Assessment of GPM-Era Satellite Products’ (IMERG and GSMaP) Ability to Detect Precipitation Extremes over Mountainous Country Nepal

The reliability of satellite precipitation products is important in climatic and hydro-meteorological studies, which is especially true in mountainous regions because of the lack of observations in these areas. Two recent satellite rainfall estimates (SREs) from Global Precipitation Measurement (GPM)-era—Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG-V06) and gauge calibrated Global Satellite Mapping of Precipitation (GSMaP-V07) are evaluated for their spatiotemporal accuracy and ability to capture extreme precipitation events using 279 gauge stations from southern slope of central Himalaya, Nepal, between 2014 and 2019. The overall result suggests that both SREs can capture the spatiotemporal precipitation variability, although they both underestimated the observed precipitation amount. Between the two, the IMERG product shows a more consistent performance with a higher correlation coefficient (0.52) and smaller bias (−2.49 mm/day) than the GSMaP product. It is worth mentioning that the monthly gauge-calibrated IMERG product yields better detection capability (higher probability of detection (POD) values) of daily precipitation events than the daily gauge calibrated GSMaP product; however, they both show similar performance in terms of false alarm ratio (FAR) and critical success index (CSI). Assessment based on extreme precipitation indices revealed that the IMERG product outperforms GSMaP in capturing daily precipitation extremes (RX1Day and RX5Day). In contrast, the GSMaP product tends to be more consistent in capturing the duration and threshold-based precipitation extremes (consecutive dry days (CDD), consecutive wet days (CWD), number of heavy precipitation days (R10mm), and number of extreme precipitation days (R25mm)). Therefore, it is suggested that the IMERG product can be a good alternative for monitoring daily extremes; meanwhile, GSMaP could be a better option for duration-based extremes in the mountainous region.

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Capability of IMERG V6 Early, Late, and Final Precipitation Products for Monitoring Extreme Precipitation Events

Remote Sensing ◽

10.3390/rs13040689 ◽

2021 ◽

Vol 13 (4) ◽

pp. 689

Author(s):

Chenguang Zhou ◽

Wei Gao ◽

Jiarui Hu ◽

Liangmin Du ◽

Lin Du

Keyword(s):

Extreme Precipitation ◽

Environmental Research ◽

Complex Topography ◽

Extreme Precipitation Events ◽

Precipitation Measurement ◽

Variation Patterns ◽

Global Precipitation Measurement ◽

Global Precipitation ◽

Early Late ◽

Precipitation Events

The monitoring of extreme precipitation events is an important task in environmental research, but the ability of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) precipitation products to monitor extreme precipitation events remains poorly understood. In this study, three precipitation products for IMERG version 6, early-, late-, and final-run products (IMERG-E, IMERG-L, and IMERG-F, respectively), were used to capture extreme precipitation, and their applicability to monitor extreme precipitation events over Hubei province in China was evaluated. We found that the accuracy of the three IMERG precipitation products is inconsistent in areas of complex and less complex topography. Compared with gauge-based precipitation data, the results reveal the following: (1) All products can accurately capture the spatiotemporal variation patterns in precipitation during extreme precipitation events. (2) The ability of IMERG-F was good in areas of complex topography, followed by IMERG-E and IMERG-L. In areas of less complex topography, IMERG-E and IMERG-L produced outcomes that were consistent with those of IMERG-F. (3) The three IMERG precipitation products can capture the actual hourly precipitation tendencies of extreme precipitation events. (4) In areas of complex topography, the rainfall intensity estimation ability of IMERG-F is better than those of IMERG-E and IMERG-L.

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How Well Can IMERG Products Capture Typhoon Extreme Precipitation Events over Southern China?

Remote Sensing ◽

10.3390/rs11010070 ◽

2019 ◽

Vol 11 (1) ◽

pp. 70 ◽

Cited By ~ 11

Author(s):

Chaoying Huang ◽

Junjun Hu ◽

Sheng Chen ◽

Asi Zhang ◽

Zhenqing Liang ◽

...

Keyword(s):

Extreme Precipitation ◽

Southern China ◽

Correlation Coefficients ◽

Heavy Precipitation ◽

Spatiotemporal Variability ◽

Bias Analysis ◽

Extreme Precipitation Events ◽

Precipitation Measurement ◽

Global Precipitation ◽

Precipitation Events

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. Observations from a dense network composed of 2449 rain gauges are used as reference to quantify the performance in terms of spatiotemporal variability, probability distribution of precipitation rates, contingency scores, and bias analysis. The results show that: (1) both IMERG with gauge calibration (IMERG_Cal) and without gauge correction (IMERG_Uncal) generally capture the spatial patterns of storm-accumulated precipitation with moderate to high correlation coefficients (CCs) of 0.57–0.87, and relative bias (RB) varying from −17.21% to 30.58%; (2) IMERG_Uncal and IMERG_Cal capture well the area-average hourly series of precipitation over rainfall centers with high CCs ranging from 0.78 to 0.94; (3) IMERG_Cal tends to underestimate precipitation especially the rainfall over the rainfall centers when compared to IMERG_Uncal. The IMERG Final Run shows promising potentials in typhoon-related extreme precipitation storm applications. 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.

