L. C.; Faghmous, M.; Heymsfield, G. M.

    1981-01-01

    Reynolds and Smith (1979) have considered the combined use of digital weather radar and satellite data in interactive systems for case study analysis and forecasting. Satellites view the top of clouds, whereas radar is capable of observing the detailed internal structure of clouds. The considered approach requires the use of a common coordinate system. In the present investigation, it was decided to use the satellite coordinate system as the base system in order to maintain the fullest resolution of the satellite data. The investigation is concerned with the development of a general interactive software system called RADPAK for remapping and analyzing conventional and Doppler radar data. RADPAK is implemented as a part of a minicomputer-based image processing system, called Atmospheric and Oceanographic Image Processing System. Attention is given to a general description of the RADPAK system, remapping methodology, and an example of satellite remapping.

  8. A method for measuring precipitation parameters and raindrop size distributions using radar reflectivity and optical extinction

    Science.gov (United States)

    Ulbrich, C. W.; Atlas, D.

    1977-01-01

    A method of determining precipitation parameters from two remotely measurable quantities, the radar reflectivity factor and the optical extinction, is described. The raindrop size spectrum is approximated by a two-parameter exponential form; when these parameters are evaluated in terms of the radar reflectivity factor and the optical extinction, an exponential spectrum is obtained that is generally in very good agreement with the observed size spectrum. Other calculated precipitation parameters, such as rainfall rate and liquid water content, which are derived from the exponential approximation, also agree with experimental data. It is indicated that other combinations of two remote measurables can also be used to obtain more accurate estimates of precipitation parameters than can be obtained by the use of an empirical relationship.

  9. Online Assessment of Satellite-Derived Global Precipitation Products

    Science.gov (United States)

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

    2012-01-01

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

  10. Precipitation Analysis at Fine Time Scales Using Multiple Satellites: Real-time and Research Products and Applications

    Science.gov (United States)

    Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold

    2004-01-01

    Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) in 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O"N-5O0S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, including: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

  11. Precipitation Analysis at Fine Time Scales using TRMM and Other Satellites: Real-time and Research Products and Applications

    Science.gov (United States)

    Adler, Robert; Huffman, George; Bolvin, David; Nelkin, Eric; Curtis, Scott; Pierce, Harold; Gu, Guo-Jon

    2004-01-01

    Quasi-global precipitation analyses at fine time scales (3-hr) are described. TRMM observations (radar and passive microwave) are used to calibrate polar-orbit microwave observations from SSM/I (and other satellites instruments, including AMSR and AMSU) and geosynchronous IR observations. The individual data sets are then merged using a priority order based on quality to form the TRMM Multi-satellite Precipitation Analysis (MPA). Raingauge information is used to help constrain the satellite-based estimates over land. The TRMM standard research product (Version 6 3B-42 of the TRMM products) will be available for the entire TRMM period (January 1998-present) by the end of 2004. The real-time version of this merged product has been produced over the past two years and is available on the U.S. TRMM web site (trmm.gsfc.nasa.gov) at 0.25" latitude-longitude resolution over the latitude range from 5O0N-50"S. Validation of daily totals indicates good results, with limitations noted in mid-latitude winter over land and regions of shallow, orographic precipitation. Various applications of these estimates are described, includmg: 1) detecting potential floods in near real-time; 2) analyzing Indian Ocean precipitation variations related to the initiation of El Nino; 3) determining characteristics of the African monsoon; and 4) analysis of diurnal variations.

  12. Satellite radar altimetry for monitoring small rivers and lakes in Indonesia

    NARCIS (Netherlands)

    Sulistioadi, Y.B.; Tseng, K.H.; Shum, C.K.; Hidayat, Hidayat; Sumaryono, M.; Suhardiman, A.; Setiawan, F.; Sunarso, S.

    2015-01-01

    Remote sensing and satellite geodetic observations are capable of hydrologic monitoring of freshwater resources. Although satellite radar altimetry has been used in monitoring water level or discharge, its use is often limited to monitoring large rivers (>1 km) with longer interval periods (&g

  13. Validation of BALTIMOS precipitation structures using BALTRAD radar data

    Science.gov (United States)

    Theusner, Michael; Hauf, Thomas

    2014-11-01

    The comparison of rain areas observed by the radar network BALTRAD and those produced by the model BALTIMOS shows that the model is able to reproduce the rain areas' basic properties. These are power law distributed frequency distributions as well as lognormal rain area size distributions. The parameters governing these distributions are also matched by power laws evident for the observations and the BALTIMOS data. The distributions also provide evidence that the model produces too many large structures and too little small ones. However, the shape of these structures, represented by their fractal dimension, is well met. The perimeter of the model structures is only slightly smoother than that of the observed ones. The model is also able to reproduce the diurnal cycle of convective activity with emerging and decaying convective cells, though some deficiencies in the timing and the magnitude of the maximum occurrence of rain areas and peaks are evident. Additionally, it was found that the methods developed within this project are a valuable tool to validate BALTIMOS and potentially also other regional climate models.

  14. Detection and quantification of precipitations signatures on synthetic aperture radar imagery at X band

    Science.gov (United States)

    Mori, Saverio; Montopoli, Mario; Pulvirenti, Luca; Marzano, Frank S.; Pierdicca, Nazzareno

    2016-10-01

    Nowadays a well-established tool for Earth remote sensing is represented by Spaceborne synthetic aperture radars (SARs) operating at L-band and above that offers a microwave perspective at very high spatial resolution in almost all-weather conditions. Nevertheless, atmospheric precipitating clouds can significantly affect the signal backscattered from the ground surface on both amplitude and phase, as assessed by numerous recent works analyzing data collected by COSMO-SkyMed (CSK) and TerraSAR-X (TSX) missions. On the other hand, such sensitivity could allow detecting and quantifying precipitations through SARs. In this work, we propose an innovative processing framework aiming at producing X-SARs precipitation maps and cloud masks. While clouds masks allow the user to detect areas interested by precipitations, precipitation maps offer the unique opportunity to ingest within flood forecasting model precipitation data at the catchment scale. Indeed, several issues still need to be fully addressed. The proposed approach allows distinguishing flooded areas, precipitating clouds together with permanent water bodies. The detection procedure uses image segmentation techniques, fuzzy logic and ancillary data such as local incident angle map and land cover; an improved regression empirical algorithm gives the precipitation estimation. We have applied the proposed methodology to 16 study cases, acquired within TSX and CSK missions over Italy and United States. This choice allows analysing different typologies of events, and verifying the proposed methodology through the available local weather radar networks. In this work, we will discuss the results obtained until now in terms of improved rain cell localization and precipitation quantification.

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

    Science.gov (United States)

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

    2016-04-01

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

  16. A Radar Climatology for Germany - a 16-year high resolution precipitation data and its possibilities

    Science.gov (United States)

    Walawender, Ewelina; Winterrath, Tanja; Brendel, Christoph; Hafer, Mario; Junghänel, Thomas; Klameth, Anna; Weigl, Elmar; Becker, Andreas

    2017-04-01

    One of the main features of heavy precipitation events is their small-scale distribution. Despite a local occurrence, these intensive rainfalls may, however, cause most serious damage and have significant impact on the whole river basin area resulting in e.g. flash floods or urban flooding. Thus, it is of great importance not only to detect the life-cycle of extreme precipitation during its occurrence but also to collect precise climatological information on such events. The German weather service (Deutscher Wetterdienst) operates a very dense network of more than 2000 weather stations collecting data on precipitation. It is however not sufficient for detecting spatially limited phenomena. Thanks to radar data, current monitoring of such events is possible. A quality control process is applied to real-time radar products, however only automatic rain gauges data can be used in the adjustment procedure. To merge both radar data and all available rain gauges data, the radar climatology dataset was established. Within the framework of a project financed by the federal agencies' strategic alliance 'Adaptation to Climate Change', 16 years (2001-2016) of radar data have been reanalyzed in order to gain a homogenous, quality-controlled, high-resolution precipitation data set suitable for analyzing extreme events in a climatological approach. Additional corrections methods (e.g. clutter, spokes and beam height correction) were defined and used for the reprocessing procedure to enhance the data quality. Although the time series is still rather short for a climatology, for the first time the data set allows an insight into e.g. the distribution, size, life cycle, and duration of extreme events that cannot be measured by point measurements alone. All radar climatology products share the same spatial and temporal coverage. The whole dataset has been produced for the area of Germany. With the relatively high spatial resolution of 1km, the data can be used as a component of wide

  17. Evaluation of microphysics and precipitation-type frequencies in long-term three-dimensional cloud-resolving model simulations using passive and active microwave sensors from the TRMM satellite

    Science.gov (United States)

    Matsui, T.; Zeng, X.; Tao, W.; Lang, S.; Zhang, M.; Masunaga, H.

    2007-12-01

    With significant improvements in computational power over the last decades, cloud-resolving model (CRM) simulations can now be conducted on larger scales for longer time periods to better understand cloud- precipitation systems. However, even after the decadal development of CRMs, there are many uncertainties in cloud microphysics processes and cloud-precipitation structures due to the lack of routine observations. Therefore, we need to establish a practical CRM evaluation framework using frequent observations from satellites. This evaluation framework consists of i) multi-satellite simulators and ii) the construction of statistical composites that can be used to effectively evaluate cloud-precipitation systems. First, simulated cloud- precipitation structures and microphysics processes are converted to satellite-consistent radar reflectivity and microwave brightness temperature using microwave and radar simulators in the Satellite Data Simulator Unit (SDSU). Second, the CRM-computed and satellite-observed radar reflectivities and microwave brightness temperatures are used to construct two statistical composites. One combines TRMM (Tropical Rainfall Measuring Mission) PR (precipitation radar) 13.8-GHz radar echo-top heights and TRMM VIRS (visible/infrared scanner) 10.8-micron brightness temperatures. This composite categorizes precipitating clouds into shallow warm, cumulus congestus, deep stratiform, and deep convective clouds. The other composite combines multi- frequency TMI (TRMM microwave imager) brightness temperatures. The combination of low- and high-frequency channels reveals the performance of the model cloud microphysics in terms of liquid and ice precipitation amounts. In this study, long-term CRM simulations are performed using the Goddard Cumulus Ensemble (GCE) model for three cases: ARM TWP-ICE (Tropical Warm Pool International Cloud Experiment), SCSMEX (South China Sea Monsoon Experiment), and KWAJEX (Kwajalein Experiment). Results from the proposed

  18. Comparison between radar estimations and rain gauge precipitations in the Moldavian Plateau (Romania)

    Science.gov (United States)

    Cheval, Sorin; Burcea, Sorin; Dumitrescu, Alexandru; Antonescu, Bogdan; Bell, Aurora; Breza, Traian

    2010-05-01

    Heavy rainfall events have produced significant damages and casualties in the Moldavian Plateau (Romania) in the last decades. Such phenomena are characterized by large spatial and temporal variations, and the forecast of their occurrence is thus very challenging. This study aims to compare the radar estimations and the rain gauge measurements, in order to improve the quantitative precipitation estimation (QPE) in the area of interest. The research uses data from the WSR-98D S-band Doppler radar located in Bârnova, and from rain gauges within weather stations run by Meteo Romania (Romanian National Meteorological Administration). We have focused on daily (24 h) accumulations registered at weather stations, and the output sustains the radar calibration, fostering the hydrological modeling, including flash flood forecast. The differences between R and G were investigated based on two objectives functions -the ratio R/G (BIAS) and the Root Mean Square Factor (RMSf)- while the correlations used the Pearson scores. Considerable spatial distinctions between areas with good radar accuracy for QPE and perimeters where radar is not capable to provide robust information have been emphasized during the investigations. The validation aimed to predict the rain gauge amounts in certain spots by using the radar information and resulted adjustment parameters. It has been demonstrated that the Bârnova radar data are reliable within approx. 150 km radius, and the comparison with rain gauge measurements can foster consistently the QPE accuracy in the area. This research was completed in the framework of the EU FP6 Project HYDRATE (Hydrometeorological data resources and technologies for effective flash flood forecasting), Contract no: 037024, 2006-2009.

  19. Precipitation evidences on X-Band Synthetic Aperture Radar imagery: an approach for quantitative detection and estimation

    Science.gov (United States)

    Mori, Saverio; Marzano, Frank S.; Montopoli, Mario; Pulvirenti, Luca; Pierdicca, Nazzareno

    2017-04-01

    Spaceborne synthetic aperture radars (SARs) operating at L-band and above are nowadays a well-established tool for Earth remote sensing; among the numerous civil applications we can indicate flood areas detection and monitoring, earthquakes analysis, digital elevation model production, land use monitoring and classification. Appealing characteristics of this kind of instruments is the high spatial resolution ensured in almost all-weather conditions and with a reasonable duty cycle and coverage. This result has achieved by the by the most recent generation of SAR missions, which moreover allow polarimetric observation of the target. Nevertheless, atmospheric clouds, in particular the precipitating ones, can significantly affect the signal backscattered from the ground surface (e.g. Ferrazzoli and Schiavon, 1997), on both amplitude and phase, with effects increasing with the operating frequency. In this respect, proofs are given by several recent works (e.g. Marzano et al., 2010, Baldini et al., 2014) using X-Band SAR data by COSMO-SkyMed (CSK) and TerraSAR-X (TSX) missions. On the other hand, this sensitivity open interesting perspectives towards the SAR observation, and eventually quantification, of precipitations. In this respect, a proposal approach for X-SARs precipitation maps production and cloud masking arise from our work. Cloud masking allows detection of precipitation compromised areas. Respect precipitation maps, satellite X-SARs offer the unique possibility to ingest within flood forecasting model precipitation data at the catchment scale. This aspect is particularly innovative, even if work has been done the late years, and some aspects need to still address. Our developed processing framework allows, within the cloud masking stage, distinguishing flooded areas, precipitating clouds together with permanent water bodies, all appearing dark in the SAR image. The procedure is mainly based on image segmentation techniques and fuzzy logic (e.g. Pulvirenti et

  20. Satellite radar altimetry for monitoring small river and lakes in Indonesia

    Directory of Open Access Journals (Sweden)

    Y. B. Sulistioadi

    2014-03-01

    Full Text Available Remote sensing and satellite geodetic observations are capable for hydrologic monitoring of freshwater resources. For the case of satellite radar altimetry, limited temporal resolutions (e.g., satellite revisit period prohibit the use of this method for a short ( To address this scientific challenge, this study tries to monitor small (40–200 m width and medium-sized (200–800 m width rivers and lakes using satellite altimetry through identification and choice of the over-water radar waveforms corresponding to the appropriately waveform-retracked water level. This study addresses the humid tropics of Southeast Asia, specifically in Indonesia, where similar studies do not yet exist and makes use Level 2 radar altimeter measurements generated by European Space Agency's (ESA's Envisat (Environmental Satellite mission. This experiment proves that satellite altimetry provides a good alternative, or the only means in some regions, to measure the water level of medium-sized river (200–800 m width and small lake (extent 2 in Southeast Asia humid tropic with reasonable accuracy. In addition, the procedure to choose retracked Envisat altimetry water level heights via identification or selection of standard waveform shapes for inland water is recommended and should be a standard measure especially over small rivers and lakes. This study also found that Ice-1 is not necessarily the best retracker as reported by previous studies, among the four standard waveform retracking algorithms for Envisat radar altimetry observing inland water bodies.

  1. Growth of a young pingo in the Canadian Arctic observed by RADARSAT-2 interferometric satellite radar

    OpenAIRE

    Samsonov, Sergey V.; Lantz, Trevor C.; Kokelj, Steven V; Zhang, Yu

    2016-01-01

    Advancements in radar technology are increasing our ability to detect Earth surface deformation in permafrost environments. In this paper we use satellite Differential Interferometric Synthetic Aperture Radar (DInSAR) to describe the growth of a large, relatively young pingo in the Tuktoyaktuk Coastlands. High-resolution RADARSAT-2 imagery (2011–2014) analyzed with the Multidimensional Small Baseline Subset (MSBAS) DInSAR revealed a maximum 2.7 cm yr−1 of domed uplift locate...

  2. Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

    Science.gov (United States)

    Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

    2015-04-01

    The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to

  3. Development of a polarimetric radar based hydrometeor classification algorithm for winter precipitation

    Science.gov (United States)

    Thompson, Elizabeth Jennifer

    The nation-wide WSR-88D radar network is currently being upgraded for dual-polarized technology. While many convective, warm-season fuzzy-logic hydrometeor classification algorithms based on this new suite of radar variables and temperature have been refined, less progress has been made thus far in developing hydrometeor classification algorithms for winter precipitation. Unlike previous studies, the focus of this work is to exploit the discriminatory power of polarimetric variables to distinguish the most common precipitation types found in winter storms without the use of temperature as an additional variable. For the first time, detailed electromagnetic scattering of plates, dendrites, dry aggregated snowflakes, rain, freezing rain, and sleet are conducted at X-, C-, and S-band wavelengths. These physics-based results are used to determine the characteristic radar variable ranges associated with each precipitation type. A variable weighting system was also implemented in the algorithm's decision process to capitalize on the strengths of specific dual-polarimetric variables to discriminate between certain classes of hydrometeors, such as wet snow to indicate the melting layer. This algorithm was tested on observations during three different winter storms in Colorado and Oklahoma with the dual-wavelength X- and S-band CSU-CHILL, C-band OU-PRIME, and X-band CASA IP1 polarimetric radars. The algorithm showed success at all three frequencies, but was slightly more reliable at X-band because of the algorithm's strong dependence on KDP. While plates were rarely distinguished from dendrites, the latter were satisfactorily differentiated from dry aggregated snowflakes and wet snow. Sleet and freezing rain could not be distinguished from rain or light rain based on polarimetric variables alone. However, high-resolution radar observations illustrated the refreezing process of raindrops into ice pellets, which has been documented before but not yet explained. Persistent

  4. Hydrological Applications of a High-Resolution Radar Precipitation Data Base for Sweden

    Science.gov (United States)

    Olsson, Jonas; Berg, Peter; Norin, Lars; Simonsson, Lennart

    2017-04-01

    There is an increasing need for high-resolution observations of precipitation on local, regional, national and even continental level. Urbanization and other environmental changes often make societies more vulnerable to intense short-duration rainfalls (cloudbursts) and their consequences in terms of e.g. flooding and landslides. Impact and forecasting models of these hazards put very high demands on the rainfall input in terms of both resolution and accuracy. Weather radar systems obviously have a great potential in this context, but also limitations with respect to e.g. conversion algorithms and various error sources that may have a significant impact on the subsequent hydrological modelling. In Sweden, the national weather radar network has been in operation for nearly three decades, but until recently the hydrological applications have been very limited. This is mainly because of difficulties in managing the different errors and biases in the radar precipitation product, which made it hard to demonstrate any distinct added value as compared with gauge-based precipitation products. In the last years, however, in light of distinct progress in developing error correction procedures, substantial efforts have been made to develop a national gauge-adjusted radar precipitation product - HIPRAD (High-Resolution Precipitation from Gauge-Adjusted Weather Radar). In HIPRAD, the original radar precipitation data are scaled to match the monthly accumulations in a national grid (termed PTHBV) created by optimal interpolation of corrected daily gauge observations, with the intention to attain both a high spatio-temporal resolution and accurate long-term accumulations. At present, HIPRAD covers the period 2000-present with resolutions 15 min and 2×2 km2. A key motivation behind the development of HIPRAD is the intention to increase the temporal resolution in the national flood forecasting system from 1 day to 1 hour. Whereas a daily time step is sufficient to describe the

  5. Precipitation and microphysical processes observed by three polarimetric X-band radars and ground-based instrumentation during HOPE

    OpenAIRE

    Xie, Xinxin; Evaristo, Raquel; Simmer, Clemens; Handwerker, Jan; Trömel, Silke

    2016-01-01

    This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRRs) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol...

  6. 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

  7. Radar rainfall estimation for the identification of debris-flow precipitation thresholds

    Science.gov (United States)

    Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

    2014-05-01

    Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial

  8. Testing geostatistical methods to combine radar and rain gauges for precipitation mapping in a mountainous region

    Science.gov (United States)

    Erdin, R.; Frei, C.; Sideris, I.; Kuensch, H.-R.

    2010-09-01

    There is an increasing demand for accurate mapping of precipitation at a spatial resolution of kilometers. Radar and rain gauges - the two main precipitation measurement systems - exhibit complementary strengths and weaknesses. Radar offers high spatial and temporal resolution but lacks accuracy of absolute values, whereas rain gauges provide accurate values at their specific point location but suffer from poor spatial representativeness. Methods of geostatistical mapping have been proposed to combine radar and rain gauge data for quantitative precipitation estimation (QPE). The aim is to combine the respective strengths and compensate for the respective weaknesses of the two observation platforms. Several studies have demonstrated the potential of these methods over topography of moderate complexity, but their performance remains unclear for high-mountain regions where rainfall patterns are complex, the representativeness of rain gauge measurements is limited and radar observations are obstructed. In this study we examine the potential and limitations of two frequently used geostatistical mapping methods for the territory of Switzerland, where the mountain chain of the Alps poses particular challenges to QPE. The two geostatistical methods explored are kriging with external drift (KED) using radar as drift variable and ordinary kriging of radar errors (OKRE). The radar data is a composite from three C-band radars using a constant Z-R relationship, advanced correction processings for visibility, ground clutter and beam shielding and a climatological bias adjustment. The rain gauge data originates from an automatic network with a typical inter-station distance of 25 km. Both combination methods are applied to a set of case examples representing typical rainfall situations in the Alps with their inherent challenges at daily and hourly time resolution. The quality of precipitation estimates is assessed by several skill scores calculated from cross validation errors at

  9. Characterization of tropical precipitation using drop size distribution and rain rate-radar reflectivity relation

    Science.gov (United States)

    Das, Saurabh; Maitra, Animesh

    2017-03-01

    Characterization of precipitation is important for proper interpretation of rain information from remotely sensed data. Rain attenuation and radar reflectivity (Z) depend directly on the drop size distribution (DSD). The relation between radar reflectivity/rain attenuation and rain rate (R) varies widely depending upon the origin, topography, and drop evolution mechanism and needs further understanding of the precipitation characteristics. The present work utilizes 2 years of concurrent measurements of DSD using a ground-based disdrometer at five diverse climatic conditions in Indian subcontinent and explores the possibility of rain classification based on microphysical characteristics of precipitation. It is observed that both gamma and lognormal distributions are performing almost similar for Indian region with a marginally better performance by one model than other depending upon the locations. It has also been found that shape-slope relationship of gamma distribution can be a good indicator of rain type. The Z-R relation, Z = ARb, is found to vary widely for different precipitation systems, with convective rain that has higher values of A than the stratiform rain for two locations, whereas the reverse is observed for the rest of the three locations. Further, the results indicate that the majority of rainfall (>50%) in Indian region is due to the convective rain although the occurrence time of convective rain is low (<10%).

  10. An operational weather radar-based Quantitative Precipitation Estimation and its application in catchment water resources modeling

    DEFF Research Database (Denmark)

    He, Xin; Vejen, Flemming; Stisen, Simon

    2011-01-01

    of precipitation compared with rain-gauge-based methods, thus providing the basis for better water resources assessments. The radar QPE algorithm called ARNE is a distance-dependent areal estimation method that merges radar data with ground surface observations. The method was applied to the Skjern River catchment...... reliable simulations of stream flow and water balance. The potential of using radar-based precipitation was found to be especially high at a smaller scale, where the impact of spatial resolution was evident from the stream discharge results. Also, groundwater recharge was shown to be sensitive...

  11. IoSiS: a radar system for imaging of satellites in space

    Science.gov (United States)

    Jirousek, M.; Anger, S.; Dill, S.; Schreiber, E.; Peichl, M.

    2017-05-01

    Space debris nowadays is one of the main threats for satellite systems especially in low earth orbit (LEO). More than 700,000 debris objects with potential to destroy or damage a satellite are estimated. The effects of an impact often are not identifiable directly from ground. High-resolution radar images are helpful in analyzing a possible damage. Therefor DLR is currently developing a radar system called IoSiS (Imaging of Satellites in Space), being based on an existing steering antenna structure and our multi-purpose high-performance radar system GigaRad for experimental investigations. GigaRad is a multi-channel system operating at X band and using a bandwidth of up to 4.4 GHz in the IoSiS configuration, providing fully separated transmit (TX) and receive (RX) channels, and separated antennas. For the observation of small satellites or space debris a highpower traveling-wave-tube amplifier (TWTA) is mounted close to the TX antenna feed. For the experimental phase IoSiS uses a 9 m TX and a 1 m RX antenna mounted on a common steerable positioner. High-resolution radar images are obtained by using Inverse Synthetic Aperture Radar (ISAR) techniques. The guided tracking of known objects during overpass allows here wide azimuth observation angles. Thus high azimuth resolution comparable to the range resolution can be achieved. This paper outlines technical main characteristics of the IoSiS radar system including the basic setup of the antenna, the radar instrument with the RF error correction, and the measurement strategy. Also a short description about a simulation tool for the whole instrument and expected images is shown.

  12. A Numerical Method to Generate High Temporal Resolution Precipitation Time Series by Combining Weather Radar Measurements with a Nowcast Model

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2014-01-01

    The topic of this paper is temporal interpolation of precipitation observed by weather radars. Precipitation measurements with high spatial and temporal resolution are, in general, desired for urban drainage applications. An advection-based interpolation method is developed which uses methods...... for vector field estimation already known from short-term weather radar nowcasting. However, instead of forecasting the weather radar rainfall, the proposed interpolation method exploits the advection of the rainfall in the interpolation. The interpolated rainfall fields are validated by measurements...... at ground level from laser disdrometers. The proposed interpolation method performs better when compared to traditional interpolation of weather radar rainfall where the radar observation is considered constant in time between measurements. It is demonstrated that the advection-based interpolation method...

  13. Monitoring of Arctic Conditions from a Virtual Constellation of Synthetic Aperture Radar Satellites

    Science.gov (United States)

    2014-09-30

    radars to monitor the melting and freezing cycles of the Arctic Ocean north of 65o. Satellite data collections will support in-situ buoy clusters and... ice -type, and lead expansion/contraction with temporal resolutions from hours to days. Ultimately provide a routine Arctic coverage and generate...OBJECTIVES a) Provide daily Arctic situational awareness from the CSTARS SAR satellite constellation. b) Develop a Neural Network algorithm for ice -type

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

    Directory of Open Access Journals (Sweden)

    Yiwen Mei

    2016-03-01

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

  15. C-Band Scanning ARM Precipitation Radar (C-SAPR) Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Widener, K; Bharadwaj, N

    2012-11-13

    The C-band scanning ARM precipitation radar (C-SAPR) is a scanning polarimetric Doppler radar transmitting simultaneously in both H and V polarizations. With a 350-kW magnetron transmitter, this puts 125 kW of transmitted power for each polarization. The receiver for the C-SAPR is a National Center for Atmospheric Research (NCAR) -developed Hi-Q system operating in a coherent-on-receive mode. The ARM Climate Research Facility operates two C-SAPRs; one of them is deployed near the Southern Great Plains (SGP) Central Facility near the triangular array of X-SAPRs, and the second C-SAPR is deployed at ARM’s Tropical Western Pacific (TWP) site on Manus Island in Papua New Guinea.

  16. GLUE Based Uncertainty Estimation of Urban Drainage Modeling Using Weather Radar Precipitation Estimates

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Thorndahl, Søren Liedtke; Rasmussen, Michael R.

    2011-01-01

    Distributed weather radar precipitation measurements are used as rainfall input for an urban drainage model, to simulate the runoff from a small catchment of Denmark. It is demonstrated how the Generalized Likelihood Uncertainty Estimation (GLUE) methodology can be implemented and used to estimate...... the uncertainty of the weather radar rainfall input. The main findings of this work, is that the input uncertainty propagate through the urban drainage model with significant effects on the model result. The GLUE methodology is in general a usable way to explore this uncertainty although; the exact width...... of the prediction bands can be questioned, due to the subjective nature of the method. Moreover, the method also gives very useful information about the model and parameter behaviour....

  17. Flood Monitoring and Hydrologic Studies Using Retracked Satellite Radar Altimetry

    Science.gov (United States)

    Zhang, M.; Shum, C.; Lee, H.; Alsdorf, D.; Schwartz, F.

    2008-12-01

    Nadir, pulse-limited radar altimetry measurements have been used to monitor large surface-water bodies. In spite of progress, there is a need for a robust and automated procedure, which allows classification and stage measurements in small water bodies, which lying along the orbital path, using multiple radar altimeter measurements. Here we used an algorithm, which is mainly based on radar scatter waveform response and statistical analysis of mean and standard deviation of the resulting water level change to classify surface- waters from other land covers. We tested the algorithm using 10-Hz retracked radar altimetry measurements from TOPEX over regions including the Amazon River basin, the Prairie Pothole Region in North America, and south-western Taiwan. The estimated water-level stages are compared with data from available stage measurements, and altimetry data available from public data centers. We also applied the algorithm to study the 1997 hundred-year Red River flood, and the June 2008 fifty-year flood in the Upper Midwest of the United States. For the1997 flood, it is found that the flooded regions detected by altimetry include the Red River Basin in North Dakota and Minnesota, the Missouri River Basin in North Dakota and South Dakota, the Minnesota River Basin and the Mississippi River Basin in Minnesota and Iowa. The extent of the flood agrees with the USGS record. The observed water height in Grand Forks reaches 6 meters above the normal. The ENVISAT altimetry is shown to be able to track the ebb and recede of the 2008 Iowa City flood. The results of this study could be applied to provide improved accuracy and potentially automated classification of nadir radar altimetry observed small inland water body measurements for hydrologic studies and for flood monitoring.

  18. Evaluation of radar-gauge merging methods for quantitative precipitation estimates

    Directory of Open Access Journals (Sweden)

    E. Goudenhoofdt

    2008-10-01

    Full Text Available Accurate quantitative precipitation estimates are of crucial importance for hydrological studies and applications. When spatial precipitation fields are required, rain gauge measurements are often combined with weather radar observations. In this paper, we evaluate several radar-gauge merging methods with various degrees of complexity: from mean field bias correction to geostatical merging techniques. The study area is the Walloon region of Belgium, which is mostly located in the Meuse catchment. Observations from a C-band Doppler radar and a dense rain gauge network are used to retrieve daily rainfall accumulations over this area. The relative performance of the different merging methods are assessed through a comparison against daily measurements from an independent gauge network. A 3-year verification is performed using several statistical quality parameters. It appears that the geostatistical merging methods perform best with the mean absolute error decreasing by 40% with respect to the original data. A mean field bias correction still achieves a reduction of 25%. A seasonal analysis shows that the benefit of using radar observations is particularly significant during summer. The effect of the network density on the performance of the methods is also investigated. For this purpose, a simple approach to remove gauges from a network is proposed. The analysis reveals that the sensitivity is relatively high for the geostatistical methods but rather small for the simple methods. The geostatistical methods give the best results for all network densities except for a very low density of 1 gauge per 500 km2 where a range-dependent adjustment complemented with a static local bias correction performs best.

  19. Iceland rising: Solid Earth response to ice retreat inferred from satellite radar interferometry and visocelastic modeling

    NARCIS (Netherlands)

    Auriac, A.; Spaans, K.H.; Sigmundsson, F.; Hooper, A.; Schmidt, P.; Lund, B.

    2013-01-01

    A broad uplift occurs in Iceland in response to the retreat of ice caps, which began circa 1890. Until now, this deformation signal has been measured primarily using GPS at points some distance away from the ice caps. Here, for the first time we use satellite radar interferometry (interferometric sy

  20. Mapping Offshore Winds Around Iceland Using Satellite Synthetic Aperture Radar and Mesoscale Model Simulations

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Nawri, Nikolai

    2015-01-01

    The offshore wind climate in Iceland is examined based on satellite synthetic aperture radar (SAR), coastal meteorological station measurements, and results from two atmospheric model data sets, HARMONIE and NORA10. The offshore winds in Iceland are highly influenced by the rugged coastline. Lee...

  1. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN from a Geostationary Satellite.

    Directory of Open Access Journals (Sweden)

    Yu Liu

    Full Text Available The prediction of the short-term quantitative precipitation nowcasting (QPN from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC; the Horn-Schunck optical-flow scheme (PHS; and the Pyramid Lucas-Kanade Optical Flow method (PPLK, which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6. The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  2. Effects of the Forecasting Methods, Precipitation Character, and Satellite Resolution on the Predictability of Short-Term Quantitative Precipitation Nowcasting (QPN) from a Geostationary Satellite.

    Science.gov (United States)

    Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang; Ji, Wei

    2015-01-01

    The prediction of the short-term quantitative precipitation nowcasting (QPN) from consecutive gestational satellite images has important implications for hydro-meteorological modeling and forecasting. However, the systematic analysis of the predictability of QPN is limited. The objective of this study is to evaluate effects of the forecasting model, precipitation character, and satellite resolution on the predictability of QPN using images of a Chinese geostationary meteorological satellite Fengyun-2F (FY-2F) which covered all intensive observation since its launch despite of only a total of approximately 10 days. In the first step, three methods were compared to evaluate the performance of the QPN methods: a pixel-based QPN using the maximum correlation method (PMC); the Horn-Schunck optical-flow scheme (PHS); and the Pyramid Lucas-Kanade Optical Flow method (PPLK), which is newly proposed here. Subsequently, the effect of the precipitation systems was indicated by 2338 imageries of 8 precipitation periods. Then, the resolution dependence was demonstrated by analyzing the QPN with six spatial resolutions (0.1atial, 0.3a, 0.4atial rand 0.6). The results show that the PPLK improves the predictability of QPN with better performance than the other comparison methods. The predictability of the QPN is significantly determined by the precipitation system, and a coarse spatial resolution of the satellite reduces the predictability of QPN.

  3. Accurate Characterization of Winter Precipitation Using Multi-Angle Snowflake Camera, Visual Hull, Advanced Scattering Methods and Polarimetric Radar

    Directory of Open Access Journals (Sweden)

    Branislav M. Notaroš

    2016-06-01

    Full Text Available This article proposes and presents a novel approach to the characterization of winter precipitation and modeling of radar observables through a synergistic use of advanced optical disdrometers for microphysical and geometrical measurements of ice and snow particles (in particular, a multi-angle snowflake camera—MASC, image processing methodology, advanced method-of-moments scattering computations, and state-of-the-art polarimetric radars. The article also describes the newly built and established MASCRAD (MASC + Radar in-situ measurement site, under the umbrella of CSU-CHILL Radar, as well as the MASCRAD project and 2014/2015 winter campaign. We apply a visual hull method to reconstruct 3D shapes of ice particles based on high-resolution MASC images, and perform “particle-by-particle” scattering computations to obtain polarimetric radar observables. The article also presents and discusses selected illustrative observation data, results, and analyses for three cases with widely-differing meteorological settings that involve contrasting hydrometeor forms. Illustrative results of scattering calculations based on MASC images captured during these events, in comparison with radar data, as well as selected comparative studies of snow habits from MASC, 2D video-disdrometer, and CHILL radar data, are presented, along with the analysis of microphysical characteristics of particles. In the longer term, this work has potential to significantly improve the radar-based quantitative winter-precipitation estimation.

  4. The use of airborne laser data to calibrate satellite radar altimetry data over ice sheets

    DEFF Research Database (Denmark)

    Ekholm, Simon; Bamber, J.L.; Krabill, W.B.

    2002-01-01

    -correlated noise can be effectively removed by the so-called relocation error correction method. The adjustment, however, produces a different spatial sampling of the data, which introduces a non-negligible slope related bias to the computation of digital elevation models. In this paper we incorporate high......Satellite radar altimetry is the most important data source for ice sheet elevation modeling but it is well established that the accuracy of such data from satellite borne radar altimeters degrade seriously with increasing surface slope and level of roughness. A significant fraction of the slope...... as a linear function of surface slope. This linear correspondence is in turn tested as a model for adjusting the satellite altimetry data for the observed slope correlated bias. The adjustment is shown to have a significant effect in terms of reducing the bias, thus improving the modeling accuracy of the data....

  5. Global Precipitation Mission Visualization Tool

    Science.gov (United States)

    Schwaller, Mathew

    2011-01-01

    The Global Precipitation Mission (GPM) software provides graphic visualization tools that enable easy comparison of ground- and space-based radar observations. It was initially designed to compare ground radar reflectivity from operational, ground-based, S- and C-band meteorological radars with comparable measurements from the Tropical Rainfall Measuring Mission (TRMM) satellite's precipitation radar instrument. This design is also applicable to other groundbased and space-based radars, and allows both ground- and space-based radar data to be compared for validation purposes. The tool creates an operational system that routinely performs several steps. It ingests satellite radar data (precipitation radar data from TRMM) and groundbased meteorological radar data from a number of sources. Principally, the ground radar data comes from national networks of weather radars (see figure). The data ingested by the visualization tool must conform to the data formats used in GPM Validation Network Geometry-matched data product generation. The software also performs match-ups of the radar volume data for the ground- and space-based data, as well as statistical and graphical analysis (including two-dimensional graphical displays) on the match-up data. The visualization tool software is written in IDL, and can be operated either in the IDL development environment or as a stand-alone executable function.

  6. Prediction of Water-level Changes and Water Use in the High Plains Aquifer from Radar Precipitation

    Science.gov (United States)

    Whittemore, D. O.; Butler, J. J., Jr.; Wilson, B. B.

    2015-12-01

    Meteorological conditions are the primary driver of variations in the annual volume of groundwater pumped for irrigation from the High Plains aquifer (HPA), one of the largest aquifers of the world. Correlations between climatic indices (such as the Standardized Precipitation Index [SPI]) and mean annual water-level changes and water use have been shown to be valuable tools for assessing the aquifer's response to various climatic scenarios in the semi-arid Kansas HPA (Whittemore et al., 2015). The correlations are generally better for a relatively large area (region) of the aquifer (such as that encompassed by a climatic division) because of the number of weather stations from which the climatic indices are computed. Correlations can be poor for county-sized and smaller areas (less than a few to several hundred km2) because of the low density of weather stations. Since 2005, radar precipitation data have been served online by the National Weather Service. The radar data are adjusted based on ground observations and are available at a spatial resolution of ~4x4 km. Correlations between radar precipitation and mean annual water-level changes and water use are comparable to those using SPI for the same region. Correlations using radar precipitation data are generally higher than with SPI computed for smaller areas, such as for counties and areas around individual monitoring wells. The optimum correlations for radar precipitation are determined using sums of different spans of monthly mean precipitation that include the irrigation season for the area of interest. Coefficients of determination, R2, for radar precipitation versus annual water-level change and water use can exceed 0.8 for counties and monitoring well areas in the Kansas HPA. These correlations are being used to assess the impact of drought and water-use management on HPA sustainability. These correlations can also be used to assess the quality of the reported water-use data.

  7. Comprehensive Radar Observations of Clouds and Precipitation over the Tibetan Plateau and Preliminary Analysis of Cloud Properties

    Institute of Scientific and Technical Information of China (English)

    2015-01-01

    Intensive fi eld experiment is an important approach to obtain microphysical information about clouds and precipitation. From 1 July to 31 August 2014, the third Tibetan Plateau Atmospheric Science Experiment was carried out and comprehensive measurements of water vapor, clouds, and precipitation were conducted at Naqu. The most advanced radars in China, such as Ka-band millimeter-wave cloud radar, Ku-band micro-rain radar, C-band continuous-wave radar and lidar, and microwave radiometer and disdrometer were deployed to observe high spatial-temporal vertical structures of clouds and precipitation. The C-band dual-linear polarization radar was coordinated with the China new generation weather radar to constitute a dual-Doppler radar system for the measurements of three-dimensional wind fi elds within convective precipitations and the structure and evolution of hydrometeors related to precipitation process. Based on the radar measurements in this experiment, the diurnal variations of several important cloud properties were analyzed, including cloud top and base, cloud depth, cloud cover, number of cloud layers, and their vertical structures during summertime over Naqu. The features of refl ectivity, velocity, and depolarization ratio for diff erent types of clouds observed by cloud radar are discussed. The results indicate that the cloud properties were successfully measured by using various radars in this fi eld experiment. During the summertime over Naqu, most of the clouds were located above 6 km and below 4 km above ground level. Statistical analysis shows that total amounts of clouds, the top of high-level clouds, and cloud depth, all demonstrated a distinct diurnal variation. Few clouds formed at 1000 LST (local standard time), whereas large amounts of clouds formed at 2000 LST. Newly formed cumulus and stratus clouds were often found at 3-km height, where there existed signifi cant updrafts. Deep convection reached up to 16.5 km (21 km above the mean sea level

  8. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    Directory of Open Access Journals (Sweden)

    M. P. Mittermaier

    2008-05-01

    Full Text Available A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used.

    The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  9. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    Science.gov (United States)

    Mittermaier, M. P.

    2008-05-01

    A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP) verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS) and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used. The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  10. Phase calibration of the EISCAT Svalbard Radar interferometer using optical satellite signatures

    Directory of Open Access Journals (Sweden)

    J. M. Sullivan

    2006-09-01

    Full Text Available The link between natural ion-line enhancements in radar spectra and auroral activity has been the subject of recent studies but conclusions have been limited by the spatial and temporal resolution previously available. The next challenge is to use shorter sub-second integration times in combination with interferometric programmes to resolve spatial structure within the main radar beam, and so relate enhanced filaments to individual auroral rays. This paper presents initial studies of a technique, using optical and spectral satellite signatures, to calibrate the received phase of a signal with the position of the scattering source along the interferometric baseline of the EISCAT Svalbard Radar. It is shown that a consistent relationship can be found only if the satellite passage through the phase fringes is adjusted from the passage predicted by optical tracking. This required adjustment is interpreted as being due to the vector between the theoretical focusing points of the two antennae, i.e. the true radar baseline, differing from the baseline obtained by survey between the antenna foot points. A method to obtain a measurement of the true interferometric baseline using multiple satellite passes is outlined.

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

    Science.gov (United States)

    Andersson, Axel; Bakan, Stephan; Graßl, Hartmut

    2010-08-01

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

  12. Evaluating Satellite Products for Precipitation Estimation in Mountain Regions: A Case Study for Nepal

    Directory of Open Access Journals (Sweden)

    Tarendra Lakhankar

    2013-08-01

    Full Text Available Precipitation in mountain regions is often highly variable and poorly observed, limiting abilities to manage water resource challenges. Here, we evaluate remote sensing and ground station-based gridded precipitation products over Nepal against weather station precipitation observations on a monthly timescale. We find that the Tropical Rainfall Measuring Mission (TRMM 3B-43 precipitation product exhibits little mean bias and reasonable skill in giving precipitation over Nepal. Compared to station observations, the TRMM precipitation product showed an overall Nash-Sutcliffe efficiency of 0.49, which is similar to the skill of the gridded station-based product Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE. The other satellite precipitation products considered (Global Satellite Mapping of Precipitation (GSMaP, the Climate Prediction Center Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS were less skillful, as judged by Nash-Sutcliffe efficiency, and, on average, substantially underestimated precipitation compared to station observations, despite their, in some cases, higher nominal spatial resolution compared to TRMM. None of the products fully captured the dependence of mean precipitation on elevation seen in the station observations. Overall, the TRMM product is promising for use in water resources applications.

  13. River monitoring from satellite radar altimetry in the Zambezi River basin

    DEFF Research Database (Denmark)

    Michailovsky, Claire Irene B.; McEnnis, S.; Berry, P. A. M.;

    2012-01-01

    Satellite radar altimetry can be used to monitor surface water levels from space. While current and past altimetry missions were designed to study oceans, retracking the waveforms returned over land allows data to be retrieved for smaller water bodies or narrow rivers. The objective of this study...... is the assessment of the potential for river monitoring from radar altimetry in terms of water level and discharge in the Zambezi River basin. Retracked Envisat altimetry data were extracted over the Zambezi River basin using a detailed river mask based on Landsat imagery. This allowed for stage measurements...

  14. Validation of NASA-TRMM MPA Precipitation Estimates During Tropical Storms Using Gauge and Radar-Based Estimates

    Science.gov (United States)

    Henschke, A. E.; Habib, E.

