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. Special Issue "Remote Sensing of Precipitation: Part III" - MDPI The two gauge-adjusted products were more consistent with the ground measurements than the satellite-only products in terms of statistical assessment. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earths atmosphereocean complex system. Awasthi N, Tripathi JN, Petropoulos GP, Gupta DK, Singh AK, Kathwas AK. Remote Sensing of Electric Fields Observed Within Winter Precipitation During the 2020 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) Field Campaign . 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. The raw IMERG product consistently underestimated heavy precipitation in all study regions, while the domain average rainfall magnitudes exhibited by the model were fairly accurate. Our study also indicates that accurately measuring light rainfall and winter snow is still a challenging task for the current satellite precipitation retrievals. In general, a good agreement is observed between rain gauge derived regimes and those from 3B42; however, performance is better in the rainy period. 2 Forms to Abbreviate Remote Sensing - All Acronyms What is Remote Sensing? | Earthdata In such regions, rigorous validation is necessary when using SPPs for hydrological applications. 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. The region lies within an arid and semi-arid temperate climate zone, characterized by a mean annual precipitation of approximately 430 mm . 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). 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. How to abbreviate Remote Sensing? 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). Todd Ballard, CSU Extension. 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). The availability of precipitation data is the key driver in the application of hydrological models when simulating streamflow. This study presents algorithms that we use to retrieve vertical air velocity (Vair) and hydrometeors. Remote Sensing of Clouds and Precipitation | SpringerLink It is composed of three modules for (i) snowfall detection, (ii) supercooled droplet detection and (iii) SWP retrieval. Rain properties vary spatially and temporally for several reasons. The error analysis against rain gauge observations reveals that the merged precipitation MSWEP performs best, followed by TMPA and CMORPH, which in turn outperform CHIRPS. The role of satellite remote sensing in climate change studies 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. Here, using the T-matrix formalism, we investigate the radiometric variability of two ensembles of 50 different 3D, stochastically-derived configurations from two consecutive measured RDSDs with 30 and 31 drops, respectively. This case study targeted the 48 h period from 1920 July 2016, which was characterized by the passage of. 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. The agreement between IMERG products and rain gauge measurements is low and even negative for different rainfall intensities, and the RMAE is still at a high level (>50%), indicating the IMERG products remain to be improved. 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. 3B42RT, on the other hand, underestimates rainfall in all seasons. Overall, GPM IMERG overestimates the quantity of precipitation compared to RADOLAN, especially in the winter season. However, high climate variability and extreme topography pose a challenge. PDF Remote Sensing of Precipitation - NASA Frontiers | Statistical analysis of precipitation variations and its The ground radars, chosen for this study, are located in the southeastern plains of the U.S.A. with altitudes varying from 5 to 210 m. It is a challenging task to quantitatively compare measurements from space-based and ground-based platforms due to their difference in resolution volumes and viewing geometry. The satellite estimates significantly correlated with the observations. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. 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. 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. 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 beamfilling effect is corrected based on ratios of the retrieved liquid water absorption. Results show a clear enhancement in precipitation estimates that were derived from the very last IMERGv05 in comparison to its two previous versions IMERGv03 and v04. Additionally, Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) Tbs are applied to retrieve rain rates to assess the sensitivity of this algorithm, with a mean bias and RMSE of 0.90 mm/h and 3.11 mm/h, respectively. You seem to have javascript disabled. How Well Can IMERG Products Capture Typhoon Extreme Precipitation Events over Southern China? 