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Event-Based Time Distribution Patterns, Return Levels, and Their Trends of Extreme Precipitation across Indus Basin

Water ◽

10.3390/w12123373 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3373

Author(s):

Muhammad Zaman ◽

Ijaz Ahmad ◽

Muhammad Usman ◽

Muhammad Saifullah ◽

Muhammad Naveed Anjum ◽

...

Keyword(s):

Extreme Precipitation ◽

Time Distribution ◽

Daily Precipitation ◽

Distribution Patterns ◽

Precipitation Extremes ◽

Event Duration ◽

Extreme Precipitation Events ◽

Return Levels ◽

Event Based ◽

Precipitation Events

This study presented the spatio-temporal characteristics of extreme precipitation events in the Northern Highlands of Pakistan (NHPK). Daily precipitation observations of 30 in situ meteorological stations from 1961 to 2014 were used to estimate the 11 extreme precipitation indices. Additionally, trends in time distribution patterns (TDPs) and return periods were also investigated for event based extreme precipitations (EEP). Results found that the precipitation events with an amount of 160–320 mm and with a concentration ratio of 0.8–1.0 and a duration of 4–7 consecutive days were dominant. The frequency of heavy, very heavy and extremely heavy precipitation days decreased, whereas the frequency of wet, very wet and extremely wet days increased. Most of the indices, generally, showed an increasing trend from the northeast to middle parts. The extreme precipitation events of the 20 and 50-year return period were more common in the western and central areas of NHPK. Moreover, the 20 and 50-year return levels depicted higher values (up to 420 mm) for an event duration with all daily precipitation extremes dispersed in the first half (TDP1) in the Chitral, Panjkora and Jhelum Rivers basins, whilst the maximum values (up to 700 mm) for an event duration with all daily precipitation extremes dispersed in the second half (TDP2) were observed in the eastern part of the NHPK for 20-year and eastern and south-west for 50-year, respectively.

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ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

Journal of Climate ◽

10.1175/2007jcli1705.1 ◽

2008 ◽

Vol 21 (1) ◽

pp. 22-39 ◽

Cited By ~ 48

Author(s):

Siegfried D. Schubert ◽

Yehui Chang ◽

Max J. Suarez ◽

Philip J. Pegion

Keyword(s):

United States ◽

West Coast ◽

Extreme Precipitation ◽

East Coast ◽

Daily Precipitation ◽

Precipitation Variability ◽

The West ◽

Extreme Precipitation Events ◽

The Impact ◽

Precipitation Events

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.

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Reliability of global gridded precipitation products in assessing extremes

10.5194/egusphere-egu21-3246 ◽

2021 ◽

Author(s):

Chandra Rupa Rajulapati ◽

Simon Michael Papalexiou ◽

Martyn P Clark ◽

Saman Razavi ◽

Guoqiang Tang ◽

...

Keyword(s):

Spatial Variability ◽

Extreme Precipitation ◽

Probability Distributions ◽

Extreme Precipitation Events ◽

Return Levels ◽

Time Period ◽

Precipitation Gauge ◽

Global Precipitation ◽

Surface Observations ◽

Precipitation Events

<p>Assessing extreme precipitation events is of high importance to hydrological risk assessment, decision making, and adaptation strategies. Global gridded precipitation products, constructed by combining various data sources such as precipitation gauge observations, atmospheric reanalyses and satellite estimates, can be used to estimate extreme precipitation events. Although these global precipitation products are widely used, there has been limited work to examine how well these products represent the magnitude and frequency of extreme precipitation. In this work, the five most widely used global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR and WFDEI) are compared to each other and to GHCN-daily surface observations. The spatial variability of extreme precipitation events and the discrepancy amongst datasets in predicting precipitation return levels (such as 100- and 1000-year) were evaluated for the time period 1979-2017. &#160;The behaviour of extremes, that is the frequency and magnitude of extreme precipitation, was quantified using indices of the heaviness of the upper tail of the probability distribution. Two parameterizations of the upper tail, the power and stretched-exponential, were used to reveal the probabilistic behaviour of extremes. The analysis shows strong spatial variability in the frequency and magnitude of precipitation extremes as estimated from the upper tails of the probability distributions. This spatial variability is similar to the K&#246;ppen-Geiger climate classification. The predicted 100- and 1000-year return levels differ substantially amongst the gridded products, and the level of discrepancy varies regionally, with large differences in Africa and South America and small differences in North America and Europe. The results from this work reveal the shortcomings of global precipitation products in representing extremes. The work shows that there is no single global product that performs best for all regions and climates.</p>