    2008-05-01

    The purpose of this study is the validation of the 3B42 and 3B42-RT rainfall products from NASA's Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) during major tropical rainfall events throughout the state of Louisiana. The 3B42-RT product, a near real time dataset, and the 3B42 product, a gauge calibrated dataset, are available at .25° x .25°, 3-hourly resolution, covering the globe from 50°N latitude to 50°S latitude. In order to investigate the validity of the TMPA data, radar-based and rain gauge datasets were used as reference. The radar-based dataset, a product of the NWS Stage IV multi- sensor precipitation estimation (MPE) algorithm, is available at 1-hourly intervals on a 4km x 4km spatial scale. The rain gauge dataset was obtained on an hourly scale from a national gauge network maintained by the National Climatic Data Center (NCDC). During the study, six tropical storm periods between 2002 and 2005, ranging in length from three to five days, were examined (Hurricane Lili, October 2002; Tropical Storm Bill, June 2003; Hurricane Ivan, September 2004; Tropical Storm Matthew, October 2004; Hurricane Katrina, August 2005; and Hurricane Rita, September 2005). During the analyzed storms, the radar and rain gauge data were averaged spatially and temporally to match the resolution of the TMPA pixels. The number of pixels studied during each storm varied from three to six pixels, with a minimum requirement of three gauges per 3B42 pixel, depending on the gauge density at the landfall location of the storm. Evaluation of the 3B42/3B42-RT error was performed on a storm by storm basis as well as an overall accumulation of data from all six storms using error metrics including the relative mean difference, relative standard deviation, correlation coefficient, and probability of detection. Significant variability in the performance metrics were observed between the different analyzed storms. Enhanced performance in terms of

  15. Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty

    Directory of Open Access Journals (Sweden)

    R. T. Tonboe

    2009-07-01

    Full Text Available Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009 satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

  16. Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty

    Science.gov (United States)

    Tonboe, R. T.; Pedersen, L. T.; Haas, C.

    2009-07-01

    Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009) satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea) the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

  17. Satellite Formation Design for Space Based Radar Applications

    Science.gov (United States)

    2007-07-30

    Practical Guidance Methodology for Relative Motion of LEO Spacecraft Based on the Clohessy-Wiltshire Equations,” AAS Paper 04-252, AAS/AIAA Space...Non- Circular Reference Orbit," AAS Paper 01-222, AAS/AIAA Space Flight Mechanics Meeting, Santa Barbara, CA, Feb 11-16, 2001. 11. D. Brouwer ...Small Eccentricities or Inclinations in the Brouwer Theory of the Artificial Satellite,” The Astronomical Journal, Vol. 68, October 1963, pp. 555

  18. Numerical Research on Effects Upon Precipitation Forecast of Doppler-Radar Estimated Precipitation and Retrieved Wind Field Under Different Model Initial Schemes

    Institute of Scientific and Technical Information of China (English)

    WANG Yehong; ZHAO Yuchun; CUI Chunguang

    2007-01-01

    On the basis of the joint estimated 1-h precipitation from Changde, Jingzhou, and Yichang Doppler radars as well as Wuhan digital radar, and the retrieved wind fields from Yichang and Jingzhou Doppler radars, a series of numerical experiments with an advanced regional η-coordinate model (AREM) under different model initial schemes, i.e., Grapes-3DVAR, Barnes objective analysis, and Barnes-3DVAR, are carried out for a torrential rain process occurring along the Yangtze River in the 24-h period from 2000 BT 22 July 2002 to investigate the effects of the Doppler-radar estimated rainfall and retrieved winds on the rainfall forecast. The main results are as follows: (1) The simulations are obviously different under three initial schemes with the same data source (the radiosounding and T213L31 analysis). On the whole,Barnes-3DVAR, which combines the advantages of the Barnes objective analysis and the Grapes-3DVAR method, gives the best simulations: well-simulated rain band and clear mesoscale structures, as well as their location and intensity close to observations. (2) Both Barnes-3DVAR and Grapes-3DVAR schemes are able to assimilate the Doppler-radar estimated rainfall and retrieved winds, but differences in simulation results are very large, with Barnes-3DVAR's simulation much better than Grapes-3DVAR's. (3) Under Grapes3DVAR scheme, the simulation of 24-h rainfall is improved obviously when assimilating the Doppler-radar estimated precipitation into the model in compared with the control experiment; but it becomes a little worse when assimilating the Doppler-radar retrieved winds into the model, and it becomes worse obviously when assimilating the Doppler-radar estimated precipitation as well as retrieved winds into the model. However,the simulation is different under Barnes-3DVAR scheme. The simulation is improved to a certain degree no matter assimilating the estimated precipitation or retrieved winds, or both of them. The result is the best when assimilating both

  19. Atmospheric refraction corrections of radiowave propagation for airborne and satellite_borne radars

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The atmospheric refraction corrections of radiowave propagation for airborne and satellite_borne radars for the spherically stratified (horizontally homogeneous) atmosphere (including lower atmosphere and ionosphere) are discussed. First, the critical apparent depression angle for radar and the perigee of ray are found using the refractive index profile close to the lowest point of the ray as the refractive index profile of spherically stratified atmosphere, and strict expressions of line_of_sight distance for radar that take account of refraction are presented. Then, to which condition the atmospheric refraction to be corrected belongs is determined, and the positioning corrections for all the twelve atmospheric refractive conditions are made using ray_tracing method. At last, the velocity_measuring corrections are made.

  20. Airborne Field Campaign Results of Ka-band Precipitation Measuring Radar in China%我国Ka频段降水测量雷达机载校飞试验结果

    Institute of Scientific and Technical Information of China (English)

    商建; 郭杨; 吴琼; 杨虎; 尹红刚

    2011-01-01

    2010年6-10月在天津与江苏地区开展了国内首次Ku/Ka频段星载降水测量雷达机载校飞试验.此次校飞试验获得了宝贵的机载雷达观测数据和地面、海面同步观测数据,目前已开展了外定标、数据对比与衰减订正等工作.该文给出了天津校飞试验中Ka频段降水测量雷达实测结果,对Ka频段降水测量雷达资料与天津地区S波段地基多普勒雷达资料进行了详细的对比分析,有利于更好地了解Ka频段降水测量雷达仪器本身的性能及其探测降水的能力;利用由GPS探空资料、地基多通道微波辐射计观测亮温结合微波辐射传输模式得到的雷达路径积分衰减量,对Ka频段降水测量雷达进行了衰减订正,为继续开展降水反演工作奠定了基础.%Spaceborne precipitation measuring radar can measure precipitation quantitatively, observe the vertical distribution and provide three dimensional precipitation structures. Spaceborne precipitation measuring radar is an important instrument on FY-3 meteorological satellite constellation. As a possible future member of the Global Precipitation Measurement(GPM) , this satellite will carry dual-frequency precipitation radar operating at Ku and Ka bands to provide scientific data for dual-frequency retrieval algorithm. Its two prototype devices, Ku-band and Ka-band radars have already been developed under the support of National Defense Science and Industry Bureau. Field campaign of Ku/Ka-band airborne precipitation measuring radar is carried out by National Satellite Meteorological Center of China Meteorological Administration combining several groups from June to October in 2010 in Tianjin and Jiangsu, called BH-RM 2010 and JS-RM 2010, respectively. This is the first time that China carries out airborne precipitation measuring radar field campaign. The purposes of this field campaign are to validate the correctness of internal and external calibration scheme under airborne

  1. MONITORING OF THE UNDERMINED TERRITORIES OF KARAGANDA COAL BASIN ON THE BASIS OF SATELLITE RADAR INTERFEROMETRY

    Directory of Open Access Journals (Sweden)

    S. B. Ozhigina

    2016-06-01

    Full Text Available In the Karaganda coal basin, mines are located in close proximity to each other and to the city of Karaganda and ongoing mining operations are accompanied by a dangerous process of settling the earth's surface and monitoring are essential for the region's econ-omy. Underground mining leads to the formation of voids in the rock mass, which cause displacement of the earth surface. This paper demonstrates an innovative use of the integrated approach for monitoring on the example of Karaganda coal basin, which includes estimation of the rock mass displacement using leveling profile lines and satellite radar interferometry. It is proved that satellite radar interferometry provides reliable results of surface subsidence measurements in mining areas and can be used for con-sidered sort of monitoring.

  2. Monitoring of the Undermined Territories of Karaganda Coal Basin on the Basis of Satellite Radar Interferometry

    Science.gov (United States)

    Ozhigina, S. B.; Mozer, D. V.; Ozhigin, D. S.; Ozhigin, S. G.; Bessimbayeva, O. G.; Khmyrova, E. N.

    2016-06-01

    In the Karaganda coal basin, mines are located in close proximity to each other and to the city of Karaganda and ongoing mining operations are accompanied by a dangerous process of settling the earth's surface and monitoring are essential for the region's econ-omy. Underground mining leads to the formation of voids in the rock mass, which cause displacement of the earth surface. This paper demonstrates an innovative use of the integrated approach for monitoring on the example of Karaganda coal basin, which includes estimation of the rock mass displacement using leveling profile lines and satellite radar interferometry. It is proved that satellite radar interferometry provides reliable results of surface subsidence measurements in mining areas and can be used for con-sidered sort of monitoring.

  3. Study and Tests of Improved Rain Estimates from the TRMM Precipitation Radar.

    Science.gov (United States)

    Ferreira, Franck; Amayenc, Paul; Oury, Stéphane; Testud, Jacques

    2001-11-01

    Rain rate R estimation from the 2A-25 profiling algorithm of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) is analyzed in two ways. Standard results from the operating version-5 algorithm are compared with those from the previous version 4. Also, various adjustments of the involved rain relationships in version 4 are explored, which leads to the proposal of two alternatives to the standard rain rate (Rstd-V4). The first one, (RN0), is based on N(0-scaled relations exploiting the concept of normalized -shaped drop size distributions; the second one, (RkR), relies on using constant R-k instead of constant R-Z relation as in the standard, where Z is reflectivity and k is attenuation coefficient. Error analysis points out a lower sensitivity of the alternative estimates to errors in radar calibration, or initial relations, than the standard. Results from a set of PR data, over ocean and land, show that the version-4 alternatives, and version-5 standard (Rstd-V5), produce more rain than the version-4 standard, which may correct for some reported underestimation. These approaches are tested via point-to-point comparisons of 3D PR-derived Z and R fields (versions 4 and 5) with `reference' fields derived from airborne dual-beam radar on board a National Oceanic and Atmospheric Administration P3-42 aircraft in Hurricanes Bonnie and Brett, for good cases of TRMM overpasses over the ocean. In the comparison domains, Bonnie is dominated by stratiform rain, and Brett includes convective and stratiform rain. In stratiform rain, the mean difference in Z, accounting for different frequencies and scanning geometries of both radars, lies within the uncertainty margin of residual errors in the radar calibrations. Also, the PR mean rain-rate estimates, RkR and Rstd-V5, agree fairly well with the P3 estimate, RP3, whereas Rstd-V4 and RN0 respectively underestimate and overestimate RP3. In convective rain (Brett case), the PR estimates of Z and R largely exceed

  4. 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.

  5. A satellite-borne radar wind sensor (RAWS)

    Science.gov (United States)

    Moore, Richard K.; Stuart, Michael; Propp, Timothy

    1993-01-01

    Modeling global atmospheric circulations and forecasting the weather would improve if worldwide information on winds aloft were available. Accurate prediction of weather is important to agriculture, shipping, air traffic, and many other fields. Global system models of climate are of great importance. Current global atmospheric models use pressure measurements and thermodynamic properties to calculate the effects of wind for use in Numerical Weather Prediction (NWP) models. Inputs to the NWP models are temperature, pressure and wind velocities at different heights. Clearly direct wind measurements could significantly improve the NWP model performance. The RAdar Wind Sounder (RAWS) program at the University of Kansas is a study of the feasibility and the trade-offs in the design of a space-based radar system to measure wind vectors. This can be done by measuring the Doppler shift of cloud and rain returns from three or more points and calculating the components of the wind vector. The RAWS study to date uses the candidate system selected after preliminary study of frequencies and sensitivities. Two frequencies chosen, 10 and 35 GHz, allow higher sensitivity for clouds and more penetration for rain. The past year was devoted to modeling the signal-to-noise ratio (SNR) achievable for the two frequencies. The determination of SNR versus cloud penetration depth used a cloud backscattering and attenuation model in the appropriate radar equation. Calculations assumed reasonable losses in reception and transmission, in addition to the atmospheric attenuation. We discovered that ice clouds provide a higher SNR than previously calculated, but some water clouds give lower SNRs than we calculated before. One of the primary issues in the SNR calculation was the choice of the drop size distribution. Although Xin used several distributions (e.g., log normal, Khrigian and Mazin), this year we used the Deirmendjian cloud model. SNR versus cloud penetration plots were generated to

  6. Near-Real-Time, Global Radar Data at the Alaska Satellite Facility DAAC from NASA's SMAP Satellite

    Science.gov (United States)

    Arko, S. A.; Allen, A. R.; Dixon, I. R.

    2014-12-01

    The Alaska Satellite Facility (ASF) Distributed Active Archive Center (DAAC) is supporting NASA's SMAP (Soil Moisture Active Passive) satellite mission, which launches in January 2015. SMAP will measure global soil moisture and its freeze-thaw state every 3 days using an L-band synthetic aperture radar (SAR) and radiometer. ASF, along with the National Snow and Ice Data Center DAAC and NASA's Earth Science Data and Information System (ESDIS), is identifying and developing tools and technologies to facilitate use of global, near-real-time data by the SMAP user community. ASF will host the SMAP Level 1 radar data and make them available for download through ASF's data discovery interface, Vertex, and the ASF Application Programming Interface. Vertex allows a user to search, visualize and download SAR data, browse images and relevant metadata, and will offer the complete SMAP L1 radar archive to the public. The entire SMAP archive consisting of level 1-4 data can be accessed via Reverb, the NASA EOSDIS metadata and service discovery tool. In anticipation of the SMAP launch and data release, ASF has developed and released a new website (https://www.asf.alaska.edu/smap/) and a suite of web resources, including interactive media, technical information, a product guide, related publications, and tools for working with the HDF5 data format. The ASF SMAP team is exploring OPeNDAP and the Jet Propulsion Laboratory's Webification technologies for enhancing in-browser data visualization and analysis. These technologies, and tools developed with them, represent opportunities for exposing this valuable dataset to areas with limited bandwidth or understanding of radar data. This presentation will highlight the enabling technologies and techniques ASF is employing to bring these data to new scientific and applications users and respond to ever-changing user needs.

  7. Observing and Modelling the HighWater Level from Satellite Radar Altimetry During Tropical Cyclones

    DEFF Research Database (Denmark)

    Deng, Xiaoli; Gharineiat, Zahra; Andersen, Ole Baltazar

    2016-01-01

    This paper investigates the capability of observing tropical cyclones using satellite radar altimetry. Two representative cyclones Yasi (February 2011) and Larry (March 2006) in the northeast Australian coastal area are selected based also on available tide gauge sea level measurements. It is shown...... levels predicted by the model taken into account of both altimetry and tide-gauge data agree well with those observed at Townsville during cyclone Larry....

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

    Science.gov (United States)

    Verdin, Andrew; Rajagopalan, Balaji; Kleiber, William; Funk, Chris

    2015-02-01

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

  9. Ground-based radar reflectivity mosaic of mei-yu precipitation systems over the Yangtze River-Huaihe River basins

    Science.gov (United States)

    Luo, Yali; Qian, Weimiao; Gong, Yu; Wang, Hongyan; Zhang, Da-Lin

    2016-11-01

    The 3D radar reflectivity produced by a mosaic software system, with measurements from 29 operational weather radars in the Yangtze River-Huaihe River Basins (YRHRB) during the mei-yu season of 2007, is compared to coincident TRMM PR observations in order to evaluate the value of the ground-based radar reflectivity mosaic in characterizing the 3D structures of mei-yu precipitation. Results show reasonable agreement in the composite radar reflectivity between the two datasets, with a correlation coefficient of 0.8 and a mean bias of -1 dB. The radar mosaic data at constant altitudes are reasonably consistent with the TRMM PR observations in the height range of 2-5 km, revealing essentially the same spatial distribution of radar echo and nearly identical histograms of reflectivity. However, at altitudes above 5 km, the mosaic data overestimate reflectivity and have slower decreasing rates with height compared to the TRMM PR observations. The areas of convective and stratiform precipitation, based on the mosaic reflectivity distribution at 3-km altitude, are highly correlated with the corresponding regions in the TRMM products, with correlation coefficients of 0.92 and 0.97 and mean relative differences of -7.9% and -2.5%, respectively. Finally, the usefulness of the mosaic reflectivity at 3-km altitude at 6-min intervals is illustrated using a mesoscale convective system that occurred over the YRHRB.

  10. Evaluation of Satellite and Ground Based Precipitation Products for Flood Forecasting

    Science.gov (United States)

    Chintalapudi, S.; Sharif, H.; Yeggina, S.

    2012-04-01

    The development in satellite-derived rainfall estimates encouraged the hydrological modeling in sparse gauged basins or ungauged basins. Especially, physically-based distributed hydrological models can benefit from the good spatial and temporal coverage of satellite precipitation products. In this study, three satellite derived precipitation datasets (TRMM, CMORPH, and PERSIANN), NEXRAD, and rain gauge precipitation datasets were used to drive the hydrological model. The physically-based, distributed hydrological model Gridded Surface Subsurface Hydrological Analysis (GSSHA) was used in this study. Focus will be on the results from the Guadalupe River Basin above Canyon Lake and below Comfort, Texas. The Guadalupe River Basin above Canyon Lake and below Comfort Texas drains an area of 1232 km2. Different storm events will be used in these simulations. August 2007 event was used as calibration and June 2007 event was used as validation. Results are discussed interms of accuracy of satellite precipitation estimates with the ground based precipitation estimates, predicting peak discharges, runoff volumes, time lag, and spatial distribution. The initial results showed that, model was able to predict the peak discharges and runoff volumes when using NEXRAD MPE data, and TRMM 3B42 precipitation product. The results also showed that there was time lag in hydrographs driven by both PERSIANN and CMORPH data sets.

  11. 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.

  12. Precipitation and microphysical processes observed by three polarimetric X-band radars and ground-based instrumentation during HOPE

    Science.gov (United States)

    Xie, Xinxin; Evaristo, Raquel; Simmer, Clemens; Handwerker, Jan; Trömel, Silke

    2016-06-01

    This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRRs) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Jülich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5 km × 5 km region, while three other disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.

  13. A new approach for assimilation of 2D radar precipitation in a high-resolution NWP model

    DEFF Research Database (Denmark)

    Korsholm, Ulrik Smith; Petersen, Claus; Sass, Bent Hansen

    2015-01-01

    and then a free forecast. The precipitation fields are based on a 2D composite CAPPI (constant altitude plan position indicator) field made from observations with the DMI weather radars, and have a 10 min time resolution. The results obtained in this study indicate that the new method implies fast adjustment...

  14. Statistical assessment and hydrological utility of the latest multi-satellite precipitation analysis IMERG in Ganjiang River basin

    Science.gov (United States)

    Li, Na; Tang, Guoqiang; Zhao, Ping; Hong, Yang; Gou, Yabin; Yang, Kai

    2017-01-01

    This study aims to statistically and hydrologically assess the hydrological utility of the latest Integrated Multi-satellitE Retrievals from Global Precipitation Measurement (IMERG) multi-satellite constellation over the mid-latitude Ganjiang River basin in China. The investigations are conducted at hourly and 0.1° resolutions throughout the rainy season from March 12 to September 30, 2014. Two high-quality quantitative precipitation estimation (QPE) datasets, i.e., a gauge-corrected radar mosaic QPE product (RQPE) and a highly dense network of 1200 rain gauges, are used as the reference. For the implementation of the study, first, we compare IMERG product and RQPE with rain gauge-interpolated data, respectively. The results indicate that both remote sensing products can estimate precipitation fairly well over the basin, while RQPE significantly outperforms IMERG product in almost all the studied cases. The correlation coefficients of RQPE (CC = 0.98 and CC = 0.67) are much higher than those of IMERG product (CC = 0.80 and CC = 0.33) at basin and grid scales, respectively. Then, the hydrological assessment is conducted with the Coupled Routing and Excess Storage (CREST) model under multiple parameterization scenarios, in which the model is calibrated using the rain gauge-interpolated data, RQPE, and IMERG products respectively. During the calibration period (from March 12 to May 31), the simulated streamflow based on rain gauge-interpolated data shows the highest Nash-Sutcliffe coefficient efficiency (NSCE) value (0.92), closely followed by the RQPE (NSCE = 0.84), while IMERG product performs barely acceptable (NSCE = 0.56). During the validation period (from June 1 to September 30), the three rainfall datasets are used to force the CREST model based on all the three calibrated parameter sets (i.e., nine combinations in total). RQPE outperforms rain gauge-interpolated data and IMERG product in all validation scenarios, possibly due to its advantageous capability

  15. Merging Radar Quantitative Precipitation Estimates (QPEs) from the High-resolution NEXRAD Reanalysis over CONUS with Rain-gauge Observations

    Science.gov (United States)

    Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Nickl, E.; Seo, D. J.; Kim, B.; Zhang, J.; Qi, Y.

    2015-12-01

    The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over the Continental United States (CONUS) is completed for the period covering from 2002 to 2011. While this constitutes a unique opportunity to study precipitation processes at higher resolution than conventionally possible (1-km, 5-min), the long-term radar-only product needs to be merged with in-situ information in order to be suitable for hydrological, meteorological and climatological applications. The radar-gauge merging is performed by using rain gauge information at daily (Global Historical Climatology Network-Daily: GHCN-D), hourly (Hydrometeorological Automated Data System: HADS), and 5-min (Automated Surface Observing Systems: ASOS; Climate Reference Network: CRN) resolution. The challenges related to incorporating differing resolution and quality networks to generate long-term large-scale gridded estimates of precipitation are enormous. In that perspective, we are implementing techniques for merging the rain gauge datasets and the radar-only estimates such as Inverse Distance Weighting (IDW), Simple Kriging (SK), Ordinary Kriging (OK), and Conditional Bias-Penalized Kriging (CBPK). An evaluation of the different radar-gauge merging techniques is presented and we provide an estimate of uncertainty for the gridded estimates. In addition, comparisons with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) are provided in order to give a detailed picture of the improvements and remaining challenges.

  16. Microwave retrievals of terrestrial precipitation over snow-covered surfaces: A lesson from the GPM satellite

    Science.gov (United States)

    Ebtehaj, A. M.; Kummerow, C. D.

    2017-06-01

    Satellites are playing an ever-increasing role in estimating precipitation over remote areas. Improving satellite retrievals of precipitation requires increased understanding of its passive microwave signatures over different land surfaces. Snow-covered surfaces are notoriously difficult to interpret because they exhibit both emission from the land below and scattering from the ice crystals. Using data from the Global Precipitation Measurement (GPM) satellite, we demonstrate that microwave brightness temperatures of rain and snowfall transition from a scattering to an emission regime from summer to winter, due to expansion of less emissive snow cover. Evidence suggests that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The results demonstrate that, using a multifrequency matching method, the probability of snowfall detection can even be higher than rainfall—chiefly because of the information content of the low-frequency channels that respond to the (near) surface temperature.

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

    Science.gov (United States)

    Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye

    2016-10-01

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

  18. Inter-Comparison of High-Resolution Satellite Precipitation Products over Central Asia

    Directory of Open Access Journals (Sweden)

    Hao Guo

    2015-06-01

    Full Text Available This paper examines the spatial error structures of eight precipitation estimates derived from four different satellite retrieval algorithms including TRMM Multi-satellite Precipitation Analysis (TMPA, Climate Prediction Center morphing technique (CMORPH, Global Satellite Mapping of Precipitation (GSMaP and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN. All the original satellite and bias-corrected products of each algorithm (3B42RTV7 and 3B42V7, CMORPH_RAW and CMORPH_CRT, GSMaP_MVK and GSMaP_Gauge, PERSIANN_RAW and PERSIANN_CDR are evaluated against ground-based Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE over Central Asia for the period of 2004 to 2006. The analyses show that all products except PERSIANN exhibit overestimation over Aral Sea and its surrounding areas. The bias-correction improves the quality of the original satellite TMPA products and GSMaP significantly but slightly in CMORPH and PERSIANN over Central Asia. 3B42RTV7 overestimates precipitation significantly with large Relative Bias (RB (128.17% while GSMaP_Gauge shows consistent high correlation coefficient (CC (>0.8 but RB fluctuates between −57.95% and 112.63%. The PERSIANN_CDR outperforms other products in winter with the highest CC (0.67. Both the satellite-only and gauge adjusted products have particularly poor performance in detecting rainfall events in terms of lower POD (less than 65%, CSI (less than 45% and relatively high FAR (more than 35%.

  19. An overview of neural network applications for soil moisture retrieval from radar satellite sensors

    Science.gov (United States)

    Santi, E.; Paloscia, S.; Pettinato, S.

    2014-10-01

    Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all applications related to the environmental disciplines, such as climatology, meteorology, hydrology and agriculture. Satellite sensors operating in the low part of microwave spectrum are very suitable for this purpose, and their signals can be directly related to the moisture content of the observed surfaces, provided that all the contributions from soil and vegetation to the measured signal are properly accounted for. Among the algorithms used for the retrieval of SMC from both active (i.e. Synthetic Aperture Radar, SAR or real aperture radars) and passive (radiometers) microwave sensors, the artificial neural networks (ANN) represent the best compromise between accuracy and computation speed. ANN based algorithms have been developed at IFAC, and adapted to several radar and radiometric satellite sensors, in order to generate SMC products at different spatial resolutions, varying from hundreds of meters to tens of kilometers. These algorithms, which use the ANN techniques for inverting theoretical and semi-empirical models, such as Advanced Integral Equation (AIEM), Oh models, and Radiative transfer Theory (RTT), have been adapted to the C-band acquisitions from SAR (Envisat/ASAR) and real aperture radar (ASCAT) and to the X-band SAR acquisitions of Cosmo-SkyMed and TerraSAR-X. Moreover, a specific ANN algorithm has also been implemented for the L-band active and passive acquisitions of the incoming SMAP mission. The latter satellite will carry onboard simultaneously one radar and one radiometer operating at the same frequency, but with different spatial resolutions (3 and 40 km, respectively). Large datasets of co-located satellite acquisitions and direct SMC measurements on several test sites located worldwide have been used along with simulations derived from forward electromagnetic models for setting up, training and validating these

  20. High-precision measurement of satellite velocity using the EISCAT radar

    Directory of Open Access Journals (Sweden)

    T. Nygrén

    2012-10-01

    Full Text Available This paper presents a method of measuring the velocity of a hard target using radar pulses reflected from the target flying through the radar beam. The method has two stages. First, the Doppler shifts of the echo pulses are calculated at a high accuracy with an algorithm which largely improves the accuracy given by the Fourier transform. The algorithm also calculates the standard deviations of the Doppler frequencies with Monte Carlo simulation. The second step is to fit the results from a sequence of radar pulses to a velocity model allowing linear variation of the second time derivative of target range. The achieved accuracies are demonstrated using radio pulses reflected by a satellite passing through the beam of the EISCAT UHF radar working at 930-MHz frequency. At high SNR levels, the standard deviations of the frequency from a single pulse reach typically down to 0.2 Hz. The best standard deviations of velocity fit are below 5 mm s−1 while those of the second time derivative of range are below 1 cm s−2.

  1. Simulation on change of generic satellite radar cross section via artificially created plasma sprays

    Science.gov (United States)

    Chung, Shen Shou Max; Chuang, Yu-Chou

    2016-06-01

    Recent advancements in antisatellite missile technologies have proven the effectiveness of such attacks, and the vulnerability of satellites in such exercises inspires a new paradigm in RF Stealth techniques suitable for satellites. In this paper we examine the possibility of using artificially created plasma sprays on the surface of the satellite’s main body to alter its radar cross section (RCS). First, we briefly review past research related to RF Stealth using plasma. Next, we discuss the physics between electromagnetic waves and plasma, and the RCS number game in RF Stealth design. A comparison of RCS in a generic satellite and a more complicated model is made to illustrate the effect of the RCS number game, and its meaning for a simulation model. We also run a comparison between finite-difference-time-domain (FDTD) and multilevel fast multipole method (MLFMM) codes, and find the RCS results are very close. We then compare the RCS of the generic satellite and the plasma-covered satellite. The incident radar wave is a differentiated Gaussian monopulse, with 3 dB bandwidth between 1.2 GHz and 4 GHz, and we simulate three kinds of plasma density, with a characteristic plasma frequency ω P  =  0.1, 1, and 10 GHz. The electron-neutral collision frequency ν en is set at 0.01 GHz. We found the RCS of plasma-covered satellite is not necessarily smaller than the originally satellite. When ω P is 0.1 GHz, the plasma spray behaves like a dielectric, and there is minor reduction in the RCS. When ω P is 1 GHz, the X-Y cut RCS increases. When ω P is 10 GHz, the plasma behaves more like a metal to the radar wave, and stronger RCS dependency to frequency appears. Therefore, to use plasma as an RCS adjustment tool requires careful fine-tuning of plasma density and shape, in order to achieve the so-called plasma stealth effect.

  2. Mapping dynamics of deforestation and forest degradation in tropical forests using radar satellite data

    DEFF Research Database (Denmark)

    Joshi, Neha; Mitchard, Edward TA; Woo, Natalia

    2015-01-01

    Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes...... of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow- and fast-recovering changes in backscatter in close spatial...... along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter...

  3. Mapping dynamics of deforestation and forest degradation in tropical forests using radar satellite data

    DEFF Research Database (Denmark)

    Joshi, Neha; Mitchard, Edward TA; Woo, Natalia;

    2015-01-01

    Mapping anthropogenic forest disturbances has largely been focused on distinct delineations of events of deforestation using optical satellite images. In the tropics, frequent cloud cover and the challenge of quantifying forest degradation remain problematic. In this study, we detect processes...... of deforestation, forest degradation and successional dynamics, using long-wavelength radar (L-band from ALOS PALSAR) backscatter. We present a detection algorithm that allows for repeated disturbances on the same land, and identifies areas with slow- and fast-recovering changes in backscatter in close spatial...... along the tri-national Interoceanic Highway, as well as in mining areas and areas under no land use allocation. A continuous spatial gradient of disturbance was observed, highlighting artefacts arising from imposing discrete boundaries on deforestation events. The magnitude of initial radar backscatter...

  4. Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile

    Science.gov (United States)

    Yang, Zhongwen; Hsu, Kuolin; Sorooshian, Soroosh; Xu, Xinyi; Braithwaite, Dan; Verbist, Koen M. J.

    2016-04-01

    Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009-2014. The historical data (satellite and gauge) for 2009-2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide.

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

    Science.gov (United States)

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

    2017-04-01

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

  6. A review of satellite radar altimetry applied to coastal ocean studies

    Science.gov (United States)

    Vignudelli, Stefano

    2016-07-01

    Satellite radar altimetry is today considered a mature technique in open ocean. The data stream from the various satellite missions are routinely used for a number of applications. In the last decade, significant research has been carried out into overcoming the problems to extend the capabilities of radar altimeters to the coastal zone, with the aim to integrate the altimeter-derived measurements of sea level, wind speed and significant wave height into coastal ocean observing systems. More/better (and new) datasets are being produced. Moreover, the advent of new satellite missions, both nadir-viewing (e.g., Sentinel-3) and wide-swath (e.g. SWOT), should globally improve both quantity and quality of coastal altimetry data. In this talk, after a brief review of the challenges in coastal altimetry and description of the new products, we showcase some application examples how the new products can be exploited, and we discuss directions for a global coastal altimetry dataset as an asset for long term monitoring of sea level and sea state in the coastal ocean.

  7. Evaluation of satellite-based precipitation estimates in winter season using an object-based approach

    Science.gov (United States)

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

    2012-12-01

    Verification has become an integral component of satellite precipitation algorithms and products. A number of object-based verification methods have been proposed to provide diagnostic information regarding the precipitation products' ability to capture the spatial pattern, intensity, and placement of precipitation. However, most object-based methods are not capable of investigating precipitation objects at the storm-scale. In this study, an image processing approach known as watershed segmentation was adopted to detect the storm-scale rainfall objects. Then, a fuzzy logic-based technique was utilized to diagnose and analyze storm-scale object attributes, including centroid distance, area ratio, intersection area ratio and orientation angle difference. Three verification metrics (i.e., false alarm ratio, missing ratio and overall membership score) were generated for validation and verification. Three satellite-based precipitation products, including PERSIANN, CMORPH, 3B42RT, were evaluated against NOAA stage IV MPE multi-sensor composite rain analysis at 0.25° by 0.25° on a daily scale in the winter season of 2010 over the contiguous United States. Winter season is dominated by frontal systems which usually have larger area coverage. All three products and the stage IV observation tend to find large size storm objects. With respect to the evaluation attributes, PERSIANN tends to obtain larger area ratio and consequently has larger centroid distance to the stage IV observations, while 3B42RT are found to be closer to the stage IV for the object size. All evaluation products give small orientation angle differences but vary significantly for the missing ratio and false alarm ratio. This implies that satellite estimates can fail to detect storms in winter. The overall membership scores are close for all three different products which indicate that all three satellite-based precipitation products perform well for capturing the spatial and geometric characteristics of

  8. Validation of Chinese HY-2 satellite radar altimeter significant wave height

    Institute of Scientific and Technical Information of China (English)

    YE Xiaomin; LIN Mingsen; XU Ying

    2015-01-01

    Chinese Haiyang-2(HY-2) satellite is the first Chinese marine dynamic environment satellite. The dual-frequency (Ku and C band) radar altimeter onboard HY-2 has been working effective to provide operational significant wave height (SWH) for more than three years (October 1, 2011 to present).We validated along-track Ku-band SWH data of HY-2 satellite against National Data Buoy Center (NDBC)in-situ measurements over a time period of three years from October 1, 2011 to September 30, 2014, the root mean square error (RMSE) and mean bias of HY-2 SWH is 0.38 m and (–0.13±0.35) m, respectively. We also did cross validation against Jason-2 altimeter SWH data,the RMSE and the mean bias is 0.36m and (–0.22±0.28) m, respectively. In order to compare the statistical results between HY-2 and Jason-2 satellite SWH data, we validated the Jason-2 satellite radar altimeter along-track Ku-band SWH data against NDBC measurements using the same method. The results demonstrate the validation method in this study is scientific and the RMSE and mean bias of Jason-2 SWH data is 0.26 m and (0.00±0.26) m, respectively. We also validated both HY-2 and Jason-2 SWH data every month, the mean bias of Jason-2 SWH data almost equaled to zero all the time, while the mean bias of HY-2 SWH data was no less than –0.31m before April 2013 and dropped to zero after that time. These results indicate that the statistical results for HY-2 altimeter SWH are reliable and HY-2 altimeter along-track SWH data were steady and of high quality in the last three years. The results also indicate that HY-2 SWH data have greatly been improved and have the same accuracy with Jason-2 SWH data after April, 2013. SWH data provided by HY-2 satellite radar altimeter are useful and acceptable for ocean operational applications.

  9. Global Precipitation: Means, Variations and Trends During the Satellite Era (1979-2014)

    Science.gov (United States)

    Adler, Robert F.; Gu, Guojun; Sapiano, Matthew; Wang, Jian-Jian; Huffman, George J.

    2017-07-01

    Global precipitation variations over the satellite era are reviewed using the Global Precipitation Climatology Project (GPCP) monthly, globally complete analyses, which integrate satellite and surface gauge information. Mean planetary values are examined and compared, over ocean, with information from recent satellite programs and related estimates, with generally positive agreements, but with some indication of small underestimates for GPCP over the global ocean. Variations during the satellite era in global precipitation are tied to ENSO events, with small increases during El Ninos, and very noticeable decreases after major volcanic eruptions. No overall significant trend is noted in the global precipitation mean value, unlike that for surface temperature and atmospheric water vapor. However, there is a pattern of positive and negative trends across the planet with increases over tropical oceans and decreases over some middle latitude regions. These observed patterns are a result of a combination of inter-decadal variations and the effect of the global warming during the period. The results reviewed here indicate the value of such analyses as GPCP and the possible improvement in the information as the record lengthens and as new, more sophisticated and more accurate observations are included.

  10. Improvement of Radar Quantitative Precipitation Estimation Based on Real-Time Adjustments to Z-R Relationships and Inverse Distance Weighting Correction Schemes

    Institute of Scientific and Technical Information of China (English)

    WANG Gaili; LIU Liping; DING Yuanyuan

    2012-01-01

    The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations.In this study,a real-time adjustment to the radar reflectivity-rainfall rates (Z R) relationship scheme and the gauge-corrected,radar-based,estimation scheme with inverse distance weighting interpolation was developed.Based on the characteristics of the two schemes,the two-step correction technique of radar quantitative precipitation estimation is proposed.To minimize the errors between radar quantitative precipitation estimations and rain gauge observations,a real-time adjustnent to the Z-R relationship scheme is used to remove systematic bias on the time-domain.The gauge-corrected,radar-based,estination scheme is then used to eliminate non-uniform errors in space.Based on radar data and rain gauge observations near the Huaihe River,the two-step correction technique was evaluated using two heavy-precipitation events.The results show that the proposed scheme improved not only in the underestination of rainfall but also reduced the root-mean-square error and the mean relative error of radar-rain gauge pairs.

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

    Science.gov (United States)

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

    2017-04-01

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

  12. Clouds-Aerosols-Precipitation Satellite Analysis Tool (CAPSAT

    Directory of Open Access Journals (Sweden)

    I. M. Lensky

    2008-03-01

    Full Text Available A methodology for representing much of the physical information content of the METEOSAT Second Generation (MSG geostationary satellite using red-green-blue (RGB composites of the computed physical values of the picture elements is presented. The physical values are the solar reflectance in the solar channels and brightness temperature in the thermal channels. The main RGB compositions are (1 "Day Natural Colors", presenting vegetation in green, bare surface in brown, sea surface in black, water clouds as white, ice as magenta; (2 "Day Microphysical", presenting cloud microstructure using the solar reflectance component of the 3.9 μm, visible and thermal IR channels; (3 "Night Microphysical", also presenting clouds microstructure using the brightness temperature differences between 10.8 and 3.9 μm; (4 "Day and Night", using only thermal channels for presenting surface and cloud properties, desert dust and volcanic emissions; (5 "Air Mass", presenting mid and upper tropospheric features using thermal water vapor and ozone channels. The scientific basis for these rendering schemes is provided, with examples for the applications. The expanding use of these rendering schemes requires their proper documentation and setting as standards, which is the main objective of this publication.

  13. Surface topography of the Greenland Ice Sheet from satellite radar altimetry

    Science.gov (United States)

    Bindschadler, Robert A.; Zwally, H. Jay; Major, Judith A.; Brenner, Anita C.

    1989-01-01

    Surface elevation maps of the southern half of the Greenland subcontinent are produced from radar altimeter data acquired by the Seasat satellite. A summary of the processing procedure and examples of return waveform data are given. The elevation data are used to generate a regular grid which is then computer contoured to provide an elevation contour map. Ancillary maps show the statistical quality of the elevation data and various characteristics of the surface. The elevation map is used to define ice flow directions and delineate the major drainage basins. Regular maps of the Jakobshavns Glacier drainage basin and the ice divide in the vicinity of Crete Station are presented. Altimeter derived elevations are compared with elevations measured both by satellite geoceivers and optical surveying.

  14. Offshore wind resource mapping for Europe by Synthetic Aperture Radar (SAR) satellite data

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete

    2015-01-01

    For the New European Wind Atlas (NEWA) project with 8 participating countries during5 years (March 2015 – March 2020) we will develop a new wind atlas covering most of the European countries as well as most of the offshore areas in Europe. For the offshore atlas we will rely on a combination...... of satellite remote sensing observations and atmospheric modelling. The satellite data include Synthetic Aperture Radar (SAR) from the European Space Agency from Envisat and the Copernicus mission Sentinel-1. SAR has the advantage of high spatial resolution such that we can cover near-coastal areas where many...... wind farms are planned. In the Danish RUNE project near-shore offshore winds are investigate from SAR, atmospheric modelling and ground-based remote sensing lidar. In the European Space Agency project ResGrow SAR wind resource maps at various locations in the European Seas are used to estimate the wind...

  15. Towards stochastically downscaled precipitation in the Tropics based on a robust 1DD combined satellite product and a high resolution IR-based rain mask

    Science.gov (United States)

    Guilloteau, Clement; Roca, Rémy; Gosset, Marielle

    2015-04-01

    In the Tropics where the ground-based rain gauges network is very sparse, satellite rainfall estimates are becoming a compulsory source of information for various applications: hydrological modeling, water resources management or vegetation-monitoring. The tropical Tropical Amount of Precipitation with Estimate of Error (TAPEER) algorithm, developed within the framework of Megha-Tropiques satellite mission is a robust estimate of surface rainfall accumulations at the daily, one degree resolution. TAPEER validation in West Africa has proven its accuracy. Nevertheless applications that involve non-linear processes (such as surface runoff) require finer space / time resolution than one degree one day, or at least the statistical characterization of the sub-grid rainfall variability. TAPEER is based on a Universally Adjusted Global Precipitation Index (UAGPI) technique. The one degree, one day estimation relies on the combination of observations from microwave radiometers embarked on the 7 platforms forming the GPM constellation of low earth orbit satellites together with geostationary infra-red (GEO-IR) imagery. TAPEER provides as an intermediate product a high-resolution rain-mask based on the GEO-IR information (2.8 km, 15 min in Africa). The main question of this work is, how to use this high-resolution mask information as a constraint for downscaling ? This work first presents the multi-scale evaluation of TAPEER's rain detection mask against ground X-band polarimetric radar data and TRMM precipitation radar data in West Africa, through wavelet transform. Other algorithms (climate prediction center morphing technique CMORPH, global satellite mapping of precipitation GSMaP, multi-sensor precipitation estimate MPE) detection capabilities are also evaluated. Spatio-temporal wavelet filtering of the detection mask is then used to compute precipitation probability at the GEO-IR resolution. The wavelet tool is finally used to stochastically generate rain / no rain field

  16. Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China

    Science.gov (United States)

    Guo, Hao; Chen, Sheng; Bao, Anming; Behrangi, Ali; Hong, Yang; Ndayisaba, Felix; Hu, Junjun; Stepanian, Phillip M.

    2016-07-01

    Two post-real time precipitation products from the Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) are systematically evaluated over China with China daily Precipitation Analysis Product (CPAP) as reference. The IMERG products include the gauge-corrected IMERG product (IMERG_Cal) and the version of IMERG without direct gauge correction (IMERG_Uncal). The post-research TRMM Multisatellite Precipitation Analysis version 7 (TMPA-3B42V7) is also evaluated concurrently with IMERG for better perspective. In order to be consistent with CPAP, the evaluation and comparison of selected products are performed at 0.25° and daily resolutions from 12 March 2014 through 28 February 2015. The results show that: Both IMERG and 3B42V7 show similar performances. Compared to IMERG_Uncal, IMERG_Cal shows significant improvement in overall and conditional bias and in the correlation coefficient. Both IMERG_Cal and IMERG_Uncal perform relatively poor in winter and over-detect slight precipitation events in northwestern China. As an early validation of the GPM-era IMERG products that inherit the TRMM-era global satellite precipitation products, these findings will provide useful feedbacks and insights for algorithm developers and data users over China and beyond.

  17. Assessment of North Atlantic Precipitation and Freshwater Flux from the HOAPS-3 satellite climatology

    Science.gov (United States)

    Andersson, A.; Klepp, C.; Bakan, S.; Schulz, J.

