However, the effect of these circulations on rain microstructures has not been sufficiently addressed. These algorithms, optimized for Europe, Africa and the Southern Atlantic region, provide estimates for the MSG full disk area. The results of both the Vair and the distribution of hydrometeors were found to be realistic for a thunderstorm associated with significant lightning activity on 1 June 2018. what: 50 participants from precipitation research community met to develop a list of research priorities and recommendations in the field of remote sensing of precipitation whEn: 15-Overview Of recOmmendatiOns (i) Uncertainty of merged products and multisensor observations warrants a great deal of research. Weather radar measurements from airborne or satellite platforms can be an effective remote-sensing tool for examining the three-dimensional structures of clouds and precipitation. Proprioception is the body awareness sense. Authors may use MDPI's Accurate estimation of precipitation is critical for hydrological, meteorological, and climate models. Additionally, the most effective TRMM based SPEs products are also considered to provide a first insight into the GPM effectiveness in ensuring TRMM continuity. Atmospheric and hydrological models in combination with remote-sensing and surface observations are used to analyze these phenomena. This algorithm takes into account environmental conditions to retrieve SWP and does not rely on any surface classification scheme. Subscribe to receive issue release notifications and newsletters from MDPI journals, You can make submissions to other journals. This shows changes in the spatial pattern of precipitation changes through time as well as the differences in precipitation between wet and dry regions. Based on observations from. A greater MBE and RMSE are found with both TMPA rain measurements in monsoon and post-monsoon seasons. Analysis of quantitative (Bias, Relative RMSE) and categorical statistics (POD, FAR) for the whole period show a more accurate spatial distribution of mean daily rainfall estimations in the lowlands than in the Andean regions. . To process the single-frequency observations in Precise Point Positioning (PPP) mode, we apply the Satellite-specific Epoch-differenced Ionospheric Delay (SEID) model using two different reference network configurations of 5080 km and 200300 km mean station distances, respectively. Ground weather stations are regularly used to measure precipitation. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne. On the other hand, XPOL-hydro simulation resulted to discharge about 115 m, Flash floods which occur due to heavy rainfall in hilly and semi-hilly areas may prove deleterious when they hit urban centers. It also reproduces the mesoscale belts and cell patterns of sizes from a few to ten kilometers in precipitation fields. This paper studies the feasibility of using low-cost receivers to increase the density of GNSS networks for retrieval of PWV. The results indicate significant differences between the datasets. This paper evaluates the use of precipitation forecasts from a numerical weather prediction (NWP) model for near-real-time satellite precipitation adjustment based on 81 flood-inducing heavy precipitation events in seven mountainous regions over the conterminous United States. Hourly rain rates are assessed by employing the most commonly used statistical measures, such as correlation coefficients (CC), mean bias error (MBE), mean absolute error (MAE), and root-mean-square error (RMSE). It has also been established that local weather conditions are influenced by large-scale circulations. The results also indicated a positive impact of assimilating satellite radiances, which was primarily reflected by the improved performance of quantitative precipitation forecasting and higher spatial correlation in the forecast range of 612 h. Satellite radiance observations provided certain valuable information that was related to the temperature profile, which increased the scope of the prediction of heavy rainfall and led to an improvement in the rainfall scoring in the RMAPS. Overall, the model-adjusted IMERG product performed best over inland regions by taking advantage of the more accurate rainfall magnitude from NWP and the spatial distribution from IMERG. Overall, the IMERG products show an underestimation with respect to OceanRAIN. The kriging method with external drift has been applied to surface rain intensity (SRI) data obtained through the Operative Precipitation Estimation at Microwave Frequencies (OPEMW), which is an algorithm for rain rate retrieval based on Advanced Microwave Sounding Units (AMSU) and Microwave Humidity Sounder (MHS) observations. A subset of models was selected based on the smallest discrepancy relative to CloudSat and ERA-I reanalysis using a combined ranking for bias and spatial root mean square error (RMSE). However, the GOCART-AFWA aerosol module does not incorporate a wet scavenging scheme, nor does it interact with cloud processes. The near-real-time legacy product of Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (3B42RT) and the equivalent products of Integrated Multi-satellite Retrievals for Global Precipitation Measurement mission (IMERG-E and IMERG-L) were evaluated and compared over Mainland China from 1 January 2015 to 31 December 2016 at the daily timescale, against rain gauge measurements. Remote Sensing of Precipitation Using Reflected GNSS Signals: Response Analysis of Polarimetric Observations Abstract: For the first time, rain effects on