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Spatiotemporal Changes in Extreme Precipitation and Its Dependence on Topography over the Poyang Lake Basin, China

Advances in Meteorology ◽

10.1155/2019/1253932 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15 ◽

Cited By ~ 4

Author(s):

Xianghu Li ◽

Qi Hu

Keyword(s):

Water Resources ◽

Extreme Precipitation ◽

Poyang Lake ◽

Precipitation Extremes ◽

Lake Basin ◽

Extreme Precipitation Events ◽

Poyang Lake Basin ◽

Spatiotemporal Changes ◽

Increasing Trends ◽

Precipitation Events

Spatiotemporal changes in extreme precipitation at local scales in the context of climate warming are overwhelmingly important for prevention and mitigation of water-related disasters and also provide critical information for effective water resources management. In this study, the variability and trends of extreme precipitation in both time and space in the Poyang Lake basin over the period of 1960–2012 are analyzed. Also, changes in precipitation extremes with topography are investigated, and possible causes are briefly discussed. The results show that extreme precipitation over the Poyang Lake basin is intensified during the last 50 years, especially the increasing trends are more significant before the end of the 1990s. Moreover, high contribution rates of extreme precipitation to the total rainfall (40–60%) indicated that extreme precipitation plays an important role to the total water resources in this area. The precipitation extremes also exhibited a significant spatial dependence in the basin. The northeastern and eastern areas are exposed to high risk of flood disaster with the higher frequency of extreme precipitation events. In addition, the distribution of precipitation extremes had a clear dependence on elevation, and the topography is an important factor affecting the variability of extreme precipitation over the Poyang Lake basin.

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Systematical Evaluation of GPM IMERG and TRMM 3B42V7 Precipitation Products in the Huang-Huai-Hai Plain, China

Remote Sensing ◽

10.3390/rs11060697 ◽

2019 ◽

Vol 11 (6) ◽

pp. 697 ◽

Cited By ~ 18

Author(s):

Fenglin Xu ◽

Bin Guo ◽

Bei Ye ◽

Qia Ye ◽

Huining Chen ◽

...

Keyword(s):

Tropical Rainfall Measuring Mission ◽

Accurate Estimation ◽

Detection Capability ◽

Satellite Precipitation ◽

Precipitation Measurement ◽

Daily Precipitation Data ◽

Precipitation Estimates ◽

Global Precipitation Measurement ◽

Global Precipitation ◽

Precipitation Events

Accurate estimation of high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) and Tropical Rainfall Measuring Mission (TRMM) is critical for hydrological and meteorological research, providing a benchmark for the continued development and future improvement of these products. This study aims to comprehensively evaluate the Integrated Multi-Satellite Retrievals for GPM (IMERG) and TRMM 3B42V7 products at multiple temporal scales from 1 January 2015 to 31 December 2017 over the Huang-Huai-Hai Plain in China, using daily precipitation data from 59 meteorological stations. Three commonly used statistical metrics (CC, RB, and RMSE) are adopted to quantitatively verify the accuracy of two satellite precipitation products. The assessment also takes into account the precipitation detection capability (POD, FAR, CSI, and ACC) and frequency of different precipitation intensities. The results show that the IMERG and 3B42V7 present strong correlation with meteorological stations observations at annual and monthly scales (CC > 0.90), whereas moderate at the daily scale (CC = 0.76 and 0.69 for IMERG and 3B42V7, respectively). The spatial variability of the annual and seasonal precipitation is well captured by these two satellite products. And spatial patterns of precipitation gradually decrease from south to north over the Huang-Huai-Hai Plain. Both IMERG and 3B42V7 products overestimate precipitation compared with the station observations, of which 3B42V7 has a lower degree of overestimation. Relative to the IMERG, annual precipitation estimates from 3B42V7 show lower RMSE (118.96 mm and 142.67 mm, respectively), but opposite at the daily, monthly, and seasonal scales. IMERG has a better precipitation detection capability than 3B42V7 (POD = 0.83 and 0.67, respectively), especially when detecting trace and solid precipitation. The two precipitation products tend to overestimate moderate (2–10 mm/d) and heavy (10–50 mm/d) precipitation events, but underestimate violent (>50 mm/d) precipitation events. The IMERG is not found capable to detecting precipitation events of different frequencies more precisely. In general, the accuracy of IMERG is better than 3B42V7 product in the Huang-Huai-Hai Plain. The IMERG satellite precipitation product with higher temporal and spatial resolutions can be regarded a reliable data sources in studying hydrological and climatic research.