    2009-04-01

    To attain a better understanding and modeling of climate processes attaining a proper knowledge of global water cycle components is essential. For the assessment of the freshwater flux at the ocean surface on global scale, exchange processes at the air-sea interface play a key-role. With the ability to derive ocean latent heat flux and precipitation from satellite data with acceptable accuracy, and frequent global coverage, a climatological assessment of the crucial processes has become possible. The HOAPS-3 climatology (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) contains fields of precipitation, surface fluxes and atmospheric parameters over the global ice-free ocean between 1987 and 2005. Except for the NOAA Pathfinder SST, all basic state variables needed for the derivation of the fluxes are calculated from SSM/I passive microwave radiometer measurements. Multi-satellite averages, inter-sensor calibration, and an efficient sea ice detection procedure make HOAPS a suitable data set for climatological applications as well as for case studies. Gridded 0.5 degree monthly, pentad and twice daily data products are freely available from www.hoaps.org. For the precipitation parameter, quasi-global coverage is achieved by complementing HOAPS-3 over land areas using the rain gauge based "Full Data Reanalysis Product Version 4", which is provided by the Global Precipitation Climatology Centre (GPCC). North Atlantic intra-decadal precipitation variability is investigated using this combined data set. The mutual response of the two independent precipitation data sources to the North Atlantic Oscillation (NAO) reveals coherent patterns and a detailed view on the structural changes in precipitation during the high and low states of the NAO. A second focus will be put on the evaluation of HOAPS-3 ocean surface freshwater fluxes and their interaction with the NAO.

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

    Science.gov (United States)

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

    2001-01-01

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

  19. Satellite cloud and precipitation property retrievals for climate monitoring and hydrological applications

    Science.gov (United States)

    Wolters, E. L. A.

    2012-03-01

    This thesis presents the retrieval, evaluation, and application of cloud physical property datasets (cloud phase, cloud particle effective radius, and precipitation occurrence and intensity) obtained from Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectance measurements using the Cloud Physical Properties (CPP) retrieval algorithm. In Chapter 3 it is shown that the CPP cloud-phase retrieval algorithm has sufficient accuracy (West Africa. During the afternoon, precipitation occurrence frequency over dry soils becomes significantly higher than over wet soils, whereas for precipitation intensity no significant difference is discerned. The study demonstrates that the combination of satellite-based soil moisture and precipitation observations can be helpful in improving the understanding of the land surface-precipitation interaction over tropical areas. The thesis concludes with a number of recommendations on future algorithm improvements and potential research applications. For both cloud phase and precipitation properties, extension of the algorithm to include nighttime observations would be desirable to enable detailed studies on the full diurnal cycle. Further, the SEVIRI High-Resolution Visible (HRV) channel could be incorporated to correct retrieved cloud physical properties for broken and inhomogeneous cloud cases. Finally, the accurate cloud phase and precipitation datasets combined with the high SEVIRI spatial and temporal sampling resolution enables possibilities for detailed research on climate monitoring, nowcasting applications, evaluation of cloud schemes in climate models, studies on land surface-precipitation interactions (with a special focus on the diurnal cycle), and assimilation of the datasets in weather and climate models

  20. Creation of a high resolution precipitation data set by merging gridded gauge data and radar observations for Sweden

    Science.gov (United States)

    Berg, Peter; Norin, Lars; Olsson, Jonas

    2016-10-01

    Hydrological forecasting systems require accurate initial conditions, particularly for real time precipitation data, which are problematic to retrieve. This is especially difficult for high temporal and spatial resolutions, e.g. sub-daily and less than 10-20 km. Forecasting fast processes such as flash flood are, however, dependent on such high resolution data. Gridded gauge data produces too smooth fields and underestimates small scale phenomena, such as convection, whereas radar composites contain the small scale information, but suffer from inconsistencies between individual radars and have poor long term statistics. Here, we present a method to merge a radar composite with daily resolution gridded gauge data for Sweden for the time period 2009-2014 to produce a one hourly 4 × 4 km2 data set. The method consists of a main step where monthly accumulations of the radar data are scaled by those retrieved from the gridded data for each month. An optional quantile mapping based bias correction step makes sure that the daily intensity distribution agrees with the gridded observations. Finally, the data are dis-aggregated to an hourly time resolution. This results in a data set which has the same long-term spatial properties as the gridded observations, but with the spatial and temporal details of the radar data. Validation of the method is performed with high resolution gauge data, and shows a high quality of the derived product.

  1. On safe ground? Analysis of European urban geohazards using satellite radar interferometry

    Science.gov (United States)

    Capes, Renalt; Teeuw, Richard

    2017-06-01

    Urban geological hazards involving ground instability can be costly, dangerous, and affect many people, yet there is little information about the extent or distribution of geohazards within Europe's urban areas. A reason for this is the impracticality of measuring ground instability associated with the many geohazard processes that are often hidden beneath buildings and are imperceptible to conventional geological survey detection techniques. Satellite radar interferometry, or InSAR, offers a remote sensing technique to map mm-scale ground deformation over wide areas given an archive of suitable multi-temporal data. The EC FP7 Space project named PanGeo (2011-2014), used InSAR to map areas of unstable ground in 52 of Europe's cities, representing ∼15% of the EU population. In partnership with Europe's national geological surveys, the PanGeo project developed a standardised geohazard-mapping methodology and recorded 1286 instances of 19 types of geohazard covering 18,000 km2. Presented here is an analysis of the results of the PanGeo-project output data, which provides insights into the distribution of European urban geohazards, their frequency and probability of occurrence. Merging PanGeo data with Eurostat's GeoStat data provides a systematic estimate of population exposures. Satellite radar interferometry is shown to be as a valuable tool for the systematic detection and mapping of urban geohazard phenomena.

  2. The Cloud Radar System

    Science.gov (United States)

    Racette, Paul; Heymsfield, Gerald; Li, Lihua; Tian, Lin; Zenker, Ed

    2003-01-01

    Improvement in our understanding of the radiative impact of clouds on the climate system requires a comprehensive view of clouds including their physical dimensions, dynamical generation processes, and detailed microphysical properties. To this end, millimeter vave radar is a powerful tool by which clouds can be remotely sensed. The NASA Goddard Space Flight Center has developed the Cloud Radar System (CRS). CRS is a highly sensitive 94 GHz (W-band) pulsed-Doppler polarimetric radar that is designed to fly on board the NASA high-altitude ER-2 aircraft. The instrument is currently the only millimeter wave radar capable of cloud and precipitation measurements from above most all clouds. Because it operates from high-altitude, the CRS provides a unique measurement perspective for cirrus cloud studies. The CRS emulates a satellite view of clouds and precipitation systems thus providing valuable measurements for the implementation and algorithm validation for the upcoming NASA CloudSat mission that is designed to measure ice cloud distributions on the global scale using a spaceborne 94 GHz radar. This paper describes the CRS instrument and preliminary data from the recent Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE). The radar design is discussed. Characteristics of the radar are given. A block diagram illustrating functional components of the radar is shown. The performance of the CRS during the CRYSTAL-FACE campaign is discussed.

  3. 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

    Floods are one of the most common and dangerous natural hazards, causing every year thousands of casualties and damages worldwide. The main tool for assessing flood risk and reducing damages is represented by hydrologic early warning systems that allow to forecast flood events by using real time data obtained through ground monitoring networks (e.g., raingauges and radars). However, the use of such data, mainly rainfall, presents some issues firstly related to the network density and to the limited spatial representativeness of local measurements. A way to overcome these issues may be the use of satellite-based rainfall products (SRPs) that nowadays are available on a global scale at ever increasing spatial/temporal resolution and accuracy. However, despite the large availability and increased accuracy of SRPs (e.g., the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA); the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF); and the recent Global Precipitation Measurement (GPM) mission), remotely sensed rainfall data are scarcely used in hydrological modeling and only a small number of studies have been carried out to outline some guidelines for using satellite data as input for hydrological modelling. Reasons may be related to: 1) the large bias characterizing satellite precipitation estimates, which is dependent on rainfall intensity and season, 2) the spatial/temporal resolution, 3) the timeliness, which is often insufficient for operational purposes, and 4) a general (often not justified) skepticism of the hydrological community in the use of satellite products for land applications. The objective of this study is to explore the feasibility of using SRPs in a lumped hydrologic model (MISDc, "Modello Idrologico Semi-Distribuito in continuo", Masseroni et al., 2017) over 10 basins in the Mediterranean area with different sizes and physiographic characteristics. Specifically

  4. Continued development of a global precipitation dataset from satellite and ground-based gauges

    Science.gov (United States)

    Dietzsch, Felix; Andersson, Axel; Schröder, Marc; Ziese, Markus; Becker, Andreas

    2017-04-01

    The project framework MiKlip ("Mittelfristige Klimaprognosen") is focused on the development of an operational forecast system for decadal climate predictions. The objective of the "Daily Precipitation Analysis for the validation of Global medium-range Climate predictions Operationalized" (DAPAGLOCO) project, is the development and operationalization of a global precipitation dataset for forecast validation of the MPI-ESM experiments used in MiKlip. The dataset is a combination of rain gauge measurement data over land and satellite-based precipitation retrievals over ocean. Over land, gauge data from the Global Precipitation Climatology Centre (GPCC) at Deutscher Wetterdienst (DWD) are used. Over ocean, retrievals from the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) dataset are used as data source. The currently available dataset consists of 21 years of data (1988-2008) and is provided in different spatial resolutions of 1° and 2.5° on the global scale, and 0.5° for Europe. Rain rates over ocean are currently derived from satellite microwave imagers by using a neuronal network. For the future it is intended to switch this retrieval method to a 1D-Var method. The current state of the dataset is presented, an introduction to the future retrieval and its features is given and first results from evaluation and application are shown.

  5. Open science: Investigating precipitation cycles in dynamically downscaled data using openly available radar data and open source software

    Science.gov (United States)

    Collis, Scott; helmus, Jonathan; Kotamarthi, Rao; Wang, Jiali; Feng, Yan; Ghate, Virendra

    2016-04-01

    In order to assess infrastructure resilience to climate change in urban centers, climate model output is needed at spatial resolutions required for urban planning. This is most commonly achieved using either empirical or dynamic downscaling at present. The utility of these downscaling methods for assessments depends on having estimates of biases in the models estimate climate variables and their extremes, surface temperature and precipitation as an example, developed using historical data sets. Since precipitation is a multi-scale stochastic process direct comparison with observations is challenging and even modern data sets work at scales too coarse to capture extreme events. Gauge data requires a direct hit by a storm to see the highest rain rates, often leading to an underestimation in the 1-100 year rainfall. This is exacerbated by phenomena such as training that can cause very high gradients in accumulation. This presentation details a long-term (multi-year) study of precipitation derived from open data from the NOAA Next-Generation Radar (NEXRAD) network. Two locations are studied; Portland, Maine, location for a pilot study conducted by the US Department of Homeland Security's on regional resilience to climate change and the Southern Great Plains of Oklahoma, home to the Department of Energy's ARM program. Both are located within 40km of a NEXRAD radar allowing retrievals of rainfall rates on the order of one kilometer using the Python-ARM Radar Toolkit (Py-ART). Both the diurnal and season cycle of precipitation is studied and compared to WRF dynamically downscaled precipitation rates. This project makes heavy use of open source community tools such as project Jupyter and the Scientific Python ecosystem to manage and process 10's of TB of data on midrange cluster infrastructure. Both the meteorological aspects and the data infrastructure and architecture will be discussed.

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

    Directory of Open Access Journals (Sweden)

    Jong Pil Kim

    2016-07-01

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

  7. 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

  8. PM-GCD - a combined IR-MW satellite technique for frequent retrieval of heavy precipitation

    Science.gov (United States)

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

    2012-01-01

    Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach high level of accuracy - especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications - especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave - Global Convective Diagnostic, (PM-GCD). This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD) technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 μm) and thermal-IR (10.8 μm) channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU) radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1-2 October 2009.

  9. 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.

  10. The Evolution of El Nino-Precipitation Relationships from Satellites and Gauges

    Science.gov (United States)

    Curtis, Scott; Adler, Robert F.; Starr, David OC (Technical Monitor)

    2002-01-01

    This study uses a twenty-three year (1979-2001) satellite-gauge merged community data set to further describe the relationship between El Nino Southern Oscillation (ENSO) and precipitation. The globally complete precipitation fields reveal coherent bands of anomalies that extend from the tropics to the polar regions. Also, ENSO-precipitation relationships were analyzed during the six strongest El Ninos from 1979 to 2001. Seasons of evolution, Pre-onset, Onset, Peak, Decay, and Post-decay, were identified based on the strength of the El Nino. Then two simple and independent models, first order harmonic and linear, were fit to the monthly time series of normalized precipitation anomalies for each grid block. The sinusoidal model represents a three-phase evolution of precipitation, either dry-wet-dry or wet-dry-wet. This model is also highly correlated with the evolution of sea surface temperatures in the equatorial Pacific. The linear model represents a two-phase evolution of precipitation, either dry-wet or wet-dry. These models combine to account for over 50% of the precipitation variability for over half the globe during El Nino. Most regions, especially away from the Equator, favor the linear model. Areas that show the largest trend from dry to wet are southeastern Australia, eastern Indian Ocean, southern Japan, and off the coast of Peru. The northern tropical Pacific and Southeast Asia show the opposite trend.

  11. Large Response to Precipitation and Tidal Forcing at Columbia Glacier Imaged with Terrestrial Radar Interferometry

    Science.gov (United States)

    Cassotto, R.; Fahnestock, M. A.; O'Neel, S.; Sass, L.; McNabb, R. W.; Pfeffer, W. T.

    2015-12-01

    Columbia Glacier, one of Alaska's largest tidewater glaciers (TWG), stretches from sea level in Prince William Sound to the high peaks of Alaska's Chugach Mountains. One of the last TWG in the area to retreat from its Little Ice Age (LIA) moraine, Columbia has lost about half its ice volume as its terminus receded 22 km behind the LIA maximum position. At this time the glacier has split into two branches, with termini thought to be located near the heads of the submarine parts of the fjord, and may be nearing the end of its retreat phase. Seasonal variations in speed near the termini on both branches are large (~90%), with late summer speeds as low as a few meters per day. We deployed a terrestrial radar interferometer in October 2014 to observe short-term variations in speed during the slowest part of the seasonal cycle. Initial observations showed very slow speeds, with both termini exhibiting strong tidal modulation; however, significant rainfall from Tropical Storm Phanfone produced pronounced accelerations. We measured strong responses along both branches, with the largest increase (300%) occurring a few kilometers behind the calving fronts and lasted for several days. The large responses of the glacier's termini to this precipitation event, to tidal variations, and also the large seasonal variations in speed, suggest that Columbia's termini are not strongly grounded, are subject to large variations in sliding over short time periods, and may not yet have reached a more stable configuration in their retreats. The stability of Columbia's termini, based on our observations and bed models that suggest that a deep bed continues upfjord of the calving fronts for several kilometers, imply that Columbia's >30 year retreat may still be ongoing.

  12. Object-based Evaluation of Satellite Precipitation Retrievals: A Case Study of the Summer Season over CONUS

    Science.gov (United States)

    Li, J.; Xu, P.

    2015-12-01

    Satellite precipitation retrievals that have high spatial and temporal resolutions are suitable for various applications, such as hydrologic modeling and watershed management. Many validation studies have been established to understand the strengths and limitations of these satellite precipitation retrievals. In this study, an object-based validation approach is adopted to evaluate several satellite precipitation retrievals focusing on the spatial and geometric patterns of precipitation. This object-based validation approach identifies precipitation objects using an image processing technique referred to as watershed transform. Several object attributes are diagnosed and analyzed based on the distance measurement. Three object-based verification scores are summarized to determine the overall performances of satellite precipitation retrievals. The Integrated Multi-satellitE Retrievals for GPM (IMERG) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) were evaluated using the object-based approach. The NOAA stage IV MPE multi-sensor composite rain analysis was utilized as the ground observations. The comparative assessments were conducted at 0.25° by 0.25° on a daily scale in the summer season of 2014 over the continental United States (CONUS). The results suggest that IMERG possesses the similar spatial pattern of local-scale precipitation areas against stage IV observations. In addition, IMERG depicts the sizes and locations of precipitation areas more accurately against stage IV.

  13. A statistical method to get surface level air-temperature from satellite observations of precipitable water

    Digital Repository Service at National Institute of Oceanography (India)

    Pankajakshan, T.; Shikauchi, A.; Sugimori, Y.; Kubota, M.

    Vol. 49, pp. 551 to 558. 1993 A Statistical Method to Get Surface Level Air-Temperature from Satellite Observations of Precipitable Water PANKAJAKSHAN THADATHIL*, AKIRA SHIKAUCHI, YASUHIRO SUGIMORI and MASAHISA KUBOTA School of Marine Science... observations for getting the estimates of heat flux across the air-sea boundary (Miller, 1981; Liu, 1988). Bulk method has widely been used for this purpose and the parameters required are: sea surface temperature, and wind speed, air-temperature and specific...

  14. Scanning Radar Investigations to Characterize Cloud and Precipitation Processes for ASR

    Energy Technology Data Exchange (ETDEWEB)

    Venkatachalam, Chandrasekar [Colorado State Univ., Fort Collins, CO (United States). Dept. of Electrical and Computer Engineering. Cooperative Inst. for Research in the Atmosphere (CIRA)

    2016-12-17

    The project conducted investigations in the following areas related to scanning radar retrievals: a) Development for Cloud drizzle separation studies for the ENA site based on Doppler Spectra b) Advanced radar retrieval for the SGP site c) Characterizing falling snow using multifrequency dual-polarization measurements d) BAECC field experiment. More details about these investigations can be found within each subtopic within the report.

  15. Bias reduction for Satellite Based Precipitation Estimates using statistical transformations in Guiana Shield

    Science.gov (United States)

    Ringard, Justine; Becker, Melanie; Seyler, Frederique; Linguet, Laurent

    2016-04-01

    Currently satellite-based precipitation estimates exhibit considerable biases, and there have been many efforts to reduce these biases by merging surface gauge measurements with satellite-based estimates. In Guiana Shield all products exhibited better performances during the dry season (August- December). All products greatly overestimate very low intensities (50 mm). Moreover the responses of each product are different according to hydro climatic regimes. The aim of this study is to correct spatially the bias of precipitation, and compare various correction methods to define the best methods depending on the rainfall characteristic correcting (intensity, frequency). Four satellites products are used: Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) research product (3B42V7) and real time product (3B42RT), the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network (PERSIANN) and the NOAA Climate Prediction Center (CPC) Morphing technique (CMORPH), for six hydro climatic regimes between 2001 and 2012. Several statistical transformations are used to correct the bias. Statistical transformations attempt to find a function h that maps a simulated variable Ps such that its new distribution equals the distribution of the observed variable Po. The first is the use of a distribution derived transformations which is a mixture of the Bernoulli and the Gamma distribution, where the Bernoulli distribution is used to model the probability of precipitation occurrence and the Gamma distribution used to model precipitation intensities. The second a quantile-quantile relation using parametric transformation, and the last one is a common approach using the empirical CDF of observed and modelled values instead of assuming parametric distributions. For each correction 30% of both, simulated and observed data sets, are used to calibrate and the other part used to validate. The validation are test with statistical

  16. Accurate Characterization of Winter Precipitation Using In-Situ Instrumentation, CSU-CHILL Radar, and Advanced Scattering Methods

    Science.gov (United States)

    Newman, A. J.; Notaros, B. M.; Bringi, V. N.; Kleinkort, C.; Huang, G. J.; Kennedy, P.; Thurai, M.

    2015-12-01

    We present a novel approach to remote sensing and characterization of winter precipitation and modeling of radar observables through a synergistic use of advanced in-situ instrumentation for microphysical and geometrical measurements of ice and snow particles, image processing methodology to reconstruct complex particle three-dimensional (3D) shapes, computational electromagnetics to analyze realistic precipitation scattering, and state-of-the-art polarimetric radar. Our in-situ measurement site at the Easton Valley View Airport, La Salle, Colorado, shown in the figure, consists of two advanced optical imaging disdrometers within a 2/3-scaled double fence intercomparison reference wind shield, and also includes PLUVIO snow measuring gauge, VAISALA weather station, and collocated NCAR GPS advanced upper-air system sounding system. Our primary radar is the CSU-CHILL radar, with a dual-offset Gregorian antenna featuring very high polarization purity and excellent side-lobe performance in any plane, and the in-situ instrumentation site being very conveniently located at a range of 12.92 km from the radar. A multi-angle snowflake camera (MASC) is used to capture multiple different high-resolution views of an ice particle in free-fall, along with its fall speed. We apply a visual hull geometrical method for reconstruction of 3D shapes of particles based on the images collected by the MASC, and convert these shapes into models for computational electromagnetic scattering analysis, using a higher order method of moments. A two-dimensional video disdrometer (2DVD), collocated with the MASC, provides 2D contours of a hydrometeor, along with the fall speed and other important parameters. We use the fall speed from the MASC and the 2DVD, along with state parameters measured at the Easton site, to estimate the particle mass (Böhm's method), and then the dielectric constant of particles, based on a Maxwell-Garnet formula. By calculation of the "particle-by-particle" scattering

  17. An adaptive spatial model for precipitation data from multiple satellites over large regions

    KAUST Repository

    Chakraborty, Avishek

    2015-03-01

    Satellite measurements have of late become an important source of information for climate features such as precipitation due to their near-global coverage. In this article, we look at a precipitation dataset during a 3-hour window over tropical South America that has information from two satellites. We develop a flexible hierarchical model to combine instantaneous rainrate measurements from those satellites while accounting for their potential heterogeneity. Conceptually, we envision an underlying precipitation surface that influences the observed rain as well as absence of it. The surface is specified using a mean function centered at a set of knot locations, to capture the local patterns in the rainrate, combined with a residual Gaussian process to account for global correlation across sites. To improve over the commonly used pre-fixed knot choices, an efficient reversible jump scheme is used to allow the number of such knots as well as the order and support of associated polynomial terms to be chosen adaptively. To facilitate computation over a large region, a reduced rank approximation for the parent Gaussian process is employed.

  18. Satellite based radar interferometry to estimate large-scale soil water depletion from clay shrinkage: possibilities and limitations

    NARCIS (Netherlands)

    Brake, te B.; Hanssen, R.F.; Ploeg, van der M.J.; Rooij, de G.H.

    2013-01-01

    Satellite-based radar interferometry is a technique capable of measuring small surface elevation changes at large scales and with a high resolution. In vadose zone hydrology, it has been recognized for a long time that surface elevation changes due to swell and shrinkage of clayey soils can serve as

  19. Satellite optical and radar data used to track wetland forest impact and short-term recovery from Hurricane Katrina

    Science.gov (United States)

    Ramsey, Elijah W.; Rangoonwala, A.; Middleton, B.; Lu, Zhiming

    2009-01-01

    Satellite Landsat Thematic Mapper (TM) and RADARSAT-1 (radar) satellite image data collected before and after the landfall of Hurricane Katrina in the Pearl River Wildlife Management Area on the Louisiana-Mississippi border, USA, were applied to the study of forested wetland impact and recovery. We documented the overall similarity in the radar and optical satellite mapping of impact and recovery patterns and highlighted some unique differences that could be used to provide consistent and relevant ecological monitoring. Satellite optical data transformed to a canopy foliage index (CFI) indicated a dramatic decrease in canopy cover immediately after the storm, which then recovered rapidly in the Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) forest. Although CFI levels in early October indicated rapid foliage recovery, the abnormally high radar responses associated with the cypress forest suggested a persistent poststorm difference in canopy structure. Impact and recovery mapping results showed that even though cypress forests experienced very high wind speeds, damage was largely limited to foliage loss. Bottomland hardwoods, experiencing progressively lower wind speeds further inland, suffered impacts ranging from increased occurrences of downed trees in the south to partial foliage loss in the north. In addition, bottomland hardwood impact and recovery patterns suggested that impact severity was associated with a difference in stand structure possibly related to environmental conditions that were not revealed in the prehurricane 25-m optical and radar image analyses. ?? 2009 The Society of Wetland Scientists.

  20. Satellite based radar interferometry to estimate large-scale soil water depletion from clay shrinkage: possibilities and limitations

    NARCIS (Netherlands)

    Brake, te B.; Hanssen, R.F.; Ploeg, van der M.J.; Rooij, de G.H.

    2013-01-01

    Satellite-based radar interferometry is a technique capable of measuring small surface elevation changes at large scales and with a high resolution. In vadose zone hydrology, it has been recognized for a long time that surface elevation changes due to swell and shrinkage of clayey soils can serve as

  1. Le «puzzle» de la banquise arctique vue par le radar du satellite ERS-1

    Directory of Open Access Journals (Sweden)

    Claude KERGOMARD

    1994-03-01

    Full Text Available Le radar à synthèse d'ouverture (SAR à bord du satellite européen ERS-1 est le premier outil de télédétection permettant d’analyser simultanément la distribution des types de glaces de mer dans l’Arctique en relation avec leur dynamique.

  2. Capturing the fingerprint of Etna volcano activity in gravity and satellite radar data.

    Science.gov (United States)

    Del Negro, Ciro; Currenti, Gilda; Solaro, Giuseppe; Greco, Filippo; Pepe, Antonio; Napoli, Rosalba; Pepe, Susi; Casu, Francesco; Sansosti, Eugenio

    2013-10-30

    Long-term and high temporal resolution gravity and deformation data move us toward a better understanding of the behavior of Mt Etna during the June 1995 - December 2011 period in which the volcano exhibited magma charging phases, flank eruptions and summit crater activity. Monthly repeated gravity measurements were coupled with deformation time series using the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique on two sequences of interferograms from ERS/ENVISAT and COSMO-SkyMed satellites. Combining spatiotemporal gravity and DInSAR observations provides the signature of three underlying processes at Etna: (i) magma accumulation in intermediate storage zones, (ii) magmatic intrusions at shallow depth in the South Rift area, and (iii) the seaward sliding of the volcano's eastern flank. Here we demonstrate the strength of the complementary gravity and DInSAR analysis in discerning among different processes and, thus, in detecting deep magma uprising in months to years before the onset of a new Etna eruption.

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

    Science.gov (United States)

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

    2013-01-01

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

  4. Precipitation fields interpolated from gauge stations versus a merged radar-gauge precipitation product: influence on modelled soil moisture at local scale and at SMOS scale

    Directory of Open Access Journals (Sweden)

    J. T. dall'Amico

    2012-03-01

    Full Text Available For the validation of coarse resolution soil moisture products from missions such as the Soil Moisture and Ocean Salinity (SMOS mission, hydrological modelling of soil moisture is an important tool. The spatial distribution of precipitation is among the most crucial input data for such models. Thus, reliable time series of precipitation fields are required, but these often need to be interpolated from data delivered by scarcely distributed gauge station networks. In this study, a commercial precipitation product derived by Meteomedia AG from merging radar and gauge data is introduced as a novel means of adding the promising area-distributed information given by a radar network to the more accurate, but point-like measurements from a gauge station network. This precipitation product is first validated against an independent gauge station network. Further, the novel precipitation product is assimilated into the hydrological land surface model PROMET for the Upper Danube Catchment in southern Germany, one of the major SMOS calibration and validation sites in Europe. The modelled soil moisture fields are compared to those obtained when the operational interpolation from gauge station data is used to force the model. The results suggest that the assimilation of the novel precipitation product can lead to deviations of modelled soil moisture in the order of 0.15 m3 m−3 on small spatial (∼1 km2 and short temporal resolutions (∼1 day. As expected, after spatial aggregation to the coarser grid on which SMOS data are delivered (~195 km2, these differences are reduced to the order of 0.04 m3 m−3, which is the accuracy benchmark for SMOS. The results of both model runs are compared to brightness temperatures measured by the airborne L-band radiometer EMIRAD during the SMOS Validation Campaign 2010. Both comparisons yield equally good correlations, confirming the model's ability to

  5. Similarities and differences between three coexisting spaceborne radars in global rainfall and snowfall estimation

    Science.gov (United States)

    Tang, Guoqiang; Wen, Yixin; Gao, Jinyu; Long, Di; Ma, Yingzhao; Wan, Wei; Hong, Yang

    2017-05-01

    Precipitation is one of the most important components in the water and energy cycles. Radars are considered the best available technology for observing the spatial distribution of precipitation either from the ground since the 1980s or from space since 1998. This study, for the first time ever, compares and evaluates the only three existing spaceborne precipitation radars, i.e., the Ku-band precipitation radar (PR), the W-band Cloud Profiling Radar (CPR), and the Ku/Ka-band Dual-frequency Precipitation Radar (DPR). The three radars are matched up globally and intercompared in the only period which they coexist: 2014-2015. In addition, for the first time ever, TRMM PR and GPM DPR are evaluated against hourly rain gauge data in Mainland China. Results show that DPR and PR agree with each other and correlate very well with gauges in Mainland China. However, both show limited performance in the Tibetan Plateau (TP) known as the Earth's third pole. DPR improves light precipitation detectability, when compared with PR, whereas CPR performs best for light precipitation and snowfall. DPR snowfall has the advantage of higher sampling rates than CPR; however, its accuracy needs to be improved further. The future development of spaceborne radars is also discussed in two complementary categories: (1) multifrequency radar instruments on a single platform and (2) constellations of many small cube radar satellites, for improving global precipitation estimation. This comprehensive intercomparison of PR, CPR, and DPR sheds light on spaceborne radar precipitation retrieval and future radar design.

  6. Evaluation of radar-derived precipitation estimates using runoff simulation : report for the NFR Energy Norway funded project 'Utilisation of weather radar data in atmospheric and hydrological models'

    Energy Technology Data Exchange (ETDEWEB)

    Abdella, Yisak; Engeland, Kolbjoern; Lepioufle, Jean-Marie

    2012-11-01

    This report presents the results from the project called 'Utilisation of weather radar data in atmospheric and hydrological models' funded by NFR and Energy Norway. Three precipitation products (radar-derived, interpolated and combination of the two) were generated as input for hydrological models. All the three products were evaluated by comparing the simulated and observed runoff at catchments. In order to expose any bias in the precipitation inputs, no precipitation correction factors were applied. Three criteria were used to measure the performance: Nash, correlation coefficient, and bias. The results shows that the simulations with the combined precipitation input give the best performance. We also see that the radar-derived precipitation estimates give reasonable runoff simulation even without a region specific parameters for the Z-R relationship. All the three products resulted in an underestimation of the estimated runoff, revealing a systematic bias in measurements (e.g. catch deficit, orographic effects, Z-R relationships) that can be improved. There is an important potential of using radar-derived precipitation for simulation of runoff, especially in catchments without precipitation gauges inside.(Author)

  7. Nexrad-In-Space - A Geostationary Satellite Doppler Weather Radar for Hurricane Studies

    Science.gov (United States)

    Im, E.; Chandrasekar, V.; Chen, S. S.; Holland, G. J.; Kakar, R.; Lewis, W. E.; Marks, F. D.; Smith, E. A.; Tanelli, S.; Tripoli, G. J.

    2007-12-01

    The Nexrad-In-Space (NIS) is a revolutionary atmospheric radar observation concept from the geostationary orbiting platform. It was developed over the last 4 years under the auspices of NASA's Earth Science Instrument Incubator Program (IIP). The NIS radar would provide Ka-band (35 GHz) reflectivity and line-of-sight Doppler velocity profiles over a circular Earth region of approximately 5200 km in diameter with a 12-km horizontal resolution, and a minimum detectable signal of 5 dBZ. The NIS radar achieves its superb sampling capabilities by use of a 35-m diameter, deployable antenna made from lightweight membrane material. The antenna has two transmit-receive array pairs that create a dual-beam, spiral-feed combined profile image of both reflectivity and Doppler velocity approximately every 60 minutes. This sampling time can be shortened even further by increasing the number of transmit-receive array pairs. It is generally recognized that the processes important in governing hurricane intensity and structure span a wide range of spatial and temporal scales. The environmental forcing considerations require a large domain. The vortex response to the environmental forcing ultimately involves convection on small horizontal scales in the eyewall and rainband regions. Resolving this environment-vortex-convection feedback in a numerical model requires observations on the space and time scales necessary to unambiguously define these structures within and surrounding the tropical cyclone. Because the time and space scales of these processes are small, continuous 3-dimensional independent observations of the 3-dimensional wind and precipitation structures will be needed to initialize numerical models critical for this purpose. The proposed NIS Doppler radar would be the first instrument capable of accomplishing this feat at time scales less than hours, and would create the opportunity for hurricane science to enter a new era of understanding and improved prediction. This

  8. Comparison of radar and gauge precipitation data in watershed models across varying spatial and temporal scales

    Science.gov (United States)

    Precipitation is a key control on watershed hydrologic modelling output, with errors in rainfall propagating through subsequent stages of water quantity and quality analysis. Most watershed models incorporate precipitation data from rain gauges; higher-resolution data sources are...

  9. Comparison of radar and gauge precipitation data in watershed models across varying spatial and temporal scales

    Science.gov (United States)

    Precipitation is a key control on watershed hydrologic modelling output, with errors in rainfall propagating through subsequent stages of water quantity and quality analysis. Most watershed models incorporate precipitation data from rain gauges; higher-resolution data sources are...

  10. Evidence of hydrocarbon pollution in soil exploiting satellite optical and radar images

    Science.gov (United States)

    Monsivais-Huertero, A.; Galvan-Pineda, J.; Espinosa-Hernandez, A.; Jimenez-Escalona, J. C.; Ramos-Rodriguez, J. M.

    2013-05-01

    Oil spills are one of the most important sources of hydrocarbon pollution in soils of areas near centers of extraction, storage or transportation of petroleum products. These spills or leaks can occur arising from deficient maintenance of facilities or accidents. The effects of these spills can spread for kilometers affecting large areas. This has a strong impact on the local ecosystem disturbing the flora and fauna. In costal tourist areas, this type of contaminants represents significant health risks for visitors and therefore, economic losses for the place. For this reason, it is very important to know and identify the areas affected by this type of pollution in order to create action plans for remediation of the ecosystem. Due to the large land extensions that can cover such disasters, satellite images become a valuable tool because of their large spatial coverage. Nowadays, different satellite techniques have been developed to recognize land affected by the presence of hydrocarbons. In the optical spectrum, optical sensing imagery (e.g. Landsat, SPOT, MODIS, etc.) has been widely used. However, these techniques have the intrinsic limitation in scenes with vegetation cover. In contrast, techniques exploiting radar images are still rare. The type of signal that is detected by the radar provides information even in areas with vegetation cover. The radar signal interacts with the vegetation and soil collecting information about the dielectric properties of the soil. This study identifies zones of contaminated soil by using the synergy of optical and radar images. This site of study is located in Paraiso, Tabasco, in Southern Mexico (18°27'N 93°32'W). The region is composed of coastal and tropical forest ecosystems and includes the Port Dos Bocas. The Port Dos Bocas has its points of extractions 130m away from the coast. The annual activities report 10 millions of tons of hydrocarbons transported using around 5500 ships. The methodology presented in this paper

  11. Utilizing Satellite Precipitation Products to Understand the Link Between Climate Variability and Malaria

    Science.gov (United States)

    Maggioni, V.; Mousam, A.; Delamater, P. L.; Cash, B. A.; Quispe, A.

    2015-12-01

    Malaria is a public health threat to people globally leading to 198 million cases and 584,000 deaths annually. Outbreaks of vector borne diseases such as malaria can be significantly impacted by climate variables such as precipitation. For example, an increase in rainfall has the potential to create pools of water that can serve as breeding locations for mosquitos. Peru is a country that is currently controlling malaria, but has not been able to completely eliminate the disease. Despite the various initiatives in order to control malaria - including regional efforts to improve surveillance, early detection, prompt treatment, and vector management - malaria cases in Peru have risen between 2011 and 2014. The purpose of this study is to test the hypothesis that climate variability plays a fundamental role in malaria occurrence over a 12-year period (2003-2014) in Peru. When analyzing climate variability, it is important to obtain high-quality, high-resolution data for a time series long enough to draw conclusion about how climate variables have been and are changing. Remote sensing is a powerful tool for measuring and monitoring climate variables continuously in time and space. A widely used satellite-based precipitation product, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), available globally since 1998, was used to obtain 3-hourly data with a spatial resolution of 0.25° x 0.25°. The precipitation data was linked to weekly (2003-2014) malaria cases collected by health centers and available at a district level all over Peru to investigate the relationship between precipitation and the seasonal and annual variations in malaria incidence. Further studies will incorporate additional climate variables such as temperature, humidity, soil moisture, and surface pressure from remote sensing data products and climate models. Ultimately, this research will help us to understand if climate variability impacts malaria incidence

  12. Persistent scatterers detection on synthetic aperture radar images acquired by Sentinel-1 satellite

    Science.gov (United States)

    Dǎnişor, Cosmin; Popescu, Anca; Datcu, Mihai

    2016-12-01

    Persistent Scatterers Interferometry (PS-InSAR) has become a popular method in remote sensing because of its capability to measure terrain deformations with very high accuracy. It relies on multiple Synthetic Aperture Radar (SAR) acquisitions, to monitor points with stable proprieties over time, called Persistent Scatterers (PS)[1]. These points are unaffected by temporal decorrelation, therefore by analyzing their interferometric phase variation we can estimate the scene's deformation rates within a given time interval. In this work, we apply two incoherent detection algorithms to identify Persistent Scatterers candidates in the city of Focșani, Romania. The first method studies the variation of targets' intensities along the SAR acquisitions and the second method analyzes the spectral proprieties of the scatterers. The algorithms were implemented on a dataset containing 11 complex images of the region covering Buzău, Brăila and Focșani cities. Images were acquired by Sentinel-1 satellite in a time span of 5 months, from October 2014 to February 2015. The processing chain follows the requirements imposed by the new C-band SAR images delivered by the Sentinel-1 satellite (launched in April 2014) imaging in Interferometric Wide (IW) mode. Considering the particularities of the TOPS (Terrain Observation with Progressive Scans in Azimuth) imaging mode[2], special requirements had to be considered for pre-processing steps. The PS detection algorithms were implemented in Gamma RS program, a software which contains various function packages dedicated to SAR images focalization, analysis and processing.

  13. Combined Use of Multi-Temporal Optical and Radar Satellite Images for Grassland Monitoring

    Directory of Open Access Journals (Sweden)

    Pauline Dusseux

    2014-06-01

    Full Text Available The aim of this study was to assess the ability of optical images, SAR (Synthetic Aperture Radar images and the combination of both types of data to discriminate between grasslands and crops in agricultural areas where cloud cover is very high most of the time, which restricts the use of visible and near-infrared satellite data. We compared the performances of variables extracted from four optical and five SAR satellite images with high/very high spatial resolutions acquired during the growing season. A vegetation index, namely the NDVI (Normalized Difference Vegetation Index, and two biophysical variables, the LAI (Leaf Area Index and the fCOVER (fraction of Vegetation Cover were computed using optical time series and polarization (HH, VV, HV, VH. The polarization ratio and polarimetric decomposition (Freeman–Durden and Cloude–Pottier were calculated using SAR time series. Then, variables derived from optical, SAR and both types of remotely-sensed data were successively classified using the Support Vector Machine (SVM technique. The results show that the classification accuracy of SAR variables is higher than those using optical data (0.98 compared to 0.81. They also highlight that the combination of optical and SAR time series data is of prime interest to discriminate grasslands from crops, allowing an improved classification accuracy.

  14. A new strategic sampling for offshore wind assessment using radar satellite images

    Energy Technology Data Exchange (ETDEWEB)

    Beaucage, P.; Lafrance, G.; Bernier, M.; Lafrance, J. [Institut National de la Recherche Scientifique, Varennes, PQ (Canada); Choisnard, J. [Hydro-Quebec, Varennes, PQ (Canada)

    2007-07-01

    Synthetic Aperture Radar (SAR) satellite images have been used for offshore wind assessment. Several offshore wind farms are in operation or under construction in northern Europe. The European target for 2030 is 300 GW, of which half is intended for onshore and half for offshore development. Offshore projects in the east coast United States, the Gulf of Mexico and west coast of Canada are in the planning stage. Information obtained from SAR can be used to supplement current mapping methods of offshore wind energy resources. SAR is a useful tool to localize wind pattern over water surfaces. Other sources of offshore wind observations include meteorological stations such as buoys and masts; remote sensing instruments onboard satellites such as scatterometers (QuikSCAT, ASCAT) or passive microwave radiometers; and numerical weather prediction models. The synergy between scatterometers and SAR was discussed. The SAR system has been used for microscale resolution wind mapping in the Gaspe Peninsula. Strategic sampling zones were chosen in proximity to the QuikSCAT grid. It was concluded that 270 and 570 SAR images are needed to calculate average wind speed (U) and mean power output of a 3 MW wind turbine (P) over the Gaspe Peninsula region, respectively. It was concluded that microscale regional wind mapping can be produced at a lower cost with strategic sampling compared to random sampling. refs., tabs., figs.

  15. Correlating Global Precipitation Measurement satellite data with karst spring hydrographs for rapid catchment delineation

    Science.gov (United States)

    Longenecker, Jake; Bechtel, Timothy; Chen, Zhao; Goldscheider, Nico; Liesch, Tanja; Walter, Robert

    2017-05-01

    To protect karst spring water resources, catchments must be known. We have developed a method for correlating spring hydrographs with newly available, high-resolution, satellite-based Global Precipitation Measurement data to rapidly and remotely locate recharge areas. We verify the method using a synthetic comparison of ground-based rain gage data with the satellite precipitation data set. Application to karst springs is proven by correlating satellite data with hydrographs from well-known springs with published catchments in Europe and North America. Application to an unknown-catchment spring in Pennsylvania suggests distant recharge, requiring a flow path that crosses topographic divides, as well as multiple lithologies, physiographic provinces, and tectonic boundaries. Although surprising, this latter result is consistent with published geologic/geophysical, monitoring well, and stream gage data. We conclude that the method has considerable potential to improve the speed and accuracy of catchment identification and hydrodynamic characterization, with applications to water resource protection and groundwater exploration, among others.

  16. CLASSIFIER FUSION OF HIGH-RESOLUTION OPTICAL AND SYNTHETIC APERTURE RADAR (SAR SATELLITE IMAGERY FOR CLASSIFICATION IN URBAN AREA

    Directory of Open Access Journals (Sweden)

    T. Alipour Fard

    2014-10-01

    Full Text Available This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR and optical sensors refer to different properties of the observed scene and it is believed that when they are fused together, they complement each other to improve the performance of a particular application. In this paper, two category of features are generate and six classifier fusion operators implemented and evaluated. Implementation results show significant improvement in the classification accuracy.

  17. The accuracy of satellite radar altimeter data over the Greenland ice sheet determined from airborne laser data

    DEFF Research Database (Denmark)

    Bamber, J.L.; Ekholm, Simon; Krabill, W.

    1998-01-01

    The 336 days of the geodetic phase of ERS-1 provides dense coverage, by satellite radar altimetry, of the whole of the Greenland ice sheet. These data have been used to produce a digital elevation model of the ice sheet. The errors present in the altimeter data were investigated via a comparison...... with airborne laser altimeter data an absolute accuracy typically in the range 2-10 cm +/- 10 cm. Comparison of differences between the radar and laser derived elevations, showed a correlation with surface slope. The difference between the two data sets ranged from 84 cm +/- 79 cm for slopes below 0.1 degrees...

