scholarly journals Ground validation of GPM IMERG-F precipitation products with the point rain gauge records on the extreme rainfall over a mountainous area of Sumatra Island

2022 ◽  
Vol 8 (1) ◽  
pp. 163-170
Author(s):  
Ravidho Ramadhan ◽  
Marzuki Marzuki ◽  
Helmi Yusnaini ◽  
Ayu Putri Ningsih ◽  
Hiroyuki Hashiguchi ◽  
...  

Accurate satellite precipitation estimates over areas of complex topography are still challenging, while such accuracy is of importance to the adoption of satellite data for hydrological applications. This study evaluated the ability of Integrated Multi-satellitE Retrievals for GPM -Final (IMERG) V06 product to observe the extreme rainfall over a mountainous area of Sumatra Island. Fifteen years of optical rain gauge (ORG) observation at Kototabang, West Sumatra, Indonesia (100.32°E, 0.20°S, 865 m above sea level), were used as reference surface measurement. The performance of IMERG-F was evaluated using 13 extreme rain indexes formulated by the Expert Team on Climate Change Detection and Indices (ETCCDI). The IMERG-F overestimated the values of all precipitation amount-based indices (PRCPTOT, R85P, R95P, and R99P), three precipitation frequency-based indices (R1mm, R10mm, R20mm), one precipitation duration-based indices (CWD), and one precipitation intensity-based indices (RX5day). Furthermore, the IMERG-F underestimated the values of precipitation frequency-based indices (R50mm), one precipitation duration-based indices (CDD), one precipitation intensity-based indices (SDII). In terms of correlation, only five indexes have a correlation coefficient (R) > 0.5, consistent with Kling–Gupta Efficiency (KGE) value. These results confirm the need to improve the accuracy of the IMERG-F data in mountainous areas.

2020 ◽  
Vol 21 (3) ◽  
pp. 533-550 ◽  
Author(s):  
Cheng Chen ◽  
Zhe Li ◽  
Yina Song ◽  
Zheng Duan ◽  
Kangle Mo ◽  
...  

AbstractPrecipitation in arid mountainous areas is characterized by low rainfall intensity and large spatial heterogeneity, which challenges satellite-based monitoring by the spaceborne sensors. This study aims to comparatively evaluate the detection ability of spatiotemporal patterns and extremes of rainfall by a range of mainstream satellite precipitation products [TMPA, Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), and PERSIANN–Climate Data Record (PERSIANN-CDR)] over a typical arid mountainous basin of China, benchmarking against rain gauge data from 2000 to 2015. Results showed that satellite precipitation estimates had relatively low accuracy at the daily scale, while a significant improvement of correlation coefficient (CC; >0.6) and a significant reduction of relative root-mean-square error (RRMSE; <1.0) were found as time scale increases beyond the monthly scale. CHIRPS tended to overestimate the gauge precipitation with positive relative bias (RB), while the negative RB values for TMPA and PERSIANN-CDR indicated there was an underestimation. CHIRPS had the most similar spatial pattern and slope trends of the seasonal precipitation and interannual variations of annual precipitation with gauge observations. With the increase in rainfall rates, the probability of detection (POD) and critical success index (CSI) were reduced and the false alarm ratio (FAR) was increased significantly, demonstrating the limited capability for all the three satellite products for detecting heavy rainfall events. CHIRPS showed the best performance in detecting rainfall extremes compared to TMPA and PERSIANN-CDR, evidenced by the larger CSI values and similar extreme rainfall indices obtained from gauge records. This study provides valuable guidance for choosing satellite precipitation products instead of gauge observations for rainfall monitoring (especially rainfall extremes) and agricultural production management over arid mountainous area.


Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 63
Author(s):  
Marzuki Marzuki ◽  
Helmi Yusnaini ◽  
Ravidho Ramadhan ◽  
Fredolin Tangang ◽  
Abdul Azim Bin Amirudin ◽  
...  

