Are Storm Characteristics the Same When Viewed Using Merged Surface Radars or a Merged Satellite Product?

2021 ◽  
Vol 22 (1) ◽  
pp. 43-62
Author(s):  
Hooman Ayat ◽  
Jason P. Evans ◽  
Steven Sherwood ◽  
Ali Behrangi
Keyword(s):  
High Resolution ◽  
Flash Flood ◽  
Saturation Properties ◽  
Precipitation Measurement ◽  
Object Based ◽  
Evaluation Mode ◽  
Storm Characteristics ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Droplet Aggregation

AbstractHigh-resolution datasets offer the potential to improve our understanding of spatial and temporal precipitation patterns and storm structures. The goal of this study is to evaluate the similarities and differences of object-based storm characteristics as observed using space- or land-based sensors. The Method of Object-based Diagnostic Evaluation (MODE) Time Domain (MTD) is used to identify and track storm objects in two high-resolution merged datasets: the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) final product V06B and gauge-corrected ground-radar-based Multi-Radar Multi-Sensor (MRMS) quantitative precipitation estimations. Characteristics associated with landfalling hurricanes were also examined as a separate category of storm. The results reveal that IMERG and MRMS agree reasonably well across many object-based storm characteristics. However, there are some discrepancies that are statistically significant. MRMS storms are more concentrated, with smaller areas and higher peak intensities, which implies higher flash flood risks associated with the storms. On the other hand, IMERG storms can travel longer distances with a higher volume of precipitation, which implies higher risk of riverine flooding. Agreement between the datasets is higher for faster-moving hurricanes in terms of the averaged intensity. Finally, MRMS indicates a higher average precipitation intensity during the hurricane’s lifetime. However, in non-hurricanes, the opposite result was observed. This is likely related to MRMS having higher resolution; monitoring the hurricanes from many viewing angles, leading to different signal saturation properties compared to IMERG; and/or the dominance of droplet aggregation effects over evaporation effects at lower altitudes.

scholarly journals Assessment of Heavy Rainfall using GPM- IMERG Satellite Product over Nepal

Jalawaayu ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 79-95
Author(s):  
Nirmala Regmi ◽  
Bikash Nepal ◽  
Shankar Sharma ◽  
Dibas Shrestha ◽  
Govind Kumar Jha
Keyword(s):  
Extreme Precipitation ◽  
Extreme Rainfall ◽  
Heavy Precipitation ◽  
Mode Analysis ◽  
Extreme Rainfall Events ◽  
Precipitation Measurement ◽  
Object Based ◽  
Evaluation Mode ◽  
Global Precipitation Measurement ◽  
Global Precipitation

This study evaluates the Integrated Multi-satellite Retrievals from Global Precipitation Measurement (IMERG) final product’s ability to represent the extreme precipitation against 310 observations from Nepal between 2015 and 2017. Additionally, Method of Object-based Diagnostic Evaluation (MODE) analysis was also performed to analyze IMERG ability to capture actual spatial distribution of the rainfall extremes. Both datasets show the extreme rainfall events are mostly concentrated at southern low land areas of the country. MODE tool further revealed the slight shifting of heavy precipitation location by IMERG product as compared to observation. It is also noted that, as precipitation intensity increases (threshold values of rainfall), the number of extreme events decreases. Moreover, this work provides a systematic quantification of the performance of IMERG gauge calibrated product and its applicability in extreme precipitation over mountainous region.

scholarly journals Validation of the First Years of GPM Operation over Cyprus

2018 ◽  
Vol 10 (10) ◽  
pp. 1520 ◽  
Author(s):  
Adrianos Retalis ◽  
Dimitris Katsanos ◽  
Filippos Tymvios ◽  
Silas Michaelides
Keyword(s):  
High Resolution ◽  
Prediction Models ◽  
Weather Prediction ◽  
Monthly Basis ◽  
Rain Gauges ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
First Results ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Global Precipitation Measurement (GPM) high-resolution product is validated against rain gauges over the island of Cyprus for a three-year period, starting from April 2014. 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. The comparison performed is twofold: first the GPM data are compared with the precipitation measurements on a monthly basis and then the comparison focuses on extreme events, recorded throughout the first 3 years of GPM’s operation. The validation is based on ground data from a dense and reliable network of rain gauges, also available in high temporal (hourly) resolution. 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. 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.

scholarly journals Global View Of Real-Time Trmm Multisatellite Precipitation Analysis: Implications For Its Successor Global Precipitation Measurement Mission