  18. Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia

    Directory of Open Access Journals (Sweden)

    Mou Leong Tan

    2015-01-01

    Full Text Available Satellite precipitation products (SPPs potentially constitute an alternative to sparse rain gauge networks for assessing the spatial distribution of precipitation. However, applications of these products are still limited due to the lack of robust quality assessment. This study compares daily, monthly, seasonal, and annual rainfall amount at 342 rain gauges over Malaysia to estimations using five SPPs (3B42RT, 3B42V7, GPCP-1DD, PERSIANN-CDR, and CMORPH and a ground-based precipitation product (APHRODITE. The performance of the precipitation products was evaluated from 2003 to 2007 using continuous (RMSE, R2, ME, MAE, and RB and categorical (ACC, POD, FAR, CSI, and HSS statistical approaches. Overall, 3B42V7 and APHRODITE performed the best, while the worst performance was shown by GPCP-1DD. 3B42RT, 3B42V7, and PERSIANN-CDR slightly overestimated observed precipitation by 2%, 4.7%, and 2.1%, respectively. By contrast, APHRODITE and CMORPH significantly underestimated precipitations by 19.7% and 13.2%, respectively, whereas GPCP-1DD only slightly underestimated by 2.8%. All six precipitation products performed better in the northeast monsoon than in the southwest monsoon. The better performances occurred in eastern and southern Peninsular Malaysia and in the north of East Malaysia, which receives higher rainfall during the northeast monsoon, whereas poor performances occurred in the western and dryer Peninsular Malaysia. All precipitation products underestimated the no/tiny (<1 mm/day and extreme (≥20 mm/day rainfall events, while they overestimated low (1–20 mm/day rainfall events. 3B42RT and 3B42V7 showed the best ability to detect precipitation amounts with the highest HSS value (0.36. Precipitations during flood events such as those which occurred in late 2006 and early 2007 were estimated the best by 3B42RT and 3B42V7, as shown by an R2 value ranging from 0.49 to 0.88 and 0.52 to 0.86, respectively. These results on SPPs’ uncertainties

  19. Challenge and opportunities of space-based precipitation radar for spatio-temporal hydrology analysis in tropical maritime influenced catchment: Case study on the hilly tropical watershed of Peninsular Malaysia

    Science.gov (United States)

    Mahmud, M. R.; Numata, S.; Matsuyama, H.; Hosaka, T.; Hashim, M.

    2014-02-01

    This paper highlights two critical issues regarding hilly watershed in Peninsular Malaysia; (1) current status of spatio-temporal condition of rain gauge based measurement, and (2) potential of space-based precipitation radar to study the rainfall dynamics. Two analyses were carried out represent each issue consecutively. First, the spatial distribution and efficiency of rain gauge in hilly watershed Peninsular Malaysia is evaluated with respect to the land use and elevation information using Geographical Information System (GIS) approach. Second, the spatial pattern of rainfall changes is analysed using the Tropical Rainfall Measuring Mission (TRMM) satellite information. The spatial analysis revealed that the rain gauge distribution had sparse coverage on hilly watershed and possessed inadequate efficiency for effective spatial based assessment. Significant monthly rainfall changes identified by TRMM satellite on the upper part of the watershed had occurred occasionally in 1999, 2000, 2001, 2006, and 2009 went undetected by conventional rain gauge. This study informed the potential and opportunities of space-based precipitation radar to fill the gaps of knowledge on spatio-temporal rainfall patterns for hydrology and related fields in tropical region.

  20. Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

    Directory of Open Access Journals (Sweden)

    Basile Pauthier

    2016-01-01

    Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

  1. Improving quantitative precipitation nowcasting with a local ensemble transform Kalman filter radar data assimilation system: observing system simulation experiments

    Directory of Open Access Journals (Sweden)

    Chih-Chien Tsai

    2014-03-01

    Full Text Available This study develops a Doppler radar data assimilation system, which couples the local ensemble transform Kalman filter with the Weather Research and Forecasting model. The benefits of this system to quantitative precipitation nowcasting (QPN are evaluated with observing system simulation experiments on Typhoon Morakot (2009, which brought record-breaking rainfall and extensive damage to central and southern Taiwan. The results indicate that the assimilation of radial velocity and reflectivity observations improves the three-dimensional winds and rain-mixing ratio most significantly because of the direct relations in the observation operator. The patterns of spiral rainbands become more consistent between different ensemble members after radar data assimilation. The rainfall intensity and distribution during the 6-hour deterministic nowcast are also improved, especially for the first 3 hours. The nowcasts with and without radar data assimilation have similar evolution trends driven by synoptic-scale conditions. Furthermore, we carry out a series of sensitivity experiments to develop proper assimilation strategies, in which a mixed localisation method is proposed for the first time and found to give further QPN improvement in this typhoon case.

  2. A Doppler Radar Observation of a Cold Front: Three-Dimensional Air Circulation, Related Precipitation System, and Associated Wavelike Motions.

    Science.gov (United States)

    Testud, J.; Amayenc, P.; Chong, M.; Nutten, B.; Sauvaget, A.

    1980-01-01

    This paper is based on the observation of a cold front using a C-band Doppler radar. The extent of the precipitation system associated with the front allowed collection of Doppler radar data during 12 consecutive hours. The methodology for data acquisition presently used is conical scanning. The data analysis has been extended to the case of a nonuniform distribution of tracers.The air circulation is presented in a reference frame moving at the speed of the front. A pronounced cross-frontal circulation is found to be associated with significant cross-frontal acceleration. The thermal structure across the front is reconstructed by means of the equations of motion.From the vertical velocity field an estimate of the height-integrated condensation rate is made. It is found to agree with the rainfall rate inferred from the radar reflectivity data.Also, large-amplitude small-scale motions are detected and identified as a well-characterized atmospheric wave. Theoretical considerations support the explanation that it is the manifestation of a dynamical instability of the shear flow within the frontal zone.

  3. Improved global high resolution precipitation estimation using multi-satellite multi-spectral information

    Science.gov (United States)

    Behrangi, Ali

    In respond to the community demands, combining microwave (MW) and infrared (IR) estimates of precipitation has been an active area of research since past two decades. The anticipated launching of NASA's Global Precipitation Measurement (GPM) mission and the increasing number of spectral bands in recently launched geostationary platforms will provide greater opportunities for investigating new approaches to combine multi-source information towards improved global high resolution precipitation retrievals. After years of the communities' efforts the limitations of the existing techniques are: (1) Drawbacks of IR-only techniques to capture warm rainfall and screen out no-rain thin cirrus clouds; (2) Grid-box- only dependency of many algorithms with not much effort to capture the cloud textures whether in local or cloud patch scale; (3) Assumption of indirect relationship between rain rate and cloud-top temperature that force high intensity precipitation to any cold cloud; (4) Neglecting the dynamics and evolution of cloud in time; (5) Inconsistent combination of MW and IR-based precipitation estimations due to the combination strategies and as a result of above described shortcomings. This PhD dissertation attempts to improve the combination of data from Geostationary Earth Orbit (GEO) and Low-Earth Orbit (LEO) satellites in manners that will allow consistent high resolution integration of the more accurate precipitation estimates, directly observed through LEO's PMW sensors, into the short-term cloud evolution process, which can be inferred from GEO images. A set of novel approaches are introduced to cope with the listed limitations and is consist of the following four consecutive components: (1) starting with the GEO part and by using an artificial-neural network based method it is demonstrated that inclusion of multi-spectral data can ameliorate existing problems associated with IR-only precipitating retrievals; (2) through development of Precipitation Estimation

  4. Investigation of S3-2 satellite data for local time variation of energetic electron precipitation

    Science.gov (United States)

    Robbe, S.; Sheldon, W. R.; Benbrook, J. R.; Bering, E. A.; Vampola, A. L.

    1994-01-01

    Data on precipitating electrons from the S3-2 satellite were investigated for local time variation at four L = 4 stations in the southern hemisphere. The equatorial pitch angles of electrons mirroring at 100 km, assumed to be the edge of the bounce loss cone, are calculated for L = 4 using the International Geomagnetic Reference Field for the epoch of the S3-2 data, along with the variation in mirror altitude per degree of equatorial pitch angle. The largest obstacle to the investigation was uneven sampling in terms of local time for all of the stations. However, this situation was improved upon by the use of S3-2 measurements at the conjugate locations of the four stations which provided additional data on electrons in the southern hemisphere bounce loss cone. Evidence for an effect of the dawn-to-dusk geoelectric field was found at two of the stations, Halley Bay and Siple, in the form of a minimum in electron precipitation at dusk. However, the present study does not completely resolve the question of local time modulation of electron precipitation at L = 4 in the southern hemisphere. Furthermore, while the average precipitation was lowest at the Kerguelen site, as would be expected on the basis of drift loss cone (DLC) theories, the intensity at that site exceeds the level that is expected on the basis of these DLC theories.

  5. Estimate of Precipitation from the Dual-Beam Airborne Radars in TOGA COARE. Part II: Precipitation Efficiency in the 9 February 1993 MCS.

    Science.gov (United States)

    Oury, Stéphane; Dou, Xiankang; Testud, Jacques

    2000-12-01

    Dual-beam airborne Doppler radars are commonly used in convection experiments for their ability to describe the dynamical structure of weather systems. However, instrumental limitations impose the use of wavelengths such as X-band, which are largely attenuated through heavy rain.This paper is the second of a series of two, which aim at developing schemes for attenuation correction. The authors' final objective is to improve the estimation of precipitation sampled from airborne radars. The first paper was dealing with the application of `differential algorithms' (`stereoradar' and `quad beam') to the independent retrieval of the specific attenuation and nonattenuated reflectivity, which shed some light on the physics of the precipitation. This second paper develops a more extensive procedure based upon the hybridization of a `differential' and an `integral' algorithm. It is much more flexible than the methods proposed in part one and allows full rainfall-rate retrievals in single aircraft experiments. This procedure is applied to the 9 February mesoscale convective system (MCS) study case from Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE), and the impact of the reflectivity correction on the water budget at the cloud system scale is discussed.As expected, the production of water in the 9 February squall line is maximum below the freezing level and is located in the updraft resulting from the interaction between the warm inflow and rear-to-front cold flow. The authors' analysis shows that the precipitation efficiency in the convective region of the system is 31%. Therefore, the large majority of water vapor condensed into cloud droplets and ice crystals does not immediately reach the surface as precipitation. It travels toward the rear of the system at the speed of the horizontal air motion, which suggests a large contribution of the stratiform area in the global water budget. The same calculation performed using raw

  6. Uncertainty Estimation of Global Precipitation Measurement through Objective Validation Strategy

    Science.gov (United States)

    KIM, H.; Utsumi, N.; Seto, S.; Oki, T.

    2014-12-01

    Since Tropical Rainfall Measuring Mission (TRMM) has been launched in 1997 as the first satellite mission dedicated to measuring precipitation, the spatiotemporal gaps of precipitation observation have been filled significantly. On February 27th, 2014, Dual-frequency Precipitation Radar (DPR) satellite has been launched as a core observatory of Global Precipitation Measurement (GPM), an international multi-satellite mission aiming to provide the global three hourly map of rainfall and snowfall. In addition to Ku-band, Ka-band radar is newly equipped, and their combination is expected to introduce higher precision than the precipitation measurement of TRMM/PR. In this study, the GPM level-2 orbit products are evaluated comparing to various precipitation observations which include TRMM/PR, in-situ data, and ground radar. In the preliminary validation over intercross orbits of DPR and TRMM, Ku-band measurements in both satellites shows very close spatial pattern and intensity, and the DPR is capable to capture broader range of precipitation intensity than of the TRMM. Furthermore, we suggest a validation strategy based on 'objective classification' of background atmospheric mechanisms. The Japanese 55-year Reanalysis (JRA-55) and auxiliary datasets (e.g., tropical cyclone best track) is used to objectively determine the types of precipitation. Uncertainty of abovementioned precipitation products is quantified as their relative differences and characterized for different precipitation mechanism. Also, it is discussed how the uncertainty affects the synthesis of TRMM and GPM for a long-term satellite precipitation observation records which is internally consistent.

  7. Evaluation of Satellite Precipitation Products with Rain Gauge Data at Different Scales: Implications for Hydrological Applications

    Directory of Open Access Journals (Sweden)

    Ruifang Guo

    2016-07-01

    Full Text Available Rain gauge and satellite-retrieved data have been widely used in basin-scale hydrological applications. While rain gauges provide accurate measurements that are generally unevenly distributed in space, satellites offer spatially regular observations and common error prone retrieval. Comparative evaluation of gauge-based and satellite-based data is necessary in hydrological studies, as precipitation is the most important input in basin-scale water balance. This study uses quality-controlled rain gauge data and prevailing satellite products (Tropical Rainfall Measuring Mission (TRMM 3B43, 3B42 and 3B42RT to examine the consistency and discrepancies between them at different scales. Rain gauges and TRMM products were available in the Poyang Lake Basin, China, from 1998 to 2007 (3B42RT: 2000–2007. Our results show that the performance of TRMM products generally increases with increasing spatial scale. At both the monthly and annual scales, the accuracy is highest for TRMM 3B43, with 3B42 second and 3B42RT third. TRMM products generally overestimate precipitation because of a high frequency and degree of overestimation in light and moderate rain cases. At the daily scale, the accuracy is relatively low between TRMM 3B42 and 3B42RT. Meanwhile, the performances of TRMM 3B42 and 3B42RT are highly variable in different seasons. At both the basin and pixel scales, TRMM 3B43 and 3B42 exhibit significant discrepancies from July to September, performing worst in September. For TRMM 3B42RT, all statistical indices fluctuate and are low throughout the year, performing worst in July at the pixel scale and January at the basin scale. Furthermore, the spatial distributions of the statistical indices of TRMM 3B43 and 3B42 performed well, while TRMM 3B42RT displayed a poor performance.

  8. Evaluating Cloud and Precipitation Processes in Numerical Models using Current and Potential Future Satellite Missions

    Science.gov (United States)

    van den Heever, S. C.; Tao, W. K.; Skofronick Jackson, G.; Tanelli, S.; L'Ecuyer, T. S.; Petersen, W. A.; Kummerow, C. D.

    2015-12-01

    Cloud, aerosol and precipitation processes play a fundamental role in the water and energy cycle. It is critical to accurately represent these microphysical processes in numerical models if we are to better predict cloud and precipitation properties on weather through climate timescales. Much has been learned about cloud properties and precipitation characteristics from NASA satellite missions such as TRMM, CloudSat, and more recently GPM. Furthermore, data from these missions have been successfully utilized in evaluating the microphysical schemes in cloud-resolving models (CRMs) and global models. However, there are still many uncertainties associated with these microphysics schemes. These uncertainties can be attributed, at least in part, to the fact that microphysical processes cannot be directly observed or measured, but instead have to be inferred from those cloud properties that can be measured. Evaluation of microphysical parameterizations are becoming increasingly important as enhanced computational capabilities are facilitating the use of more sophisticated schemes in CRMs, and as future global models are being run on what has traditionally been regarded as cloud-resolving scales using CRM microphysical schemes. In this talk we will demonstrate how TRMM, CloudSat and GPM data have been used to evaluate different aspects of current CRM microphysical schemes, providing examples of where these approaches have been successful. We will also highlight CRM microphysical processes that have not been well evaluated and suggest approaches for addressing such issues. Finally, we will introduce a potential NASA satellite mission, the Cloud and Precipitation Processes Mission (CAPPM), which would facilitate the development and evaluation of different microphysical-dynamical feedbacks in numerical models.

  9. X-band Scanning ARM Precipitation Radar (X-SAPR) Instrument Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Widener, K; Bharadwaj, N

    2012-10-29

    The X-band scanning ARM cloud radar (X-SAPR) is a full-hemispherical scanning polarimetric Doppler radar transmitting simultaneously in both H and V polarizations. With a 200 kW magnetron transmitter, this puts 100 kW of transmitted power for each polarization. The receiver for the X-SAPR is a Vaisala Sigmet RVP-900 operating in a coherent-on-receive mode. Three X-SAPRs are deployed around the Southern Great Plains (SGP) Central Facility in a triangular array. A fourth X-SAPR is deployed near Barrow, Alaska on top of the Barrow Arctic Research Center.

  10. Avalanche Debris Detection Using Satellite- and Drone Based Radar and Optical Remote Sensing

    Science.gov (United States)

    Eckerstorfer, M.; Malnes, E.; Vickers, H.; Solbø, S. A.; Tøllefsen, A.

    2014-12-01

    The mountainous fjord landscape in the county of Troms, around its capital Tromsø in Northern Norway is prone to high avalanche activity during the snow season. Large avalanches pose a hazard to infrastructure, such as buildings and roads, located between the steep mountainsides and the fjords. A prolonged cold spell during January and February 2014 was followed by rapid new-snow loading during March 2014, inducing a significant avalanche cycle with many spontaneous, size D4 avalanches that affected major transport veins. During and shortly after the avalanche cycle of March 2014, we obtained 11 Radarsat-2 Ultrafine mode scenes, chosen according to reported avalanche activity. We further collected four Radarsat-2 ScanSAR mode scenes and two Landsat-8 scenes covering the entire county of Troms. For one particular avalanche, we obtained a drone-based orthophoto, from which a DEM of the avalanche debris surface was derived, using structure-from-motion photogrammetry. This enabled us to calculate the debris volume accurately. We detected avalanche debris in the radar images visually, by applying two detection algorithms that make use of the increased backscatter in avalanche debris. This backscatter increase is a product of increased snow water equivalent and surface roughness, roughly of the order of 3 dB. In addition, we applied a multi-temporal approach by repeatedly detecting avalanche debris at different acquisition times, as well as a multi-sensor approach, covering similar areas with different sensors. This multi-temporal and multi-sensor approach enabled us to map the spatial extent and magnitude of the March 2014 avalanche cycle in the county Troms. With ESA's Sentinel-1 satellite, providing high-resolution, large swath radar images with a short repeat cycle, a complete avalanche record for a forecasting region could become feasible. In this first test season, we detected more than 550 avalanches that were released during a one-month period over an area of

  11. River monitoring from satellite radar altimetry in the Zambezi River basin

    Directory of Open Access Journals (Sweden)

    C. I. Michailovsky

    2012-07-01

    Full Text Available Satellite radar altimetry can be used to monitor surface water levels from space. While current and past altimetry missions were designed to study oceans, retracking the waveforms returned over land allows data to be retrieved for smaller water bodies or narrow rivers. The objective of this study is the assessment of the potential for river monitoring from radar altimetry in terms of water level and discharge in the Zambezi River basin. Retracked Envisat altimetry data were extracted over the Zambezi River basin using a detailed river mask based on Landsat imagery. This allowed for stage measurements to be obtained for rivers down to 80 m wide with an RMSE relative to in situ levels of 0.32 to 0.72 m at different locations. The altimetric levels were then converted to discharge using three different methods adapted to different data-availability scenarios: first with an in situ rating curve available, secondly with one simultaneous field measurement of cross-section and discharge, and finally with only historical discharge data available. For the two locations at which all three methods could be applied, the accuracies of the different methods were found to be comparable, with RMSE values ranging from 4.1 to 6.5% of the mean annual in situ gauged amplitude for the first method and from 6.9 to 13.8% for the second and third methods. The precision obtained with the different methods was analyzed by running Monte Carlo simulations and also showed comparable values for the three approaches with standard deviations found between 5.7 and 7.2% of the mean annual in situ gauged amplitude for the first method and from 8.7 to 13.0% for the second and third methods.

  12. Thirty years of elevation change on Antarctic Peninsula ice shelves from multimission satellite radar altimetry

    Science.gov (United States)

    Fricker, Helen Amanda; Padman, Laurie

    2012-02-01

    We use data acquired between 1978 and 2008 by four satellite radar altimeter missions (Seasat, ERS-1, ERS-2 and Envisat) to determine multidecadal elevation change rates (dhi/dt) for six major Antarctic Peninsula (AP) ice shelves. In areas covered by the Seasat orbit (to 72.16°S), regional-averaged 30-year trends were negative (surface lowering), with rates between -0.03 and -0.16 m a-1. Surface lowering preceded the start of near-continuous radar altimeter operations that began with ERS-1 in 1992. The average rate of lowering for the first 14 years of the period was typically smaller than the 30-year average; the exception was the southern Wilkins Ice Shelf, which experienced negligible lowering between 2000 and 2008, when a series of large calving events began. Analyses of the continuous ERS/Envisat time series (to 81.5°) for 1992-2008 reveal a period of strong negative dhi/dt on most ice shelves between 1992 and 1995. Based on prior studies of regional atmospheric and oceanic conditions, we hypothesize that the observed elevation changes on Larsen C Ice Shelf are driven primarily by firn compaction while the western AP ice shelves are responding to changes in both surface mass balance and basal melt rates. Our time series also show that large changes in dhi/dt can occur on interannual time scales, reinforcing the importance of long time series altimetry to separate long-term trends associated with climate change from interannual to interdecadal natural variability.

  13. Real-time, Quasi-Global, Multi-Satellite Precipitation Analysis Using TRMM and other Satellite Observations

    Science.gov (United States)

    Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric

    2003-01-01

    A TRMM-based 3-hr analyses that use TRMM observations to calibrate polar-orbit microwave observations from SSM/I (and other satellites) and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map is described. This TRMM standard product will be available for the entire TRMM period (January 1998-present) in 2003 as part of Version 6 of the TRMM products. A real-time version of this merged product is being produced and is available at 0.25" latitude-longitude resolution over the latitude range from 50 N-500S. Examples will be shown, including its use in monitoring flood conditions and in relating weather-scale patterns to climate-scale patterns. Plans to incorporate the TRMM data and 3-hourly analysis into the Global Precipitation Climatology Project (GPCP) products are outlined. The outcome in the near future should be an improved global analysis and climatology on monthly scales for the 23 year period and finer time scale analyses for more recent periods, including 3-hourly analyses over the globe. These technique developments are potential prototypes for analyses with the Global Precipitation Measurement (GPM) mission.

  14. 用PR资料分析热带气旋卡特里娜降水特征%Precipitation Characteristics in Tropical Cyclone Katrina Using TRMM Precipitation Radar

    Institute of Scientific and Technical Information of China (English)

    游然; 卢乃锰; 邱红; 李小青

    2011-01-01

    利用TRMM(Tropical Rainfall Measuring Mission)卫星降水雷达(Precipitation Radar,PR)资料对2005年8月发生在墨西哥湾的热带气旋卡特里娜(Katrina)初生、发展和变性3个阶段的层状云和对流云的近地面降水和降水垂直廓线进行分析.结果表明:在热带气旋的整个生命期,对流性降水个数约是层状云降水个数的四分之一;随着气旋的发展,对流性和层状云降水的平均强度逐渐增强,在登陆前有所减弱,登陆后对流性降水和总平均降水均增强,层状云降水稍有减弱;大部分降水廓线都随高度升高均呈现先略增大(到4 km高度)、再减小的趋势,在6~7 km处由于冻结层的存在使得降水达到最小值.%Tropical cyclone is a primary disastrous synoptic system in China. Its monitoring mainly depends on optical data, i. e. , visible and infrared data. These sensors observe the albedo and temperature of cloud top which is somewhat related with the precipitation, but leave the precipitation particles inside the precipitation-cloud system unseen. Fortunately, the microwave sensor can penetrate into the cloud and sense precipitation particles in and even below the cloud system, and observe precipitation more directly.Based on TRMM PR (Precipitation Radar) product, 6 orbit data in four days covering the main part of the cyclone are analyzed to study the characteristics of near-surface precipitation and vertical precipitation profile of stratiform and convective cloud in nascent, developing, and recessionary stages of the cyclone Katrina.Results indicate that the convective rain percent is 15%-22% and stratiform rain occupies 78%-85%. The average stratiform rain rate is 2.7-5.9 mm · h-1 , the convective rain rate is 7.7-17.5 mm ·h-1 , and the total rain rate is 3.5-7.7 mm · h-1. During the life cycle of the cyclone, the pixel number with convective rain is one fourth of stratiforn one's, while the average intensity/rain rate of convective

  15. Assessment of the Impact of Reservoirs in the Upper Mekong River Using Satellite Radar Altimetry and Remote Sensing Imageries

    Directory of Open Access Journals (Sweden)

    Kuan-Ting Liu

    2016-04-01

    Full Text Available Water level (WL and water volume (WV of surface-water bodies are among the most crucial variables used in water-resources assessment and management. They fluctuate as a result of climatic forcing, and they are considered as indicators of climatic impacts on water resources. Quantifying riverine WL and WV, however, usually requires the availability of timely and continuous in situ data, which could be a challenge for rivers in remote regions, including the Mekong River basin. As one of the most developed rivers in the world, with more than 20 dams built or under construction, Mekong River is in need of a monitoring system that could facilitate basin-scale management of water resources facing future climate change. This study used spaceborne sensors to investigate two dams in the upper Mekong River, Xiaowan and Jinghong Dams within China, to examine river flow dynamics after these dams became operational. We integrated multi-mission satellite radar altimetry (RA, Envisat and Jason-2 and Landsat-5/-7/-8 Thematic Mapper (TM/Enhanced Thematic Mapper plus (ETM+/Operational  Land Imager (OLI optical remote sensing (RS imageries to construct composite WL time series with enhanced spatial resolutions and substantially extended WL data records. An empirical relationship between WL variation and water extent was first established for each dam, and then the combined long-term WL time series from Landsat images are reconstructed for the dams. The R2 between altimetry WL and Landsat water area measurements is >0.95. Next, the Tropical Rainfall Measuring Mission (TRMM data were used to diagnose and determine water variation caused by the precipitation anomaly within the basin. Finally, the impact of hydrologic dynamics caused by the impoundment of the dams is assessed. The discrepancy between satellite-derived WL and available in situ gauge data, in term of root-mean-square error (RMSE is at 2–5 m level. The estimated WV variations derived from combined RA

  16. What is a Proper Resolution of Weather Radar Precipitation Estimates for Urban Drainage Modelling?

    DEFF Research Database (Denmark)

    Nielsen, Jesper Ellerbæk; Rasmussen, Michael R.; Thorndahl, Søren Liedtke

    2012-01-01

    The resolution of distributed rainfall input for drainage models is the topic of this paper. The study is based on data from high resolution X-band weather radar used together with an urban drainage model of a medium size Danish village. The flow, total run-off volume and CSO volume are evaluated...

  17. 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

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

    Science.gov (United States)

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

    2009-04-01

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

  19. Tracking Low Earth Orbit Small Debris with GPS Satellites as Bistatic Radar

    Science.gov (United States)

    Mahmud, M.; Qaisar, S.; Benson, C.

    2016-09-01

    Space debris is a growing problem and collisions are potentially lethal to satellites. Trajectories for small objects are predicted based on infrequent measurements, and the scale and therefore cost of maneuver required to avoid collisions is a function of trajectory accuracy. Frequent and precise observations will improve trajectory accuracy. In this paper, we extend on aspects of the feasibility of tracking space debris in Low Earth Orbit using emissions from GNSS satellites as bistatic radar illuminators. The wavelengths of GNSS signals are of order 20 cm and our primary focus is to track debris smaller than this, thereby maintaining phase stability of the scattered signals, enabling very long coherent processing intervals. However, the signals scattered by debris will be very weak at a terrestrial receiver, requiring the computationally expensive integration of a large number of signals, over an extended duration and with a large phased array. Detection of such weak signals in the presence of relatively strong direct-arrival signals requires extremely high cross-correlation protection. We show that sufficient cross-correlation protection can be obtained due to the large and varying Doppler shift, and also illustrate a novel processing approach utilizing downshifting of the collected signal to audio frequency. This technique dramatically reduces the cost and complexity of updating debris trajectories. The processing cost of preserving an uncertainty volume of many hundreds of meters around the predicted debris track is very modest, and searching within that uncertainty volume is undertaken at audio sampling rates. Moreover, we explore techniques that further lower the already modest cost of the non-linear search within the preserved uncertainty volume. We conclude with an outline of a system using these techniques that could provide centimetre level tracking of large quantities of small orbital objects at a modest cost.

  20. Fifteen Years of Synthetic Aperture Radar Calibration Using Trihedral Reflectors at the Alaska Satellite Facility

    Science.gov (United States)

    Albright, W.; Atwood, D.; Lawlor, O. S.; Utley, P.; Slater, C.

    2006-12-01

    For the past 15 years, the Alaska Satellite Facility (ASF) has provided calibration support for singly polarized SAR datasets in C-band (ERS-1, ERS-2, and RADARSAT-1 and L-Band (JERS-1. Passive point targets like trihedral corner reflectors offer a reliable and well established means to perform radiometric, geometric, and impulse response measurements for SAR calibration. Routine support of an array of corner reflectors in interior Alaska has permitted ASF an opportunity to monitor satellite health, calibrate SAR processors, and experiment with new reflector designs. Corner reflectors offer the advantages of low maintenance and low cost compared to active devices such as transponders. In order to maintain radar cross section, as the microwave wavelength get longer, so too does the size of the reflector. Increased size means decreased portability, exacerbating the difficulty of providing calibration support in remote locations. In response, ASF is developing low cost, light weight corner reflectors that can be deployed with minimal effort and no maintenance. These efforts will help to extend our present calibration efforts to more remote locations. But more importantly, these designs are expected to play an important role in Permanent Scatterer InSAR (PS-InSAR) methodology. The use of corner reflector arrays in support PS-InSAR may provide new means for monitoring terrain displacements in regions of heavy vegetation. This paper presents some long term measurements from ASF's array of corner reflectors, outlines improvements performed on trihedral corner reflectors, and describes current efforts at ASF to support the next generation of SAR missions and techniques.

  1. Forecast of wheat yield throughout the agricultural season using optical and radar satellite images

    Science.gov (United States)

    Fieuzal, R.; Baup, F.

    2017-07-01

    The aim of this study is to estimate the capabilities of forecasting the yield of wheat using an artificial neural network combined with multi-temporal satellite data acquired at high spatial resolution throughout the agricultural season in the optical and/or microwave domains. Reflectance (acquired by Formosat-2, and Spot 4-5 in the green, red, and near infrared wavelength) and multi-configuration backscattering coefficients (acquired by TerraSAR-X and Radarsat-2 in the X- and C-bands, at co- (abbreviated HH and VV) and cross-polarization states (abbreviated HV and VH)) constitute the input variable of the artificial neural networks, which are trained and validated on the successively acquired images, providing yield forecast in near real-time conditions. The study is based on data collected over 32 fields of wheat distributed over a study area located in southwestern France, near Toulouse. Among the tested sensor configurations, several satellite data appear useful for the yield forecasting throughout the agricultural season (showing coefficient of determination (R2) larger than 0.60 and a root mean square error (RMSE) lower than 9.1 quintals by hectare (q ha-1)): CVH, CHV, or the combined used of XHH and CHH, CHH and CHV, or green reflectance and CHH. Nevertheless, the best accurate forecast (R2 = 0.76 and RMSE = 7.0 q ha-1) is obtained longtime before the harvest (on day 98, during the elongation of stems) using the combination of co- and cross-polarized backscattering coefficients acquired in the C-band (CVV and CVH). These results highlight the high interest of using synthetic aperture radar (SAR) data instead of optical ones to early forecast the yield before the harvest of wheat.

  2. 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

  3. Interpretation of Radar Data from the Icy Galilean Satellites and Triton

    Science.gov (United States)

    Gurrola, Eric Michael

    1995-01-01

    We extend Eshleman's (Science 234, 1986, 587-590) analysis of an icy buried crater model and show that it can explain anomalous 3.5 and 13 cm-lambda radar echoes from the icy Galilean satellites- -radar albedos sigma~ 0.7 -2.6, circular and linear polarization ratios mu C~1.5 and mu L~0.5, and Doppler spectra with cosmTheta scattering law exponents m~1 -2. The model hypothesizes that radio waves are totally internally reflected N times from the walls of buried craters --tens of meters in radii with a water-ice overburden of permittivity varepsilon_1~3.2 varepsilon_0 that is larger than the permittivity varepsilon_2 of the material (probably porous ice) below the crater walls--and are brought to a focus, appearing to come from annular "glory halos" inside the craters, which break up into several coherent glints, each of azimuthal extent H, filling the halo to fraction F. We use geometrical and wave optics to include effects not accounted for by Eshleman, including: the ice overburden, arbitrary crater position, and crater shadowing. The values N = 3 and varepsilon_2/varepsilon _1 = 0.63 give mu_ {C} = 1.6, muL = 0.4, m = 1.9, and spectra that agree well with the general trends in the observations. With FH/ lambda = 10, the areal densities of buried craters on the three satellites required to fit the observed radar albedos are, 0.38, 0.21, and 0.10 for Europa, Ganymede, and Callisto. We determine that Triton's N_2 atmosphere's surface pressure is 1.4 +/- 0.1 Pa and "equivalent isothermal temperature" is 42 +/- 4 K using least squares inversion of the 3.6 and 13 cm-lambda Voyager 2 radio occultation phase data with an exponential model of the atmospheric contribution to the phase (1.7 rad at 3.6 cm-lambda in lower 60 km) and a polynomial model of the nonlinear phase drift (1 rad per 100 km altitude) of the Voyager ultrastable oscillator (USO). Assuming vapor pressure equilibrium between the N_2 gas and ice, the surface temperature is 37.5 +/- 0.5 K, which, together

  4. The 2015 Gorkha earthquake investigated from radar satellites: Slip and stress modeling along the MHT

    Directory of Open Access Journals (Sweden)

    Faqi eDiao

    2015-10-01

    Full Text Available The active collision at the Himalayas combines crustal shortening and thickening, associated with the development of hazardous seismogenic faults. The 2015 Kathmandu earthquake largely affected Kathmandu city and partially ruptured a previously identified seismic gap. With a magnitude of Mw 7.8 as determined by the GEOFON seismic network, the 25 April 2015 earthquake displays uplift of the Kathmandu basin constrained by interferometrically processed ALOS-2, RADARSAT-2 and Sentinel-1 satellite radar data. An area of about 7,000 km² in the basin showed ground uplift locally exceeding 2 m, and a similarly large area (approx. 9000 km2 showed subsidence in the north, both of which could be simulated with a fault that is localized beneath the Kathmandu basin at a shallow depth of 5-15 km. Coulomb stress calculations reveal that the same fault adjacent to the Kathmandu basin experienced stress increase, similar as at sub-parallel faults of the thin skinned nappes, exactly at the location where the largest aftershock occurred (Mw 7.3 on 12. May, 2015. Therefore this study provides insights into the shortening and uplift tectonics of the Himalayas and shows the stress redistribution associated with the earthquake.

  5. The 2015 Gorkha earthquake investigated from radar satellites: slip and stress modeling along the MHT

    Science.gov (United States)

    Diao, Faqi; Walter, Thomas R.; Motagh, Mahdi; Prats, Pau; Wang, Rongjiang; Samsonov, Sergey

    2016-04-01

    The active collision at the Himalayas combines crustal shortening and thickening, associated with the development of hazardous seismogenic faults. The 2015 Gorkha earthquake largely affected Kathmandu city and partially ruptured a previously identified seismic gap. With a magnitude of Mw 7.8 as determined by the GEOFON seismic network, the 25 April 2015 earthquake displays uplift of the Kathmandu basin constrained by interferometrically processed ALOS-2, RADARSAT-2, and Sentinel-1 satellite radar data. An area of about 7000 km2 in the basin showed ground uplift locally exceeding 2 m, and a similarly large area (~9000 km2) showed subsidence in the north, both of which could be simulated with a fault that is localized beneath the Kathmandu basin at a shallow depth of 5-15 km. Coulomb stress calculations reveal that those areas that are laterally extending the active fault zone experienced stress increase, exactly at the location where the largest aftershock occurred (Mw 7.3 on 12. May, 2015). The subparallel faults of the thin-skinned system, in turn, experienced clear stress decrease at locations above (or below) the active fault. Therefore, this study provides insights into the shortening and uplift tectonics of the Himalayas and shows the stress redistribution associated with the earthquake.

  6. Steady state deformation of the Coso Range, east central California, inferred from satellite radar interferometry

    Science.gov (United States)

    Wicks, C.W.; Thatcher, W.; Monastero, F.C.; Hasting, M.A.

    2001-01-01

    Observations of deformation from 1992 to 1997 in the southern Coso Range using satellite radar interferometry show deformation rates of up to 35 mm yr-1 in an area ???10 km by 15 km. The deformation is most likely the result of subsidence in an area around the Coso geothermal field. The deformation signal has a short-wavelength component, related to production in the field, and a long-wavelength component, deforming at a constant rate, that may represent a source of deformation deeper than the geothermal reservoir. We have modeled the long-wavelength component of deformation and inferred a deformation source at ???4 km depth. The source depth is near the brittle-ductile transition depth (inferred from seismicity) and ???1.5 km above the top of the rhyolite magma body that was a source for the most recent volcanic eruption in the Coso volcanic field [Manley and Bacon, 2000]. From this evidence and results of other studies in the Coso Range, we interpret the source to be a leaking deep reservoir of magmatic fluids derived from a crystallizing rhyolite magma body.

  7. Characterization of Terrestrial Water Dynamics in the Congo Basin Using GRACE and Satellite Radar Altimetry

    Science.gov (United States)

    Lee, Lyongki; Beighley, R. Edward; Alsdorf, Douglas; Jung, Hahn Chul; Shum, C. K.; Duan, Jianbin; Guo, Junyi; Yamazaki, Dai; Andreadis, Konstantinos

    2011-01-01

    The Congo Basin is the world's third largest in size (approximately 3.7 million km^2), and second only to the Amazon River in discharge (approximately 40,200 cms annual average). However, the hydrological dynamics of seasonally flooded wetlands and floodplains remains poorly quantified. Here, we separate the Congo wetland into four 3 degree x 3 degree regions, and use remote sensing measurements (i.e., GRACE, satellite radar altimeter, GPCP, JERS-1, SRTM, and MODIS) to estimate the amounts of water filling and draining from the Congo wetland, and to determine the source of the water. We find that the amount of water annually filling and draining the Congo wetlands is 111 km^3, which is about one-third the size of the water volumes found on the mainstem Amazon floodplain. Based on amplitude comparisons among the water volume changes and timing comparisons among their fluxes, we conclude that the local upland runoff is the main source of the Congo wetland water, not the fluvial process of river-floodplain water exchange as in the Amazon. Our hydraulic analysis using altimeter measurements also supports our conclusion by demonstrating that water surface elevations in the wetlands are consistently higher than the adjacent river water levels. Our research also highlights differences in the hydrology and hydrodynamics between the Congo wetland and the mainstem Amazon floodplain.

  8. River monitoring from satellite radar altimetry in the Zambezi River Basin

    Directory of Open Access Journals (Sweden)

    C. I. Michailovsky

    2012-03-01

    Full Text Available Satellite radar altimetry can be used to monitor surface water levels from space. While current and past altimetry missions were designed to study oceans, retracking the waveforms returned over land allows data to be retrieved for smaller water bodies or narrow rivers. In this study, retracked Envisat altimetry data was extracted over the Zambezi River Basin using a detailed river mask based on Landsat imagery. This allowed for stage measurements to be obtained for rivers down to 80 m wide with an RMSE relative to in situ levels of 0.32 to 0.72 m at different locations. The altimetric levels were then converted to discharge using three different methods adapted to different data-availability scenarios: first with an in situ rating curve available, secondly with one simultaneous field measurement of cross-section and discharge, and finally with only historical discharge data available. For the two locations at which all three methods could be applied the accuracies of the different methods were found to be comparable, with RMSE values ranging from 5.5 to 7.4 % terms of high flow estimation relative to in situ gauge measurements. The precision obtained with the different methods was analyzed by running Monte Carlo simulations and also showed comparable values for the three approaches with standard deviations found between 8.2 and 25.8 % of the high flow estimates.

  9. Capturing the fingerprint of Etna volcano activity in gravity and satellite radar data

    Science.gov (United States)

    Negro, Ciro Del; Currenti, Gilda; Solaro, Giuseppe; Greco, Filippo; Pepe, Antonio; Napoli, Rosalba; Pepe, Susi; Casu, Francesco; Sansosti, Eugenio

    2013-01-01

    Long-term and high temporal resolution gravity and deformation data move us toward a better understanding of the behavior of Mt Etna during the June 1995 – December 2011 period in which the volcano exhibited magma charging phases, flank eruptions and summit crater activity. Monthly repeated gravity measurements were coupled with deformation time series using the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique on two sequences of interferograms from ERS/ENVISAT and COSMO-SkyMed satellites. Combining spatiotemporal gravity and DInSAR observations provides the signature of three underlying processes at Etna: (i) magma accumulation in intermediate storage zones, (ii) magmatic intrusions at shallow depth in the South Rift area, and (iii) the seaward sliding of the volcano's eastern flank. Here we demonstrate the strength of the complementary gravity and DInSAR analysis in discerning among different processes and, thus, in detecting deep magma uprising in months to years before the onset of a new Etna eruption. PMID:24169569

  10. Measurement of interseismic strain accumulation across the North Anatolian Fault by satellite radar interferometry

    Science.gov (United States)

    Wright, Tim; Parsons, Barry; Fielding, Eric

    In recent years, interseismic crustal velocities and strains have been determined for a number of tectonically active areas through repeated measurements using the Global Positioning System. The terrain in such areas is often remote and difficult, and the density of GPS measurements relatively sparse. In principle, satellite radar interferometry can be used to make millimetric-precision measurements of surface displacement over large surface areas. In practice, the small crustal deformation signal is dominated over short time intervals by errors due to atmospheric, topographic and orbital effects. Here we show that these effects can be over-come by stacking multiple interferograms, after screening for atmospheric anomalies, effectively creating a new interferogram that covers a longer time interval. In this way, we have isolated a 70 km wide region of crustal deformation across the eastern end of the North Anatolian Fault, Turkey. The distribution of deformation is consistent with slip of 17-32 mm/yr below 5-33 km on the extension of the surface fault at depth. If the GPS determined slip rate of 24±1 mm/yr is accepted, the locking depth is constrained to 18±6 km.

  11. Validation of GPM Ka-Radar Algorithm Using a Ground-based Ka-Radar System

    Science.gov (United States)

    Nakamura, Kenji; Kaneko, Yuki; Nakagawa, Katsuhiro; Furukawa, Kinji; Suzuki, Kenji

    2016-04-01

    GPM led by the Japan Aerospace Exploration Agency (JAXA) and the National Aeronautics and Space Administration of US (NASA) aims to observe global precipitation. The core satellite is equipped with a microwave radiometer (GMI) and a dual-frequency radar (DPR) which is the first spaceborne Ku/Ka-band dual-wavelength radar dedicated for precipitation measurement. In the DPR algorithm, measured radar reflectivity is converted to effective radar reflectivity by estimating the rain attenuation. Here, the scattering/attenuation characteristics of Ka-band radiowaves are crucial, particularly for wet snow. A melting layer observation using a dual Ka-band radar system developed by JAXA was conducted along the slope of Mt. Zao in Yamagata Prefecture, Japan. The dual Ka-band radar system consists of two nearly identical Ka-band FM-CW radars, and the precipitation systems between two radars were observed in opposite directions. From this experiment, equivalent radar reflectivity (Ze) and specific attenuation (k) were obtained. The experiments were conducted for two winter seasons. During the data analyses, it was found that k estimate easily fluctuates because the estimate is based on double difference calculation. With much temporal and spatial averaging, k-Ze relationship was obtained for melting layers. One of the results is that the height of the peak of k seems slightly higher than that of Ze. The results are compared with in-situ precipitation particle measurements.

  12. Capabilities and uncertainties of aircraft measurements for the validation of satellite precipitation products – a virtual case study

    Directory of Open Access Journals (Sweden)

    Andrea Lammert

    2015-08-01

    Full Text Available Remote sensing sensors on board of research aircraft provide detailed measurements of clouds and precipitation which can be used as reference data to validate satellite products. Such satellite derived precipitation data using passive microwave radiometers with a resolution of typically 50×50km2$50\\times50\\,\\text{km}^2$ stands against high spatial and temporal resolved airborne measurements, but only along a chosen line. This paper focuses on analysis on the uncertainty arising from the different spatial resolution and coverage. Therefore we use a perfect model approach, with a high resolved forecast model yielding perfect virtual aircraft and satellite observations. The mean precipitation and standard deviation per satellite box were estimated with a Gaussian approach. The comparison of the mean values shows a high correlation of 0.92, but a very wide spread. As criterion to define good agreement between satellite mean and reference, we choose a deviation of one standard deviation of the virtual aircraft as threshold. Considering flight tracks in the range of 50 km (one overflight, the perfect agreement of satellite and aircraft observations is only detected in 65 % of the cases. To increase this low reliability the precipitation distributions of the virtual aircraft were fitted by a gamma density function. Using the same quality criterion, the usage of gamma density fit yields an improvement of the Aircraft reliability up to 80 %.