In this study we investigate the characteristics of the diurnal precipitation cycle including the Madden–Julian oscillation (MJO) and seasonal influences over a mountainous area in Sumatra Island based on the in situ measurement of precipitation using the optical rain gauge (ORG). For comparison with ORG data, the characteristics based on the Global Precipitation Measurement (GPM) mission (IMERG) and Weather Research and Forecasting (WRF) simulations were also investigated. Fifteen years of ORG data over a mountainous area of Sumatra, namely, at Kototabang (100.32° E, 0.20° S), were analyzed to obtain the characteristics of the diurnal cycle of precipitation in this region. The diurnal cycle of precipitation presented a single peak in the late afternoon, and the peak time difference was closely related to the rain event duration. The MJO acts to modulate the diurnal amplitude but not the diurnal phase. A high precipitation amount (PA) and frequency (PF) were observed during phases 2, 3, and 4, along with an increase in the number of longer-duration rain events, but the diurnal phase was similar in all MJO phases. In terms of season, the highest PA and PF values were observed during pre-southwest and pre-northeast monsoon seasons. WRF simulation reproduced the diurnal phase correctly and more realistically than the IMERG products. However, it largely overestimated the amplitude of the diurnal cycle in comparison with ORG. These disagreements could be related to the resolution and quality of IMERG and WRF data.


2007 ◽  
Vol 20 (19) ◽  
pp. 4801-4818 ◽  
Author(s):  
Ying Sun ◽  
Susan Solomon ◽  
Aiguo Dai ◽  
Robert W. Portmann

Abstract Daily precipitation data from climate change simulations using the latest generation of coupled climate system models are analyzed for potential future changes in precipitation characteristics. For the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1 (a low projection), A1B (a medium projection), and A2 (a high projection) during the twenty-first century, all the models consistently show a shift toward more intense and extreme precipitation for the globe as a whole and over various regions. For both SRES B1 and A2, most models show decreased daily precipitation frequency and all the models show increased daily precipitation intensity. The multimodel averaged percentage increase in the precipitation intensity (2.0% K−1) is larger than the magnitude of the precipitation frequency decrease (−0.7% K−1). However, the shift in precipitation frequency distribution toward extremes results in large increases in very heavy precipitation events (&gt;50 mm day−1), so that for very heavy precipitation, the percentage increase in frequency is much larger than the increase in intensity (31.2% versus 2.4%). The climate model projected increases in daily precipitation intensity are, however, smaller than that based on simple thermodynamics (∼7% K−1). Multimodel ensemble means show that precipitation amount increases during the twenty-first century over high latitudes, as well as over currently wet regions in low- and midlatitudes more than other regions. This increase mostly results from a combination of increased frequency and intensity. Over the dry regions in the subtropics, the precipitation amount generally declines because of decreases in both frequency and intensity. This indicates that wet regions may get wetter and dry regions may become drier mostly because of a simultaneous increase (decrease) of precipitation frequency and intensity.


2020 ◽  
Vol 12 (11) ◽  
pp. 1836 ◽  
Author(s):  
Shankar Sharma ◽  
Yingying Chen ◽  
Xu Zhou ◽  
Kun Yang ◽  
Xin Li ◽  
...  

The Global Precipitation Measurement (GPM) mission provides high-resolution precipitation estimates globally. However, their accuracy needs to be accessed for algorithm enhancement and hydro-meteorological applications. This study applies data from 388 gauges in Nepal to evaluate the spatial-temporal patterns presented in recently-developed GPM-Era satellite-based precipitation (SBP) products, i.e., the Integrated Multi-satellite Retrievals for GPM (IMERG), satellite-only (IMERG-UC), the gauge-calibrated IMERG (IMERG-C), the Global Satellite Mapping of Precipitation (GSMaP), satellite-only (GSMaP-MVK), and the gauge-calibrated GSMaP (GSMaP-Gauge). The main results are as follows: (1) GSMaP-Gauge datasets is more reasonable to represent the observed spatial distribution of precipitation, followed by IMERG-UC, GSMaP-MVK, and IMERG-C. (2) The gauge-calibrated datasets are more consistent (in terms of relative root mean square error (RRMSE) and correlation coefficient (R)) than the satellite-only datasets in representing the seasonal dynamic range of precipitation. However, all four datasets can reproduce the seasonal cycle of precipitation, which is predominately governed by the monsoon system. (3) Although all four SBP products underestimate the monsoonal precipitation, the gauge-calibrated IMERG-C yields smaller mean bias than GSMaP-Gauge, while GSMaP-Gauge shows the smaller RRMSE and higher R-value; indicating IMERG-C is more reliable to estimate precipitation amount than GSMaP-Gauge, whereas GSMaP-Gauge presents more reasonable spatial distribution than IMERG-C. Only IMERG-C moderately reproduces the evident elevation-dependent pattern of precipitation revealed by gauge observations, i.e., gradually increasing with elevation up to 2000 m and then decreasing; while GSMaP-Gauge performs much better in representing the gauge observed spatial pattern than others. (4) The GSMaP-Gauge calibrated based on the daily gauge analysis is more consistent with detecting gauge observed precipitation events among the four datasets. The high-intensity related precipitation extremes (95th percentile) are more intense in regions with an elevation below 2500 m; all four SBP datasets have low accuracy (<30%) and mostly underestimated (by >40%) the frequency of extreme events at most of the stations across the country. This work represents the quantification of the new-generation SBP products on the southern slopes of the central Himalayas in Nepal.