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. Pixel-to-point comparisons are made between the values offered by the QPEs and those obtained by two networks of rain gauges. Katsanos, D.; Retalis, A.; Tymvios, F.; Michaelides, S. Analysis of precipitation extremes based on satellite (CHIRPS) and in situ dataset over Cyprus. Results indicate similar behavior for IMERG and TMPA products, showing that they overestimate precipitation, while GSMaP tend to slightly underestimate the amount of rainfall in most of the analyzed regions. The rapid development of remote sensing techniques has made precipitation estimation more accurate and cover broader regions compared with traditional rain gauges around the world. A special issue of Remote Sensing (ISSN 2072-4292). The method shows an improvement of precipitation prediction within the radar location area in both the rain rates and spatial pattern presentation. In this study, the ability of recent Integrated Multi-satellitE Retrievals for Global Precipitation Mission (GPM-IMERG) final-run product to capture the magnitudes and spatial (0.1 0.1)/temporal (hourly) patterns of rainfall resulting from hurricane Harvey was evaluated. 1996-2023 MDPI (Basel, Switzerland) unless otherwise stated. The inclusion of satellite radiance observations was found to have a small but beneficial impact on the prediction of heavy rainfall events as it relates to our case study conditions. 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 assimilation of satellite radiance data from the advanced microwave sounding unit-A (AMSU-A) and microwave humidity sounding (MHS) improved the skills of the quantitative precipitation forecast to a certain extent. 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. Please visit the Instructions for Authors page before submitting a manuscript. This study presents a pre-processing approach adopted for the radar reflectivity data assimilation and results of simulations with the Harmonie numerical weather prediction model. All QPEs forced simulations underestimate the streamflow with exceedance probabilities below 5.0%, while they overestimate the streamflow with exceedance probabilities above 30.0%. 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. Special Issue "Remote Sensing of Precipitation: Part II" - MDPI The quality of satellite rainfall products has improved significantly in recent decades; however, such algorithms require validation studies using observational rainfall data. Journal of Hydrology | Remote Sensing of Precipitation for Ground-based remote sensing of precipitation in the Arctic 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. 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. In regions where typical precipitation measurement gauges are sparse, gridded products aim to provide alternative data sources. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. . English editing service prior to publication or during author revisions. This indicates that local thermodynamic effects explain much of the net high-latitude precipitation change. Remote Sensing | Free Full-Text | Performance Assessment of - MDPI For the long term and on a wide scale, metrics created from satellite remote sensing data have been well established [28,29]. However, the dynamic variation of soil moisture, simulated by precipitation with higher precision, is more consistent with the measured results. Urban areas often experience high precipitation rates and heights associated with flash flood events. Authors may use MDPI's Moreover, shortcomings in detection performance arise in this season with significant erroneously-detected, yet also missed precipitation events compared to the weather radar data. Remote sensing is the acquiring of information from a distance. Dual-frequency Global Navigation Satellite Systems (GNSSs) enable the estimation of Zenith Tropospheric Delay (ZTD) which can be converted to Precipitable Water Vapor (PWV). 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). This algorithm takes into account environmental conditions to retrieve SWP and does not rely on any surface classification scheme. Based on observations from. Since the GPM-DPR cannot use information from polarization diversity, radar reflectivity. This study is aimed at exploring the capacity of the satellite-based rainfall product Tropical Rainfall Measurement Mission. No special The study shows that single-frequency GNSS receivers can achieve a quality similar to that of geodetic receivers in terms of RMSE for ZTD estimations. However, cloud radars provide us with detailed information on cloud particles from which the precipitation consists of. However, high climate variability and extreme topography pose a challenge. Precipitation: Measurement, remote sensing, climatology and modeling. Editors Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Microphysical processes of super typhoon Lekima (2019) and their - ACP Hurricanes and other severe coastal storms have become more frequent and destructive during recent years. We evaluated four precipitation datasets (the model forecasts, raw IMERG, gauge-adjusted IMERG and model-adjusted IMERG) through comparisons against Stage IV at six-hourly and event length scales. 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. This study presents a pre-processing approach adopted for the radar reflectivity data assimilation and results of simulations with the Harmonie numerical weather prediction model. To achieve its objective, the project will utilize the Global Precipitation Measurement (GPM) satellite constellation as a single multi-frequency microwave . 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. Remote Sensing | Special Issue : Remote Sensing of Clouds and - MDPI 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. Results indicate that both satellite estimates showed a high Pearson correlation coefficient (. However, the effect of these circulations, Rain properties vary spatially and temporally for several reasons. 