  13. Forecasting Lake-Effect Precipitation in the Great Lakes Region Using NASA Enhanced-Satellite Data

    Science.gov (United States)

    Cipullo, Michelle; Molthan, Andrew; Shafer, Jackie; Case, Jonathan; Jedlovec, Gary

    2011-01-01

    Lake-effect precipitation is common in the Great Lakes region, particularly during the late fall and winter. The synoptic processes of lake-effect precipitation are well understood by operational forecasters, but individual forecast events still present a challenge. Locally run, high resolution models can assist the forecaster in identifying the onset and duration of precipitation, but model results are sensitive to initial conditions, particularly the assumed surface temperature of the Great Lakes. The NASA Short-term Prediction Research and Transition (SPoRT) Center has created a Great Lakes Surface Temperature (GLST) composite, which uses infrared estimates of water temperatures obtained from the MODIS instrument aboard the Aqua and Terra satellites, other coarser resolution infrared data when MODIS is not available, and ice cover maps produced by the NOAA Great Lakes Environmental Research Lab (GLERL). This product has been implemented into the Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS), used within forecast offices to run local, high resolution forecasts. The sensitivity of the model forecast to the GLST product was analyzed with a case study of the Lake Effect Storm Echinacea, which produced 10 to 12 inches of snowfall downwind of Lake Erie, and 8 to 18 inches downwind of Lake Ontario from 27-29 January 2010. This research compares a forecast using the default Great Lakes surface temperatures from the Real Time Global sea surface temperature (RTG SST), in the WRF-EMS model to the enhanced NASA SPoRT GLST product to study forecast impacts. Results from this case study show that the SPoRT GLST contained less ice cover over Lake Erie and generally cooler water temperatures over Lakes Erie and Ontario. Latent and sensible heat fluxes over Lake Ontario were decreased in the GLST product. The GLST product decreased the quantitative precipitation forecast (QPF), which can be correlated to the decrease in temperatures and heat

  14. A Wide-band, Ka-band Amplifier and Radar System for Precipitation Retrievals Project

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA is committed to measuring precipitation on a global scale. In 1997, NASA launched the Tropical Rain Measuring Mission which carried the first spaceborne...

  15. A Novel Low-Cost Dual-Wavelength Precipitation Radar Sensor Network Project

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA is committed to measuring precipitation on a global scale. In 1997, NASA launched the Tropical Rain Measuring Mission which carried the first spaceborne...

  16. Precipitating Snow Retrievals from Combined Airborne Cloud Radar and Millimeter-Wave Radiometer Observations

    Science.gov (United States)

    Grecu, Mircea; Olson, William S.

    2008-01-01

    An algorithm for retrieving snow over oceans from combined cloud radar and millimeter-wave radiometer observations is developed. The algorithm involves the use of physical models to simulate cloud radar and millimeter-wave radiometer observations from basic atmospheric variables such as hydrometeor content, temperature, and relative humidity profiles and is based on an optimal estimation technique to retrieve these variables from actual observations. A high-resolution simulation of a lake-effect snowstorm by a cloud-resolving model is used to test the algorithm. That is, synthetic observations are generated from the output of the cloud numerical model, and the retrieval algorithm is applied to the synthetic data. The algorithm performance is assessed by comparing the retrievals with the reference variables used in synthesizing the observations. The synthetic observation experiment indicates good performance of the retrieval algorithm. The algorithm is also applied to real observations from the Wakasa Bay field experiment that took place over the Sea of Japan in January and February 2003. The application of the retrieval algorithm to data from the field experiment yields snow estimates that are consistent with both the cloud radar and radiometer observations.

  17. A Precipitation Satellite Downscaling & Re-Calibration Routine for TRMM 3B42 and GPM Data Applied to the Tropical Andes

    Science.gov (United States)

    Manz, B.; Buytaert, W.; Tobón, C.; Villacis, M.; García, F.

    2014-12-01

    With the imminent release of GPM it is essential for the hydrological user community to improve the spatial resolution of satellite precipitation products (SPPs), also retrospectively of historical time-series. Despite the growing number of applications, to date SPPs have two major weaknesses. Firstly, geosynchronous infrared (IR) SPPs, relying exclusively on cloud elevation/ IR temperature, fail to replicate ground rainfall rates especially for convective rainfall. Secondly, composite SPPs like TRMM include microwave and active radar to overcome this, but the coarse spatial resolution (0.25°) from infrequent orbital sampling often fails to: a) characterize precipitation patterns (especially extremes) in complex topography regions, and b) allow for gauge comparisons with adequate spatial support. This is problematic for satellite-gauge merging and subsequent hydrological modelling applications. We therefore present a new re-calibration and downscaling routine that is applicable to 0.25°/ 3-hrly TRMM 3B42 and Level 3 GPM time-series to generate 1 km estimates. 16 years of instantaneous TRMM radar (TPR) images were evaluated against a unique dataset of over 100 10-min rain gauges from the tropical Andes (Colombia & Ecuador) to develop a spatially distributed error surface. Long-term statistics on occurrence frequency, convective/ stratiform fraction and extreme precipitation probability (Gamma & Generalized Pareto distributions) were computed from TPR at the 1 km scale as well as from TPR and 3B42 at the 0.25° scale. To downscale from 0.25° to 1 km a stochastic generator was used to restrict precipitation occurrence to a fraction of the 1 km pixels within the 0.25° gridcell at every time-step. Regression modelling established a relationship between probability distributions at the 0.25° scale and rainfall amounts were assigned to the retained 1 km pixels by quantile-matching to the gridcell. The approach inherently provides mass conservation of the downscaled

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

    Science.gov (United States)

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

    2016-10-01

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

  19. 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

  20. Assessment of GPM and TRMM Multi-Satellite Precipitation Products in Streamflow Simulations in a Data-Sparse Mountainous Watershed in Myanmar

    National Research Council Canada - National Science Library

    Fei Yuan; Limin Zhang; Khin Wah Wah Win; Liliang Ren; Chongxu Zhao; Yonghua Zhu; Shanhu Jiang; Yi Liu

    2017-01-01

    ...) final run and the TRMM Multi-satellite Precipitation Analysis 3B42V7 precipitation products, and their feasibility in streamflow simulations in the Chindwin River basin, Myanmar, from April 2014...

  1. A study of cloud microphysics and precipitation over the Tibetan Plateau by radar observations and cloud-resolving model simulations: Cloud Microphysics over Tibetan Plateau

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Wenhua [State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing China; Pacific Northwest National Laboratory, Richland Washington USA; Sui, Chung-Hsiung [Department of Atmospheric Sciences, National Taiwan University, Taipei Taiwan; Fan, Jiwen [Pacific Northwest National Laboratory, Richland Washington USA; Hu, Zhiqun [State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing China; Zhong, Lingzhi [State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing China

    2016-11-27

    Cloud microphysical properties and precipitation over the Tibetan Plateau (TP) are unique because of the high terrains, clean atmosphere, and sufficient water vapor. With dual-polarization precipitation radar and cloud radar measurements during the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III), the simulated microphysics and precipitation by the Weather Research and Forecasting model (WRF) with the Chinese Academy of Meteorological Sciences (CAMS) microphysics and other microphysical schemes are investigated through a typical plateau rainfall event on 22 July 2014. Results show that the WRF-CAMS simulation reasonably reproduces the spatial distribution of 24-h accumulated precipitation, but has limitations in simulating time evolution of precipitation rates. The model-calculated polarimetric radar variables have biases as well, suggesting bias in modeled hydrometeor types. The raindrop sizes in convective region are larger than those in stratiform region indicated by the small intercept of raindrop size distribution in the former. The sensitivity experiments show that precipitation processes are sensitive to the changes of warm rain processes in condensation and nucleated droplet size (but less sensitive to evaporation process). Increasing droplet condensation produces the best area-averaged rain rate during weak convection period compared with the observation, suggesting a considerable bias in thermodynamics in the baseline simulation. Increasing the initial cloud droplet size causes the rain rate reduced by half, an opposite effect to that of increasing droplet condensation.

  2. Combined High Spectral Resolution Lidar and Millimeter Wavelength Radar Measurement of Ice Crystal Precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Eloranta, Edwin [Univ. of Wisconsin, Madison, WI (United States)

    2016-10-28

    The goal of this research has been to improve measurements of snowfall using a combination of millimeter-wavelength radar and High Spectral Resolution Lidar (HSRL) Observations. Snowflakes are large compared to the 532nm HSRL wavelength and small compared to the 3.2 and 8.6 mm wavelength radars used in this study. This places the particles in the optical scattering regime of the HSRL, where extinction cross-section is proportional to the projected area of the particles, and in the Rayleigh regime for the radar, where the backscatter cross-section is proportional to the mass-squared of the particles. Forming a ratio of the radar measured cross-section to the HSRL measured cross section eliminates any dependence on the number of scattering particles, yielding a quantity proportional to the average mass-squared of the snowflakes over the average area of the flakes. Using simultaneous radar measurements of particle fall velocities, which are dependent particle mass and cross-sectional area it is possible to derive the average mass of the snow flakes, and with the radar measured fall velocities compute the snowfall rate. Since this retrieval requires the optical extinction cross-section we began by considering errors this quantity. The HSRL is particularly good at measuring the backscatter cross-section. In previous studies of snowfall in the high Arctic were able to estimate the extinction cross-section directly as a fixed ratio to the backscatter cross-section. Measurements acquired in the STORMVEX experiment in Colorado showed that this approach was not valid in mid-latitude snowfalls and that direct measurement of the extinction cross-section is required. Attempts to measure the extinction directly uncovered shortcomings in thermal regulation and mechanical stability of the newly deployed DOE HSRL systems. These problems were largely mitigated by modifications installed in both of the DOE systems. We also investigated other sources of error in the HSRL direct

  3. Quantitative measurement of precipitation using radar in comparison with ground-level measurements, taking orographic influences into account; Quantitative Niederschlagsmessung mit Radar im Vergleich mit Bodenmessungen in orographisch gegliedertem Gelaende

    Energy Technology Data Exchange (ETDEWEB)

    Gysi, H. [Radar-Info, Karlsruhe (Germany)

    1998-01-01

    The methods of correction applied to the determination of the spatial distribution of precipitation on the basis of the volumes established by the Karlsruhe C-band precipitation radar distinctly enhance the quality of statements regarding precipitation intensities and their time integration both in summer and winter. (orig./KW) [Deutsch] Die fuer die Bestimmung der raeumlichen Niederschlagsverteilung aus Volumendaten des Karlsruher C-Band Niederschlagradars angewandten Korrekturverfahren verbessern sowohl im Sommer als auch im Winter deutlich die Qualitaet und quantitative Aussagekraft der dargestellten Niederschlagsintensitaeten und deren zeitlichen Integrationen. (orig./KW)

  4. The Contribution Of Sampling Errors In Satellite Precipitation Estimates To High Flood Uncertainty In Subtropical South America

    Science.gov (United States)

    Demaria, E. M.; Valdes, J. B.; Nijssen, B.; Rodriguez, D.; Su, F.

    2009-12-01

    Satellite precipitation estimates are becoming increasingly available at temporal and spatial scales of interest for hydrological applications. Unfortunately precipitation estimated from global satellites is prone to errors hailing from different sources. The impact of sampling errors on the hydrological cycle of a large-size basin was assessed with a macroscale hydrological model. Synthetic precipitation fields were generated in a Monte Carlo fashion by perturbing observed precipitation fields with sampling errors. Three sampling intervals were chosen to generate the precipitation fields: one-hour, three-hours which is the canonical Global Precipitation Mission (GPM) sampling interval, and six-hours. The Variable Infiltration Capacity (VIC) model was used to assess the impact of sampling errors on hydrological fluxes and states in the Iguazu basin in South America for the period 1982-2005. The propagation of sampling errors through the hydrological cycle was evaluated for high flow events that have the 2% chance of being exceeded in any given time. Results show that observed event volumes are underestimated for small volumes for the three and six-hours sampling intervals but for the one-hour sampling interval the difference is almost negligible.The timing of the hydrograph is not affected by uncertainty existent in satellite-derived precipitation when it propagates through the hydrological cycle. Results of two non-parametric tests: the Kruskal-Wallis test on the mean ranks of the population and the Ansari-Bradley test on the equality of the variances indicate that sampling errors do no affect the occurrence of high flows since their probability distribution is not affected. The applicability of these results is limited to a humid climate. However the Iguazu basin is representative of several basins located in subtropical regions around the world, many of which are under-instrumented catchments, where satellite precipitation might be one of the few available data

  5. A Cloud and Precipitation Radar System Concept for the ACE Mission

    Science.gov (United States)

    Durden, S. L.; Tanelli, S.; Epp, L.; Jamnejad, V.; Perez, R.; Prata, A.; Samoska, L.; Long, E; Fang, H.; Esteban-Fernandez, D.; Lee, C.

    2011-01-01

    One of the instruments recommended for deployment on the Aerosol/Cloud/Ecosystems (ACE) mission is a new advanced cloud profiling radar. In this paper, we describe such a radar design, called ACERAD, which has 35- and 94-GHz channels, each having Doppler and dual-polarization capabilities. ACERAD will scan at Ka-band and will be nadir-looking at W-band. To get a swath of 25-30 km, considered the minimum useful for Ka-band, ACERAD needs to scan at least 2 degrees off nadir; this is at least 20 beamwidths, which is quite large for a typical parabolic reflector. This problem is being solved with a Dragonian design; a scaled prototype of the antenna is being fabricated and will be tested on an antenna range. ACERAD also uses a quasi-optical transmission line at W-band to connect the transmitter to the antenna and antenna to the receiver. A design for this has been completed and is being laboratory tested. This paper describes the current ACERAD design and status.

  6. Routine Ocean Monitoring With Synthetic Aperture Radar Imagery Obtained From the Alaska Satellite Facility

    Science.gov (United States)

    Pichel, W. G.; Clemente-Colon, P.; Li, X.; Friedman, K.; Monaldo, F.; Thompson, D.; Wackerman, C.; Scott, C.; Jackson, C.; Beal, R.; McGuire, J.; Nicoll, J.

    2006-12-01

    The Alaska Satellite Facility (ASF) has been processing synthetic aperture radar (SAR) data for research and for near-real-time applications demonstrations since shortly after the launch of the European Space Agency's ERS-1 satellite in 1991. The long coastline of Alaska, the vast extent of ocean adjacent to Alaska, a scarcity of in-situ observations, and the persistence of cloud cover all contribute to the need for all-weather ocean observations in the Alaska region. Extensive experience with SAR product processing algorithms and SAR data analysis techniques, and a growing sophistication on the part of SAR data and product users have amply demonstrated the value of SAR instruments in providing this all-weather ocean observation capability. The National Oceanic and Atmospheric Administration (NOAA) has been conducting a near-real-time applications demonstration of SAR ocean and hydrologic products in Alaska since September 1999. This Alaska SAR Demonstration (AKDEMO) has shown the value of SAR-derived, high-resolution (sub kilometer) ocean surface winds to coastal weather forecasting and the understanding of coastal wind phenomena such as gap winds, barrier jets, vortex streets, and lee waves. Vessel positions and ice information derived from SAR imagery have been used for management of fisheries, protection of the fishing fleet, enforcement of fisheries regulations, and protection of endangered marine mammals. Other ocean measurements, with potentially valuable applications, include measurement of wave state (significant wave height, dominant wave direction and wavelength, and wave spectra), mapping of oil spills, and detection of shallow-water bathymetric features. In addition to the AKDEMO, ASF-processed SAR imagery is being used: (1) in the Gulf of Mexico for hurricane wind studies, and post-hurricane oil-spill and oil-platform analyses (the latter employing ship-detection algorithms for detection of changes in oil-platform locations); (2) in the North Pacific

  7. Gap Filling of the CALYPSO HF Radar Sea Surface Current Data through Past Measurements and Satellite Wind Observations

    Directory of Open Access Journals (Sweden)

    Adam Gauci

    2016-01-01

    Full Text Available High frequency (HF radar installations are becoming essential components of operational real-time marine monitoring systems. The underlying technology is being further enhanced to fully exploit the potential of mapping sea surface currents and wave fields over wide areas with high spatial and temporal resolution, even in adverse meteo-marine conditions. Data applications are opening to many different sectors, reaching out beyond research and monitoring, targeting downstream services in support to key national and regional stakeholders. In the CALYPSO project, the HF radar system composed of CODAR SeaSonde stations installed in the Malta Channel is specifically serving to assist in the response against marine oil spills and to support search and rescue at sea. One key drawback concerns the sporadic inconsistency in the spatial coverage of radar data which is dictated by the sea state as well as by interference from unknown sources that may be competing with transmissions in the same frequency band. This work investigates the use of Machine Learning techniques to fill in missing data in a high resolution grid. Past radar data and wind vectors obtained from satellites are used to predict missing information and provide a more consistent dataset.

  8. The impact of assimilating radar-estimated rain rates on simulation of precipitation in the 17-18 July 1996 Chicago floods

    Science.gov (United States)

    Wang, Xingbao; Yau, M. K.; Nagarajan, B.; Fillion, Luc

    2010-03-01

    Rainfall prediction remains one of the most challenging problems in weather forecasting. In order to improve high-resolution quantitative precipitation forecasts (QPF), a new procedure for assimilating rainfall rate derived from radar composite reflectivity has been proposed and tested in a numerical simulation of the Chicago floods of 17-18 July 1996. The methodology is based on the one-dimensional variation scheme (1DVAR) assimilation approach introduced by Fillion and Errico but applied here using the Kain-Fritsch convective parameterization scheme (KF CPS). The novel feature of this work is the continuous assimilation of radar estimated rain rate over a three hour period, rather than a single assimilation at the initial (analysis) time. Most of the characteristics of this precipitation event, including the propagation, regeneration of mesoscale convective systems, the frontal boundary across the Midwest and the evolution of the low-level jet are better captured in the simulation as the radar-estimated precipitation rate is assimilated. The results indicate that precipitation assimilation during the early stage can improve the simulated mesoscale feature of the convection system and shorten the spin-up time significantly. Comparison of precipitation forecasts between the experiments with and without the 1DVAR indicates that the 1DVAR scheme has a positive impact on the QPF up to 36 hours in terms of the bias and bias equalized threat scores.

  9. Evaluation of the latest satellite-gauge precipitation products and their hydrologic applications over the Huaihe River basin

    Science.gov (United States)

    Sun, Ruochen; Yuan, Huiling; Liu, Xiaoli; Jiang, Xiaoman

    2016-05-01

    Satellite-gauge quantitative precipitation estimate (QPE) products may reduce the errors in near real-time satellite precipitation estimates by combining rain gauge data, which provides great potential to hydrometeorological applications. This study aims to comprehensively evaluate four of the latest satellite-gauge QPEs, including NASA's Tropical Rainfall Measuring Mission (TRMM) 3B42V7 product, NOAA's Climate Prediction Center (CPC) MORPHing technique (CMORPH) bias-corrected product (CMORPH CRT), CMORPH satellite-gauge merged product (CMORPH BLD) and CMORPH satellite-gauge merged product developed at the National Meteorological Information Center (NMIC) of the China Meteorological Administration (CMA) (CMORPH CMA). These four satellite-gauge QPEs are statistically evaluated over the Huaihe River basin during 2003-2012 and applied into the distributed Variable Infiltration Capacity (VIC) model to assess hydrologic utilities. Compared to the China Gauge-based Daily Precipitation Analysis (CGDPA) newly developed at CMA/NMIC, the four satellite-gauge QPEs generally depict the spatial distribution well, with the underestimation in the southern mountains and overestimation in the northern plain of the Huaihe River basin. Specifically, both TRMM and CMORPH CRT adopt simple gauge adjustment algorithms and exhibit relatively poor performance, with evidently deteriorated quality in winter. In contrast, the probability density function-optimal interpolation (PDF-OI) gauge adjustment procedure has been applied in CMORPH BLD and CMORPH CMA, resulting in higher quality and more stable performance. CMORPH CMA further benefits from a merged dense gauge observation network and outperforms the other QPEs with significant improvements in rainfall amount and spatial/temporal distributions. Due to the insufficient gauge observations in the merging process, CMORPH BLD features the similar error characteristics of CMORPH CRT with a positive bias of light precipitation and a negative

  10. Comparison and evaluation of satellite- and reanalysis-based precipitation products for water resources management in the Brahmaputra River basin

    Science.gov (United States)

    Saleh Khan, Abu; Sohel Masud, Md.; Abdulla Hel Kafi, Md.; Sultana, Tashrifa; Lopez Lopez, Patricia

    2017-04-01

    The Brahmaputra River, with a transboundary basin area of approx. 554,500 km2, has its origin on the northern slope of the Himalayas in China, from where it flows through India, Bhutan and finally Bangladesh. Brahmaputra basin's climatology is heavily conditioned by precipitation during the monsoon months, concentrating about the 85 % of the rainfall in this period and originating severe and frequent floods that impact specially the Bangladeshi population in the delta region. Recent campaigns to increase the quality and to share ground-based hydro-meteorological data, in particular precipitation, within the basin have provided limited results. Global rainfall data from satellite and reanalysis may improve the temporal and spatial availability of in-situ observations for advanced water resources management. This study aims to evaluate the applicability of several global precipitation products from satellite and reanalysis in comparison with in-situ data to quantify their added value for hydrological modeling at a basin and sub-basin scale for the Brahmaputra River. Precipitation products from CMORPH, TRMM-3B42, GsMAP, WFDEI, MSWEP and various combinations with ground-based data were evaluated at basin and sub-basin level at a daily and monthly temporal resolution. The Brahmaputra was delineated into 54 sub-basins for a more detailed evaluation of the precipitation products. The data were analysed and inter-compared for the time period from 2002 to 2010. Precipitation performance assessment was conducted including several indicators, such as probability of detection (POD), false alarm ratio (FAR), Pearson's correlation coefficient (r), bias and root mean square error (RMSE). Preliminary results indicate high correlation and low bias and RMSE values between WFDEI, TRMM-3B42 and CMORPH precipitation and in-situ observations at a monthly time scale. Lower correlations and higher bias and RMSE values were found between GsMAP and MSWEP and ground-observed precipitation

  11. Mediterranean hurricanes: large-scale environment and convective and precipitating areas from satellite microwave observations

    Directory of Open Access Journals (Sweden)

    C. Claud

    2010-10-01

    Full Text Available Subsynoptic scale vortices that have been likened to tropical cyclones or polar lows (medicanes are occasionally observed over the Mediterranean Sea. Generated over the sea, they are usually associated with strong winds and heavy precipitation and thus can be highly destructive in islands and costal areas. Only an accurate forecasting of such systems could mitigate these effects. However, at the moment, the predictability of these systems remains limited.

    Due to the scarcity of conventional observations, use is made of NOAA/MetOp satellite observations, for which advantage can be taken of the time coverage differences between the platforms that carry it, to give a very complete temporal description of the disturbances. A combination of AMSU-B (Advanced Microwave Sounding Unit-B/MHS (Microwave Humidity Sounder observations permit to investigate precipitation associated with these systems while coincident AMSU-A (Advanced Microwave Sounding Unit-A observations give insights into the larger synoptic-scale environment in which they occur.

    Three different cases (in terms of intensity, location, trajectory, duration, and periods of the year – May, September and December, respectively were investigated. Throughout these time periods, AMSU-A observations show that the persisting deep outflow of cold air over the sea together with an upper-level trough upstream constituted a favourable environment for the development of medicanes. AMSU-B/MHS based diagnostics show that convection and precipitation areas are large in the early stage of the low, but significantly reduced afterwards. Convection is maximum just after the upper-level trough, located upstream of cold mid-tropospheric air, reached its maximum intensity and acquired a cyclonic orientation.

  12. Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia

    Science.gov (United States)

    Tekeli, Ahmet Emre; Fouli, Hesham

    2016-10-01

    Floods are among the most common disasters harming humanity. In particular, flash floods cause hazards to life, property and any type of structures. Arid and semi-arid regions are equally prone to flash floods like regions with abundant rainfall. Despite rareness of intensive and frequent rainfall events over Kingdom of Saudi Arabia (KSA); an arid/semi-arid region, occasional flash floods occur and result in large amounts of damaging surface runoff. The flooding of 16 November, 2013 in Riyadh; the capital city of KSA, resulted in killing some people and led to much property damage. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) Real Time (RT) data (3B42RT) are used herein for flash flood forecasting. 3B42RT detected high-intensity rainfall events matching with the distribution of observed floods over KSA. A flood early warning system based on exceedance of threshold limits on 3B42RT data is proposed for Riyadh. Three different indexes: Constant Threshold (CT), Cumulative Distribution Functions (CDF) and Riyadh Flood Precipitation Index (RFPI) are developed using 14-year 3B42RT data from 2000 to 2013. RFPI and CDF with 90% captured the three major flooding events that occurred in February 2005, May 2010 and November 2013 in Riyadh. CT with 3 mm/h intensity indicated the 2013 flooding, but missed those of 2005 and 2010. The methodology implemented herein is a first-step simple and accurate way for flash flood forecasting over Riyadh. The simplicity of the methodology enables its applicability for the TRMM follow-on missions like Global Precipitation Measurement (GPM) mission.

  13. Validation of Satellite Precipitation (trmm 3B43) in Ecuadorian Coastal Plains, Andean Highlands and Amazonian Rainforest

    Science.gov (United States)

    Ballari, D.; Castro, E.; Campozano, L.

    2016-06-01

    Precipitation monitoring is of utmost importance for water resource management. However, in regions of complex terrain such as Ecuador, the high spatio-temporal precipitation variability and the scarcity of rain gauges, make difficult to obtain accurate estimations of precipitation. Remotely sensed estimated precipitation, such as the Multi-satellite Precipitation Analysis TRMM, can cope with this problem after a validation process, which must be representative in space and time. In this work we validate monthly estimates from TRMM 3B43 satellite precipitation (0.25° x 0.25° resolution), by using ground data from 14 rain gauges in Ecuador. The stations are located in the 3 most differentiated regions of the country: the Pacific coastal plains, the Andean highlands, and the Amazon rainforest. Time series, between 1998 - 2010, of imagery and rain gauges were compared using statistical error metrics such as bias, root mean square error, and Pearson correlation; and with detection indexes such as probability of detection, equitable threat score, false alarm rate and frequency bias index. The results showed that precipitation seasonality is well represented and TRMM 3B43 acceptably estimates the monthly precipitation in the three regions of the country. According to both, statistical error metrics and detection indexes, the coastal and Amazon regions are better estimated quantitatively than the Andean highlands. Additionally, it was found that there are better estimations for light precipitation rates. The present validation of TRMM 3B43 provides important results to support further studies on calibration and bias correction of precipitation in ungagged watershed basins.

  14. A strategy for merging objective estimates of global daily precipitation from gauge observations, satellite estimates, and numerical predictions

    Science.gov (United States)

    Nie, Suping; Wu, Tongwen; Luo, Yong; Deng, Xueliang; Shi, Xueli; Wang, Zaizhi; Liu, Xiangwen; Huang, Jianbin

    2016-07-01

    This paper describes a strategy for merging daily precipitation information from gauge observations, satellite estimates (SEs), and numerical predictions at the global scale. The strategy is designed to remove systemic bias and random error from each individual daily precipitation source to produce a better gridded global daily precipitation product through three steps. First, a cumulative distribution function matching procedure is performed to remove systemic bias over gauge-located land areas. Then, the overall biases in SEs and model predictions (MPs) over ocean areas are corrected using a rescaled strategy based on monthly precipitation. Third, an optimal interpolation (OI)-based merging scheme (referred as the HL-OI scheme) is used to combine unbiased gauge observations, SEs, and MPs to reduce random error from each source and to produce a gauge—satellite-model merged daily precipitation analysis, called BMEP-d (Beijing Climate Center Merged Estimation of Precipitation with daily resolution), with complete global coverage. The BMEP-d data from a four-year period (2011-14) demonstrate the ability of the merging strategy to provide global daily precipitation of substantially improved quality. Benefiting from the advantages of the HL-OI scheme for quantitative error estimates, the better source data can obtain more weights during the merging processes. The BMEP-d data exhibit higher consistency with satellite and gauge source data at middle and low latitudes, and with model source data at high latitudes. Overall, independent validations against GPCP-1DD (GPCP one-degree daily) show that the consistencies between BMEP-d and GPCP-1DD are higher than those of each source dataset in terms of spatial pattern, temporal variability, probability distribution, and statistical precipitation events.

  15. Evaluation of the Potential of NASA Multi-satellite Precipitation Analysis in Global Landslide Hazard Assessment

    Science.gov (United States)

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

    2007-01-01

    Landslides are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage every year. In the U.S. alone landslides occur in every state, causing an estimated $2 billion in damage and 25- 50 deaths each year. Annual average loss of life from landslide hazards in Japan is 170. The situation is much worse in developing countries and remote mountainous regions due to lack of financial resources and inadequate disaster management ability. Recently, a landslide buried an entire village on the Philippines Island of Leyte on Feb 17,2006, with at least 1800 reported deaths and only 3 houses left standing of the original 300. Intense storms with high-intensity , long-duration rainfall have great potential to trigger rapidly moving landslides, resulting in casualties and property damage across the world. In recent years, through the availability of remotely sensed datasets, it has become possible to conduct global-scale landslide hazard assessment. This paper evaluates the potential of the real-time NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA) system to advance our understanding of and predictive ability for rainfall-triggered landslides. Early results show that the landslide occurrences are closely associated with the spatial patterns and temporal distribution of rainfall characteristics. Particularly, the number of landslide occurrences and the relative importance of rainfall in triggering landslides rely on the influence of rainfall attributes [e.g. rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms). TMPA precipitation data are available in both real-time and post-real-time versions, which are useful to assess the location and timing of rainfall-triggered landslide hazards by monitoring landslide-prone areas while receiving heavy rainfall. For the purpose of identifying rainfall-triggered landslides, an empirical global rainfall intensity

  16. Simultaneous measurements from the Millstone Hill radar and the Active satellite during the SAID/SAR arc event of the March 1990 CEDAR storm

    Directory of Open Access Journals (Sweden)

    M. Förster

    Full Text Available During a nearby passage of the Active satellite above the Millstone Hill radar on 21 March 1990 at local sunset, the satellite and the radar performed simultaneous measurements of upper ionospheric parameters in nearly the same spatial volume. For this purpose the radar carried out a special azimuth-elevation scan to track the satellite. Direct comparisons of radar data and in situ satellite measurements have been carried out quite rarely. In this case, the coincidence of co-ordinated measurements and active ionospheric-magnetospheric processes during an extended storm recovery phase presents a unique occasion resulting in a very valuable data set. The measurements show generally good agreement both during quiet prestorm and storm conditions and the combination of radar and satellite observations gives a more comprehensive picture of the physical processes involved. We find a close relationship between the rapid westward ion drift peak at subauroral latitudes (SAID event and the occurrence of a stable auroral red (SAR arc observed after sunset by an all-sky imager and reported in an earlier study of this event. The SAID electric field is caused by the penetration of energetic ions with energies between about 1 keV and 100 keV into the outer plasmasphere to a latitude equatorward of the extent of the plasmasheet electrons. Charge separation results in the observed polarisation field and the SAID. Unusually high molecular ion densities measured by the satellite at altitudes of 700-870 km at subauroral and auroral latitudes point on strong upward-directed ion acceleration processes and an intense neutral gas upwelling. These structures are collocated with a narrow trough in electron density and an electron temperature peak as observed simultaneously by the radar and the satellite probes.

    Key words. Ionosphere (ionosphere-magnetosphere interactions; plasma temperature and density; Magnetospheric physics (plasmasphere.

  17. On the balance of precipitation and evaporation over global oceans in satellite based and reanalysis data sets

    Science.gov (United States)

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

    2009-04-01

    Over the global oceans, precipitation should be smaller than evaporation and the balance should be compensated by the global runoff from land surfaces. But to which extent do satellite climatologies and reanalysis products reproduce this basic feature of the global water cycle? The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data set, HOAPS-3 (www.hoaps.org), contains fields of precipitation and evaporation over the global ocean and all basic state variables needed for the derivation of the fluxes. Except for the NOAA Pathfinder SST data set, all variables are derived from SSM/I satellite data over the ice free global ocean between 1987 and 2005. Special emphasis has been put into quality control and inter-satellite calibration in order to derive the data fields as homogeneous as possible. One of the major design goals of HOAPS was to provide a data set that is based exclusively on retrieval procedures which avoid any additional model or reanalysis input. On a global scale, the average evaporation since 1987 exceeds precipitation rate over the oceans in HOAPS-3 systematically, with almost negligible yearly cycle and small monthly variations. While the globally averaged precipitation time series does not exhibit any significant trend over the study period, evaporation shows a continuous increase during this time. Regionally, this increase concentrates in the subtropics and is, together with some reduction in precipitation, consistent with a strengthening of the Hadley circulation during the observation period. These results are compared with similar data fields of the same period from various satellite climatologies to insure the consistency of our results and to the NCEP and ERA40 as well as ERAInterim reanalysis products. Remarkable similarities and differences between the different information sources have been found and will be discussed in the presentation.

  18. Advantages of using satellite soil moisture estimates over precipitation products to assess regional vegetation water availability and activity

    Science.gov (United States)

    Chen, Tiexi

    2017-04-01

    To improve the understanding of water-vegetation relationships, direct comparative studies assessing the utility of satellite remotely sensed soil moisture, gridded precipitation products, and land surface model output are needed. A case study was investigated for a water-limited, lateral inflow receiving area in northeastern Australia during December 2008 to May 2009. In January 2009, monthly precipitation showed strong positive anomalies, which led to strong positive soil moisture anomalies. The precipitation anomalies disappeared within a month. In contrast, the soil moisture anomalies persisted for months. Positive anomalies of Normalized Difference Vegetation Index (NDVI) appeared in February, in response to water supply, and then persisted for several months. In addition to these temporal characteristics, the spatial patterns of NDVI anomalies were more similar to soil moisture patterns than to those of precipitation and land surface model output. The long memory of soil moisture mainly relates to the presence of clay-rich soils. Modeled soil moisture from four of five global land surface models failed to capture the memory length of soil moisture and all five models failed to present the influence of lateral inflow. This case study indicates that satellite-based soil moisture is a better predictor of vegetation water availability than precipitation in environments having a memory of several months and thus is able to persistently affect vegetation dynamics. These results illustrate the usefulness of satellite remotely sensed soil moisture in ecohydrology studies. This case study has the potential to be used as a benchmark for global land surface model evaluations. The advantages of using satellite remotely sensed soil moisture over gridded precipitation products are mainly expected in lateral-inflow and/or clay-rich regions worldwide.

  19. Analysis of Terminal Velocity and VHF Backscatter of Precipitation Particles Using Chung-Li VHF Radar Combined with Ground-Based Disdrometer

    Directory of Open Access Journals (Sweden)

    Ching-Lun Su and Yen-Hsyang Chu

    2007-01-01

    Full Text Available The backscatter from precipitation particles observed by the vertically pointed antenna beam of the Chung-Li VHF radar and the drop size distributions measured by a ground-based disdrometer co-located at the radar site are analyzed and studied in this article. We find that the disdrometermeasured drop size distribution can be well approximated to a Gamma distribution. On the basis of this property and a power law approximation to the fallspeed-diameter relation VD = ADB, we derive the theoretical relation between terminal velocity VD and range-corrected VHF backscatter P of the precipitation particles. We find that the VD - P relation follows a power law in the form of VD = _ where _ _ both the functions of the precipitation parameters. Chu et al. (1999 first found that the relation between _ _ be empirically approximated to an exponential form of _ _ where _ a function of B and _ a factor associated with precipitation. In this article, under the assumptions of the Gamma distribution of the drop size distribution and the power-law relation between VD and D, we theoretically show that the analytical relation between _ _ follows an exponential form of _ _ where _ a function of the drop size distribution. The experimental results obtained by the Chung-Li VHF radar combined with the ground-based disdrometer measurements validate the exponential approximation to the _ _ The uses of the _ _ for the investigations of the rainfall rate and properties of drop size distribution are presented and discussed.

  20. Using R for analysing spatio-temporal datasets: a satellite-based precipitation case study

    Science.gov (United States)

    Zambrano-Bigiarini, Mauricio

    2017-04-01

    Increasing computer power and the availability of remote-sensing data measuring different environmental variables has led to unprecedented opportunities for Earth sciences in recent decades. However, dealing with hundred or thousands of files, usually in different vectorial and raster formats and measured with different temporal frequencies, impose high computation challenges to take full advantage of all the available data. R is a language and environment for statistical computing and graphics which includes several functions for data manipulation, calculation and graphical display, which are particularly well suited for Earth sciences. In this work I describe how R was used to exhaustively evaluate seven state-of-the-art satellite-based rainfall estimates (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. First, built-in functions were used to automatically download the satellite-images in different raster formats and spatial resolutions and to clip them into the Chilean spatial extent if necessary. Second, the raster package was used to read, plot, and conduct an exploratory data analysis in selected files of each SRE product, in order to detect unexpected problems (rotated spatial domains, order or variables in NetCDF files, etc). Third, raster was used along with the hydroTSM package to aggregate SRE files into different temporal scales (daily, monthly, seasonal, annual). Finally, the hydroTSM and hydroGOF packages were used to carry out a point-to-pixel comparison between precipitation time series measured at 366 stations and the corresponding grid cell of each SRE. The modified Kling-Gupta index of model performance was used to identify possible sources of systematic errors in each SRE, while five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities

  1. Correcting satellite-based precipitation products from SMOS soil moisture data assimilation using two models of different complexity

    Science.gov (United States)

    Román-Cascón, Carlos; Pellarin, Thierry; Gibon, François

    2017-04-01

    Real-time precipitation information at the global scale is quite useful information for many applications. However, satellite-based precipitation products in real time are known to be biased from real values observed in situ. On the other hand, the information about precipitation contained in soil moisture data can be very useful to improve precipitation estimation, since the evolution of this variable is highly influenced by the amount of rainfall at a certain area after a rain event. In this context, the soil moisture data from the Soil Moisture Ocean Salinity (SMOS) satellite is used to correct the precipitation provided by real-time satellite-based products such as CMORPH, TRMM-3B42RT or PERSIANN. In this work, we test an assimilation algorithm based on the data assimilation of SMOS measurements in two models of different complexity: a simple hydrological model (Antecedent Precipitation Index (API)) and a state-of-the-art complex land-surface model (Surface Externalisée (SURFEX)). We show how the assimilation technique, based on a particle filter method, leads to the improvement of correlation and root mean squared error (RMSE) of precipitation estimates, with slightly better results for the simpler (and less expensive computationally) API model. This methodology has been evaluated for six years in ten sites around the world with different features, showing the limitations of the methodology in regions affected by mountainous terrain or by high radio-frequency interferences (RFI), which notably affect the quality of the soil moisture retrievals from brightness temperatures by SMOS. The presented results are promising for a potential near-real time application at the global scale.

  2. Meteo-marine parameters for highly variable environment in coastal regions from satellite radar images

    Science.gov (United States)

    Pleskachevsky, A. L.; Rosenthal, W.; Lehner, S.

    2016-09-01

    The German Bight of the North Sea is the area with highly variable sea state conditions, intensive ship traffic and with a high density of offshore installations, e.g. wind farms in use and under construction. Ship navigation and the docking on offshore constructions is impeded by significant wave heights HS > 1.3 m. For these reasons, improvements are required in recognition and forecasting of sea state HS in the range 0-3 m. Thus, this necessitates the development of new methods to determine the distribution of meteo-marine parameters from remote sensing data with an accuracy of decimetres for HS. The operationalization of these methods then allows the robust automatic processing in near real time (NRT) to support forecast agencies by providing validations for model results. A new empirical algorithm XWAVE_C (C = coastal) for estimation of significant wave height from X-band satellite-borne Synthetic Aperture Radar (SAR) data has been developed, adopted for coastal applications using TerraSAR-X (TS-X) and Tandem-X (TD-X) satellites in the German Bight and implemented into the Sea Sate Processor (SSP) for fully automatic processing for NRT services. The algorithm is based on the spectral analysis of subscenes and the model function uses integrated image spectra parameters as well as local wind information from the analyzed subscene. The algorithm is able to recognize and remove the influence of non-sea state produced signals in the Wadden Sea areas such as dry sandbars as well as nonlinear SAR image distortions produced by e.g. short wind waves and breaking waves. Also parameters of very short waves, which are not visible in SAR images and produce only unsystematic clutter, can be accurately estimated. The SSP includes XWAVE_C, a pre-filtering procedure for removing artefacts such as ships, seamarks, buoys, offshore constructions and slicks, and an additional procedure performing a check of results based on the statistics of the whole scene. The SSP allows an

  3. Performance of TMPA satellite precipitation product over the Northern Great Plains

    Science.gov (United States)

    Kharel, G.; Kirilenko, A.; Zhang, X.

    2011-12-01

    Satellite derived precipitation can be used as supplement and/or replacement to ground data in various applications including modeling and weather forecasting based on its accuracy, reliability and validity. We analyzed Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA) 3B42 v.6 Level 3 product (0.25° × 0.25°, 3-hour resolution) against the United States Historical Climatology Network (USHCN) ground data from 98 stations in the Northern Great Plains (NGP) over the period of seven years (2003 to 2009). NGP, comprised of Wyoming, Montana, North Dakota, Minnesota, South Dakota and Nebraska states of the US, is located between the latitudes 41° - 49° N and longitudes 94° - 113.5° E within the TMPA product latitude band (50° NS).The goal of this research was to investigate the performance of TMPA over the NGP region. Results showed that the TMPA daily data has poor rainfall detection ability (POD ~ 0.3), weak correlation with the meteorological data (ρ=0.46) and high root mean square deviation (RMSD = 4.9 mm/day). We also found noticeable seasonal differences in the daily TMPA product performance. It underperformed during cold season (November to March) with weaker correlation (0.25) and worse POD (~ 0.15), as compared to relatively modest correlation (0.47) and POD (~0.30) during warm season (April to October). Our analysis at monthly scale revealed significantly better performance of TMPA with higher correlation (0.82) and lower RMSD (0.72 mm/day). Based on our findings, the TMPA daily data might be a poor replacement to ground data, however, at a monthly scale, TMPA can be used to estimate spatial rainfall distribution in NGP and/or as an input to a stochastic daily weather generator.

  4. Satellite radar altimetry over ice. Volume 1: Processing and corrections of Seasat data over Greenland

    Science.gov (United States)

    Zwally, H. Jay; Brenner, Anita C.; Major, Judith A.; Martin, Thomas V.; Bindschadler, Robert A.

    1990-01-01

    The data-processing methods and ice data products derived from Seasat radar altimeter measurements over the Greenland ice sheet and surrounding sea ice are documented. The corrections derived and applied to the Seasat radar altimeter data over ice are described in detail, including the editing and retracking algorithm to correct for height errors caused by lags in the automatic range tracking circuit. The methods for radial adjustment of the orbits and estimation of the slope-induced errors are given.

  5. Flood occurrence mapping of the middle Mahakam lowland area using satellite radar

    Directory of Open Access Journals (Sweden)

    H. Hidayat

    2012-07-01

    Full Text Available Floodplain lakes and peatlands in the middle Mahakam lowland area are considered as ecologically important wetland in East Kalimantan, Indonesia. However, due to a lack of data, the hydrological functioning of the region is still poorly understood. Among remote sensing techniques that can increase data availability, radar is well-suitable for the identification, mapping, and measurement of tropical wetlands, for its cloud unimpeded sensing and night and day operation. Here we aim to extract flood extent and flood occurrence information from a series of radar images of the middle Mahakam lowland area. We explore the use of Phased Array L-band Synthetic Aperture Radar (PALSAR imagery for observing flood inundation dynamics by incorporating field water level measurements. Water level measurements were carried out along the river, in lakes and in peatlands, using pressure transducers. For validation of the open water flood occurrence map, bathymetry measurements were carried out in the main lakes. A series of PALSAR images covering the middle and lower Mahakam area in the years 2007 through 2010 were collected. A fully inundated region can be easily recognized on radar images from a dark signature. Open water flood occurrence was mapped using a threshold value taken from radar backscatter of the permanently inundated river and lakes areas. Radar backscatter intensity analysis of the vegetated floodplain area revealed consistently high backscatter values, indicating flood inundation under forest canopy. We used those values as the threshold for flood occurrence mapping in the vegetated area.