the polarimetric observations of the global navigation satellite system reflectometry (GNSS-R) are investigated. Dual-frequency Global Navigation Satellite Systems (GNSSs) enable the estimation of Zenith Tropospheric Delay (ZTD) which can be converted to Precipitable Water Vapor (PWV). Finally, all of the considered SPEs have presented a strong spatial variability in terms of accuracy with none of them outperforming the others, for all of the gauges locations over the considered regions. As expected, GSMaPv07 precipitation estimates are more accurate than the previous GSMaPv06. Like other satellite products, GPM had the highest RMSE and bias in summer, suggesting limitations in its way of representing small-scale precipitation systems and isolated deep convection. Recent advances in remote sensing have enabled us to retrieve unprecedented precipitation information, representing a significant contribution toward mapping global precipitation. It reconstructed precipitation with nearly 62% accuracy, although it systematically under-represented rainfall in coastal areas and over-represented rainfall over the high-intensity regions. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne. The complex precipitation microphysics associated with super typhoon Lekima (2019) and its potential impacts on the consistency of multi-source datasets and radar quantitative precipitation estimation were disentangled using a suite of in situ and remote sensing observations around the waterlogged area in the groove windward slope (GWS) of Yandang Mountain (YDM) and Kuocang Mountain . The use of satellites to collect the imagery is called remote sensing. Precipitation: Measurement, remote sensing, climatology and modeling. Daily IMERG products (early, late, final) and microwave-only (MW) and Infrared-only (IR) precipitation components are evaluated at four different spatial resolutions (0.5, 1, 2, and 3) during a 3-year study period (March 2014February 2017). The results show that the random distribution of drops in space has a measurable but apparently small effect in the scattering calculations with the exception of the asymmetry factor. Editors Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. For The precipitation estimates are available in both high temporal (half hourly) and spatial (10 km) resolution and combine data from all passive microwave instruments in the GPM constellation. Under two parameterization scenarios, the MSWEP provides the best streamflow simulation results and TMPA forced simulation ranks second. As far as the chemistry component is concerned, the Georgia Tech Goddard Global Ozone Chemistry Aerosol Radiation and Transport of the Air Force Weather Agency (GOCART-AFWA) module is applied, as it supports a binary scheme for dust emissions and transport. The comparison between MWRI and NSIDC rain rates is relatively encouraging, with a mean bias of 0.14 mm/h and an overall root-mean-square error (RMSE) of 1.99 mm/h. This study evaluates the advantages of using X-band polarimetric (XPOL) radar as a means to fill the coverage gaps and improve complex terrain precipitation estimation and associated hydrological applications based on a field experiment conducted in an area of Northeast Italian Alps characterized by large elevation differences. Threshold values are <2.0 mm/day, below which 3B42RT is unreliable at detecting rain; and <1.0 mm/day, below which both 3B42RT and IMERG products are more likely to cause false alarms. The integration of a dust wet deposition scheme following Seinfeld and Pandis into the WRF-Chem model is assessed through a case study of large-scale Saharan dust transport over the Eastern Mediterranean that is characterized by severe wet deposition over Greece. Generally, the contribution of the random error in all four quantitative precipitation estimates (QPEs) is larger than the systematic error. Therefore, detection metrics are evaluated along with standard statistical measures to test both datasets. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars),. The MSWEP has a greater potential for basinscale hydrological modeling than TMPA. Please let us know what you think of our products and services. Furthermore, this work examined whether TRMM 3B42 V7 rainfall estimates for all the grid points in the AB, outgoing longwave radiation (OLR) and water vapor flux patterns are consistent in the northeast of AB. Firstly, the radar data was treated with an overall quality index which includes corrections for different error sources like ground clutter, range distance, rain-induced attenuation, among others. The analysis is conducted over different geomorphic and meteorological regions of Pakistan while using 88 precipitations gauges as the reference. permission provided that the original article is clearly cited. As the limitation of rainfall collection by ground measurement has been widely recognized, satellite-based rainfall estimate is a promising high-resolution alternative in both time and space. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Furthermore, diurnal rainfall analysis indicates low credibility of 3B42RT to detect flash flooding. It is shown that the approach provides higher accuracy with respect to ordinary kriging, given a choice of auxiliary variables that depends on precipitation type, here classified as convective or stratiform. Results show that: (1) Both 3B42RT and IMERG products overestimate light rain (0.19.9 mm/day), while underestimate moderate rain (10.024.9 mm/day) to heavy rainstorm (250.0 mm/day), with an increase in mean (absolute) error and a decrease in relative mean absolute error (RMAE). Satellite precipitation products provide alternative precipitation data in mountain areas. However, the dynamic variation of soil moisture, simulated by precipitation with higher precision, is more consistent with the measured results. The second and the third are QPEs from a meteorological radar with Doppler capabilities that works in the C band. The results of the soil moisture simulation indicate that the influence of the precipitation input on the RE of the simulated soil moisture is insignificant. Quantitative Precipitation Estimation (QPE). With the advantage of high resolution and improved accuracy, the GPM creates new opportunities for understanding the precipitation pattern across the complex terrains of the Tianshan Mountains, and it could improve hydrological/ecological research in the area. Since then, various SPE versions have been successively made available from the GPM mission. Overall, a weak correlation and high MBE between the TMPA (3B42RT, 3B42V7) and reference gauge hourly rain rates are found at a three-hourly time scale (CC = 0.41, 0.38, MBE = 0.92, 0.70). GPM also performed the best in detecting precipitation events, especially light and moderate precipitation, possibly due to the newly added Ka-band and high-frequency microwave channels. For the long term and on a wide scale, metrics created from satellite remote sensing data have been well established [28,29]. Case Study: Hurricane Harvey. The proposed method creates a 3D regular grid in which a horizontal size of meshes coincides with the horizontal model resolution. The Global Precipitation Measurement (GPM) mission Core Observatory is equipped with a dual-frequency precipitation radar (DPR) with capability of measuring precipitation simultaneously at frequencies of 13.6 GHz (Ku-band) and 35.5 GHz (Ka-band). Basic and probabilistic statistical indices of the satellite rainfall products were examined. Description Remote Sensing of Aerosols, Clouds, and Precipitation compiles recent advances in aerosol, cloud, and precipitation remote sensing from new satellite observations. For this reason, this study aims to apply the H-SAF consolidated radar data processing to the X-band radar used in the CHUVA campaigns and apply the well established H-SAF validation procedure to these data and verify the quality of EUMETSAT H-SAF operational passive microwave precipitation products in two regions of Brazil (Vale do Paraba and Manaus). Of this, around 60% of the precipitation occurs during the summer months. Our results show that spatial correlation and RMSE would be little affected at the monthly scale in the constellation, but that the precise location of the maximum of precipitation could be compromised; depending on the application, this may be an issue. Future improvements in satellite technology are likely to follow two strategies. This study presents algorithms that we use to retrieve vertical air velocity (Vair) and hydrometeors. Quantitative Precipitation Estimates (QPEs) obtained from remote sensing or ground-based radars could complement or even be an alternative to rain gauge readings. The validation is based on ground data from a dense and reliable network of rain gauges, also available in high temporal (hourly) resolution. This study assesses the performance of the latest version 05B (V5B) Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM) (IMERG) Early and Final Runs over southern China during six extremely heavy precipitation events brought by six powerful typhoons from 2016 to 2017. The finding of this paper gives an overview of the capacity of TMPA products in the lower part of the RedThai Binh River Basin regarding water resource applications and provides a simple bias correction that can be used to improve the correctness of TMPA products. The beamfilling effect is corrected based on ratios of the retrieved liquid water absorption. With high resolution and wide coverage, satellite precipitation products like Global Precipitation Measurement (GPM) could support hydrological/ecological research in the Tianshan Mountains, where the spatial heterogeneity of precipitation is high, but where rain gauges are sparse and unevenly distributed. Remote sensing of orographic precipitation Ana P. Barros, Malarvizhi Arulraj Research output: Chapter in Book/Report/Conference proceeding Chapter Overview Fingerprint Abstract Quantitative precipitation estimation (QPE) in mountainous regions remains a challenging task owing to its high spatiotemporal variability. 1. The main conclusion, assuming the information from the rain gauges as ground truth, is that neither PERSIANN-CCS nor radar, without empirical calibration, are acceptable QPEs for the real-time monitoring of meteorological extremes in the southeast of the Iberian Peninsula. Over 250 GPM overpass cases at 5 NEXRAD locations, starting from April 2014 to June 2018, have been considered. Remote sensing of precipitation is critical for regional, continental, and global water and climate research. Rain gauge and ground. CHAOS simulation unveils the persistent orographic convergence of humid southeasterly airflow over Pateras mountain as the dominant parameter for the evolution of the storm. An ensemble of regional climate models (RCMs) and three gauge and satellite-derived observational precipitation datasets are compared. This study develops a deep learning mechanism to link between point-wise rain gauge measurements, ground-based, and spaceborne radar reflectivity observations. The