2015 ◽  
Vol 96 (2) ◽  
pp. 283-296 ◽  
Author(s):  
Bin Yong ◽  
Die Liu ◽  
Jonathan J. Gourley ◽  
Yudong Tian ◽  
George J. Huffman ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Global Scale ◽  
Accurate Estimation ◽  
Landslide Monitoring ◽  
Error Characteristics ◽  
Precipitation Measurement ◽  
Precipitation Analysis ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract Accurate estimation of high-resolution precipitation on the global scale is extremely challenging. The operational Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) has created over 16 years of high-resolution quantitative precipitation estimation (QPE), and has built the foundation for improved measurements in the upcoming Global Precipitation Measurement (GPM) mission. TMPA is intended to produce the “best effort” estimates of quasi-global precipitation from almost all available satelliteborne precipitation-related sensors by consistently calibrating them with the high-quality measurements from the core instrument platform aboard TRMM. Recently, the TMPA system has been upgraded to version 7 to take advantage of newer and better sources of satellite inputs than version 6, and has attracted a large user base. A key product from TMPA is the near-real-time product (TMPA-RT), as its timeliness is particularly appealing for time-sensitive applications such as flood and landslide monitoring. TMPA-RT’s error characteristics on a global scale have yet to be extensively quantified and understood. In this study, efforts are focused on a systematic evaluation of four sets of mainstream TMPA-RT estimates on the global scale. The analysis herein indicates that the latest version 7 TMPA-RT with the monthly climatological calibration had the lowest daily systematic biases of approximately 9% over land and –11% over ocean (relative to the gauge-adjusted research product). However, there still exist some unresolved issues in mountainous areas (especially the Tibetan Plateau) and high-latitude belts, and for estimating extreme rainfall rates with high variability at small scales. These global error characteristics and their regional and seasonal variations revealed in this paper are expected to serve as the benchmark for the upcoming GPM mission.

scholarly journals Subgrid Precipitation Properties of Mesoscale Atmospheric Systems Represented by MODIS Cloud Regimes

2019 ◽  
Vol 32 (6) ◽  
pp. 1797-1812 ◽  
Author(s):  
Jackson Tan ◽  
Lazaros Oreopoulos
Keyword(s):  
High Resolution ◽  
Linear Relationship ◽  
Precipitation Behavior ◽  
Convective Systems ◽  
Precipitation Measurement ◽  
Cloud Regime ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Cloud Regimes ◽  
Atmospheric Systems

Abstract The distribution of mesoscale precipitation exhibits diverse patterns: precipitation can be intense but sporadic, or it can be light but widespread. This range of behaviors is a reflection of the different weather systems in the global atmosphere. Using MODIS global cloud regimes as proxies for different atmospheric systems, this study investigates the subgrid precipitation properties within these systems. Taking advantage of the high resolution of Integrated Multisatellite Retrievals for GPM (IMERG; GPM is the Global Precipitation Measurement mission), precipitation values at 0.1° are composited with each cloud regime at 1° grid cells to characterize the regime’s spatial subgrid precipitation properties. The results reveal the diversity of the subgrid precipitation behavior of the atmospheric systems. Organized convection is associated with the highest grid-mean precipitation rates and precipitating fraction, although on average only half the grid is precipitating and there is substantial variability between different occurrences. Summer extratropical storms have the next highest precipitation, driven mainly by moderate precipitation rates over large areas. These systems produce more precipitation than isolated convective systems, for which the lower precipitating fractions balance out the high intensities. Most systems produce heavier precipitation in the afternoon than in the morning. The grid-mean precipitation rate is also found to scale with the fraction of precipitation within the grid in a faster-than-linear relationship for most systems. This study elucidates the precipitation properties within cloud regimes, thus advancing our understanding of the precipitation structures of these atmospheric systems.

scholarly journals An Efficient Downscaling Scheme for High-Resolution Precipitation Estimates over a High Mountainous Watershed

2021 ◽  
Vol 13 (2) ◽  
pp. 234
Author(s):  
Na Zhao
Keyword(s):  
High Resolution ◽  
Model Performance ◽  
Absolute Error ◽  
Rain Gauge ◽  
Monthly Precipitation ◽  
Precipitation Measurement ◽  
Precipitation Estimates ◽  
Residual Correction ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Satellites are capable of observing precipitation over large areas and are particularly suitable for estimating precipitation in high mountains and poorly gauged regions. However, the coarse resolution and relatively low accuracy of satellites limit their applications. In this study, a downscaling scheme was developed to obtain precipitation estimates with high resolution and high accuracy in the Heihe watershed. Shannon’s entropy, together with a semi-variogram, was applied to establish the optimal precipitation station network. A combination of the random forest (RF) method and the residual correction approach with the established rain gauge network was applied to downscale monthly precipitation products from Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG). The results indicated that the RF model showed little improvement in the accuracy of IMERG-based precipitation downscaling. Including residual modification could improve the results of the RF model. The mean absolute error (MAE) and root mean square error (RMSE) values decreased by 19% and 21%, respectively, after residual corrections were added to the RF approach. Moreover, we found that enough rain gauge records are necessary for and remain an important component of tuning model performance. The application of more rain gauges improves the performance of the combined RF and residual modification methods, with the MAE and RMSE values reduced by 8% and 9%, respectively. Residual correction, together with enough precipitation stations, can effectively enhance the quality of the precipitation patterns and magnitudes obtained in the RF downscaling process. The proposed downscaling scheme is an effective tool for increasing the accuracy and spatial resolution of precipitation fields in the Heihe watershed.