  6. Characteristics of precipitating monsoon clouds over rain-shadow and drought-hit regions of India using radar

    Science.gov (United States)

    Morwal, S. B.; Narkhedkar, S. G.; Padmakumari, B.; Maheskumar, R. S.; Kulkarni, J. R.

    2017-07-01

    C-band radars were installed at Baramati and Shegaon as a part of operational cloud seeding program of Maharashtra State in the monsoon season (June-September) 2004. These provided first time a unique opportunity to study (1) characteristics of precipitating monsoon clouds (2) convection and (3) number of seedable clouds over Indian meteorological subdivisions of Madhya Maharashtra (rain-shadow) and Vidarbha (drought-hit). The monsoon season is divided into active and break periods. The cloud characteristics studied are: diurnal variation, cloud top heights and durations. Diurnal variation of cloud frequency shows maximum in the afternoon hours (10-11 UTC) and minimum in the early morning hours (3-4 UTC) in both the periods. Cloud tops show trimodal distributions with modes at 2-3, 8-9 and above 9 km. Mean cloud duration is 55 min. Congestus has been found prominent cloud type (65%) with mean top height of 6.76 km. Frequency of cumulonimbus clouds is found higher in the break periods. Cloud scale is taken as a metric for characterization of convection. Maximum frequency of cloud scale is found at C scale (mesoscale: area 100-1000 km2). Mesoscale Convective System has been found dominating convection type. The convection over the area has been shown to be hybrid type, consisting of basic oceanic type modulated by land convection. Convective clouds having maximum reflectivities between 25 and 35 dBZ, suitable for hygroscopic and glaciogenic seeding, are found in a large number. Understanding of characteristics of clouds and convection is useful for the diagnostic and precipitation enhancement studies over the rain-shadow/drought-hit regions.

  7. Bias correction of satellite precipitation products for flood forecasting application at the Upper Mahanadi River Basin in Eastern India

    Science.gov (United States)

    Beria, H.; Nanda, T., Sr.; Chatterjee, C.

    2015-12-01

    High resolution satellite precipitation products such as Tropical Rainfall Measuring Mission (TRMM), Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF), etc., offer a promising alternative to flood forecasting in data scarce regions. At the current state-of-art, these products cannot be used in the raw form for flood forecasting, even at smaller lead times. In the current study, these precipitation products are bias corrected using statistical techniques, such as additive and multiplicative bias corrections, and wavelet multi-resolution analysis (MRA) with India Meteorological Department (IMD) gridded precipitation product,obtained from gauge-based rainfall estimates. Neural network based rainfall-runoff modeling using these bias corrected products provide encouraging results for flood forecasting upto 48 hours lead time. We will present various statistical and graphical interpretations of catchment response to high rainfall events using both the raw and bias corrected precipitation products at different lead times.

  8. Identification of precipitation onset based on Cloudsat observations

    Science.gov (United States)

    Wang, Yu; Chen, Yujue; Fu, Yunfei; Liu, Guosheng

    2017-02-01

    Observations of cloud vertical structure by Cloud Profiling Radar on CloudSat satellite provide a unique opportunity to globally identify the onset of precipitation. In this study, based on a conceptual model for an adiabatic cloud, a new method to determine the onset of precipitation in marine warm clouds is developed. The new method uses the slope of radar reflectivities near the cloud top, which gradually reverses its signs as drizzle occurs. By analyzing multiyear CloudSat data, it is found that globally the radar reflectivity threshold for precipitation onset varies from -18 to -13 dBZ with an average value of -16 dBZ. The corresponding liquid water path threshold for precipitation onset is also studied by analyzing satellite microwave observations collocated with CloudSat data. Results show that the liquid water path threshold is 190 g m-2 as a global mean, varying from 150 to over 300 g m-2 depending on regions.

  9. PM-GCD – a combined IR–MW satellite technique for frequent retrieval of heavy precipitation

    Directory of Open Access Journals (Sweden)

    D. Casella

    2012-01-01

    Full Text Available Precipitation retrievals based on measurements from microwave (MW radiometers onboard low-Earth-orbit (LEO satellites can reach high level of accuracy – especially regarding convective precipitation. At the present stage though, these observations cannot provide satisfactory coverage of the evolution of intense and rapid precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications – especially in supporting authorities for flood alerts and weather warnings. To tackle this problem, over the past two decades several techniques have been developed combining accurate MW estimates with frequent infrared (IR observations from geosynchronous (GEO satellites, such as the European Meteosat Second Generation (MSG. In this framework, we have developed a new fast and simple precipitation retrieval technique which we call Passive Microwave – Global Convective Diagnostic, (PM-GCD. This method uses MW retrievals in conjunction with the Global Convective Diagnostic (GCD technique which discriminates deep convective clouds based on the difference between the MSG water vapor (6.2 μm and thermal-IR (10.8 μm channels. Specifically, MSG observations and the GCD technique are used to identify deep convective areas. These areas are then calibrated using MW precipitation estimates based on observations from the Advanced Microwave Sounding Unit (AMSU radiometers onboard operational NOAA and Eumetsat satellites, and then finally propagated in time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique, analyzing its results for a case study that refers to a flood event that struck the island of Sicily in southern Italy on 1–2 October 2009.

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

    Directory of Open Access Journals (Sweden)

    M. Ashrafi

    2005-01-01

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

  11. Analysis of TRMM 3-Hourly Multi-Satellite Precipitation Estimates Computed in Both Real and Post-Real Time

    Science.gov (United States)

    Huffman, George J.; Adler, Robert F.; Stocker, Erich; Bolvin, David T.; Nelkin, Eric J.

    2002-01-01

    Satellite data form the core of the information available for estimating precipitation on a global basis. While it is possible to create such estimates solely from one sensor, researchers have increasingly moved to using combinations of sensors in an attempt to improve accuracy, coverage, and resolution. This poster updates a long-term project in which the authors are working to provide routine combined-sensor estimates of precipitation over the entire globe at relatively fine time and space intervals. The goal is to produce these globally complete precipitation estimates on a 25-km grid every 3 hours. Since late January 2002 we have been estimating precipitation for the latitude band 50 degrees N-S within about 6 hours of observation time. This work is 1 of only 2 or 3 such efforts in the world. Now we are preparing to provide similar estimates for the last 5 years. All of this work is being carried out as part of the Tropical Rainfall Measuring Mission (TRMM). Initially, TRMM was focused on providing excellent long-term averages of precipitation in tropical regions, but since its launch in November 1997 continued research has allowed the same satellite and data system to be used for addressing weather-scale problems as well.

  12. Estimate of Precipitation from the Dual-Beam Airborne Radars in TOGA COARE. Part 1: The K-Z Relationships Derived from Stereo and Quad-Beam Analysis.

    Science.gov (United States)

    Oury, Stéphane; Testud, Jacques; Marécal, Virginie

    1999-02-01

    The recent development of dual-beam airborne Doppler weather radar offers the possibility to perform high-resolution observations of the three-dimensional air motion and precipitation fields associated with severe weather systems. However, the limited size of the onboard antennas imposes the use of high radar frequencies (e.g., X band) in order to achieve satisfactory beam resolutions. Therefore, the sampled radar reflectivity is attenuated when intercepting intense rain cells. This paper aims at developing algorithms for correcting the observed radar reflectivity for attenuation that fully exploit the dual-beam sampling strategy and the multiple aircraft operations conducted in Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Its specific contribution is twofold.Algorithm development. On the one hand, the former stereoradar analysis helps to retrieve independently the`true' (nonattenuated) radar reflectivity Z and specific attenuation K when using two radar beams from one aircraft. The algorithm is reformulated in Cartesian coordinates, which greatly improves its flexibility. And on the other hand, a new approach is developed, the quad-beam analysis, which is particularly powerful when processing the data of a two dual-beam aircraft operation focused on the same rain cells.Data analysis. An application of the stereoradar and quad-beam analysis to a TOGA COARE weather system is presented. The corrected Z and K fields are cross validated using different algorithms or datasets for the same event. The radar derived K-Z relationships are also compared with that deduced from in situ microphysical probes sampling using a scattering model. The full three-dimensional description of the Z and K fields is then used to appreciate to what extent the observed heavy rain reached the `equilibrium' described by previous authors in response to droplet coalescence and breakup.

  13. The interaction of large scale and mesoscale environment leading to formation of intense thunderstorms over Kolkata. Part I: Doppler radar and satellite observations

    Indian Academy of Sciences (India)

    P Mukhopadhyay; M Mahakur; H A K Singh

    2009-10-01

    The weather systems that predominantly affect the eastern and northeastern parts of India during the pre-monsoon summer months (March,April and May)are severe thunderstorms,known as Nor ’westers.The storms derive their names from the fact that they frequently strike cities and towns in the southern part of West Bengal in the afternoon from the north-west direction while traveling far from its place of genesis over the Bihar plateau.The storms are devastating in nature particularly due to strong (gusty)winds,heavy rains and hails associated with it.Although these storms are well known for its power of causing damages,studies on them are relatively few due to their small size and sparse network of observations.To address this important issue,the evolution of two Nor ’westers of 12 March and 22 May 2003 over Kolkata is studied in detail in this paper using hourly Doppler weather radar (DWR)observations and high resolution Meteosat-5 imageries.In addition,supporting meteorological reports are used to find the large scale conditions that influence the moisture convergence and vertical wind shear.The genesis of both the storms is found to be over Bihar –Jharkhand region and beyond the range of the DWR.The satellite observations are found to be useful in identifying the location and initiation of the storms.The movements of the storms are captured by the DWR estimated vertical cross-section of reflectivities.The Doppler estimate shows that the 12 March storm had a vertical extent of about 10 –12 km at the time of maturity and that of 22 May reaching up to 18 km signifying deep convection associated with these events.The genesis, maturity and dissipation are well brought out by the hourly DWR and satellite imageries.The DWR observations suggest that the systems move at a speed of 20 –25 m/s.The DWR estimated precipitation shows a detailed spatial distribution around Kolkata with several localized zones of heavy rain and this is found to be well supported by

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

    Directory of Open Access Journals (Sweden)

    T. Cohen Liechti

    2011-08-01

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

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

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

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

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

  15. Coastal flood inundation monitoring with Satellite C-band and L-band Synthetic Aperture Radar data

    Science.gov (United States)

    Ramsey, Elijah W.; Rangoonwala, Amina; Bannister, Terri

    2013-01-01

    Satellite Synthetic Aperture Radar (SAR) was evaluated as a method to operationally monitor the occurrence and distribution of storm- and tidal-related flooding of spatially extensive coastal marshes within the north-central Gulf of Mexico. Maps representing the occurrence of marsh surface inundation were created from available Advanced Land Observation Satellite (ALOS) Phased Array type L-Band SAR (PALSAR) (L-band) (21 scenes with HH polarizations in Wide Beam [100 m]) data and Environmental Satellite (ENVISAT) Advanced SAR (ASAR) (C-band) data (24 scenes with VV and HH polarizations in Wide Swath [150 m]) during 2006-2009 covering 500 km of the Louisiana coastal zone. Mapping was primarily based on a decrease in backscatter between reference and target scenes, and as an extension of previous studies, the flood inundation mapping performance was assessed by the degree of correspondence between inundation mapping and inland water levels. Both PALSAR- and ASAR-based mapping at times were based on suboptimal reference scenes; however, ASAR performance seemed more sensitive to reference-scene quality and other types of scene variability. Related to water depth, PALSAR and ASAR mapping accuracies tended to be lower when water depths were shallow and increased as water levels decreased below or increased above the ground surface, but this pattern was more pronounced with ASAR. Overall, PALSAR-based inundation accuracies averaged 84% (n = 160), while ASAR-based mapping accuracies averaged 62% (n = 245).

  16. Nanosar-case study of synthetic aperture radar for nano-satellites

    NARCIS (Netherlands)

    Engelen, S.; Oever, M. van den; Mahapatra, P.; Sundaramoorthy, P.; Gill, E.; Meijer, R.J.; Verhoeven, C.

    2012-01-01

    Nano-satellites have a cost advantage due to their low mass and usage of commercial-off-the-shelf technologies. However, the low mass also restricts the functionality of a nano-satellite's payload. Typically, this would imply instruments with very low to low resolution and accuracy, essentially

  17. Nanosar-case study of synthetic aperture radar for nano-satellites

    NARCIS (Netherlands)

    Engelen, S.; Oever, M. van den; Mahapatra, P.; Sundaramoorthy, P.; Gill, E.; Meijer, R.J.; Verhoeven, C.

    2012-01-01

    Nano-satellites have a cost advantage due to their low mass and usage of commercial-off-the-shelf technologies. However, the low mass also restricts the functionality of a nano-satellite's payload. Typically, this would imply instruments with very low to low resolution and accuracy, essentially ruli

  18. Relating surface backscatter response from TRMM precipitation radar to soil moisture: results over a semi-arid region

    Directory of Open Access Journals (Sweden)

    H. Stephen

    2010-02-01

    Full Text Available The Tropical Rainfall Measuring Mission (TRMM carries aboard the Precipitation Radar (TRMMPR that measures the backscatter (σ° of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms in the Lower Colorado River Basin (LCRB. σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI. A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using the Variable Infiltration Capacity (VIC model and measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW.

    σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with a correlation coefficient (R of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry and August (wet 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new

  19. Evaluation of GPM-based Multi-satellite IMERG Precipitation Products Over the Lower Colorado River Basin, Texas

    Science.gov (United States)

    Omranian, S. E.; Sharif, H. O.

    2016-12-01

    This study evaluates the Global Precipitation Measurement (GPM) satellite products by analyzing extreme rainfall events over the Lower Colorado River Basin, Texas that resulted in unprecedented flash floods in May 2015. Records of a dense rain gauge network (241 stations) are compared with Integrated Multi-satellite Retrievals for GPM (IMERG) products. The spatial resolution of the GPM satellite product is 0.1º x 0.1º and the temporal resolution is 30 minutes. Reference gauge-based observations are distributed through the basin with total area of over 5,000 square kilometers at 15-minute time intervals. A preliminary assessment of GPM-based IMERG precipitation products shows reasonable correlation, especially when for periods of high amounts of rainfall. the results indicate that GPM satellite products can potentially be employed in hydrologic modeling, especially for large events. Moreover, since the IMERG products have semi-global coverage, it can be extremely useful in hydrological modeling and analysis studies over ungauged or poorly gauged regions.

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

    Science.gov (United States)

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

    2016-05-01

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

  1. Precipitation effects on the selection of suitable non-variant targets intended for atmospheric correction of satellite remotely sensed imagery

    Science.gov (United States)

    Themistocleous, Kyriacos; Hadjimitsis, Diofantos G.; Retalis, Adrianos; Chrysoulakis, Nektarios; Michaelides, Silas

    2013-09-01

    One of the most well-established atmospheric correction methods of satellite imagery is the use of the empirical line method using non-variant targets. Non-variant targets serve as pseudo-invariant targets since their reflectance values are stable across time. A recent adaptation of the empirical line method incorporates the use of ground reflectance measurements of selected non-variant targets. Most of the users are not aware of the existing conditions of the pseudo-invariant targets; i.e., whether they are dry or wet. Any omission of such effects may cause erroneous results; therefore, remote sensing users must be aware of such effects. This study assessed the effects of precipitation on five types of commonly located surfaces, including asphalt, concrete and sand, intended as pseudo-invariant targets for atmospheric correction. Spectroradiometric measurements were taken in wet and dry conditions to obtain the spectral signatures of the targets, from January 2010 to May 2011 (46 campaigns). An atmospheric correction of eleven Landsat TM/ETM + satellite images using the empirical line method was conducted. To identify the effects of precipitation, a comparison was conducted of the atmospheric path radiance component for wet and dry conditions. It was found that precipitation conditions such as rainfall affected the reflectance values of the surfaces, especially sand. Therefore, precipitation conditions need to be considered when using non-variant targets in atmospheric correction methods.

  2. Formation flying orbit design for the distributed synthetic aperture radar satellite

    Institute of Scientific and Technical Information of China (English)

    CHEN Jie; ZHOU Yinqing; LI Chunsheng

    2004-01-01

    Formation flying orbit design is one of the key technologies for system design and performance analysis of the distributed SAR satellites. The approximately analytic solution of the passive stable formation flying orbit elements is explored based on the expansion form of Kepler's equation. A new method of orbital parameters design for three-dimensional formation flying SAR satellites is presented, and the precision of the orbital elements is analyzed. Formation flying orbit elements are calculated for the L-Band distributed SAR satellites using the formulas deduced in this paper. The accuracy of the orbital elements is validated by the computer simulation results presented in this paper.

  3. Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops

    Directory of Open Access Journals (Sweden)

    R. Fieuzal

    2011-04-01

    Full Text Available The objective of this study is to get a better understanding of radar signal over irrigated wheat fields and to assess the potentialities of radar observations for the monitoring of soil moisture. Emphasis is put on the use of high spatial and temporal resolution satellite data (Envisat/ASAR and Formosat-2. Time series of images were collected over the Yaqui irrigated area (Mexico throughout one agricultural season from December 2007 to May 2008, together with measurements of soil and vegetation characteristics and agricultural practices. The comprehensive analysis of these data indicates that the sensitivity of the radar signal to vegetation is masked by the variability of soil conditions. On-going irrigated areas can be detected all over the wheat growing season. The empirical algorithm developed for the retrieval of topsoil moisture from Envisat/ASAR images takes advantage of the Formosat-2 instrument capabilities to monitor the seasonality of wheat canopies. This monitoring is performed using dense time series of images acquired by Formosat-2 to set up the SAFY vegetation model. Topsoil moisture estimates are not reliable at the timing of plant emergence and during plant senescence. Estimates are accurate from tillering to grain filling stages with an absolute error about 9% (0.09 m3 m−3, 35% in relative value. This result is attractive since topsoil moisture is estimated at a high spatial resolution (i.e. over subfields of about 5 ha for a large range of biomass water content (from 5 and 65 t ha−1 independently from the viewing angle of ASAR acquisition (incidence angles IS1 to IS6.

  4. Application of Multifractal Analysis to Segmentation of Water Bodies in Optical and Synthetic Aperture Radar Satellite Images

    CERN Document Server

    Martin, Victor Manuel San

    2016-01-01

    A method for segmenting water bodies in optical and synthetic aperture radar (SAR) satellite images is proposed. It makes use of the textural features of the different regions in the image for segmentation. The method consists in a multiscale analysis of the images, which allows us to study the images regularity both, locally and globally. As results of the analysis, coarse multifractal spectra of studied images and a group of images that associates each position (pixel) with its corresponding value of local regularity (or singularity) spectrum are obtained. Thresholds are then applied to the multifractal spectra of the images for the classification. These thresholds are selected after studying the characteristics of the spectra under the assumption that water bodies have larger local regularity than other soil types. Classifications obtained by the multifractal method are compared quantitatively with those obtained by neural networks trained to classify the pixels of the images in covered against uncovered b...

  5. Rheology of the Ronne Ice Shelf, Antarctica, Inferred from Satellite Radar Interferometry Data using an Inverse Control Method

    Science.gov (United States)

    Larour, E.; Rignot, E.; Joughin, I.; Aubry, D.

    2005-01-01

    The Antarctic Ice Sheet is surrounded by large floating ice shelves that spread under their own weight into the ocean. Ice shelf rigidity depends on ice temperature and fabrics, and is influenced by ice flow and the delicate balance between bottom and surface accumulation. Here, we use an inverse control method to infer the rigidity of the Ronne Ice Shelf that best matches observations of ice velocity from satellite radar interferometry. Ice rigidity, or flow law parameter B, is shown to vary between 300 and 900 kPa a(sup 1/3). Ice is softer along the side margins due to frictional heating, and harder along the outflow of large glaciers, which advect cold continental ice. Melting at the bottom surface of the ice shelf increases its rigidity, while freezing decreases it. Accurate numerical modelling of ice shelf flow must account for this spatial variability in mechanical characteristics.

  6. Ground settlement of Chek Lap Kok Airport, Hong Kong,detected by satellite synthetic aperture radar interferometry

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Satellite synthetic aperture radar (SAR) interferometry is used to investigate the slowly accumulating ground settlement at the new Chek Lap Kok Airport in Hong Kong. Most of the land occupied by the airport was reclaimed from the sea and therefore certain ground settlement in the area has been expected. A pair of ERS-2 SAR images spanning nearly a year is used in the study. The high spatial resolution (20 m× 20 m) ground settlement map derived indicates that the settlement that occurred in the area over the time period is as large as 50 mm. The SAR measurement results agree with the levelling measurements at some benchmarks in the area to well within 1 cm(rms error),and the overall correlation between the two types of results is 0.89. The paper presents some brief background of interferometric SAR, and outlines the data processing methods and results.

  7. Rheology of the Ronne Ice Shelf, Antarctica, Inferred from Satellite Radar Interferometry Data using an Inverse Control Method

    Science.gov (United States)

    Larour, E.; Rignot, E.; Joughin, I.; Aubry, D.

    2005-01-01

    The Antarctic Ice Sheet is surrounded by large floating ice shelves that spread under their own weight into the ocean. Ice shelf rigidity depends on ice temperature and fabrics, and is influenced by ice flow and the delicate balance between bottom and surface accumulation. Here, we use an inverse control method to infer the rigidity of the Ronne Ice Shelf that best matches observations of ice velocity from satellite radar interferometry. Ice rigidity, or flow law parameter B, is shown to vary between 300 and 900 kPa a(sup 1/3). Ice is softer along the side margins due to frictional heating, and harder along the outflow of large glaciers, which advect cold continental ice. Melting at the bottom surface of the ice shelf increases its rigidity, while freezing decreases it. Accurate numerical modelling of ice shelf flow must account for this spatial variability in mechanical characteristics.

  8. Caractérisation spatiale de l’aléa inondation à partir d’images satellites RADAR

    Directory of Open Access Journals (Sweden)

    Renaud Hostache

    2007-07-01

    Full Text Available Dans le cadre de la gestion du risque d’inondation, la caractérisation spatiale de l’aléa est une problématique récurrente pour laquelle les techniques de télédétection, en particulier satellitales, peuvent s’avérer très utiles. L’objectif général de notre étude est d’évaluer les apports de l’utilisation de ces données et, en particulier, de développer des méthodes de valorisation des images satellites RADAR d’inondations pour la caractérisation spatiale de l’aléa. A terme, notre étude vise l’aide à la modélisation hydraulique par évaluation de hauteurs et de volumes d’eau. La méthode que nous proposons s’articule en trois étapes principales : 1 cartographie de l’extension des eaux à partir d’images RADAR et extraction des limites informatives, 2 estimation primaire de niveaux d’eau par croisement entre les limites informatives et un MNT, 3 réduction des incertitudes d’estimation des niveaux d’eau par introduction de concepts de cohérence hydraulique.

  9. Comparison between weather radar and rain gauges data of precipitations that triggered debris flows in the Dolomites (North Eastern Italian Alps)

    Science.gov (United States)

    Bernard, Martino; Gregoretti, Carlo

    2016-04-01

    High intensity and short duration (usually 15-30 minutes) rainfalls are able to generate sudden and abundant runoff in rocky cliffs that can entrain large quantities of sediments and originate debris flow phenomena. A rain gauge network has been set up in two different areas of Dolomites (North Eastern Italian Alps) far each other about 15 km: Fiames (Cortina d'Ampezzo) and Rovina di Cancia (Borca di Cadore). The first network is composed of 9 rain gauges in an area of 1 km2, while the second is composed of 6 rain gauges in an area of 2 km2. In both the areas, the rain gauges are positioned both upstream and downstream the initiation areas of the occurring debris flows. Another single rain gauge is positioned close to the initiation area of Rudavoi debris flow (Auronzo di Cadore) and is far about 5 km from the Fiames rain gauges network. All the rain gauges sample precipitation depth at 5 minutes intervals. In the years 2009-2015 records of rainfalls that triggered 22 debris flows were taken. In most cases, the recorded rainfalls show an higher variability both along distance (200-500 m) and along altitude (200-600 m). Precipitation data recorded by the rain gauges are then compared with those estimated by means of a C-Band weather radar about 70 km away from there, to verify the possible interchangeability of the two measurement systems. Rainfall depths estimated by radar are provided with the temporal interval of the rain gauges (5 minutes) but with a different spatial scale (500 x 500 m raster resolution). To avoid the observation scale gap between the different techniques, in addition to standard comparisons between point gauge and radar rainfall measures, mean areal precipitations were derived from rain gauge network and compared with radar data. Results seem to demonstrate that radar tends to underestimate precipitation evaluated from rain gauges network, both on different measurement scales and on mean spatial data. On average, underestimation regards both

  10. Natural radio emission of Jupiter as interferences for radar investigations of the icy satellites of Jupiter

    Science.gov (United States)

    Cecconi, B.; Hess, S.; Hérique, A.; Santovito, M. R.; Santos-Costa, D.; Zarka, P.; Alberti, G.; Blankenship, D.; Bougeret, J.-L.; Bruzzone, L.; Kofman, W.

    2012-02-01

    Radar instruments are part of the core payload of the two Europa Jupiter System Mission (EJSM) spacecraft: NASA-led Jupiter Europa Orbiter (JEO) and ESA-led Jupiter Ganymede Orbiter (JGO). At this point of the project, several frequency bands are under study for radar, which ranges between 5 and 50 MHz. Part of this frequency range overlaps with that of the natural jovian radio emissions, which are very intense in the decametric range, below 40 MHz. Radio observations above 40 MHz are free of interferences, whereas below this threshold, careful observation strategies have to be investigated. We present a review of spectral intensity, variability and sources of these radio emissions. As the radio emissions are strongly beamed, it is possible to model the visibility of the radio emissions, as seen from the vicinity of Europa or Ganymede. We have investigated Io-related radio emissions as well as radio emissions related to the auroral oval. We also review the radiation belts synchrotron emission characteristics. We present radio sources visibility products (dynamic spectra and radio source location maps, on still frames or movies), which can be used for operation planning. This study clearly shows that a deep understanding of the natural radio emissions at Jupiter is necessary to prepare the future EJSM radar instrumentation. We show that this radio noise has to be taken into account very early in the observation planning and strategies for both JGO and JEO. We also point out possible synergies with RPW (Radio and Plasma Waves) instrumentations.

  11. Monitoring of Arctic Conditions from a Virtual Constellation of Synthetic Aperture Radar Satellites

    Science.gov (United States)

    2013-09-30

    of glaciers and the speed of motion. h) Monitoring of the Northwest Passage. APPROACH 2013 MIZ Pilot Program: Starting in June to end of...Flux Buoy (AOFB), and CRREL Ice Mass Balance (IMB) buoy so comparisons of the in-situ data can be calculated with the SAR data. By tracking the...programming the satellite collections for the dynamic and sometimes erratic movements of the buoy was not trivial and required tasking the satellite

  12. Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

    Science.gov (United States)

    Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

    2014-01-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

  13. Joint statistical correction of clutters, spokes and beam height for a radar derived precipitation climatology in southern Germany

    Directory of Open Access Journals (Sweden)

    A. Wagner

    2012-11-01

    Full Text Available First results of radar derived climatology have emerged over the last years, as datasets of appropriate extent are becoming available. Usually, these statistics are based on time series lasting up to ten years as continuous storage of radar data was often not achieved before. This kind of climatology demands a high level of data quality. Small deviations or minor systematic under- or overestimations in single radar images become a major cause of error in statistical analysis. Extensive corrections of radar data are a crucial prerequisite for radar derived climatology. We present a new statistical post-correction scheme based on a climatological analysis of seven years of radar data of the Munich weather radar (2000–2006 operated by DWD (German Weather Service. Original radar products are used subject only to corrections within the signal processor without any further corrections on single radar images. The aim of this statistical correction is to make up for the average systematic errors caused by clutter, propagation, or measuring effects but to conserve small-scale natural variations in space.

    The statistical correction is based on a thorough analysis of the different causes of possible errors for the Munich weather radar. This analysis revealed the following basic effects: the decrease of rain amount as a function of height and distance from the radar, clutter effects such as clutter remnants after filtering, holes by eliminated clutter or shading effects from obstacles near the radar, visible as spokes, as well as the influence of the bright band. The correction algorithm is correspondingly based on these results. It consists of three modules. The first one is an altitude correction which minimises measuring effects. The second module corrects clutter effects and disturbances and the third one realises a mean adjustment to selected rain gauges. Two different sets of radar products are used. The statistical analysis as well as

  14. Optical and Radar Satellite Remote Sensing for Large Area Analysis of Landslide Activity in Southern Kyrgyzstan, Central Asia

    Science.gov (United States)

    Roessner, S.; Behling, R.; Teshebaeva, K. O.; Motagh, M.; Wetzel, H. U.

    2014-12-01

    The presented work has been investigating the potential of optical and radar satellite remote sensing for the spatio-temporal analysis of landslide activity at a regional scale along the eastern rim of the Fergana Basin representing the area of highest landslide activity in Kyrgyzstan. For this purpose a multi-temporal satellite remote sensing database has been established for a 12.000 km2 study area in Southern Kyrgyzstan containing a multitude of optical data acquired during the last 28 years as well as TerraSAR-X and ALOS-PALSAR acquired since 2007. The optical data have been mainly used for creating a multi-temporal inventory of backdated landslide activity. For this purpose an automated approach for object-oriented multi-temporal landslide detection has been developed which is based on the analysis of temporal NDVI-trajectories complemented by relief information to separate landslide-related surface changes from other land cover changes. Applying the approach to the whole study area using temporal high resolution RapidEye time series data has resulted in the automated detection of 612 landslide objects covering a total area of approx. 7.3 km². Currently, the approach is extended to the whole multi-sensor time-series database for systematic analysis of longer-term landslide occurrence at a regional scale. Radar remote sensing has been focussing on SAR Interferometry (InSAR) to detect landslide related surface deformation. InSAR data were processed by repeat-pass interferometry using the DORIS and SARScape software. To better assess ground deformation related to individual landslide objects, InSAR time-series analysis has been applied using the Small Baseline Subset (SBAS) method. Analysis of the results in combination with optical data and DEM information has revealed that most of the derived deformations are caused by slow movements in areas of already existing landslides indicating the reactivation of older slope failures. This way, InSAR analysis can

  15. Application of satellite precipitation data to analyse and model arbovirus activity in the tropics

    Directory of Open Access Journals (Sweden)

    Corner Robert J

    2011-01-01

    Full Text Available Abstract Background Murray Valley encephalitis virus (MVEV is a mosquito-borne Flavivirus (Flaviviridae: Flavivirus which is closely related to Japanese encephalitis virus, West Nile virus and St. Louis encephalitis virus. MVEV is enzootic in northern Australia and Papua New Guinea and epizootic in other parts of Australia. Activity of MVEV in Western Australia (WA is monitored by detection of seroconversions in flocks of sentinel chickens at selected sample sites throughout WA. Rainfall is a major environmental factor influencing MVEV activity. Utilising data on rainfall and seroconversions, statistical relationships between MVEV occurrence and rainfall can be determined. These relationships can be used to predict MVEV activity which, in turn, provides the general public with important information about disease transmission risk. Since ground measurements of rainfall are sparse and irregularly distributed, especially in north WA where rainfall is spatially and temporally highly variable, alternative data sources such as remote sensing (RS data represent an attractive alternative to ground measurements. However, a number of competing alternatives are available and careful evaluation is essential to determine the most appropriate product for a given problem. Results The Tropical Rainfall Measurement Mission (TRMM Multi-satellite Precipitation Analysis (TMPA 3B42 product was chosen from a range of RS rainfall products to develop rainfall-based predictor variables and build logistic regression models for the prediction of MVEV activity in the Kimberley and Pilbara regions of WA. Two models employing monthly time-lagged rainfall variables showed the strongest discriminatory ability of 0.74 and 0.80 as measured by the Receiver Operating Characteristics area under the curve (ROC AUC. Conclusions TMPA data provide a state-of-the-art data source for the development of rainfall-based predictive models for Flavivirus activity in tropical WA. Compared to

  16. Recent trends of the tropical hydrological cycle inferred from Global Precipitation Climatology Project and International Satellite Cloud Climatology Project data

    Science.gov (United States)

    Zhou, Y. P.; Xu, Kuan-Man; Sud, Y. C.; Betts, A. K.

    2011-05-01

    Scores of modeling studies have shown that increasing greenhouse gases in the atmosphere impact the global hydrologic cycle; however, disagreements on regional scales are large, and thus the simulated trends of such impacts, even for regions as large as the tropics, remain uncertain. The present investigation attempts to examine such trends in the observations using satellite data products comprising Global Precipitation Climatology Project precipitation and International Satellite Cloud Climatology Project cloud and radiation. Specifically, evolving trends of the tropical hydrological cycle over the last 20-30 years were identified and analyzed. The results show (1) intensification of tropical precipitation in the rising regions of the Walker and Hadley circulations and weakening over the sinking regions of the associated overturning circulation; (2) poleward shift of the subtropical dry zones (up to 2° decade-1 in June-July-August (JJA) in the Northern Hemisphere and 0.3-0.7° decade-1 in June-July-August and September-October-November in the Southern Hemisphere) consistent with an overall broadening of the Hadley circulation; and (3) significant poleward migration (0.9-1.7° decade-1) of cloud boundaries of Hadley cell and plausible narrowing of the high cloudiness in the Intertropical Convergence Zone region in some seasons. These results support findings of some of the previous studies that showed strengthening of the tropical hydrological cycle and expansion of the Hadley cell that are potentially related to the recent global warming trends.

  17. Ku/Ka-band electrically-scanned line array for tri-band cloud and precipitation radar applications Project

    Data.gov (United States)

    National Aeronautics and Space Administration — A spaceborne radar system that operates simultaneously at multiple frequency bands from microwave through millimeter-wave frequencies can exploit the largely varying...

  18. Significance of spatial variability in precipitation for process-oriented modelling: results from two nested catchments using radar and ground station data

    Directory of Open Access Journals (Sweden)

    D. Tetzlaff

    2005-01-01

    Full Text Available The importance of considering the spatial distribution of rainfall for process-oriented hydrological modelling is well-known. However, the application of rainfall radar data to provide such detailed spatial resolution is still under debate. In this study the process-oriented TACD (Tracer Aided Catchment model, Distributed model had been used to investigate the effects of different spatially distributed rainfall input on simulated discharge and runoff components on an event base. TACD is fully distributed (50x50m2 raster cells and was applied on an hourly base. As model input rainfall data from up to 7 ground stations and high resolution rainfall radar data from operational C-band radar were used. For seven rainfall events the discharge simulations were investigated in further detail for the mountainous Brugga catchment (40km2 and the St. Wilhelmer Talbach (15.2km2 sub-basin, which are located in the Southern Black Forest Mountains, south-west Germany. The significance of spatial variable precipitation data was clearly demonstrated. Dependent on event characteristics, localized rain cells were occasionally poorly captured even by a dense ground station network, and this resulted in inadequate model results. For such events, radar data can provide better input data. However, an extensive data adjustment using ground station data is required. For this purpose a method was developed that considers the temporal variability in rainfall intensity in high temporal resolution in combination with the total rainfall amount of both data sets. The use of the distributed catchment model allowed further insights into spatially variable impacts of different rainfall estimates. Impacts for discharge predictions are the largest in areas that are dominated by the production of fast runoff components. The improvements for distributed runoff simulation using high resolution rainfall radar input data are strongly dependent on the investigated scale, the event

  19. Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

    Science.gov (United States)

    Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne

    2012-01-01

    Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

  20. NanoSAR – Case study of synthetic aperture radar for nano-satellites

    NARCIS (Netherlands)

    Engelen, S.; Oever, M. van den; Mahapatra, P.S.; Sundaramoorthy, P.P.; Gill, E.K.A.; Meijer, R.J.; Verhoeven, C.J.M.

    2012-01-01

    Nano-satellites have a cost advantage due to their low mass and usage of commercial-off-the-shelf technologies. However, the low mass also restricts the functionality of a nano-satellite’s payload. Typically, this would imply instruments with very low to low resolution and accuracy, essentially

  1. Great Lakes Ice Cover Classification and Mapping Using Satellite Synthetic Aperture Radar (SAR) Data

    Science.gov (United States)

    Nghiem, S.; Leshkevich, G.; Kwok, R.

    1998-01-01

    Owing to the size and extent of the Great Lakes and the variety of ice types features found there, the timely and objective qualities inherent in computer processing of satellite data make it well suited for monitoring and mapping ice cover.

  2. Geostationary Satellite Observation of Precipitable Water Vapor Using an Empirical Orthogonal Function (EOF based Reconstruction Technique over Eastern China

    Directory of Open Access Journals (Sweden)

    Man Sing Wong

    2015-05-01

    Full Text Available Water vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV is urgently needed, but has long been constrained by data availability. Our study derived the vertically integrated precipitable water vapor over eastern China using Multi-functional Transport Satellite (MTSAT data, which is in geostationary orbit with high temporal resolution. The missing pixels caused by cloud contamination were reconstructed using an Empirical Orthogonal Function (EOF decomposition method over both spatial and temporal dimensions. GPS meteorology data were used to validate the retrieval and the reconstructed results. The diurnal variation of PWV over eastern China was analyzed using harmonic analysis, which indicates that the reconstructed PWV data can depict the diurnal cycle of PWV caused by evapotranspiration and local thermal circulation.

  3. Observed and blended gauge-satellite precipitation estimates perspective on meteorological drought intensity over South Sulawesi, Indonesia

    Science.gov (United States)

    Setiawan, A. M.; Koesmaryono, Y.; Faqih, A.; Gunawan, D.

    2017-01-01

    South Sulawesi province as one of the rice production center for national food security are highly influenced by climate phenomenon that lead to drought condition. This paper quantifies meteorological drought based on Standardized Precipitation Index (SPI) recommended by the World Meteorological Organization (WMO) and Consecutive Dry Days (CDD) as one of the extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). The indices were calculated by using (i) quality controlled daily and monthly observational precipitation data from 23 weather stations of various record lengths within 1967-2015 periods, and (ii) 0.05o x 0.05o blended gauge-satellite of daily and monthly precipitation estimates of the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset. Meteorological drought intensity represented by Average Duration of Drought Intensity (ADI) from three-monthly SPI (SPI3) show spatial differences characteristic between eastern and western region. Observed and CHIRPS have relatively similar perspective on meteorological drought intensity over South Sulawesi. Relatively high values of ADI and longest CDD observed mainly over south western part of study area.

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

    Directory of Open Access Journals (Sweden)

    S.A. Margulis

    2001-01-01

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

  5. Satellite cloud and precipitation property retrievals for climate monitoring and hydrological applications

    NARCIS (Netherlands)

    Wolters, E.L.A.

    2012-01-01

    This thesis presents the retrieval, evaluation, and application of cloud physical property datasets (cloud phase, cloud particle effective radius, and precipitation occurrence and intensity) obtained from Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectance measurements using the Cloud

  6. Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations

    Energy Technology Data Exchange (ETDEWEB)

    Mehran, Ali [Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering; AghaKouchak, Amir [Univ. of California, Irvine, CA (United States). Dept. of Civil and Environmental Engineering; Phillips, Thomas J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-02-25

    Numerous studies have emphasized that climate simulations are subject to various biases and uncertainties. The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies and biases for both entire data distributions and their upper tails. The results of the Volumetric Hit Index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas, but that their replication of observed precipitation over arid regions and certain sub-continental regions (e.g., northern Eurasia, eastern Russia, central Australia) is problematical. Overall, the VHI of the multi-model ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (e.g., the 75th and 90th percentiles), all climate models display low skill in simulating precipitation, except over North America, the Amazon, and central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g. western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, inter-model variations in bias over Australia and Amazonia are considerable. The Quantile Bias (QB) analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. Lastly, we found that a simple mean-field bias removal improves the overall B and VHI values, but does not make a significant improvement in these model performance metrics at high quantiles of precipitation.

  7. Evaluation of CMIP5 continental precipitation simulations relative to satellite-based gauge-adjusted observations

    Science.gov (United States)

    Mehran, A.; AghaKouchak, A.; Phillips, T. J.

    2014-02-01

    The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies, and biases for both entire distributions and their upper tails. The results of the volumetric hit index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas but that their replication of observed precipitation over arid regions and certain subcontinental regions (e.g., northern Eurasia, eastern Russia, and central Australia) is problematical. Overall, the VHI of the multimodel ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (75th and 90th percentiles), all climate models display low skill in simulating precipitation, except over North America, the Amazon, and Central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g., western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, intermodel variations in bias over Australia and Amazonia are considerable. The quantile bias analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. It is found that a simple mean field bias removal improves the overall B and VHI values but does not make a significant improvement at high quantiles of precipitation.

  8. New signatures of underground nuclear tests revealed by satellite radar interferometry

    Science.gov (United States)

    Vincent, P.; Larsen, S.; Galloway, D.; Laczniak, R.J.; Walter, W.R.; Foxall, W.; Zucca, J.J.

    2003-01-01

    New observations of surface displacement caused by past underground nuclear tests at the Nevada Test Site (NTS) are presented using interferometric synthetic aperture radar (InSAR). The InSAR data reveal both coseismic and postseismic subsidence signals that extend one kilometer or more across regardless of whether or not a surface crater was formed from each test. While surface craters and other coseismic surface effects (ground cracks, etc.) may be detectable using high resolution optical or other remote sensing techniques, these broader, more subtle subsidence signals (one to several centimeters distributed over an area 1-2 kilometers across) are not detectable using other methods [Barker et al., 1998]. A time series of interferograms reveal that the postseismic signals develop and persist for months to years after the tests and that different rates and styles of deformation occur depending on the geologic and hydrologic setting and conditions of the local test area.

  9. Satellite radar altimetry over ice. Volume 2: Users' guide for Greenland elevation data from Seasat

    Science.gov (United States)

    Zwally, H. Jay; Major, Judith A.; Brenner, Anita C.; Bindschadler, Robert A.; Martin, Thomas V.

    1990-01-01

    A gridded surface-elevation data set and a geo-referenced data base for the Seasat radar altimeter data over Antarctica are described. It is intended to be a user's guide to accompany the data provided to data centers and other users. The grid points are on a polar stereographic projection with a nominal spacing of 20 km. The gridded elevations are derived from the elevation data in the geo-referenced data base by a weighted fitting of a surface in the neighborhood of each grid point. The gridded elevations are useful for the creating smaller-scale contour maps, and examining individual elevation measurements in specific geographic areas. Tape formats are described, and a FORTRAN program for reading the data tape is listed and provided on the tape.

  10. Satellite radar altimetry over ice. Volume 4: Users' guide for Antarctica elevation data from Seasat

    Science.gov (United States)

    Zwally, H. Jay; Major, Judith A.; Brenner, Anita C.; Bindschadler, Robert A.; Martin, Thomas V.

    1990-01-01

    A gridded surface-elevation data set and a geo-referenced data base for the Seasat radar altimeter data over Greenland are described. This is a user guide to accompany the data provided to data centers and other users. The grid points are on a polar stereographic projection with a nominal spacing of 20 km. The gridded elevations are derived from the elevation data in the geo-referenced data base by a weighted fitting of a surface in the neighborhood of each grid point. The gridded elevations are useful for the creating of large-scale contour maps, and the geo-referenced data base is useful for regridding, creating smaller-scale contour maps, and examinating individual elevation measurements in specific geographic areas. Tape formats are described, and a FORTRAN program for reading the data tape is listed and provided on the tape.

  11. S-band synthetic aperture radar on-board NISAR satellite

    Science.gov (United States)

    Misra, Tapan; Bhan, Rakesh; Putrevu, Deepak; Mehrotra, Priyanka; Chakrabarty, Soumyabrata

    2016-05-01

    provide single, dual, compact and quasi-quad polarization imaging modes. Centre frequency for S-band SAR is 3200MHz with highest bandwidth of 75MHz. S-Band SAR utilizes 24 transmit receive modules (T/R Modules) to illuminate >240kms swath during transmit event and digital beam forming (DBF) on receive to reduce data rate by combining 24 receive channels and enhance SNR of the system. This paper provides details of S-band SAR system design, configuration and realization which is a challenging task since both L-band and S-band radars need to operate at same PRF and clock reference during simultaneous imaging operation. Further to this, SweepSAR technique demands PRF dithering (changing) to avoid dead gaps in the swath due to receive echo conflicting with transmit event.