book examines a wide range of measurements from microwave (both active and passive), visible, and infrared portions of the spectrum. Hurricane Harvey, one of the most extreme events in recent history, advanced as a category IV storm and brought devastating rainfall to the Houston, TX, region during 2529. No special The aim is to provide a snapshot of some of the This work is part of a larger effort to validate GPM products over nontraditional regions such as oceans. Since oceanic precipitation is one of the factors affecting the thermohaline circulation, the feedback mechanisms of the changes in the net influx of freshwater from precipitation are relevant not only for improving oceanic-atmospheric coupled models but also to ascertain the climate signal in a global warming scenario. Knowledge and studies on precipitation in the Amazon Basin (AB) are determinant for environmental aspects such as hydrology, ecology, as well as for social aspects like agriculture, food security, or health issues. Additionally, papers on new technological advances as well as campaigns and missions on precipitation remote sensing (e.g., TRMM (Tropical Rainfall Measuring Mission), GPM (Global Precipitation Measurement) ) are welcome. In regions where typical precipitation measurement gauges are sparse, gridded products aim to provide alternative data sources. The region lies within an arid and semi-arid temperate climate zone, characterized by a mean annual precipitation of approximately 430 mm . To assess the performance of this algorithm, MWRI measurements are matched with the National Snow and Ice Data Center (NSIDC) precipitation for six TCs. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Availability of rainfall data at high spatio-temporal resolution is thus crucial for these purposes. Visit our dedicated information section to learn more about MDPI. This study examines the performance of NASAs Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG, GPM). The current study evaluates the efficacy of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) three-hourly products, i.e., 3B42 near-real-time (3B42RT) and 3B42 research version (3B42V7) at a sub-daily time scale. A possible solution is. SPPs were compared with gauge rainfall from 1998 to 2010 at multiple temporal (daily, monthly) and spatial scales (grid, basin). Based on DSD measurements from 16 disdrometers located in Lausanne, Switzerland, we present evidence that rain DSD differs among general weather patterns (GWLs). Research article | 22 Feb 2023 Microphysical processes of super typhoon Lekima (2019) and their impacts on polarimetric radar remote sensing of precipitation Yabin Gou, Haonan Chen, Hong Zhu, and Lulin Xue Download Final revised paper (published on 22 Feb 2023) Preprint (discussion started on 12 Aug 2022) Interactive discussion Status: closed Orographic variables, such as slope, aspect and elevation, are used as auxiliary data in kriging with external drift, together with observations from Meteosat Second Generation-Spinning Enhanced Visible and InfraRed Imager (MSG-SEVIRI) in the water vapor band (6.2 m and 7.3 m) and in thermal-infrared (10.8 m and 8.7 m). Precipitation products based on satellites observations can provide valuable information needed to understand the evolution of such devastating storms. The volumes of precipitation obtained from the GPDs tend to be smaller than those from the gauged data. GR (Gnie Rural) hydrological models were used to evaluate the utility of the three SPPs for daily and monthly streamflow simulation. Awasthi N, Tripathi JN, Petropoulos GP, Gupta DK, Singh AK, Kathwas AK. For comparison, three satellite-based precipitation products (SPPs), including Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) Version 2.0, Climate Prediction Center MORPHing technique (CMORPH) bias-corrected product Version 1.0, and Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 Version 7, were evaluated. 9. They showed a northwestsoutheast precipitation gradient that reflected the effects of large-scale circulations and a characteristic seasonal precipitation gradient that matched the observed regional precipitation pattern. The products from the Integrated. The use of sensors closer to your field that are mounted on planes, helicopters or drones is called proximal sensing. The IMERG Final Run shows promising potentials in typhoon-related extreme precipitation storm applications. Manuscripts can be submitted until the deadline. This paper presents a geostatistical downscaling procedure to improve the spatial resolution of precipitation data. those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). The algorithm classifying hydrometeors consists of calculating the terminal velocity of hydrometeors and the vertical temperature profile. The beamfilling effect is corrected based on ratios of the retrieved liquid water absorption and theoretical Mie absorption coefficients at 18.7 and 36.5 GHz. A comparison of pixel-to-pixel retrievals shows that MWRI retrievals are constrained to reasonable levels for most rain categories, with a minimum error of 1.1% in the 1015 mm/h category; however, with maximum errors around 22% at the lowest (00.5 mm/h) and highest rain rates (2530 mm/h). In summary, satellite remote sensing of precipitation has the potential to considerably advance our understanding of the water cycle, and research has to be focused on answering the basic questions of the water cycle under climate change conditions, i.e., water vapor residence time in the atmosphere and recycling