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. Finally, based on the moderate correlation between climatologytopography characteristics and correction factors of linear-scaling (LS) approach, a set of multiple linear models was developed to reduce the error between TMPA products and the observations. Case Study: Hurricane Harvey. Here, two IMERG Final Run products (uncalibrated IMERG (IMERG-UC) and gauge-calibrated IMERG (IMEEG-C)) and two GSMaP products (GSMaP Moving Vector with Kalman Filter (GSMaP-MVK) and gauge-adjusted GSMaP (GSMaP-Gauge)) were evaluated from April 2014 to March 2017. However, spatial coverage is often limited in low-population areas and mountain areas. The performance of GPDs highly depends on the climate, so that the more humid the watershed is, the better results can be achieved. SPPs were compared with gauge rainfall from 1998 to 2010 at multiple temporal (daily, monthly) and spatial scales (grid, basin). ACP - Peer review - Microphysical processes of super typhoon Lekima 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. The results showed that climatologytopography-based linear-scaling approach (CTLS) significantly reduced the percentage bias (PBIAS) score and moderately improved the NashSutcliffe efficiency (NSE) score. The first results show very good correlation regarding monthly values; however, the correspondence of GPM in extreme precipitation varies from no correlation to high correlation, depending on case. A possible solution is the utilization of satellite-based precipitation products. Availability of rainfall data at high spatio-temporal resolution is thus crucial. All submissions that pass pre-check are peer-reviewed. 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 The model exhibited error in the locations of intense precipitation over inland regions, however, while the IMERG product generally showed correct spatial precipitation patterns. Their performance is assessed based on both categorical and continuous performance metrics, including correlation coefficient, probability of detection, success ratio, bias, and root mean square error (RMSE). Unfortunately, the CHIRPS and CMORPH forced simulations produce unsatisfactory results. The SH55 land areas show stable spatial correlations between the simulated present and future climate, indicative of small changes in the spatial pattern, but this is not true of NH55 land. In particular, rain types (convective and stratiform) affect the rain drop size distribution (DSD). The prediction of such localized and heterogeneous phenomena is a challenge due to a scarcity of in-situ rainfall. IR estimates show relatively large errors and low correlations with OceanRAIN compared to the other products. 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). Recent advances in remote sensing have enabled us to retrieve unprecedented precipitation information, representing a significant contribution toward mapping global precipitation. 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. 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. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Lane, J.; Kasparis, T.; Michaelides, S.; Metzger, P. A phenomenological relationship between vertical air motion and disdrometer derived A-b coefficients. Each spatial configuration is equivalent to any other in terms of the RDSD function, but not in terms of radiometric characteristics, both near and far from field, because of changes in the relative phases among the particles. The quality of satellite rainfall products has improved significantly in recent decades; however, such algorithms require validation studies using observational rainfall data. In such regions, rigorous validation is necessary when using SPPs for hydrological applications. Precipitation products based on satellites observations can provide valuable information needed to understand the evolution of such devastating storms. It also reproduces the mesoscale belts and cell patterns of sizes from a few to ten kilometers in precipitation fields. To overcome such problems, data fusion methods have been devised to take advantage of synergisms between available data, but these methods also present issues and limitations. Observations. 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. 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). Special Issues, Collections and Topics in MDPI journals, Editorial for Special Issue Remote Sensing of Precipitation, Assessment of Level-3 Gridded Global Precipitation Mission (GPM) Products Over Oceans. Manuscripts can be submitted until the deadline. Further, a diurnal analysis is performed to authenticate TMPAs performance in specific hours of the day. The snowfall detection module is able to detect 83% of snowfall events including light SWP (down to 1 10, In mountain basins, the use of long-range operational weather radars is often associated with poor quantitative precipitation estimation due to a number of challenges posed by the complexity of terrain. (PDF) remote sensing Evaluation of Multi-Satellite Precipitation
How To Comfort A Crying Girl Over Text,
What Was The Drinking Age In 1970 In Wisconsin,
Articles R