  12. Arctic sea surface height variability and change from satellite radar altimetry and GRACE, 2003-2014

    Science.gov (United States)

    Armitage, Thomas W. K.; Bacon, Sheldon; Ridout, Andy L.; Thomas, Sam F.; Aksenov, Yevgeny; Wingham, Duncan J.

    2016-06-01

    Arctic sea surface height (SSH) is poorly observed by radar altimeters due to the poor coverage of the polar oceans provided by conventional altimeter missions and because large areas are perpetually covered by sea ice, requiring specialized data processing. We utilize SSH estimates from both the ice-covered and ice-free ocean to present monthly estimates of Arctic Dynamic Ocean Topography (DOT) from radar altimetry south of 81.5°N and combine this with GRACE ocean mass to estimate steric height. Our SSH and steric height estimates show good agreement with tide gauge records and geopotential height derived from Ice-Tethered Profilers. The large seasonal cycle of Arctic SSH (amplitude ˜5 cm) is dominated by seasonal steric height variation associated with seasonal freshwater fluxes, and peaks in October-November. Overall, the annual mean steric height increased by 2.2 ± 1.4 cm between 2003 and 2012 before falling to circa 2003 levels between 2012 and 2014 due to large reductions on the Siberian shelf seas. The total secular change in SSH between 2003 and 2014 is then dominated by a 2.1 ± 0.7 cm increase in ocean mass. We estimate that by 2010, the Beaufort Gyre had accumulated 4600 km3 of freshwater relative to the 2003-2006 mean. Doming of Arctic DOT in the Beaufort Sea is revealed by Empirical Orthogonal Function analysis to be concurrent with regional reductions in the Siberian Arctic. We estimate that the Siberian shelf seas lost ˜180 km3 of freshwater between 2003 and 2014, associated with an increase in annual mean salinity of 0.15 psu yr-1. Finally, ocean storage flux estimates from altimetry agree well with high-resolution model results, demonstrating the potential for altimetry to elucidate the Arctic hydrological cycle.

  13. Military Hydrology. Report 8. Feasibility of Utilizing Satellite and Radar Data in Hydrologic Forecasting.

    Science.gov (United States)

    1985-09-01

    Keown , Chief, ECG, under the general super- vision of Dr. Lewis E. Link, Chief, ESD, and Dr. John Harrison, Chief, EL. During the preparation of this... Martin , D. W., Stout, J., and Sikdar, 1). N. 1976. "Rainfall Estimation from Geo- synchronous Satellite Imagery During Daylight Hours," NOAA...Technical Report ERL 356-WMPO 7, US Department of Commerce. Griffith, C. G., Woodley, W. L., Grube, P. G., Martin , D. W., Stout, J., and Sikdar. D. N. 1978

  14. Fusing enhanced radar precipitation, in-situ hydrometeorological measurements and airborne LIDAR snowpack estimates in a hyper-resolution hydrologic model to improve seasonal water supply forecasts

    Science.gov (United States)

    Gochis, D. J.; Busto, J.; Howard, K.; Mickey, J.; Deems, J. S.; Painter, T. H.; Richardson, M.; Dugger, A. L.; Karsten, L. R.; Tang, L.

    2015-12-01

    Scarcity of spatially- and temporally-continuous observations of precipitation and snowpack conditions in remote mountain watersheds results in fundamental limitations in water supply forecasting. These limitationsin observational capabilities can result in strong biases in total snowmelt-driven runoff amount, the elevational distribution of runoff, river basin tributary contributions to total basin runoff and, equally important for water management, the timing of runoff. The Upper Rio Grande River basin in Colorado and New Mexico is one basin where observational deficiencies are hypothesized to have significant adverse impacts on estimates of snowpack melt-out rates and on water supply forecasts. We present findings from a coordinated observational-modeling study within Upper Rio Grande River basin whose aim was to quanitfy the impact enhanced precipitation, meteorological and snowpack measurements on the simulation and prediction of snowmelt driven streamflow. The Rio Grande SNOwpack and streamFLOW (RIO-SNO-FLOW) Prediction Project conducted enhanced observing activities during the 2014-2015 water year. Measurements from a gap-filling, polarimetric radar (NOXP) and in-situ meteorological and snowpack measurement stations were assimilated into the WRF-Hydro modeling framework to provide continuous analyses of snowpack and streamflow conditions. Airborne lidar estimates of snowpack conditions from the NASA Airborne Snow Observatory during mid-April and mid-May were used as additional independent validations against the various model simulations and forecasts of snowpack conditions during the melt-out season. Uncalibrated WRF-Hydro model performance from simulations and forecasts driven by enhanced observational analyses were compared against results driven by currently operational data inputs. Precipitation estimates from the NOXP research radar validate significantly better against independent in situ observations of precipitation and snow-pack increases

  15. Comparison between CNA and energetic electron precipitation: simultaneous observation by Poker Flat Imaging Riometer and NOAA satellite

    Directory of Open Access Journals (Sweden)

    Y.-M. Tanaka

    2005-07-01

    Full Text Available The cosmic noise absorption (CNA is compared with the precipitating electron flux for 19 events observed in the morning sector, using the high-resolution data obtained during the conjugate observations with the imaging riometer at Poker Flat Research Range (PFRR; 65.11° N, 147.42° W, Alaska, and the low-altitude satellite, NOAA 12. We estimate the CNA, using the precipitating electron flux measured by NOAA 12, based on a theoretical model assuming an isotropic pitch angle distribution, and quantitatively compare them with the observed CNA. Focusing on the eight events with a range of variation larger than 0.4dB, three events show high correlation between the observed and estimated CNA (correlation coefficient (r0>0.7 and five events show low correlation (r0<0.5. The estimated CNA is often smaller than the observed CNA (72% of all data for 19 events, which appears to be the main reason for the low-correlation events. We examine the assumption of isotropic pitch angle distribution by using the trapped electron flux measured at 80° zenith angle. It is shown that the CNA estimated from the trapped electron flux, assuming an isotropic pitch angle distribution, is highly correlated with the observed CNA and is often overestimated (87% of all data. The underestimate (overestimate of CNA derived from the precipitating (trapped electron flux can be interpreted in terms of the anisotropic pitch angle distribution similar to the loss cone distribution. These results indicate that the CNA observed with the riometer may be quantitatively explained with a model based on energetic electron precipitation, provided that the pitch angle distribution and the loss cone angle of the electrons are taken into account.

    Keywords. Energetic particles, precipitating – Energetic particles, trapped – Ionosphere-magnetosphere interactions

  16. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the RADARSAT-2 satellite

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Synthetic Aperture Radar (SAR)-derived high resolution wind products are calculated from high resolution SAR images of normalized radar cross section (NRCS) of the...

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

    Science.gov (United States)

    1979-05-01

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

  18. A novel approach to validate satellite soil moisture retrievals using precipitation data

    Science.gov (United States)

    Karthikeyan, L.; Kumar, D. Nagesh

    2016-10-01

    A novel approach is proposed that attempts to validate passive microwave soil moisture retrievals using precipitation data (applied over India). It is based on the concept that the expectation of precipitation conditioned on soil moisture follows a sigmoidal convex-concave-shaped curve, the characteristic of which was recently shown to be represented by mutual information estimated between soil moisture and precipitation. On this basis, with an emphasis over distribution-free nonparametric computations, a new measure called Copula-Kernel Density Estimator based Mutual Information (CKDEMI) is introduced. The validation approach is generic in nature and utilizes CKDEMI in tandem with a couple of proposed bootstrap strategies, to check accuracy of any two soil moisture products (here Advanced Microwave Scanning Radiometer-EOS sensor's Vrije Universiteit Amsterdam-NASA (VUAN) and University of Montana (MONT) products) using precipitation (India Meteorological Department) data. The proposed technique yields a "best choice soil moisture product" map which contains locations where any one of the two/none of the two/both the products have produced accurate retrievals. The results indicated that in general, VUA-NASA product has performed well over University of Montana's product for India. The best choice soil moisture map is then integrated with land use land cover and elevation information using a novel probability density function-based procedure to gain insight on conditions under which each of the products has performed well. Finally, the impact of using a different precipitation (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources) data set over the best choice soil moisture product map is also analyzed. The proposed methodology assists researchers and practitioners in selecting the appropriate soil moisture product for various assimilation strategies at both basin and continental scales.

  19. Rotational temperature of N2+ (0,2 ions from spectrographic measurements used to infer the energy of precipitation in different auroral forms and compared with radar measurements

    Directory of Open Access Journals (Sweden)

    D. Lummerzheim

    2008-05-01

    Full Text Available High resolution spectral data are used to estimate neutral temperatures at auroral heights. The data are from the High Throughput Imaging Echelle Spectrograph (HiTIES which forms part of the Spectrographic Imaging Facility (SIF, located at Longyearbyen, Svalbard in Norway. The platform also contains photometers and a narrow angle auroral imager. Quantum molecular spectroscopy is used for modelling N2+ 1NG (0,2, which serves as a diagnostic tool for neutral temperature and emission height variations. The theoretical spectra are convolved with the instrument function and fitted to measured rotational transition lines as a function of temperature. Measurements were made in the magnetic zenith, and along a meridian slit centred on the magnetic zenith. In the results described, the high spectral resolution of the data (0.08 nm allows an error analysis to be performed more thoroughly than previous findings, with particular attention paid to the correct subtraction of background, and to precise wavelength calibration. Supporting measurements were made with the Svalbard Eiscat Radar (ESR. Estimates were made from both optical and radar observations of the average energy of precipitating electrons in different types of aurora. These provide confirmation that the spectral results are in agreement with the variations observed in radar profiles. In rayed aurora the neutral temperature was highest (800 K and the energy lowest (1 keV. In a bright curling arc, the temperature at the lower border was about 550 K, corresponding to energies of 2 keV. The radar and modelling results confirm that these average values are a lower limit for an estimation of the characteristic energy. In each event the energy distribution is clearly made up of more than one spectral shape. This work emphasises the need for high time resolution as well as high spectral resolution. The present work is the first to provide rotational temperatures using a method which pays particular

  20. Mapping plasma structures in the high-latitude ionosphere using beacon satellite, incoherent scatter radar and ground-based magnetometer observations

    Directory of Open Access Journals (Sweden)

    T. Neubert

    2002-06-01

    Full Text Available In the autumn of the year 2000, four radio receivers capable of tracking various beacon satellites were set up along the southwestern coast of Greenland. They are used to reconstruct images of the ionospheric plasma density distribution via the tomographic method. In order to test and validate tomographic imaging under the highly variable conditions often prevailing in the high-latitude ionosphere, a time interval was selected when the Sondrestrom incoherent scatter radar conducted measurements of the ionospheric plasma density while the radio receivers tracked a number of beacon satellites. A comparison between two-dimensional images of the plasma density distribution obtained from the radar and the satellite receivers revealed generally good agreement between radar measurements and tomographic images. Observed discrepancies can be attributed to F region plasma patches moving through the field of view with a speed of several hundred meters per second, thereby smearing out the tomographic image. A notable mismatch occurred around local magnetic midnight when a magnetospheric substorm breakup occurred in the vicinity of southwest Greenland (identified from ground-based magnetometer observations. The breakup was associated with a sudden intensification of the westward auroral electrojet which was centered at about 69 and extended up to some 73 corrected geomagnetic latitude. Ground-based magnetometer data may thus have the potential of indicating when the tomographic method is at risk and may fail. We finally outline the application of tomographic imaging, when combined with magnetic field data, to estimate ionospheric Joule heating rates.

  1. Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

    Science.gov (United States)

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

    2008-01-01

    Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

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

    Directory of Open Access Journals (Sweden)

    L. Fita

    2009-08-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-01

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

  4. The precipitation products generation chain for the EUMETSAT Hydrological Satellite Application Facility at C.N.M.C.A.

    Science.gov (United States)

    Biron, Daniele; Melfi, Davide; Zauli, Francesco

    2008-08-01

    The EUMETSAT Satellite Application Facility in support to Hydrology (H-SAF) focuses on development of new geophysical products on precipitation, soil moisture and snow parameters and the utilisation of these parameters in hydrological models, NWP models and water management. The development phase of the H-SAF started in September 2005 under the leadership of Italian Meteorological Service. The "Centro Nazionale di Meteorologia e Climatologia Aeronautica (C.N.M.C.A.)", the Italian National Weather Centre, that physically hosts the generation chain of precipitation products, carried on activities to reach the final target: development of algorithms, validation of results, implementation of operative procedure to supply the service and to monitor the service performances. The paper shows the architectural status of the H-SAF precipitation group and stress the component of operations. It is shown the full correspondence with the EUMETSAT approved H-SAF documents, in particular the Algorithm Theoretical Design Document (ATDD), where products characteristics are referenced. Are also reported the first results, produced during the first H-SAF Workshop, held in Rome in October 2007, of validation activities performed on version 1 products, and last results of products distribution to beta-users in preparation of distributing version 2.

  5. Estimation of an eartquake focal mechanism from a satellite radar interferogram:Application to the December 4, 1992 Landers aftershock

    Science.gov (United States)

    Feigl, Kurt L.; Sergent, Arnaud; Jacq, Dominique

    1995-05-01

    Interferometric fringes generated by the phase difference between a pair of synthetic-aperture radar images acquired by the ERS-1 satellite were used to estimate the focal mechanism of a small, shallow thrust earthquake. The inversion procedure is an iterative, linerarized least-squares algorithm based on a standard elastic dislocation formulation for coseismic displacements. The preferred estimate is a thrust focal mechanism with its hypocenter at (N34.35 deg +/- 0.4 km, W 116.91 deg +/- 0.2 km, 2.6 +/- 0.3 km depth) on a plane dipping southward beneath the San Bernardino Mountains, with a moment magnitude of 5.4. The strike, dip and rake are N106 deg E +/- 7 deg, 28 deg +/- 4 deg, and 93 deg +/- 4deg, respectively on a fault 3.1 +/- 0.5 km wide and 2.9 +/- 0.4 km long. The precision of these estimates is competitive with seismological determinations.

  6. A multi-subwaveform parametric retracker of the radar satellite altimetric waveform and recovery of gravity anomalies over coastal oceans

    Institute of Scientific and Technical Information of China (English)

    HWANG; CheinWay

    2010-01-01

    The quality of satellite radar altimetric data is very important in studies of geodesy,geophysics,and oceanography.Over coastal oceans,altimeter waveforms are contaminated by the terrain and physical environments so that the accuracy of altimeter data is lower than that over open oceans.Here we develop a new multi-subwaveform parametric retracker(MSPR) to improve the quality of altimeter data for the recovery of gravity anomaly in coastal oceans.The least squares collocation method is used to recover the residual gravity anomaly over the coastal water from altimetric data.The waveform data records from Geosat/GM around Taiwan Island are practically retracked with MSPR.When compared with the Taiwan geoid height,the results retracked by MSPR are more accurate than those retracked by the well-known β-5-parmeter method and from the geophysical data records(GDRs).The gravity anomalies over Taiwan coastal waters are calculated from the retracked altimeter data with the least squares collocation.When we compared gravity anomalies computed using altimeter GDRs with the ship-borne gravity data over Taiwan coastal ocean,we found that the results from retracked data are more accurate than those from GDRs.

  7. Combining weather radar nowcasts and numerical weather prediction models to estimate short-term quantitative precipitation and uncertainty

    DEFF Research Database (Denmark)

    Jensen, David Getreuer

    -TREC based REM. The filter is calibrated against atmospheric observations of radial velocity measured by a Doppler radar. The results from pooled skill scores from 16 events show only a slight improvement. The positive contribution, from applying Kalman filtering, is increased stability computed...

  8. Contemporary ground-based and satellite precipitating system characterization for desertification studies in Southern Italy

    Directory of Open Access Journals (Sweden)

    M. Casazza

    2008-07-01

    Full Text Available During the research project RIADE (Ricerca Integrata per l'Applicazione di tecnologie e processi innovativi per la lotta alla DEsertificazione, devoted to the study on the potential risk of desertification in Southern Italy, a particular attention has been paid also to the analysis of precipitations from three surface stations (Licata, Sicily; Rotondella, Basilicata; Surigheddu, Sardinia in order to improve the knowledge derived from the most modern climatological studies related to this subject. The point of view adopted is to better define the precipitation microphysical properties (in particular, the Drop Size Distribution, DSD, and its moments, which are deeply related to the cloud system that generates the precipitation events. In particular we have used a newly introduced Convective Stratiform discrimination technique, that allowed us to observe a prevalence of events, concentrated along Winter (Wi season, of different microphysical nature. In fact the prevailing Stratiform nature is related to Licata station, while for Surigheddu and for Rotondella the nature is mainly Convective. This distinction is related to the presence of drops of bigger dimensions and more intense precipitations in the latter case, while, in the former case, a prevalence of smaller drops and a less intense precipitation is recorded. This confirms the distinctive belonging to three different climatic regions, as indicated in the study by Brunetti et al. (2006. Our findings are important in the framework of desertification studies, because the cause of desertification can be related either to fertile soils removal (in the case of Convective events or to lack of precipitated water (in the case of Stratiform events. We have also analysed a sub-set of ten events, with contemporary presence of data from VIS/IR channels of METEOSAT-7, SSM/I data from F13 and MODIS data from Terra platform. This has been done both to confirm the findings of PLUDIX data analysis (which

  9. A Preliminary Analysis of Precipitation Properties and Processes during NASA GPM IFloodS

    Science.gov (United States)

    Carey, Lawrence; Gatlin, Patrick; Petersen, Walt; Wingo, Matt; Lang, Timothy; Wolff, Dave

    2014-01-01

    The Iowa Flood Studies (IFloodS) is a NASA Global Precipitation Measurement (GPM) ground measurement campaign, which took place in eastern Iowa from May 1 to June 15, 2013. The goals of the field campaign were to collect detailed measurements of surface precipitation using ground instruments and advanced weather radars while simultaneously collecting data from satellites passing overhead. Data collected by the radars and other ground instruments, such as disdrometers and rain gauges, will be used to characterize precipitation properties throughout the vertical column, including the precipitation type (e.g., rain, graupel, hail, aggregates, ice crystals), precipitation amounts (e.g., rain rate), and the size and shape of raindrops. The impact of physical processes, such as aggregation, melting, breakup and coalescence on the measured liquid and ice precipitation properties will be investigated. These ground observations will ultimately be used to improve rainfall estimates from satellites and in particular the algorithms that interpret raw data for the upcoming GPM mission's Core Observatory satellite, which launches in 2014. The various precipitation data collected will eventually be used as input to flood forecasting models in an effort to improve capabilities and test the utility and limitations of satellite precipitation data for flood forecasting. In this preliminary study, the focus will be on analysis of NASA NPOL (S-band, polarimetric) radar (e.g., radar reflectivity, differential reflectivity, differential phase, correlation coefficient) and NASA 2D Video Disdrometers (2DVDs) measurements. Quality control and processing of the radar and disdrometer data sets will be outlined. In analyzing preliminary cases, particular emphasis will be placed on 1) documenting the evolution of the rain drop size distribution (DSD) as a function of column melting processes and 2) assessing the impact of range on ground-based polarimetric radar estimates of DSD properties.

  10. Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

    Directory of Open Access Journals (Sweden)

    R. Zubieta

    2017-07-01

    Full Text Available In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG (product/final run as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015 when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively. In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ∼  20 %. Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin. GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins, probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

  11. Hydrological modeling of the Peruvian-Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset

    Science.gov (United States)

    Zubieta, Ricardo; Getirana, Augusto; Carlo Espinoza, Jhan; Lavado-Casimiro, Waldo; Aragon, Luis

    2017-07-01

    In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM) have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM) mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG) (product/final run) as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015) when all datasets are available. TRMM products (TMPA V7 and TMPA RT datasets) and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 %, respectively). In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected ( ˜ 20 %). Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali Basin). GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Marañón and Napo basins), probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon.

  12. Intercomparison of Vertical Structure of Storms Revealed by Ground-Based (NMQ and Spaceborne Radars (CloudSat-CPR and TRMM-PR

    Directory of Open Access Journals (Sweden)

    Veronica M. Fall

    2013-01-01

    Full Text Available Spaceborne radars provide great opportunities to investigate the vertical structure of clouds and precipitation. Two typical spaceborne radars for such a study are the W-band Cloud Profiling Radar (CPR and Ku-band Precipitation Radar (PR, which are onboard NASA’s CloudSat and TRMM satellites, respectively. Compared to S-band ground-based radars, they have distinct scattering characteristics for different hydrometeors in clouds and precipitation. The combination of spaceborne and ground-based radar observations can help in the identification of hydrometeors and improve the radar-based quantitative precipitation estimation (QPE. This study analyzes the vertical structure of the 18 January, 2009 storm using data from the CloudSat CPR, TRMM PR, and a NEXRAD-based National Mosaic and Multisensor QPE (NMQ system. Microphysics above, within, and below the melting layer are studied through an intercomparison of multifrequency measurements. Hydrometeors’ type and their radar scattering characteristics are analyzed. Additionally, the study of the vertical profile of reflectivity (VPR reveals the brightband properties in the cold-season precipitation and its effect on the radar-based QPE. In all, the joint analysis of spaceborne and ground-based radar data increases the understanding of the vertical structure of storm systems and provides a good insight into the microphysical modeling for weather forecasts.

  13. Rapid damage mapping for the 2015 M7.8 Gorkha earthquake using synthetic aperture radar data from COSMO-SkyMed and ALOS-2 satellites

    Science.gov (United States)

    Yun, Sang-Ho; Hudnut, Kenneth W.; Owen, Susan; Webb, Frank; Simons, Mark; Sacco, Patrizia; Gurrola, Eric; Manipon, Gerald; Liang, Cunren; Fielding, Eric; Milillo, Pietro; Hua, Hook; Coletta, Alessandro

    2015-01-01

    The 25 April 2015 Mw 7.8 Gorkha earthquake caused more than 8000 fatalities and widespread building damage in central Nepal. The Italian Space Agency’s COSMO–SkyMed Synthetic Aperture Radar (SAR) satellite acquired data over Kathmandu area four days after the earthquake and the Japan Aerospace Exploration Agency’s Advanced Land Observing Satellite-2 SAR satellite for larger area nine days after the mainshock. We used these radar observations and rapidly produced damage proxy maps (DPMs) derived from temporal changes in Interferometric SAR coherence. Our DPMs were qualitatively validated through comparison with independent damage analyses by the National Geospatial-Intelligence Agency and the United Nations Institute for Training and Research’s United Nations Operational Satellite Applications Programme, and based on our own visual inspection of DigitalGlobe’s WorldView optical pre- versus postevent imagery. Our maps were quickly released to responding agencies and the public, and used for damage assessment, determining inspection/imaging priorities, and reconnaissance fieldwork.

  14. Global Precipitation Measurement (GPM) Mission: Precipitation Processing System (PPS) GPM Mission Gridded Text Products Provide Surface Precipitation Retrievals

    Science.gov (United States)

    Stocker, Erich Franz; Kelley, O.; Kummerow, C.; Huffman, G.; Olson, W.; Kwiatkowski, J.

    2015-01-01

    In February 2015, the Global Precipitation Measurement (GPM) mission core satellite will complete its first year in space. The core satellite carries a conically scanning microwave imager called the GPM Microwave Imager (GMI), which also has 166 GHz and 183 GHz frequency channels. The GPM core satellite also carries a dual frequency radar (DPR) which operates at Ku frequency, similar to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar, and a new Ka frequency. The precipitation processing system (PPS) is producing swath-based instantaneous precipitation retrievals from GMI, both radars including a dual-frequency product, and a combined GMIDPR precipitation retrieval. These level 2 products are written in the HDF5 format and have many additional parameters beyond surface precipitation that are organized into appropriate groups. While these retrieval algorithms were developed prior to launch and are not optimal, these algorithms are producing very creditable retrievals. It is appropriate for a wide group of users to have access to the GPM retrievals. However, for researchers requiring only surface precipitation, these L2 swath products can appear to be very intimidating and they certainly do contain many more variables than the average researcher needs. Some researchers desire only surface retrievals stored in a simple easily accessible format. In response, PPS has begun to produce gridded text based products that contain just the most widely used variables for each instrument (surface rainfall rate, fraction liquid, fraction convective) in a single line for each grid box that contains one or more observations.This paper will describe the gridded data products that are being produced and provide an overview of their content. Currently two types of gridded products are being produced: (1) surface precipitation retrievals from the core satellite instruments GMI, DPR, and combined GMIDPR (2) surface precipitation retrievals for the partner constellation

  15. 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

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

    Directory of Open Access Journals (Sweden)

    Bahjat Alhammoud

    2014-05-01

    Full Text Available The Mediterranean region is characterized by its vulnerability to changes in the water cycle, with the impact of global warming on the water resources being one of the major concerns in social, economical and scientific ambits. Even if precipitation is the best-known term of the Mediterranean water budget, large uncertainties remain due to the lack of suitable offshore observational data. In this study, we use the data provided by the Advanced Microwave Sounding Unit-B (AMSU-B on board NOAA satellites to detect and analyze precipitating and convective events over the last decade at spatial resolution of 0.2° latitude × 0.2° longitude. AMSU-B observation shows that rain occurrence is widespread over the Mediterranean in wintertime while reduced in the eastern part of the basin in summer. Both precipitation and convection occurrences display a weak diurnal cycle over sea. In addition, convection occurrences, which are essentially located over land during summertime, shift to mostly over the sea during autumn with maxima in the Ionian sub-basin and the Adriatic Sea. Precipitation occurrence is also inferred over the sea from two other widely used climatological datasets, HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data and the European Centre for Medium-Range Weather Forecasts (ECMWF reanalysis interim (ERA-Interim. There is generally a rather fair agreement between these climatologies for describing the large-scale patterns such as the strong latitudinal gradient of rain and eastward rain signal propagation. Furthermore, the higher spatial resolution of AMSU-B measurements (16 km at nadir gives access to mesoscale details in the region (e.g., coastal areas. AMSU-B measurements show less rain occurrences than HOAPS during wintertime, thereby suggesting that some of the thresholds used in our method might be too stringent during this season. We also observed that convection occurrences in ERA-Interim are systematically

  17. 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...

  18. Numerical simulation of heavy precipitation events using mesoscale weather forecast models. Validation with radar data and diagnosis of the atmospheric moisture budget; Numerische Simulation von Starkniederschlagsereignissen mit mesoskaligen Wettervorhersagemodellen. Ueberpruefung mit Radar-Daten und Diagnose der atmosphaerischen Wasserbilanz

    Energy Technology Data Exchange (ETDEWEB)

    Keil, C.

    2000-07-01

    Convective precipitation systems contribute substantially to the summertime rainfall maximum in the northern Alpine region. The capability of mesoscale weather forecast models in capturing such heavy precipitation events is investigated. The complementary application of so far hardly used areal radar data and conventional rain gauge observations enables a case-study-type evaluation of summertime precipitation episodes. Different rainfall episodes are simulated with the former operational model (DM, meshsize 14 km) of Deutscher Wetterdienst (DWD). The influence of the horizontal resolution and the parameterization of moist convection is subsequently studied with a higher resolution atmospheric model (MC2, meshsize 2 km). Diagnostic studies on the atmospheric water budget regarding the rainfall episode, which instigated the Oder-flood in summer 1997, allow an examination of the origin of the moisture and the genesis of the copious precipitation. (orig.) [German] Konvektive Niederschlagssysterne tragen im Nordalpenraum wesentlich zum sommerlichen Niederschlagsmaximum bei. Die Faehigkeit mesoskaliger Wettervorhersagemodelle, solche Starkniederschlagsereignisse zu erfassen, wird in dieser Arbeit untersucht. Durch den komplementaeren Gebrauch von, bisher kaum genutzten, flaechendeckenden Radardaten und konventionellen Niederschlagsmessungen des Bodenmessnetzes werden Modellergebnisse sommerlicher Niederschlagssysteme fallstudienhaft detailliert ueberprueft. Fuer verschiedene Starkniederschlagsereignisse werden dazu Modellsimulationen mit dem in den 90er Jahren operationellen Modell (DM, Maschenweite 14 km) des Deutschen Wetterdienstes (DWD) durchgefuehrt. Zur Untersuchung des Einflusses der horizontalen Maschenweite und der Niederschlagsparametrisierung werden ferner numerische Simulationen mit einem hoeher aufloesdenden Atmosphaerenmodell (MC2, Maschenweite 2 km) behandelt. Anhand diagnostischer Untersuchungen der atmosphaerischen Wasserbilanz laesst sich ausserdem die

  19. Detection of Weather Radar Clutter

    DEFF Research Database (Denmark)

    Bøvith, Thomas

    2008-01-01

    Weather radars provide valuable information on precipitation in the atmosphere but due to the way radars work, not only precipitation is observed by the weather radar. Weather radar clutter, echoes from non-precipitating targets, occur frequently in the data, resulting in lowered data quality....... Especially in the application of weather radar data in quantitative precipitation estimation and forecasting a high data quality is important. Clutter detection is one of the key components in achieving this goal. This thesis presents three methods for detection of clutter. The methods use supervised...... and precipitating and non-precipitating clouds. Another method uses the difference in the motion field of clutter and precipitation measured between two radar images. Furthermore, the direction of the wind field extracted from a weather model is used. The third method uses information about the refractive index...

  20. Statistical and Hydrological Evaluation of TRMM-Based Multi-Satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the Latest Satellite Precipitation Products 3B42V7 Ready for Use in Ungauged Basins?

    Science.gov (United States)

    Xue, Xianwu; Hong, Yang; Limaye, Ashutosh S.; Gourley, Jonathan; Huffman, George J.; Khan, Sadiq Ibrahim; Dorji, Chhimi; Chen, Sheng

    2013-01-01

    The objective of this study is to quantitatively evaluate the successive Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products and further to explore the improvements and error propagation of the latest 3B42V7 algorithm relative to its predecessor 3B42V6 using the Coupled Routing and Excess Storage (CREST) hydrologic model in the mountainous Wangchu Basin of Bhutan. First, the comparison to a decade-long (2001-2010) daily rain gauge dataset reveals that: 1) 3B42V7 generally improves upon 3B42V6s underestimation both for the whole basin (bias from -41.15 to -8.38) and for a 0.250.25 grid cell with high-density gauges (bias from -40.25 to 0.04), though with modest enhancement of correlation coefficients (CC) (from 0.36 to 0.40 for basin-wide and from 0.37 to 0.41 for grid); and 2) 3B42V7 also improves its occurrence frequency across the rain intensity spectrum. Using the CREST model that has been calibrated with rain gauge inputs, the 3B42V6-based simulation shows limited hydrologic prediction NSCE skill (0.23 in daily scale and 0.25 in monthly scale) while 3B42V7 performs fairly well (0.66 in daily scale and 0.77 in monthly scale), a comparable skill score with the gauge rainfall simulations. After recalibrating the model with the respective TMPA data, significant improvements are observed for 3B42V6 across all categories, but not as much enhancement for the already well-performing 3B42V7 except for a reduction in bias (from -26.98 to -4.81). In summary, the latest 3B42V7 algorithm reveals a significant upgrade from 3B42V6 both in precipitation accuracy (i.e., correcting the underestimation) thus improving its potential hydrological utility. Forcing the model with 3B42V7 rainfall yields comparable skill scores with in-situ gauges even without recalibration of the hydrological model by the satellite precipitation, a compensating approach often used but not favored by the hydrology community, particularly in ungauged basins.

  1. Long Term Monitoring of Ground Motions in Upper Silesia Coal Basin (USCB) Using Satellite Radar Interferometry

    Science.gov (United States)

    Graniczny, Marek; Przylucka, Maria; Kowalski, Zbigniew

    2016-08-01

    Subsidence hazard and risk within the USCB are usually connected with the deep coal mining. In such cases, the surface becomes pitted with numerous collapse cavities or basins which depth may even reach tens of meters. The subsidence is particularly dangerous because of causing severe damage to gas and water pipelines, electric cables, and to sewage disposal systems. The PGI has performed various analysis of InSAR data in this area, including all three SAR bands (X, C and L) processed by DInSAR, PSInSAR and SqueeSAR techniques. These analyses of both conventional and advanced DInSAR approaches have proven to be effective to detect the extent and the magnitude of mining subsidence impact on urban areas. In this study an analysis of two series of subsequent differential interferograms obtained in the DInSAR technique are presented. SAR scenes are covering two periods and were acquired by two different satellites: ALOS-P ALSAR data from 22/02/2007- 27/05/2008 and TerraSAR-X data from 05/07/2011-21/06/2012. The analysis included determination of the direction and development of subsidence movement in relation to the mining front and statistic comparison between range and value of maximum subsidence detected for each mining area. Detailed studies were performed for Bobrek-Centrum mining area. They included comparison of mining fronts and location of the extracted coal seams with the observed subsidence on ALOS-P ALSAR InSAR interferograms. The data can help in estimation not only the range of the subsidence events, but also its value, direction of changes and character of the motion.

  2. Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

    Science.gov (United States)

    Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

    2016-12-01

    In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

  3. Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

    Science.gov (United States)

    Liu, Zhong; Heo, Gil

    2015-01-01

    Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

  4. On Some Aspects of Precipitation over Tropical Indian Ocean Using Satellite Data

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.; Sreejith, O.P.

    rainfall. The next most important error, due to fair weather bias, arises due to the lack of precipitation measurements caused by the lows, depressions and cyclones, which most of the ships try to avoid. This problem is especially true in the case... of the Bay of Bengal, which is frequented by lows, depressions and cyclones throughout the year. Major drawbacks to studies of the rainfall over a particular area or region are the coverage of the instruments and their accuracy in measuring the areal...

  5. Dome growth, collapse, and valley fill at Soufrière Hills Volcano, Montserrat, from 1995 to 2013: Contributions from satellite radar measurements of topographic change

    Science.gov (United States)

    Arnold, D. W. D.; Biggs, J.; Wadge, G.; Ebmeier, S. K.; Odbert, H. M.; Poland, Michael P.

    2016-01-01

    Frequent high-resolution measurements of topography at active volcanoes can provide important information for assessing the distribution and rate of emplacement of volcanic deposits and their influence on hazard. At dome-building volcanoes, monitoring techniques such as LiDAR and photogrammetry often provide a limited view of the area affected by the eruption. Here, we show the ability of satellite radar observations to image the lava dome and pyroclastic density current deposits that resulted from 15 years of eruptive activity at Soufrière Hills Volcano, Montserrat, from 1995 to 2010. We present the first geodetic measurements of the complete subaerial deposition field on Montserrat, including the lava dome. Synthetic aperture radar observations from the Advanced Land Observation Satellite (ALOS) and TanDEM-X mission are used to map the distribution and magnitude of elevation changes. We estimate a net dense-rock equivalent volume increase of 108 ± 15M m3 of the lava dome and 300 ± 220M m3 of talus and subaerial pyroclastic density current deposits. We also show variations in deposit distribution during different phases of the eruption, with greatest on-land deposition to the south and west, from 1995 to 2005, and the thickest deposits to the west and north after 2005. We conclude by assessing the potential of using radar-derived topographic measurements as a tool for monitoring and hazard assessment during eruptions at dome-building volcanoes.

  6. Volcanic and Tectonic Activity in the Red Sea Region (2004-2013): Insights from Satellite Radar Interferometry and Optical Imagery

    KAUST Repository

    Xu, Wenbin

    2015-04-01

    Studying recent volcanic and tectonic events in the Red Sea region is important for improving our knowledge of the Red Sea plate boundary and for regional geohazard assessments. However, limited information has been available about the past activity due to insufficient in-situ data and remoteness of some of the activity. In this dissertation, I have used satellite remote sensing to derive new information about several recent volcanic and tectonic events in the Red Sea region. I first report on three volcanic eruptions in the southern Red Sea, the 2007-8 Jebel at Tair eruption and the 2011-12 & 2013 Zubair eruptions, which resulted in formation of two new islands. Series of high- resolution optical images were used to map the extent of lava flows and to observe and analyze the growth and destructive processes of the new islands. I used Interferometric Synthetic Aperture Radar (InSAR) data to study the evolution of lava flows, to estimate their volumes, as well as to generate ground displacements maps, which were used to model the dikes that fed the eruptions. I then report on my work of the 2009 Harrat Lunayyir dike intrusion and the 2004 Tabuk earthquake sequence in western Saudi Arabia. I used InSAR observations and stress calculations to study the intruding dike at Harrat Lunayyir, while I combined InSAR data and Bayesian estimation to study the Tabuk earthquake activity. The key findings of the thesis are: 1) The recent volcanic eruptions in the southern Red Sea indicate that the area is magmatically more active than previously acknowledged and that a rifting episode has been taken place in the southern Red Sea; 2) Stress interactions between an ascending dike intrusion and normal faulting on graben-bounding faults above the dike can inhibit vertical propagation of magma towards the surface; 3) InSAR observations can improve locations of shallow earthquakes and fault model uncertainties are useful to associate earthquake activity with mapped faults; 4). The

  7. High-Resolution Mapping of Sea Ice, Icebergs and Growlers in Kongsfjorden, Svalbard, using Ground Based Radar, Satellite, and UAV

    Science.gov (United States)

    Lauknes, T. R.; Rouyet, L.; Solbø, S. A.; Sivertsen, A.; Storvold, R.; Akbari, V.; Negrel, J.; Gerland, S.

    2016-12-01

    The dynamics of sea ­ice has a well­ recognized role in the climate system and its extent and evolution is impacted by the global warming. In addition, calving of icebergs and growlers at the tidewater glacier fronts is a component of the mass loss in polar regions. Understanding of calving and ice ­ocean interaction, in particular at tidewater glacier front remains elusive, and a problematic uncertainty in climate change projections. Studying the distribution, volumetry and motion of sea ­ice, icebergs and growlers is thus essential to understand their interactions with the environment in order to be able to predict at short­term their drifts, e.g. to mitigate the risk for shipping, and at longer term the multiple relations with climate changes. Here, we present the results from an arctic fieldwork campaign conducted in Kongsfjorden, Svalbard in April 2016, where we used different remote sensing instruments to observe dynamics of sea ice, icebergs, and growlers. We used a terrestrial radar system, imaging the study area every second minute during the observation period. At the front of the Kronebreen glacier, calving events can be detected and the drift of the generated icebergs and growlers tracked with unprecedented spatial and temporal resolution. During the field campaign, we collected four Radarsat-2 quad-pol images, that will be used to classify the different types of sea ice. In addition, we used small unmanned aircraft (UAS) instrumented with high resolution cameras capturing HD video and still pictures. This allows to map and measure the size of icebergs and ice floes. Such information is essential to validate sensitivity and detection limits from the ground and satellite based measurements.

  8. Developing an Ice Volume Estimate of Jarvis Glacier, Alaska, using Ground-Penetrating Radar and High Resolution Satellite Imagery

    Science.gov (United States)

    Wu, N. L.; Campbell, S. W.; Douglas, T. A.; Osterberg, E. C.

    2013-12-01

    Jarvis Glacier is an important water source for Fort Greely and Delta Junction, Alaska. Yet with warming summer temperatures caused by climate change, the glacier is melting rapidly. Growing concern of a dwindling water supply has caused significant research efforts towards determining future water resources from spring melt and glacier runoff which feeds the community on a yearly basis. The main objective of this project was to determine the total volume of the Jarvis Glacier. In April 2012, a centerline profile of the Jarvis Glacier and 15 km of 100 MHz ground-penetrating radar (GPR) profiles were collected in cross sections to provide ice depth measurements. These depth measurements were combined with an interpreted glacier boundary (depth = 0 m) from recently collected high resolution WorldView satellite imagery to estimate total ice volume. Ice volume was calculated at 0.62 km3 over a surface area of 8.82 km2. However, it is likely that more glacier-ice exists within Jarvis Glacier watershed considering the value calculated with GPR profiles accounts for only the glacier ice within the valley and not for the valley side wall ice. The GLIMS glacier area database suggests that the valley accounts for approximately 50% of the total ice covered watershed. Hence, we are currently working to improve total ice volume estimates which incorporate the surrounding valley walls. Results from this project will be used in conjunction with climate change estimates and hydrological properties downstream of the glacier to estimate future water resources available to Fort Greely and Delta Junction.

  9. Simultaneous Antarctic Gravity Wave Observations in PMCs from the AIM Satellite and PMSE Observations from PANSY Radar

    Science.gov (United States)

    Buzanowicz, M. E.; Yue, J.; Russell, J. M., III; Sato, K.; Kohma, M.; Nakamura, T.

    2015-12-01

    Polar mesospheric clouds (PMCs) are high-altitude ice clouds that form in the cold summer mesopause region due to adiabatic cooling caused by an upwelling induced by the global meridional circulation, which is driven by gravity wave dissipation and forcing. Polar mesospheric summer echoes (PMSEs) are strong coherent echoes also observed in the polar summer mesosphere and are considered to be related to ionization and the small-scale structure associated with PMCs, with their origins thought to be strongly related. The peak PMSE height can be located slightly below the summer mesopause temperature minimum but above the PMC altitude. Upward propagating atmospheric gravity waves (AGWs) are usually considered to be the cause of the wave patterns seen in PMCs. Monitoring PMCs and PMSEs will provide important tools in detecting climate change in the upper atmosphere and a better understanding of the earth-climate system. The science goal I plan to accomplish is to investigate the possibility of a connection between gravity wave perturbation characteristics in PMCs from the AIM (Aeronomy of Ice in the Mesosphere) satellite and PMSE structures observed by PANSY (program of the Antarctic Syowa MST/IS radar). Data from the CIPS instrument onboard AIM, PANSY, and AIRS (Atmospheric Infrared Sounder) will be used. AIM provides a two-dimensional horizontal view of the atmosphere dynamics embedded in PMCs, while PANSY provides a vertical view of PMSEs and gravity waves with high temporal resolution. The combination of AIM and PANSY will provide a three-dimensional view of the atmosphere, AGWs, PMCs and PMSEs. AIRS provides information about AGWs in the stratosphere. Wave analysis of the Fast Fourier Transform or a wavelet analysis will be used to complete the science goal. AIRS will be used to examine how lower atmosphere meteorology may impact the PMC and PMSE structures.

  10. Estimation of areal precipitation based on rainfall data and X-band radar images in the Venero-Claro Basin (Ávila, Spain)

    Science.gov (United States)

    Guardiola-Albert, Carolina; River-Honegger, Carlos; Yagüe, Carlos; Agut, Robert Monjo i.; Díez-Herrero, Andrés; María Bodoque, José; José Tapiador, Francisco

    2015-04-01

    The aim of this work is to estimate the spatial-temporal rainfall during precipitation events with hydrological response in Venero-Claro Basin (Avila, Spain). In this small mountainous basin of 15km2, flood events of different magnitudes have been often registered. Therefore, rainfall estimation is essential to calibrate and validate hydrological models, and hence implies an improvement in the objectivity of risk studies and its predictive and preventive capacity. The geostatistical merging method of ordinary kriging of the errors (OKRE) has been applied. This technique has been already used by several authors to merge C-band radar and dense rain gauge networks. Here it is adapted to estimate hourly rainfall accumulations over the area with observations from one of the 5 existing X-band radar in Spain and 7 rain gauges located in the zone. Verification of the results has been performed through cross-validation comparing the estimation error of the OKRE with the one obtained adjusting the Marshall-Palmer relation. Analyzed errors are bias, the Hanseen-Kuiper coefficient and the relative mean root transformed error. Results have an average error of 15%, distinguishing quite well between dry and wet periods.