over the continents . A special issue of Remote Sensing (ISSN 2072-4292). Rain properties vary spatially and temporally for several reasons. Please note that many of the page functionalities won't work as expected without javascript enabled. Performance Assessment of Global-EO-Based Precipitation Products against Gridded Rainfall from the Indian Meteorological Department. DPR and ground radar observations and products are cross validated against each other with a large data set. remote sensing remote sensing Getting the Big Picture: Remote Sensing Video Embed JacobAdmin Thu, 11/12/2015 A brief animated look at the different types of remote sensing techniques that NASA uses to study the Earth. This study aimed to assess the performance of the latest Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) version 5 (IMERG V5) and Global Satellite Mapping of Precipitation version 7 (GSMaP. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. All calculations are additionally carried out for seasonal subsets of the data to assess potentially different behavior due to differences in precipitation schemes. The proposed method creates a 3D regular grid in which a horizontal size of meshes coincides with the horizontal. Precise estimates of precipitation are required for many environmental tasks, including water resources management, improvement of numerical model outputs, nowcasting and evaluation of anthropogenic impacts on global climate. permission is required to reuse all or part of the article published by MDPI, including figures and tables. Then our study aims to enhance the knowledge about the quality of this product on the entire AB and provide a useful understanding about his capacity to reproduce the annual rainfall regimes. A triple collocation analysis (TCA) is also presented to further investigate the performance of these satellite-based products. This study evaluates four widely used global precipitation datasets (GPDs): The Tropical Rainfall Measuring Mission (TRMM) 3B43, the Climate Forecast System Reanalysis (CFSR), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and the Multi-Source Weighted-Ensemble Precipitation (MSWEP), against point gauge and gridded dataset observations using multiple monthly water balance models (MWBMs) in four different meso-scale basins that cover the main climatic zones of Peninsular Spain. The algorithm is trained on an extremely large observational database, built from GPM global observations between 2014 and 2016, where the NASA 2B-CMB (V04) rainfall rate product is used as reference. We demonstrate that modeling of the ionosphere and the antenna type are the main sources influencing the ZTD precision. The algorithm calculating Vair is based on small-particle tracers, which considers the terminal velocity of small particles negligible and, thereby, Vair corresponds to the velocity of the small particles. The procedures used can be applied in regions with similar case studies to more accurately assess the resources within a system in which there is scarcity of recorded data available. This case study targeted the 48 h period from 1920 July 2016, which was characterized by the passage of. This case study targeted the 48 h period from 1920 July 2016, which was characterized by the passage of a low pressure system that produced heavy rainfall over North China. Submitted papers should be well formatted and use good English. This study examines the performance of NASAs Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG, GPM) satellite precipitation dataset in capturing the spatio-temporal variability of weather events compared to the German weather radar dataset RADOLAN RW. This Special Issue will host papers on all aspects of remote sensing of precipitation, including applications that embrace the use of remote-sensing techniques of precipitation in tackling issues, such as precipitation estimations and retrievals along with their methodologies and corresponding error assessment, precipitation modelling including validation, instrument comparison and calibration, understanding of cloud microphysical properties, precipitation downscaling, precipitation droplet size distribution, assimilation of remotely sensed precipitation into numerical weather prediction models, measurement of precipitable water vapor, etc. The precipitation estimates are available in both high temporal (half hourly) and spatial (10 km) resolution and combine data. This study is aimed at exploring the capacity of the satellite-based rainfall product Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), including 3B42V7 research data and its real-time 3B42RT data, by comparing them against data from 29 ground observation stations over the lower part of the RedThai Binh River Basin from March 2000 to December 2016. The IMERG products perform better in estimating light rain to heavy rain (25.049.9 mm/day), and heavy rainstorm, while 3B42RT has smaller error magnitude in estimating light rainstorm (50.099.9 mm/day) and moderate rainstorm (100.0249.9 mm/day). The validation is performed against measurements from a network of ground-based rain gauges in Southern Italy. These products are based on two rainfall retrieval algorithms: the physically based Bayesian Cloud Dynamics and Radiation Database (CDRD algorithm) for SSMI/S sensors and the Passive microwave Neural network Precipitation Retrieval algorithm (PNPR) for cross-track scanning radiometers (AMSU-A/AMSU-B/MHS sensors) and for the ATMS sensor.
How To Become A Listing Agent,
United Healthcare Pay Grade 29,
Articles R