The prediction of such localized and heterogeneous phenomena is a challenge due to a scarcity of in-situ rainfall. 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. 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 Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rainfall data provided by the Remote Sensing Systems (RSS) are applied to assess the representation of mesoscale structures in intense TCs, and they show good consistency with MWRI retrievals. All three SPPs performed poorly when detecting the frequency of non-rain and light rain events (<1 mm); furthermore, they tended to overestimate moderate rainfall (125 mm) and underestimate heavy and hard rainfall (>25 mm). Please let us know what you think of our products and services. This study aims to verify the GPM rain estimates, since such a high-resolution dataset has numerous applications, including the assimilation in numerical weather prediction models and the study of flash floods with hydrological models. When rainfall intensity was analyzed, both 3B42V7 and 3B42RT overestimated the no rainfall event during the dry season but underestimated these events during the wet season. The IMERG product could benefit from gauge-based adjustment, as well, but the improvement from model-based adjustment was consistently more significant. (3) Generally, both 3B42RT and IMERG products perform better in wet areas with relatively heavy rainfall intensity and/or during wet season than in dry areas with relatively light rainfall intensity and/or during dry season. Quantitative Precipitation Estimates (QPEs) obtained from remote sensing or ground-based radars could complement or even be an alternative to rain gauge readings. Special Issue "Remote Sensing of Precipitation: Part II" - MDPI Satellite precipitation products provide alternative precipitation data in mountain areas. In this study, GPMs observations of reflectivity at dual-frequency and instantaneous rainfall products are compared quantitatively against dual-polarization ground-based NEXRAD radars from the GPM Validation Network (VN). Ground-based remote sensing of precipitation in the Arctic New advances in observation, analysis, modeling and synthesis are pushing the limits of quantitative precipitation estimation and forecasting and at increasingly higher resolutions from local to global scales. Besides quantity, also timing of rainfall is of very high importance when modeling or monitoring the hydrologic cycle. These algorithms, optimized for Europe, Africa and the Southern Atlantic region, provide estimates for the MSG full disk area. How to abbreviate Remote Sensing? 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. The precipitation estimates are available in both high temporal (half hourly) and spatial (10 km) resolution and combine data. permission is required to reuse all or part of the article published by MDPI, including figures and tables. Remote Sensing of Precipitation for Hydrometeorology Edited by Dongjun Seo, Kuolin Hsu, Alan Seed, Venkatachalam Chandrasekar Last update 28 April 2022 Receive an update when the latest issues in this journal are published Sign in to set up alerts Research articleFull text access Gabella, M.; Morin, E.; Notarpietro, R.; Michaelides S. Precipitation field in the Southeastern Mediterranean area as seen by the Ku-band spaceborne weather radar and two C-band ground-based radars. IR estimates show relatively large errors and low correlations with OceanRAIN compared to the other products. 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. To assess the performance of this algorithm, MWRI measurements are matched with the National Snow and Ice Data Center (NSIDC) precipitation for six TCs. The beamfilling effect is corrected based on ratios of the retrieved liquid water absorption. Basic and probabilistic statistical indices of the satellite rainfall products were examined. 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. To overcome this limitation, gridded datasets from remote sensing have been widely used. DPR and ground radar observations and products are cross validated against each other with a large data set. The quality of satellite rainfall products has improved significantly in recent decades; however, such algorithms require validation studies using observational rainfall data. 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. To achieve its objective, the project will utilize the Global Precipitation Measurement (GPM) satellite constellation as a single multi-frequency microwave . Microphysical processes of super typhoon Lekima (2019) and their impacts on polarimetric radar remote sensing of precipitation February 2023 Atmospheric Chemistry and Physics 23 (4):2439-2463. Feature papers represent the most advanced research with significant potential for high impact in the field. Awasthi N, Tripathi JN, Petropoulos GP, Gupta DK, Singh AK, Kathwas AK. 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. Two experiments were performed and 24 h forecasts were produced every 3 h. The results indicated that the forecast prior to the satellite radiance data assimilation could not accurately predict heavy rainfall events over Beijing and the surrounding area. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Results underscore the superiority of the national gridded dataset, although the TRMM provides satisfactory results in simulating streamflow, reaching similar Nash-Sutcliffe values, between 0.70 and 0.95, and an average total volume error of 12% when using the GR2M model. This paper describes a new rainfall rate retrieval algorithm, developed within the EUMETSAT H SAF program, based on the Passive microwave Neural network Precipitation Retrieval approach (PNPR v3), designed to work with the conically scanning Global Precipitation Measurement (GPM) Microwave Imager (GMI). Dual-frequency Global Navigation Satellite Systems (GNSSs) enable the estimation of Zenith Tropospheric Delay (ZTD) which can be converted to Precipitable Water Vapor (PWV). With the highest correlation (R = 0.51), the lowest error (RMSE = 0.85 mm/day), and the smallest bias (1.27%), GPM outperformed TRMM and CMORPH in estimating daily precipitation. As far as the chemistry component is concerned, the Georgia Tech Goddard Global Ozone Chemistry, The principal objective of this study is to present and evaluate an advanced dust wet deposition scheme in the Weather and Research Forecasting model coupled with Chemistry (WRF-Chem). Precipitation products based on satellites observations can provide valuable information needed to understand the evolution of such devastating storms. Nonetheless, the availability of such estimates is hindered by technical limitations. This study is expected to give useful feedbacks about the latest V5B Final Run IMERG product to both algorithm developers and the scientific end users, providing a better understanding of how well the V5B IMERG products capture the typhoon extreme precipitation events over southern China. 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. WRF-Hydro simulated the flood using three different precipitation estimations as forcing data, obtained from the CHAOS simulation (CHAOS-hydro), the XPOL weather radar (XPOL-hydro) and the Global Precipitation Measurement (GMP)/Integrated Multi-satellitE Retrievals for GPM (IMERG) satellite dataset (GPM/IMERG-hydro). 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. You seem to have javascript disabled. 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. Remote sensing drought factor integration based on machine - Springer The first QPE is PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System) , a satellite-based QPE. Two fundamental variables for the prediction of floods are analyzed: precipitation and soil moisture. This study develops a deep learning mechanism to link between point-wise rain gauge measurements, ground-based, and spaceborne radar reflectivity observations. Future improvements in satellite technology are likely to follow two strategies. AMA Style. The relative error (RE) of QPEs is the main factor affecting the RE of simulated streamflow, especially for the results of Scenario I (model parameters calibrated by rain gauge observations). 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. The Vaisala Laser Ceilometer is a ground-based active remote sensing instrument that detects clouds by transmitting infrared pulses vertically into the atmosphere. Under two parameterization scenarios, the MSWEP provides the best streamflow simulation results and TMPA forced simulation ranks second. Previous studies underline at regional scale in the AB, and for some years, the efficiency of the Tropical Rainfall Measurement Mission (TRMM) 3B42 Version 7 (V7) (hereafter 3B42) daily product data, to provide a good view of the rainfall time variability which is important to understand the impacts of El Nino Southern Oscilation. For that purpose we compared 3B42 against 205 quality-controlled rain gauge measurements for the period from March 1998 to July 2013, with the aim to know whether 3B42 is reliable for climate studies. Our study also indicates that accurately measuring light rainfall and winter snow is still a challenging task for the current satellite precipitation retrievals. 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). Abstract. Satellite Remote Sensing of Precipitation and the Terrestrial Water 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 . This case study targeted the 48 h period from 1920 July 2016, which was characterized by the passage of. Of this, around 60% of the precipitation occurs during the summer months. In addition, detection metrics demonstrated that TMPA products could detect rainfall events in the wet season much better than in the dry season. Ground weather stations are regularly used to measure precipitation. A greater MBE and RMSE are found with both TMPA rain measurements in monsoon and post-monsoon seasons. measurements were made during seven research flights by a NASA ER-2 during the 2020 Investigation of Microphysics and Precipitation for . This study investigates the value of satellite-based observational algorithms in supporting numerical weather prediction (NWP) for improving the alert and monitoring of extreme rainfall events. 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. An acceptable agreement was found between the calculated and measured near surface PM, Utilizing reanalysis and high sensitivity W-band radar observations from CloudSat, this study assesses simulated high-latitude (5582.5) precipitation and its future changes under the RCP8.5 global warming scenario. 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. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Finally, an original way to validate the estimations is by taking into account the interannual variability of rainfall regimes (i.e., the presence of sub-regimes): four sub-regimes in the northeast AB defined from rain gauges and 3B42 were found to be in good agreement. Remote Sensing | Precipitation Education In regions where typical precipitation measurement gauges are sparse, gridded products aim to provide alternative data sources.