  11. The Impacts of Satellite Remotely Sensed Winds and Total Precipitable Vapour in WRF Tropical Cyclone Track Forecasts

    Directory of Open Access Journals (Sweden)

    Diandong Ren

    2016-01-01

    Full Text Available This study assesses the impact assimilating the scatterometer near-surface wind observations and total precipitable water from the SSMI, into WRF on genesis and track forecasting of four tropical cyclones (TCs. These TCs are selected to be representative of different intensity categories and basins. Impact is via a series of data denial experiments that systematically exclude the remote sensed information. Compared with the control case, in which only the final analysis atmospheric variables are used to initialize and provide the lateral boundary conditions, the data assimilation runs performed consistently better, but with very different skill levels for the different TCs. Eliassen-Palm flux analyses are employed. It is confirmed that if a polar orbital satellite footprint passes over the TC’s critical genesis region, the forecast will profit most from assimilating the remotely sensed information. If the critical genesis region lies within an interorbital gap then, regardless of how strong the TC later becomes (e.g., Katrina 2005, the improvement from assimilating near-surface winds and total precipitable water in the model prediction is severely limited. This underpins the need for a synergy of data from different scatterometers/radiometers. Other approaches are suggested to improve the accuracy in the prediction of TC genesis and tracks.

  12. Disentangling the Relationships between Net Primary Production and Precipitation in Southern Africa Savannas Using Satellite Observations from 1982 to 2010

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2013-08-01

    Full Text Available To obtain a better understanding of the variability in net primary production (NPP in savannas is important for the study of the global carbon cycle and the management of this particular ecosystem. Using satellite and precipitation data sets, we investigated the variations in NPP in southern African savannas from 1982 to 2010, and disentangled the relationships between NPP and precipitation by land cover classes and mean annual precipitation (MAP gradients. Specifically, we evaluate the utility of the third generation Global Inventory Monitoring and Modeling System (GIMMS3g normalized difference vegetation index (NDVI dataset, in comparison with Moderate-resolution Imaging Spectroradiometer (MODIS derived NPP products, and find strong relationships between the overlapping data periods (2000–2010, such that we can apply our model to derive NPP estimates to the full 29-year NDVI time-series. Generally, the northern portion of the study area is characterized by high NPP and low variability, whereas the southern portion is characteristic of low NPP and high variability. During the period 1982 through 2010, NPP has reduced at a rate of −2.13 g∙C∙m−2∙yr−1 (p < 0.1, corresponding to a decrease of 6.7% over 29 years, and about half of bush and grassland savanna has experienced a decrease in NPP. There is a significant positive relationship between mean annual NPP and MAP in bush and grassland savannas, but no significant relationship is observed in tree savannas. The relationship between mean annual NPP and MAP varies with increases in MAP, characterized as a linear relationship that breaks down when MAP exceeding around 850–900 mm.

  13. MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data

    Science.gov (United States)

    Beck, Hylke E.; van Dijk, Albert I. J. M.; Levizzani, Vincenzo; Schellekens, Jaap; Miralles, Diego G.; Martens, Brecht; de Roo, Ad

    2017-01-01

    Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979-2015 with a 3-hourly temporal and 0.25° spatial resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite- and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0 % of the stations and a median R of 0.67 vs. 0.44-0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments (http://www.gloh2o.org.

  14. Comparison of atmospheric instability indices derived from radiosonde observations and precipitation values measured with a weather radar and a rain gauge network in Sao Paulo, Brazil.

    Science.gov (United States)

    Alves, Mauro; Martin, Inacio; Shkevov, Rumen; Gusev, Anatoly; De Abreu, Alessandro

    2016-07-01

    Radio soundings are carried out daily in more than 800 stations throughout the world. The data collected in the soundings are used in many meteorological applications such as numerical weather prediction and climate models. Despite the relatively large number of sounding stations, they are unevenly distributed over the globe. It is generally assumed that the desired distance between stations is 300 km. In this study, we performed a comparison of 20 soundings of two stations located 85 km apart (State of São Paulo, Brazil; 23.511811° S, 46.637528° W, and 23.212578° S, 45.866581° W) to determine whether there is a concordance between atmospheric instability indices derived from the data collected by soundings at the these different locations. Additionally, precipitation data obtained by a meteorological radar and a rain gauge network during the same period as the soundings are compared to the stability indices to establish a correlation between precipitation values and these indices.

  15. Engineering implementation of satellite calibration for radar%雷达卫星标校的工程实现研究

    Institute of Scientific and Technical Information of China (English)

    郭佳意; 钮俊清

    2014-01-01

    为确保雷达系统的测量精度,给出了一种用于标校雷达动态跟踪过程中系统误差的工程实现方法--卫星标校法。该方法通过观测卫星轨迹,将量测值与真实星历值比对,通过最优化解法标定雷达的系统误差。考虑雷达结构特点导致的误差和大气折射误差修正后的残余误差,建立了卫星标校的系统误差模型。最后,采用实测数据验证了该误差模型的可行性与可靠性。该方法在标校过程中不受人为、天气等因素影响,可以适应雷达的动态技术状态。%To guarantee the measurement precision of radar system, this paper presents an engineering implementation method, named satellite calibration, used for calibrating the system error in the course of radar dynamic tracking. This method contrasts the measurement value to the real ephemeris value by observing the satellite track, and calibrate the radar’s system errors by using the optimal solution. Considering that the errors caused by the features of radar configuration and the residual errors after correction of atmosphere refraction errors, the author sets up a system error model for satellite calibration, and finally proves the feasibility and reliability of this proposed error model using the test data. As this method is not affected by some factitious and weather factors, it can be also adapted to radar’s dynamic technical state.

  16. Freeze/thaw conditions at periglacial landforms in Kapp Linné, Svalbard, investigated using field observations, in situ, and radar satellite monitoring

    Science.gov (United States)

    Eckerstorfer, M.; Malnes, E.; Christiansen, H. H.

    2017-09-01

    In periglacial landscapes, snow dynamics and microtopography have profound implications of freeze-thaw conditions and thermal regime of the ground. We mapped periglacial landforms at Kapp Linné, central Svalbard, where we chose six widespread landforms (solifluction sheet, nivation hollow, palsa and peat in beach ridge depressions, raised marine beach ridge, and exposed bedrock ridge) as study sites. At these six landforms, we studied ground thermal conditions, freeze-thaw cycles, and snow dynamics using a combination of in situ monitoring and C-band radar satellite data in the period 2005-2012. Based on these physical parameters, the six studied landforms can be classified into raised, dry landforms with minor ground ice content and a thin, discontinuous snow cover and into wet landforms with high ice content located in the topographical depressions in-between with medium to thick snow cover. This results in a differential snow-melting period inferred from the C-band radar satellite data, causing the interseasonal and interlandform variability in the onset of ground surface thawing once the ground becomes snow free. Therefore, variability also exists in the period of thawed ground surface conditions. However, the length of the season with thawed ground surface conditions does not determine the mean annual ground surface temperature, it only correlates well with the active layer depths. From the C-band radar satellite data series, measured relative backscatter trends hint toward a decrease in snow cover through time and a more frequent presence of ice layers from mid-winter rain on snow events at Kapp Linné, Svalbard.

  17. Wave activity (planetary, tidal) throughout the middle atmosphere (20-100km) over the CUJO network: Satellite (TOMS) and Medium Frequency (MF) radar observations

    OpenAIRE

    Manson, A. H.; Meek, C. E.; Chshyolkova, T.; Avery, S. K.; Thorsen, D.; MacDougall, J.W.; Hocking, W.; Murayama, Y.; Igarashi, K

    2005-01-01

    Planetary and tidal wave activity in the tropopause-lower stratosphere and mesosphere-lower thermosphere (MLT) is studied using combinations of ground-based (GB) and satellite instruments (2000-2002). The relatively new MFR (medium frequency radar) at Platteville (40° N, 105° W) has provided the opportunity to create an operational network of middle-latitude MFRs, stretching from 81° W-142° E, which provides winds and tides 70-100km. CUJO (Canada U.S. Japan Opp...

  18. 雷达监测在海南自动站降水质控中的应用方法初探%Preliminary Study on the Application of Radar Monitoring in the Precipitation Control of Automatic Station in Hainan

    Institute of Scientific and Technical Information of China (English)

    朱文婷; 姜小云; 吴俞

    2015-01-01

    In this paper, the ratio of the precipitation data and the precipitation data observed by the Haikou radar quantitative estimation of precipitation and the ratio of the precipitation data from Hainan Island automatic station is constructed, and the conversion coefficient is found to obey the normal distribution. This paper to the conversion coefficient of multiple standards poor quality space for the credibility of the test observations of precipitation, the results show that radar quantitative estimate precipitation on actual observations of precipitation of automatic weather station has good control effect, and is especially suitable for the heavy rainfall in the tropics local quality inspection.%利用海口雷达定量估测降水的格点数据与海南岛自动站实际观测到的降水数据的比值构建了折算系数,发现其折算系数服从正态分布.以折算系数的多倍标准差质控空间为检验实况观测降水的可信程度,结果表明,雷达定量估测降水对自动站实际观测降水有良好的质控效果,尤其适用于热带地区局地强降水的质量检验.

  19. Frequency-magnitude-area relationships for precipitation and flood discharges derived from Next-Generation Radar (NEXRAD): Example application in the Upper and Lower Colorado River Basins

    Science.gov (United States)

    Orem, C. A.; Pelletier, J. D.

    2012-12-01

    Flood-envelope curves, i.e. plots of measured flood discharges versus contributing area for many drainage basins in a given hydroclimatic region, are useful for constraining the upper limit of possible discharges in that region. Their usefulness, however, is limited by the lack of recurrence interval information. In this study, we show that frequency-magnitude-area (FMA) curves can be constructed for precipitation and flood discharges using Stage III Next-Generation Radar (NEXRAD) precipitation estimates and flow-routing algorithms. These FMA curves constrain extreme flood discharges in drainage basins within a region and also provide recurrence interval information. The methods in this study follow the flood-envelope curve approach in that drainage basins of similar size are grouped and data aggregated into one population. We improve on the flood-envelope curve approach by assigning a recurrence interval and errors to flood magnitudes based on a large population of NEXRAD observations taken over time and space. We demonstrate the application of these methods by quantifying the FMA curves for the Upper and Lower Colorado River Basins. Results show that areally-averaged precipitation rates are power-law functions of drainage basin area for a wide range of recurrence intervals. Regression analyses give an average exponent of approximately 0.77 ± 0.04. FMA curves of flood discharges are not power-law functions of area, but instead exhibit the characteristic concave-down shape of published flood-envelope curves in log-log space. The concave-down shape is due to both hydrodynamic and geomorphic dispersion, but not limitations on the increase in precipitation with increasing area, as evidenced by the power-law relationship between area and precipitation rate. Flood discharges calculated by our method are comparable to, but slightly higher than, those reported in the literature for our study regions, suggesting that previously published flood-envelope curves for these

  20. Scoping a field experiment: error diagnostics of TRMM precipitation radar estimates in complex terrain as a basis for IPHEx2014

    Directory of Open Access Journals (Sweden)

    Y. Duan

    2014-10-01

    in detail toward elucidating the physical basis of retrieval error. The diagnostic error analysis reveals that detection errors are linked to persistent stratiform light rainfall in the Southern Appalachians, which explains the high occurrence of FAs throughout the year, as well as the diurnal MD maximum at midday in the cold season (fall and winter, and especially in the inner region. Although UND dominates the magnitude error budget, underestimation of heavy rainfall conditions accounts for less than 20% of the total consistent with regional hydrometeorology. The 2A25 V7 product underestimates low level orographic enhancement of rainfall associated with fog, cap clouds and cloud to cloud feeder-seeder interactions over ridges, and overestimates light rainfall in the valleys by large amounts, though this behavior is strongly conditioned by the coarse spatial resolution (5 km of the terrain topography mask used to remove ground clutter effects. Precipitation associated with small-scale systems (2 and isolated deep convection tends to be underestimated, which we attribute to non-uniform beam-filling effects due to spatial averaging of reflectivity at the PR resolution. Mixed precipitation events (i.e., cold fronts and snow showers fall into OVR or FA categories, but these are also the types of events for which observations from standard ground-based raingauge networks are more likely subject to measurement uncertainty, that is raingauge underestimation errors due to under-catch and precipitation phase. Overall, the space-time structure of the errors shows strong links among precipitation, envelope orography, landform (ridge-valley contrasts, and local hydrometeorological regime that is strongly modulated by the diurnal cycle, pointing to three major error causes that are inter-related: (1 representation of concurrent vertically and horizontally varying microphysics; (2 non uniform beam filling (NUBF effects and ambiguity in the detection of bright band position; and

  1. Orographic rainfall hot spots in the Andes-Amazon transition according to the TRMM precipitation radar and in situ data

    Science.gov (United States)

    Chavez, Steven P.; Takahashi, Ken

    2017-06-01

    The Andes-Amazon transition, along the eastern Peruvian Andes, features "hot spots" with strong precipitation. Using 15 years of Tropical Rainfall Measuring Mission PR data we established a robust relation between terrain elevation and mean surface precipitation, with the latter peaking around 1000 m above sea level (asl), coinciding with the moisture flux peak of the South American Low Level Jet (SALLJ). There is strong diurnal variability, with afternoon (13-18 LT) convection in the Amazon plains, while on the eastern slopes (1000-2000 m asl), after the forcing associated with the thermal heating of the Andes subsides, convection grows during the night and surface precipitation peaks around 01-06 LT and organizes into mesoscale convective systems (MCSs). These then displace downslope to an terrain elevation of 700 m asl with stratiform regions spreading upslope and downslope and then decay during the remainder of the morning. The large MCSs contribute with at least 50% of daily rainfall (60% of the 01-06 LT rainfall). On synoptic scales, the large MCSs are more common in stronger SALLJ conditions, although subtropical cold surges are responsible for 16% of the cases.

  2. Merapi 2010 eruption-Chronology and extrusion rates monitored with satellite radar and used in eruption forecasting

    Science.gov (United States)

    Pallister, John S.; Schneider, David J.; Griswold, Julia P.; Keeler, Ronald H.; Burton, William C.; Noyles, Christopher; Newhall, Christopher G.; Ratdomopurbo, Antonius

    2013-07-01

    Despite dense cloud cover, satellite-borne commercial Synthetic Aperture Radar (SAR) enabled frequent monitoring of Merapi volcano's 2010 eruption. Near-real-time interpretation of images derived from the amplitude of the SAR signals and timely delivery of these interpretations to those responsible for warnings, allowed satellite remote sensing for the first time to play an equal role with in situ seismic, geodetic and gas monitoring in guiding life-saving decisions during a major volcanic crisis. Our remotely sensed data provide an observational chronology for the main phase of the 2010 eruption, which lasted 12 days (26 October-7 November, 2010). Unlike the prolonged low-rate and relatively low explosivity dome-forming and collapse eruptions of recent decades at Merapi, the eruption began with an explosive eruption that produced a new summit crater on 26 October and was accompanied by an ash column and pyroclastic flows that extended 8 km down the flanks. This initial explosive event was followed by smaller explosive eruptions on 29 October-1 November, then by a period of rapid dome growth on 1-4 November, which produced a summit lava dome with a volume of ~ 5 × 106 m3. A paroxysmal VEI 4 magmatic eruption (with ash column to 17 km altitude) destroyed this dome, greatly enlarged the new summit crater and produced extensive pyroclastic flows (to ~ 16 km radial distance in the Gendol drainage) and surges during the night of 4-5 November. The paroxysmal eruption was followed by a period of jetting of gas and tephra and by a second short period (12 h) of rapid dome growth on 6 November. The eruption ended with low-level ash and steam emissions that buried the 6 November dome with tephra and continued at low levels until seismicity decreased to background levels by about 23 November. Our near-real-time commercial SAR documented the explosive events on 26 October and 4-5 November and high rates of dome growth (> 25 m3 s- 1). An event tree analysis for the previous

  3. Airborne Radar Observations of Severe Hailstorms: Implications for Future Spaceborne Radar

    Science.gov (United States)

    Heymsfield, Gerald M.; Tian, Lin; Li, Lihua; McLinden, Matthew; Cervantes, Jaime I.

    2013-01-01

    A new dual-frequency (Ku and Ka band) nadir-pointing Doppler radar on the high-altitude NASA ER-2 aircraft, called the High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP), has collected data over severe thunderstorms in Oklahoma and Kansas during the Midlatitude Continental Convective Clouds Experiment (MC3E). The overarching motivation for this study is to understand the behavior of the dualwavelength airborne radar measurements in a global variety of thunderstorms and how these may relate to future spaceborne-radar measurements. HIWRAP is operated at frequencies that are similar to those of the precipitation radar on the Tropical Rainfall Measuring Mission (Ku band) and the upcoming Global Precipitation Measurement mission satellite's dual-frequency (Ku and Ka bands) precipitation radar. The aircraft measurements of strong hailstorms have been combined with ground-based polarimetric measurements to obtain a better understanding of the response of the Ku- and Ka-band radar to the vertical distribution of the hydrometeors, including hail. Data from two flight lines on 24 May 2011 are presented. Doppler velocities were approx. 39m/s2at 10.7-km altitude from the first flight line early on 24 May, and the lower value of approx. 25m/s on a second flight line later in the day. Vertical motions estimated using a fall speed estimate for large graupel and hail suggested that the first storm had an updraft that possibly exceeded 60m/s for the more intense part of the storm. This large updraft speed along with reports of 5-cm hail at the surface, reflectivities reaching 70 dBZ at S band in the storm cores, and hail signals from polarimetric data provide a highly challenging situation for spaceborne-radar measurements in intense convective systems. The Ku- and Ka-band reflectivities rarely exceed approx. 47 and approx. 37 dBZ, respectively, in these storms.

  4. 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

  5. An Integrated Method of Multiradar Quantitative Precipitation Estimation Based on Cloud Classification and Dynamic Error Analysis

    Directory of Open Access Journals (Sweden)

    Yong Huang

    2017-01-01

    Full Text Available Relationships between radar reflectivity factor and rainfall are different in various precipitation cloud systems. In this study, the cloud systems are firstly classified into five categories with radar and satellite data to improve radar quantitative precipitation estimation (QPE algorithm. Secondly, the errors of multiradar QPE algorithms are assumed to be different in convective and stratiform clouds. The QPE data are then derived with methods of Z-R, Kalman filter (KF, optimum interpolation (OI, Kalman filter plus optimum interpolation (KFOI, and average calibration (AC based on error analysis on the Huaihe River Basin. In the case of flood on the early of July 2007, the KFOI is applied to obtain the QPE product. Applications show that the KFOI can improve precision of estimating precipitation for multiple precipitation types.

  6. About uncertainties in sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise

    Science.gov (United States)

    Kern, S.; Khvorostovsky, K.; Skourup, H.; Rinne, E.; Parsakhoo, Z. S.; Djepa, V.; Wadhams, P.; Sandven, S.

    2014-03-01

    One goal of the European Space Agency Climate Change Initiative sea ice Essential Climate Variable project is to provide a quality controlled 20 year long data set of Arctic Ocean winter-time sea ice thickness distribution. An important step to achieve this goal is to assess the accuracy of sea ice thickness retrieval based on satellite radar altimetry. For this purpose a data base is created comprising sea ice freeboard derived from satellite radar altimetry between 1993 and 2012 and collocated observations of snow and sea ice freeboard from Operation Ice Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) air-borne campaigns, of sea ice draft from moored and submarine Upward Looking Sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer aboard EOS (AMSR-E) and the Warren Climatology (Warren et al., 1999). An inter-comparison of the snow depth data sets stresses the limited usefulness of Warren climatology snow depth for freeboard-to-thickness conversion under current Arctic Ocean conditions reported in other studies. This is confirmed by a comparison of snow freeboard measured during OIB and CryoVEx and snow freeboard computed from radar altimetry. For first-year ice the agreement between OIB and AMSR-E snow depth within 0.02 m suggests AMSR-E snow depth as an appropriate alternative. Different freeboard-to-thickness and freeboard-to-draft conversion approaches are realized. The mean observed ULS sea ice draft agrees with the mean sea ice draft computed from radar altimetry within the uncertainty bounds of the data sets involved. However, none of the realized approaches is able to reproduce the seasonal cycle in sea ice draft observed by moored ULS satisfactorily. A sensitivity analysis of the freeboard-to-thickness conversion suggests: in order to obtain sea ice thickness as accurate as 0.5 m from radar altimetry, besides a freeboard estimate with centimetre accuracy, an ice-type dependent sea ice density is as mandatory

  7. Overview of the relativistic electron precipitations (REP) observed on LEO satellites and ISS by Bulgarian build instruments

    Science.gov (United States)

    Dachev, Tsvetan

    Relativistic electron precipitation (REP) are observed by the R3D B2/B3 and RD3-B3 instruments during the flights of the Foton M2/M3 and “BION-M” № 1 satellite in 2005, 2007 and 2013, and by the R3DE/R instruments at the EXPOSE-E facility of the European Columbus module and at the EXPOSE-R facility of the Russian Zvezda module of the International Space Station (ISS) in the period from February 2008 till August 2010. The obtained dose rates strongly depend by the external and internal shielding of the detectors in the instruments. The highest dose rate reaching more than 20 mGy h (-1) was observed outside the ISS Zvezda module during the REP in April 2010 being the second largest in GOES history with a >2 MeV electron fluence event. REP doses behind relatively thick shielding are too small but may play considerable role during extra vehicular activity (EVA) when the cosmonauts/astronauts body is shielded only by the space suit.

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

    Directory of Open Access Journals (Sweden)

    J. C. Bergès

    2010-01-01

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

  9. Global Precipitation Measurement (GPM) Mission: Overview and Status

    Science.gov (United States)

    Hou, Arthur Y.

    2012-01-01

    The Global Precipitation Measurement (GPM) Mission is an international satellite mission specifically designed to unify and advance precipitation measurements from a constellation of research and operational microwave sensors. NASA and JAXA will deploy a Core Observatory in 2014 to serve as a reference satellite to unify precipitation measurements from the constellation of sensors. The GPM Core Observatory will carry a Ku/Ka-band Dual-frequency Precipitation Radar (DPR) and a conical-scanning multi-channel (10-183 GHz) GPM Microwave Radiometer (GMI). The DPR will be the first dual-frequency radar in space to provide not only measurements of 3-D precipitation structures but also quantitative information on microphysical properties of precipitating particles. The DPR and GMI measurements will together provide a database that relates vertical hydrometeor profiles to multi-frequency microwave radiances over a variety of environmental conditions across the globe. This combined database will be used as a common transfer standard for improving the accuracy and consistency of precipitation retrievals from all constellation radiometers. For global coverage, GPM relies on existing satellite programs and new mission opportunities from a consortium of partners through bilateral agreements with either NASA or JAXA. Each constellation member may have its unique scientific or operational objectives but contributes microwave observations to GPM for the generation and dissemination of unified global precipitation data products. In addition to the DPR and GMI on the Core Observatory, the baseline GPM constellation consists of the following sensors: (1) Special Sensor Microwave Imager/Sounder (SSMIS) instruments on the U.S. Defense Meteorological Satellite Program (DMSP) satellites, (2) the Advanced Microwave Scanning Radiometer-2 (AMSR-2) on the GCOM-W1 satellite of JAXA, (3) the Multi-Frequency Microwave Scanning Radiometer (MADRAS) and the multi-channel microwave humidity sounder

  10. Integrating geologic and satellite radar data for mapping dome-and-basin patterns in the In Ouzzal Terrane, Western Hoggar, Algeria

    Science.gov (United States)

    Deroin, Jean-Paul; Djemai, Safouane; Bendaoud, Abderrahmane; Brahmi, Boualem; Ouzegane, Khadidja; Kienast, Jean-Robert

    2014-11-01

    The In Ouzzal Terrane (IOT) located in the north-western part of the Tuareg Shield forms an elongated N-S trending block, more than 400 km long and 80 km wide. It involves an Archaean crust remobilized during a very high-temperature metamorphic event related to the Palaeoproterozoic orogeny. The IOT largely crops out in the rocky and sandy desert of Western Hoggar. It corresponds mainly to a flat area with some reliefs composed of Late Panafrican granites, dyke networks or Cambrian volcanic rocks. These flat areas are generally covered by thin sand veneers. They are favorable for discriminating bedrock geological units using imaging radar, backscattering measurements, and field checking, because the stony desert is particularly sensitive to the radar parameters such as wavelength or polarization. The main radar data used are those obtained with the ALOS-PALSAR sensor (L-band), in ScanSAR mode (large swath) and Fine Beam modes. The PALSAR sensor has been also compared to ENVISAT-ASAR and to optical imagery. Detailed mapping of some key areas indicates extensive Archaean dome-and-basin patterns. In certain parts, the supracrustal synforms and orthogneiss domes exhibit linear or circular features corresponding to shear zones or rolling structures, respectively. The geological mapping of these dome-and-basin structures, and more generally of the Archaean and Proterozoic lithological units, is more accurate with the SAR imagery, particularly when using the L-band, than with the optical imagery. A quantitative approach is carried out in order to estimate the backscatter properties of the main rock types. Due to the large variety of configurations, radar satellite imagery such as ALOS PALSAR represents a key tool for geological mapping in arid region at different scales from the largest (e.g., 1:500,000) to the smallest (e.g., 1:50,000).

  11. A Nano-satellite Mission to Study Charged Particle Precipitation from the Van Allen Radiation Belts caused due to Seismo-Electromagnetic Emissions

    CERN Document Server

    Sivadas, Nithin; Kannapan, Deepti; Yalamarthy, Ananth Saran; Dhiman, Ankit; Bhagoji, Arjun; Shankar, Athreya; Prasad, Nitin; Ramachandran, Harishankar; Koilpillai, R David

    2014-01-01

    In the past decade, several attempts have been made to study the effects of seismo-electromagnetic emissions - an earthquake precursor, on the ionosphere and the radiation belts. The IIT Madras nano-satellite (IITMSAT) mission is designed to make sensitive measurements of charged particle fluxes in a Low Earth Orbit to study the nature of charged particle precipitation from the Van Allen radiation belts caused due to such emissions. With the Space-based Proton Electron Energy Detector on-board a single nano-satellite, the mission will attempt to gather statistically significant data to verify possible correlations with seismo-electromagnetic emissions before major earthquakes.

  12. Ground validation of DPR precipitation rate over Italy using H-SAF validation methodology

    Science.gov (United States)

    Puca, Silvia; Petracca, Marco; Sebastianelli, Stefano; Vulpiani, Gianfranco

    2017-04-01

    The H-SAF project (Satellite Application Facility on support to Operational Hydrology and Water Management, funded by EUMETSAT) is aimed at retrieving key hydrological parameters such as precipitation, soil moisture and snow cover. Within the H-SAF consortium, the Product Precipitation Validation Group (PPVG) evaluate the accuracy of instantaneous and accumulated precipitation products with respect to ground radar and rain gauge data adopting the same methodology (using a Unique Common Code) throughout Europe. The adopted validation methodology can be summarized by the following few steps: (1) ground data (radar and rain gauge) quality control; (2) spatial interpolation of rain gauge measurements; (3) up-scaling of radar data to satellite native grid; (4) temporal comparison of satellite and ground-based precipitation products; and (5) production and evaluation of continuous and multi-categorical statistical scores for long time series and case studies. The statistical scores are evaluated taking into account the satellite product native grid. With the recent advent of the GPM era starting in march 2014, more new global precipitation products are available. The validation methodology developed in H-SAF can be easily applicable to different precipitation products. In this work, we have validated instantaneous precipitation data estimated from DPR (Dual-frequency Precipitation Radar) instrument onboard of the GPM-CO (Global Precipitation Measurement Core Observatory) satellite. In particular, we have analyzed the near surface and estimated precipitation fields collected in the 2A-Level for 3 different scans (NS, MS and HS). The Italian radar mosaic managed by the National Department of Civil Protection available operationally every 10 minutes is used as ground reference data. The results obtained highlight the capability of the DPR to identify properly the precipitation areas with higher accuracy in estimating the stratiform precipitation (especially for the HS). An

  13. Multi-satellite sensor study on precipitation-induced emission pulses of NOx from soils in semi-arid ecosystems

    Science.gov (United States)

    Zörner, Jan; Penning de Vries, Marloes; Beirle, Steffen; Sihler, Holger; Veres, Patrick R.; Williams, Jonathan; Wagner, Thomas

    2016-07-01

    We present a top-down approach to infer and quantify rain-induced emission pulses of NOx ( ≡ NO + NO2), stemming from biotic emissions of NO from soils, from satellite-borne measurements of NO2. This is achieved by synchronizing time series at single grid pixels according to the first day of rain after a dry spell of prescribed duration. The full track of the temporal evolution several weeks before and after a rain pulse is retained with daily resolution. These are needed for a sophisticated background correction, which accounts for seasonal variations in the time series and allows for improved quantification of rain-induced soil emissions. The method is applied globally and provides constraints on pulsed soil emissions of NOx in regions where the NOx budget is seasonally dominated by soil emissions. We find strong peaks of enhanced NO2 vertical column densities (VCDs) induced by the first intense precipitation after prolonged droughts in many semi-arid regions of the world, in particular in the Sahel. Detailed investigations show that the rain-induced NO2 pulse detected by the OMI (Ozone Monitoring Instrument), GOME-2 and SCIAMACHY satellite instruments could not be explained by other sources, such as biomass burning or lightning, or by retrieval artefacts (e.g. due to clouds). For the Sahel region, absolute enhancements of the NO2 VCDs on the first day of rain based on OMI measurements 2007-2010 are on average 4 × 1014  molec cm-2 and exceed 1 × 1015  molec cm-2 for individual grid cells. Assuming a NOx lifetime of 4 h, this corresponds to soil NOx emissions in the range of 6 up to 65 ng N m-2 s-1, which is in good agreement with literature values. Apart from the clear first-day peak, NO2 VCDs are moderately enhanced (2 × 1014  molec cm-2) compared to the background over the following 2 weeks, suggesting potential further emissions during that period of about 3.3 ng N m-2 s-1. The pulsed emissions contribute about 21-44 % to total

  14. Global Precipitation Measurement Cold Season Precipitation Experiment (GCPEx): For Measurement Sake Let it Snow

    Science.gov (United States)

    Skofronick-Jackson, Gail; Hudak, David; Petersen, Walter; Nesbitt, Stephen W.; Chandrasekar, V.; Durden, Stephen; Gleicher, Kirstin J.; Huang, Gwo-Jong; Joe, Paul; Kollias, Pavlos; Reed, Kimberly A.; Schwaller, Mathew R.; Stewart, Ronald; Tanelli, Simone; Tokay, Ali; Wang, James R.; Wolde, Mengistu

    2014-01-01

    As a component of the Earth's hydrologic cycle, and especially at higher latitudes,falling snow creates snow pack accumulation that in turn provides a large proportion of the fresh water resources required by many communities throughout the world. To assess the relationships between remotely sensed snow measurements with in situ measurements, a winter field project, termed the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx), was carried out in the winter of 2011-2012 in Ontario, Canada. Its goal was to provide information on the precipitation microphysics and processes associated with cold season precipitation to support GPM snowfall retrieval algorithms that make use of a dual-frequency precipitation radar and a passive microwave imager on board the GPM core satellite,and radiometers on constellation member satellites. Multi-parameter methods are required to be able to relate changes in the microphysical character of the snow to measureable parameters from which precipitation detection and estimation can be based. The data collection strategy was coordinated, stacked, high-altitude and in-situ cloud aircraft missions with three research aircraft sampling within a broader surface network of five ground sites taking in-situ and volumetric observations. During the field campaign 25 events were identified and classified according to their varied precipitation type, synoptic context, and precipitation amount. Herein, the GCPEx fieldcampaign is described and three illustrative cases detailed.

  15. 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.

  16. PM-GCD - A combined IR-MW satellite technique for frequent retrieval of heavy precipitation: Application to the EU FLASH project

    Science.gov (United States)

    Casella, Daniele; Dietrich, Stefano; di Paola, Francesco; Formenton, Marco; Mugnai, Alberto; Sanò, Paolo

    2010-05-01

    Precipitation retrievals based on measurements from microwave (MW) radiometers onboard low-Earth-orbit (LEO) satellites can reach a high level of accuracy - and especially so, for deep convective precipitating systems. However, these observations do not provide a satisfactorily coverage of the rapid evolution of intense precipitating systems. As a result, the obtained precipitation retrievals are often of limited use for many important applications -- including support to authorities in activating flood alarms. To avoid this problem, several techniques have been developed that combine accurate MW estimates with frequent infrared (IR) observations from geosynchronous (GEO) satellites, such as the European Meteosat Second Generation (MSG). Within the European Union FP6 FLASH project, we have developed a new combined MW-IR technique for producing frequent precipitation retrievals from space (which we call PM-GCD technique). This technique uses passive-microwave (PM) retrievals in conjunction with the Global Convection Detection (GCD) technique that discriminates deep convective clouds within the GEO observations, based on the difference between the water vapor (6.2 μm ) and thermal-IR (10.8 μm ) channels. In essence, within the PM-GCD technique, deep convective areas are defined from MSG observations, then calibrated using MW-AMSU precipitation retrievals and finally propagated over time with a simple tracking algorithm. In this paper, we describe the PM-GCD technique and discuss the results of its application to a flood event that occurred on September 12-15, 2006 over the north-western Mediterranean coastal areas, and that has been selected for joint research by the EU FLASH and HYDRATE projects.

  17. The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise

    DEFF Research Database (Denmark)

    Kern, S.; Khvorostovsky, K.; Skourup, H.

    2015-01-01

    sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer (AMSR-E) and the Warren climatology (Warren et al., 1999). We compare the different data sets in spatiotemporal scales where satellite radar altimetry yields meaningful results. An inter-comparison of the snow...

  18. GOLD MINERAL PROSPECTING USING PHASED ARRAY TYPE L-BAND SYNTHETIC APERTURE RADAR (PALSAR SATELLITE REMOTE SENSING DATA, CENTRAL GOLD BELT, MALAYSIA

    Directory of Open Access Journals (Sweden)

    A. Beiranvand Pour

    2016-06-01

    Full Text Available The Bentong-Raub Suture Zone (BRSZ of Peninsular Malaysia is one of the significant structural zones in Sundaland, Southeast Asia. It forms the boundary between the Gondwana-derived Sibumasu terrane in the west and Sukhothai arc in the east. The BRSZ is also genetically related to the sediment-hosted/orogenic gold deposits associated with the major lineaments and form-lines in the central gold belt Central Gold Belt of Peninsular Malaysia. In tropical environments, heavy tropical rainforest and intense weathering makes it impossible to map geological structures over long distances. Advances in remote sensing technology allow the application of Synthetic Aperture Radar (SAR data in geological structural analysis for tropical environments. In this investigation, the Phased Array type L-band Synthetic Aperture Radar (PALSAR satellite remote sensing data were used to analyse major geological structures in Peninsular Malaysia and provide detailed characterization of lineaments and form-lines in the BRSZ, as well as its implication for sediment-hosted/orogenic gold exploration in tropical environments. The major geological structure directions of the BRSZ are N-S, NNE-SSW, NE-SW and NW-SE, which derived from directional filtering analysis to PALSAR data. The pervasive array of N-S faults in the study area and surrounding terrain is mainly linked to the N-S trending of the Suture Zone. N-S striking lineaments are often cut by younger NE-SW and NW-SE-trending lineaments. Gold mineralized trends lineaments are associated with the intersection of N-S, NE-SW, NNW-SSE and ESE-WNW faults and curvilinear features in shearing and alteration zones. Lineament analysis on PALSAR satellite remote sensing data is a useful tool for detecting the boundary between the Gondwana-derived terranes and major geological features associated with suture zone especially for large inaccessible regions in tropical environments.

  19. Dual Ka-band radar field campaign for GPM/DPR algorithm development

    Science.gov (United States)

    Nakagawa, K.; Nishikawa, M.; Nakamura, K.; Komachi, K.; Hanado, H.; Kawamura, S.; Sugitani, S.; Minda, H.; Shimizu, S.; Oki, R.

    2012-04-01

    The Global Precipitation Measurement (GPM) mission is an expanded follow-on mission to TRMM (Tropical Rainfall Measuring Mission) and a GPM core satellite will carry dual frequency precipitation radar (DPR) and a GPM Microwave Imager on board. The DPR, which is being developed by National Institute of Information and Communications Technology (NICT) and Japan Aerospace Exploration Agency (JAXA), consists of two radars; Ku-band precipitation radar (KuPR) and Ka-band radar (KaPR). The DPR is expected to advance precipitation science by expanding the coverage of observations to higher latitudes than those of the TRMM/PR, measuring snow and light rain by the KaPR, and providing drop size distribution information based on the differential attenuation of echoes at two frequencies. In order to secure the quality of precipitation estimates, ground validation (GV) of satellite data and retrieval algorithms is essential. Since end-to-end comparisons between instantaneous precipitation data observed by satellite and ground-based instruments is not enough to improve the algorithms. The error of various physical parameters in the precipitation retrieval algorithms (e.g. attenuation factor, drop size distribution, terminal velocity, density of the snow particles, etc.) will be estimated by the comparison with the ground-based observation data. A dual Ka-band radar system is developed by the JAXA for the GPM/DPR algorithm development. The dual Ka-radar system which consists of two identical Ka-band radars can measure both the specific attenuation and the equivalent radar reflectivity at Ka-band. Those parameters are important particularly for snow measurement. Using the dual Ka-radar system along with other instruments, such as a polarimetric precipitation radar, a wind-profiler radar, ground-based precipitation measurement systems, the uncertainties of the parameters in the DPR algorithm can be reduced. The verification of improvement of rain retrieval with the DPR algorithm is

  20. Evaluation and intercomparison of clouds, precipitation, and radiation budgets in recent reanalyses using satellite-surface observations

    Science.gov (United States)

    Dolinar, Erica K.; Dong, Xiquan; Xi, Baike

    2016-04-01

    Atmospheric reanalysis datasets offer a resource for investigating climate processes and extreme events; however, their uncertainties must first be addressed. In this study, we evaluate the five reanalyzed (20CR, CFSR, Era-Interim, JRA-25, and MERRA) cloud fraction (CF), precipitation rates (PR), and top-of-atmosphere (TOA) and surface radiation budgets using satellite observations during the period 03/2000-02/2012. Compared to the annual averaged CF of 56.7 % from CERES MODIS (CM) four of the five reanalyses underpredict CFs by 1.7-4.6 %, while 20CR overpredicts this result by 7.4 %. PR from the Tropical Rainfall Measurement Mission (TRMM) is 3.0 mm/day and the reanalyzed PRs agree with TRMM within 0.1-0.6 mm/day. The shortwave (SW) and longwave (LW) TOA cloud radiative effects (CREtoa) calculated by CERES EBAF (CE) are -48.1 and 27.3 W/m2, respectively, indicating a net cooling effect of -20.8 W/m2. Of the available reanalysis results, the CFSR and MERRA calculated net CREtoa values agree with CE within 1 W/m2, while the JRA-25 result is ~10 W/m2 more negative than the CE result, predominantly due to the underpredicted magnitude of the LW warming in the JRA-25 reanalysis. A regime metric is developed using the vertical motion field at 500 hPa over the oceans. Aptly named the "ascent" and "descent" regimes, these areas are distinguishable in their characteristic synoptic patterns and the predominant cloud-types; convective-type clouds and marine boundary layer (MBL) stratocumulus clouds. In general, clouds are overpredicted (underpredicted) in the ascent (descent) regime and the biases are often larger in the ascent regime than in the descent regime. PRs are overpredicted in both regimes; however the observed and reanalyzed PRs over the ascent regime are an order of magnitude larger than those over the descent regime, indicating different types of clouds exist in these two regimes. Based upon the Atmospheric Radiation Measurement Program ground-based and CM

  1. Assessing the potential of satellite-based precipitation estimates for flood frequency analysis in ungauged or poorly gauged tributaries of China's Yangtze River basin

    Science.gov (United States)

    Gao, Zhen; Long, Di; Tang, Guoqiang; Zeng, Chao; Huang, Jiesheng; Hong, Yang

    2017-07-01

    Flood frequency analysis (FFA) is critical for water resources engineering projects, particularly the design of hydraulic structures such as dams and reservoirs. However, it is often difficult to implement FFA in ungauged or poorly gauged basins because of the lack of consistent and long-term records of streamflow observations. The objective of this study was to evaluate the utility of satellite-based precipitation estimates for performing FFA in two presumably ungauged tributaries, the Jialing and Tuojiang Rivers, of the upper Yangtze River. Annual peak flow series were simulated using the Coupled Routing and Excess STorage (CREST) hydrologic model. Flood frequency was estimated by fitting the Pearson type III distribution of both observed and modeled streamflow with historic floods. Comparison of satellite-based precipitation products with a ground-based daily precipitation dataset for the period 2002-2014 reveals that 3B42V7 outperformed 3B42RT. The 3B42V7 product also shows consistent reliability in streamflow simulation and FFA (e.g., relative errors -20%-5% in the Jialing River). The results also indicate that complex terrain, drainage area, and reservoir construction are important factors that impact hydrologic model performance. The larger basin (156,736 km2) is more likely to produce satisfactory results than the small basin (19,613 km2) under similar circumstances (e.g., Jialing/Tuojiang calibrated by 3B42V7 for the calibration period: NSCE = 0.71/0.56). Using the same calibrated parameter sets from the entire Jialing River basin, the 3B42V7/3B42RT-driven hydrologic model performs better for two tributaries of the Jialing River (e.g., for the calibration period, NSCE = 0.71/0.60 in the Qujiang River basin and 0.54/0.38 in the Fujiang River basin) than for the upper mainstem of the Jialing River (NSCE = 0.34/0.32), which has more cascaded reservoirs with all these tributaries treated as ungauged basins for model validation. Overall, this study underscores

  2. Equatorial dynamics observed by rocket, radar, and satellite during the CADRE/MALTED campaign 1. Programmatics and small-scale fluctuations

    Science.gov (United States)

    Goldberg, Richard A.; Lehmacher, Gerald A.; Schmidlin, Frank J.; Fritts, David C.; Mitchell, J. D.; Croskey, C. L.; Friedrich, M.; Swartz, W. E.

    1997-11-01

    In August 1994, the Mesospheric and Lower Thermospheric Equatorial Dynamics (MALTED) Program was conducted from the Alca‸ntara rocket site in northeastern Brazil as part of the International Guará Rocket Campaign to study equatorial dynamics, irregularities, and instabilities in the ionosphere. This site was selected because of its proximity to the geographic (2.3°S) and magnetic (~0.5°S) equators. MALTED was concerned with planetary wave modulation of the diurnal tidal amplitude, which exhibits considerable amplitude variability at equatorial and subtropical latitudes. Our goals were to study this global modulation of the tidal motions where tidal influences on the thermal structure are maximum, to study the interaction of these tidal structures with gravity waves and turbulence at mesopause altitudes, and to gain a better understanding of dynamic influences and variability on the equatorial middle atmosphere. Four (two daytime and two nighttime) identical Nike-Orion payloads designed to investigate small-scale turbulence and irregularities were coordinated with 20 meteorological falling-sphere rockets designed to measure temperature and wind fields during a 10-day period. These in situ measurements were coordinated with observations of global-scale mesospheric motions that were provided by various ground based radars and the Upper Atmosphere Research Satellite (UARS) through the Coupling and Dynamics of Regions Equatorial (CADRE) campaign. The ground-based observatories included the Jicamarca radar observatory near Lima, Peru, and medium frequency (MF) radars in Hawaii, Christmas Island, and Adelaide. Since all four Nike-Orion flights penetrated and overflew the electrojet with apogees near 125 km, these flights provided additional information about the electrodynamics and irregularities in the equatorial ionospheric E region and may provide information on wave coupling between the mesosphere and the electrojet. Simultaneous with these flights, the CUPRI 50

  3. Coupling Between Doppler Radar Signatures and Tornado Damage Tracks

    Science.gov (United States)

    Jedlovec, Gary J.; Molthan, Andrew L.; Carey, Lawrence; Carcione, Brian; Smith, Matthew; Schultz, Elise V.; Schultz, Christopher; Lafontaine, Frank

    2011-01-01

    On April 27, 2011, the southeastern United States was