Hydrology ◽  
2020 ◽  
Vol 7 (3) ◽  
pp. 40 ◽  
Author(s):  
Kalpana Hamal ◽  
Shankar Sharma ◽  
Nitesh Khadka ◽  
Binod Baniya ◽  
Munawar Ali ◽  
...  

Precipitation is the most important variable in the climate system and the dominant driver of land surface hydrologic conditions. Rain gauge measurement provides precipitation estimates on the ground surface; however, these measurements are sparse, especially in the high-elevation areas of Nepal. Reanalysis datasets are the potential alternative for precipitation measurement, although it must be evaluated and validated before use. This study evaluates the performance of second-generation Modern-ERA Retrospective analysis for Research and Applications (MERRA-2) datasets with the 141-gauge observations from Nepal between 2000 and 2018 on monthly, seasonal, and annual timescales. Different statistical measures based on the Correlation Coefficient (R), Mean Bias (MB), Root-Mean-Square Error (RMSE), and Nash–Sutcliffe efficiency (NSE) were adopted to determine the performance of both MERRA-2 datasets. The results revealed that gauge calibrated (MERRA-C) underestimated, whereas model-only (MERRA-NC) overestimated the observed seasonal cycle of precipitation. However, both datasets were able to reproduce seasonal precipitation cycle with a high correlation (R ≥ 0.95), as revealed by observation. MERRA-C datasets showed a more consistent spatial performance (higher R-value) to the observed datasets than MERRA-NC, while MERRA-NC is more reasonable to estimate precipitation amount (lower MB) across the country. Both MERRA-2 datasets performed better in winter, post-monsoon, and pre-monsoon than in summer monsoon. Moreover, MERRA-NC overestimated the observed precipitation in mid and high-elevation areas, whereas MERRA-C severely underestimated at most of the stations throughout all seasons. Among both datasets, MERRA-C was only able to reproduce the observed elevation dependency pattern. Furthermore, uncertainties in MERRA-2 precipitation products mentioned above are still worthy of attention by data developers and users.


2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Chuancheng Zhao ◽  
Shuxia Yao ◽  
Shiqiang Zhang ◽  
Haidong Han ◽  
Qiudong Zhao ◽  
...  

Precipitation is one of the important water supplies in the arid and semiarid regions of northwestern China, playing a vital role in maintaining the fragile ecosystem. In remote mountainous area, it is difficult to obtain an accurate and reliable spatialization of the precipitation amount at the regional scale due to the inaccessibility, the sparsity of observation stations, and the complexity of relationships between precipitation and topography. Furthermore, accurate precipitation is important driven data for hydrological models to assess the water balance and water resource for hydrologists. Therefore, the use of satellite remote sensing becomes an important means over mountainous area. Precipitation datasets based on station data or pure satellite data have been increasingly available in spite of several weaknesses. This paper evaluates the usefulness of three precipitation datasets including TRMM 3B43_V6, 3B43_V7, and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation with rain gauge data over Tianshan mountainous area where precipitation data is scarce. The results suggest that precipitation measurements only provided accurate information on a small scale, while the satellite remote sensing of precipitation had obvious advantages in basin scale or large scale especially over remote mountainous area.


2019 ◽  
Vol 20 (6) ◽  
pp. 1123-1145 ◽  
Author(s):  
M. Lockhoff ◽  
O. Zolina ◽  
C. Simmer ◽  
J. Schulz

Abstract This paper evaluates several daily precipitation products over western and central Europe, identifies and documents their respective strengths and shortcomings, and relates these to uncertainties associated with each of the products. We analyze one gauge-based, three satellite-based, and two reanalysis-based products using high-density rain gauge observations as reference. First, we assess spatial patterns and frequency distributions using aggregated statistics. Then, we determine the skill of precipitation event detection from these products with a focus on extremes, using temporally and spatially matched pairs of precipitation estimates. The results show that the quality of the datasets largely depends on the region, season, and precipitation characteristic addressed. The satellite and the reanalysis precipitation products are found to have difficulties in accurately representing precipitation frequency with local overestimations of more than 40%, which occur mostly in dry regions (all products) as well as along coastlines and over cold/frozen surfaces (satellite-based products). The frequency distributions of wet-day intensities are generally well reproduced by all products. Concerning the frequency distributions of wet-spell durations, the satellite-based products are found to have clear deficiencies for maritime-influenced precipitation regimes. Moreover, the analysis of the detection of extreme precipitation events reveals that none of the non-station-based datasets shows skill at the shortest temporal and spatial scales (1 day, 0.25°), but at and above the 3-day and 1.25° scale the products start to exhibit skill over large parts of the domain. Added value compared to coarser-resolution global benchmark products is found both for reanalysis and satellite-based products.