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Impacts of Atmospheric Rivers in Extreme Precipitation on the European Macaronesian Islands

Atmosphere ◽

10.3390/atmos9080325 ◽

2018 ◽

Vol 9 (8) ◽

pp. 325 ◽

Cited By ~ 3

Author(s):

Alexandre M. Ramos ◽

Ricardo M. Trigo ◽

Ricardo Tomé ◽

Margarida L. R. Liberato

Keyword(s):

Canary Islands ◽

Extreme Precipitation ◽

Daily Precipitation ◽

Comprehensive Assessment ◽

Atmospheric Rivers ◽

Extreme Precipitation Events ◽

Macaronesian Islands ◽

Weather Stations ◽

The Relationship ◽

Precipitation Events

The European Macaronesia Archipelagos (Azores, Madeira and Canary Islands) are struck frequently by extreme precipitation events. Here we present a comprehensive assessment on the relationship between atmospheric rivers and extreme precipitation events in these three Atlantic Archipelagos. The relationship between the daily precipitation from the various weather stations located in the different Macaronesia islands and the occurrence of atmospheric rivers (obtained from four different reanalyses datasets) are analysed. It is shown that the atmospheric rivers’ influence over extreme precipitation (above the 90th percentile) is higher in the Azores islands when compared to Madeira or Canary Islands. In Azores, for the most extreme precipitation days, the presence of atmospheric rivers is particularly significant (up to 50%), while for Madeira, the importance of the atmospheric rivers is reduced (between 30% and 40%). For the Canary Islands, the occurrence of atmospheric rivers on extreme precipitation is even lower.

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Assessment of IMERG-V06 Precipitation Product over Different Hydro-Climatic Regimes in the Tianshan Mountains, North-Western China

Remote Sensing ◽

10.3390/rs11192314 ◽

2019 ◽

Vol 11 (19) ◽

pp. 2314 ◽

Cited By ~ 10

Author(s):

Anjum ◽

Ahmad ◽

Ding ◽

Shangguan ◽

Zaman ◽

...

Keyword(s):

Tropical Rainfall Measuring Mission ◽

Tianshan Mountains ◽

Western China ◽

Spatiotemporal Variability ◽

Eastern Region ◽

Monthly Precipitation ◽

Precipitation Measurement ◽

Global Precipitation Measurement ◽

Global Precipitation ◽

Precipitation Events

This study presents an assessment of the version-6 (V06) of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) product from June 2014 to December 2017 over different hydro-climatic regimes in the Tianshan Mountains. The performance of IMERG-V06 was compared with IMERG-V05 and the Tropical Rainfall Measuring Mission (TRMM) 3B42V7 precipitation products. The precipitation products were assessed against gauge-based daily and monthly precipitation observations over the entire spatial domain and five hydro-climatologically distinct sub-regions. Results showed that: (1) The spatiotemporal variability of average daily precipitation over the study domain was well represented by all products. (2) All products showed better correlations with the monthly gauge-based observations than the daily data. Compared to 3B42V7, both IMERG products presented a better agreement with gauge-based observations. (3) The estimation skills of all precipitation products showed significant spatial variations. Overall performance of all precipitation products was better in the Eastern region compared to the Middle and Western regions. (4) Satellite products were able to detect tiny precipitation events, but they were uncertain in capturing light and moderate precipitation events. (5) No significant improvements in the precipitation estimation skill of IMERG-V06 were found as compared to IMERG-V05. We deduce that the IMERG-V06 precipitation detection capability could not outperform the efficiency of IMERG-V05. This comparative evaluation of the research products of Global Precipitation Measurement (GPM) and TRMM products in the Tianshan Mountains is useful for data users and algorithm developers.

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Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

Journal of Hydrometeorology ◽

10.1175/jhm-d-15-0097.1 ◽

2016 ◽

Vol 17 (2) ◽

pp. 693-711 ◽

Cited By ~ 16

Author(s):

Hamed Ashouri ◽

Soroosh Sorooshian ◽

Kuo-Lin Hsu ◽

Michael G. Bosilovich ◽

Jaechoul Lee ◽

...

Keyword(s):

United States ◽

Extreme Precipitation ◽

Gulf Coast ◽

The United States ◽

Value Theory ◽

Extreme Value ◽

Precipitation Extremes ◽

Precipitation Product ◽

Extreme Precipitation Events ◽

Precipitation Events

Abstract This study evaluates the performance of NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979–2010. The Climate Prediction Center (CPC) U.S. Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

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