PERBANDINGAN SEBARAN CURAH HUJAN HASIL OBSERVASI SATELIT GPM DENGAN MODEL CUACA WRF (Studi Kasus: Siklon Tropis Cempaka Dan Dahlia, 27 Nov – 3 Des 2017)

2019 ◽  
Vol 3 ◽  
pp. 1063
Author(s):  
Fatkhuroyan Fatkhuroyan
Keyword(s):  
Weather Research And Forecasting ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Japan Aerospace Exploration Agency ◽  
Weather Research

Satelit GPM (Global Precipitation Measurement) merupakan proyek kerjasama antara NASA (National Aeronautics and Space Administration) dan JAXA (Japan Aerospace Exploration Agency) serta lembaga internasional lainnya untuk membuat satelit generasi terbaru dalam rangka pengamatan curah hujan di bumi sejak 2014. Model Cuaca WRF (Weather Research and Forecasting) merupakan model cuaca numerik yang telah dipakai oleh BMKG (Badan Meteorologi Klimatologi dan Geofisika) untuk pelayan prediksi cuaca harian kepada masyarakat. Pada tanggal 27 November – 3 Desember 2017 telah terjadi bencana alam siklon tropis Cempaka dan Dahlia di samudra Hindia sebelah selatan pulau Jawa. Tujuan Penelitian ialah untuk mengetahui sebaran akumulasi curah hujan antara observasi satelit GPM dan model cuaca WRF, serta keakuratan model WRF terhadap observasi satelit GPM saat terjadinya bencana alam tersebut. Metode yang dipakai ialah dengan melakukan analisa meteorologi pertumbuhan terjadinya siklon tropis tersebut hingga terjadinya hujan sangat lebat secara temporal maupun spasial. Dari hasil analisa disimpulkan bahwa satelit GPM memiliki luasan sebaran curah hujan yang lebih kecil daripada sebaran hujan model cuaca WRF pada saat siklon tropis Cempaka dan Dahlia. Bias akumulasi sebaran hujan model cuaca WRF juga cukup bagus terhadap satelit GPM sehingga dapat dilakukan antisipasi dampak hujan lebat yang terjadi.

scholarly journals Validation of Satellite-Based Precipitation Products from TRMM to GPM

2021 ◽  
Vol 13 (9) ◽  
pp. 1745
Author(s):  
Jianxin Wang ◽  
Walter A. Petersen ◽  
David B. Wolff
Keyword(s):  
Regional Differences ◽  
Tropical Rainfall Measuring Mission ◽  
Decomposition Approach ◽  
Precipitation Product ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Error Decomposition ◽  
Improved Accuracy ◽  
Global Precipitation ◽  
Statistical Metrics

The global precipitation measurement mission (GPM) has been in operation for seven years and continues to provide a vast quantity of global precipitation data at finer temporospatial resolutions with improved accuracy and coverage. GPM’s signature algorithm, the integrated multisatellite retrievals for GPM (IMERG) is a next-generation of precipitation product expected for wide variety of research and operational applications. This study evaluates the latest version (V06B) of IMERG and its predecessor, the tropical rainfall measuring mission (TRMM) multisatellite precipitation (TMPA) 3B42 (V7) using ground-based and gauge-corrected multiradar multisensor system (MRMS) precipitation products over the conterminous United States (CONUS). The spatial distributions of all products are analyzed. The error characteristics are further examined for 3B42 and IMERG in winter and summer by an error decomposition approach, which partitions total bias into hit bias, biases due to missed precipitation and false precipitation. The volumetric and categorical statistical metrics are used to quantitatively evaluate the performance of the two satellite-based products. All products show a similar precipitation climatology with some regional differences. The two satellite-based products perform better in the eastern CONUS than in the mountainous Western CONUS. The evaluation demonstrates the clear improvement in IMERG precipitation product in comparison with its predecessor 3B42, especially in reducing missed precipitation in winter and summer, and hit bias in winter, resulting in better performance in capturing lighter and heavier precipitation.

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