2019 ◽  
Vol 20 (11) ◽  
pp. 2215-2227 ◽  
Author(s):  
Hua Shang ◽  
Ming Xu ◽  
Fen Zhao ◽  
Sadiya Baba Tijjani

Abstract In this paper, we examined the spatial and temporal variations in precipitation amount, frequency, and intensity in China based on daily precipitation data from 2050 weather stations from 1973 to 2016. We used two Markov chain parameters to quantify the wet persistence and dry persistence that characterizes the temporal pattern of wet and dry days, respectively. We found that China’s annual precipitation changed little from 1973 to 2016, but varied dramatically from 524 to 688 mm yr−1, with an average of 592 mm yr−1, during this period. China’s precipitation frequency, the number of days with effective precipitation (&gt;0.1 mm day−1) in a year, significantly decreased at a rate of 0.9 days decade−1 from 1973 to 2016, but precipitation intensity significantly increased at a rate of 0.12 mm day−1 decade−1 during the same period. Of the changes in China’s total precipitation amount, precipitation intensity played a dominant role, contributing 70.8%, while precipitation frequency contributed the remaining 29.2%. Little change was found in the wet persistence in China over the period of 1973–2016, but the dry persistence significantly increased with an average increasing trend of 1.62 × 10−3 probability per decade during the same period, and no significant correlations were found between these two variables. China’s precipitation also changed nonuniformly in space, with increasing trends in precipitation amount, frequency, intensity, and wet persistence in western and northeastern China but decreasing trends in the Sichuan basin, northeast of Inner Mongolia, and the Beijing–Tianjin–Hebei region.


2019 ◽  
Vol 36 (12) ◽  
pp. 2501-2520 ◽  
Author(s):  
David B. Wolff ◽  
Walter A. Petersen ◽  
Ali Tokay ◽  
David A. Marks ◽  
Jason L. Pippitt

Abstract Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on 25 August 2017 before exiting the state as a tropical storm on 29 August 2017. Left in its wake was historic flooding, with some locations measuring more than 60 in. (150 cm) of rain over a 5-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar dataset to retrieve daily and event-total precipitation estimates for the period 25–29 August 2017. The KHGX precipitation estimates were then compared with the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed drop size distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value of α = 0.015 and β = 0.600 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.


2020 ◽  
Vol 82 ◽  
pp. 97-115
Author(s):  
X Kong ◽  
A Wang ◽  
X Bi ◽  
J Wei

To evaluate and clarify the daily precipitation characteristics (i.e. amount, frequency and intensity) of the regional climate models (RCMs) in China, long-term simulations were carried out using RegCM4.5 and Weather Research and Forecasting model (WRF), which were nested within the European Centre for Medium-Range Weather Forecasts (ECMWF)’s 20th century reanalysis (ERA-20C) between 1901 and 2010. The 2 RCMs were initially run at a resolution of 50 km. Analyses mainly compared the model-simulated climatic means and interannual variations of precipitation characteristics with those of dense and high-quality station observations (STN) from 1961-2010. Both models satisfactorily reproduced the seasonal mean precipitation amount, but they overestimated its frequency and underestimated its intensity. Extreme rainfall frequency was also underestimated by both RCMs. In winter (DJF), the interannual variabilities in dry days, light precipitation and moderate precipitation were well represented by both models. However, they poorly reproduced the counterparts of extreme precipitation in winter. In summer (JJA), the 2 RCMs performed well in simulating the interannual variability of extreme precipitation. Comparably, RegCM outperformed WRF in reproducing the spatial patterns of precipitation amount, interannual variations in extreme precipitation and rain events. By contrast, WRF better represented precipitation frequency in different sub-regions overall. Moreover, when the horizontal resolution of RegCM was increased from 50 to 25 km, there was a slight improvement in the representation of precipitation amount and intensity. Our results show that RCMs perform well in reproducing actual climatic means and interannual variations of daily precipitation characteristics in China, and that high-resolution RCM simulations can produce improved results for precipitation amount and intensity.


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