Evaluating the accuracy of Climate Hazard Group (CHG) satellite rainfall estimates for precipitation based drought monitoring in Koshi basin, Nepal

Shrestha, Narayan Kumar; Qamer, Faisal Mueen; Pedreros, Diego; Murthy, M. S. R.; Wahid, Shahriar; Shrestha, Mandira Singh

doi:10.1016/j.ejrh.2017.08.004

Cited by 72 publications

(55 citation statements)

References 17 publications

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“…PERSIANN-CDR consistently overestimated in-situ precipitation, while TMPA, CHIRPS and MSWEP performed adequately. These findings concurred with those of [35,47,54,58], with a possible reason being that infrared based retrievals have limitations in estimating precipitation over complex terrains [35,59,60]. The daily scale performance suggests that GPPs were consistent for daily scale thresholds, with PERSIANN-CDR and MSWEP overestimating in some regions.…”

Section: Discussionsupporting

confidence: 75%

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Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan

et al. 2019

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Various state-of-the-art gridded satellite precipitation products (GPPs) have been derived from remote sensing and reanalysis data and are widely used in hydrological studies. An assessment of these GPPs against in-situ observations is necessary to determine their respective strengths and uncertainties. GPPs developed from satellite observations as a primary source were compared to in-situ observations, namely the Climate Hazard group Infrared Precipitation with Stations (CHIRPS), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA). These products were compared to in-situ data from 51 stations, spanning 1998-2016, across Pakistan on daily, monthly, annual and interannual time scales. Spatiotemporal climatology was well captured by all products, with more precipitation in the north eastern parts during the monsoon months and vice-versa. Daily precipitation with amount larger than 10 mm showed significant (95%, Kolmogorov-Smirnov test) agreement with the in-situ data, especially TMPA, followed by CHIRPS and MSWEP. At monthly scales, there were significant correlations (R) between the GPPs and in-situ records, suggesting similar dynamics; however, statistical metrics suggested that the performance of these products varies from north towards south. Temporal agreement on an interannual scale was higher in the central and southern parts which followed precipitation seasonality. TMPA performed the best, followed in order by CHIRPS, MSWEP and PERSIANN-CDR.

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Section: Discussionsupporting

confidence: 75%

“…These findings concur with those of [36][37][38]52] for TMPA, [47,53] for Remote Sens. 2019, 11, 628 20 of 25 PERSIANN-CDR, [51,54,55] for CHIRPS and [56,57] for MSWEP. MWSEP is a relatively new product; thus, very few studies have reported similar findings in such a diverse range of climate.…”

Section: Comparison On An Interannual Scale For Different Seasonsmentioning

confidence: 99%

Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan

et al. 2019

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“…In this sense, Quesada-Montano et al [59] highlighted that the selection of the precipitation database was more important than the selection of the drought index. e use of CHIRPS precipitation estimates for drought monitoring based on the SPI has gained attraction nowadays, as shown by studies performed in Indonesia [60], China [1,28], Nepal [11], Morocco [54], Southeast Asia [27], Central America [59], and Chile [12].…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, operational thresholds for the de nition of dry and wet conditions can also provide valuable information for decision-making, given that drought and ood monitoring is of paramount importance considering the socioeconomic activities over the region. Future validation studies should also include the Climate Hazards Group Infrared Precipitation (CHIRP) satelliteonly product, given its short latency (available 2 days after the end of a pentad) and its performance after 1992 [11].…”

Section: Discussionmentioning

confidence: 99%

“…is database was mainly used for the assessment of monthly, seasonal, and annual precipitation variability in several regions of the world. Monthly CHIRPS estimations were applied for drought monitoring in Nepal [11], Chile [12], and China [1]. e research of López-Carr et al [13] used 3month accumulations to identify changes in the growing season precipitation patterns over Africa.…”

Section: Introductionmentioning

confidence: 99%

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Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

Rivera

Hinrichs

Marianetti

2019

Advances in Meteorology

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e Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset was conceived as a tool for monitoring drought and environmental change over land. Recent validation efforts along South America have assessed its suitability for reproducing the main spatial and temporal features of precipitation. Nevertheless, little has been done regarding the ability of CHIRPS for the assessment of wet and dry conditions, particularly in areas where in situ precipitation records are scarce. In this paper, we investigated the performance of CHIRPS for monitoring wet and dry events along the semiarid Central-Western Argentina. Using the Standardized Precipitation Index (SPI), we compared the CHIRPS database with records from 49 meteorological stations along the study area for the period 1987-2016. Results indicate that the CHIRPS dataset adequately reproduced the temporal variability of SPI on multiple timescales (1 month, 3 months, and 6 months), particularly in the region dominated by warm season precipitation. e large overestimation of the seasonal precipitation in the region dominated by cold season precipitation can introduce errors that are reflected in the performance of CHIRPS over the western portion of the domain. e frequency of wet and dry classes was accurately reproduced by CHIRPS on timescales larger than 1 month (SPI1), given the existence of a wet bias that produces an underestimation of the frequency of zero values. is bias is further translated to the evaluation of the SPI1 during the spatial and temporal assessment of historical dry (1998) and wet (2016) events, especially for the classification of extreme dry/wet months. e results from the evaluation indicate that CHIRPS is a suitable tool for assessing dry and wet conditions for timescales longer than 1 month and can support decision-making process within the hydrometeorological agencies over the region.

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Evaluation of Climate Hazards Group InfraRed Precipitation Station (CHIRPS) satellite‐based rainfall estimates over Finchaa and Neshe Watersheds, Ethiopia

Geleta

Deressa

2020

Engineering Reports

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Recent advancements in the field of remote sensing have led to the development of high resolution satellite‐based rainfall products to improve the quality of observed rainfall data through proper evaluation and validation process of the products. This study therefore, intended to evaluate the performance of CHIRPS (Climate Hazards Group InfraRed Precipitation Station) satellite‐based rainfall products in Finchaa and Neshe watersheds of Blue Nile Basin. Daily ground‐ and satellite‐based rainfall data are collected from Ethiopian National Meteorological Agency and CHIRPS dataset of CHG (Climate Hazards Group) respectively, for the time slice of 25 years (1991–2015). The performance of CHIRPS product is evaluated using quantitative statistical performance indicators and graphical comparison methods. CHIRPS satellite product tends to slightly overestimate the mean rainfall depth at the study area. A positive strong linear correlation (R = 0.93 and R2 = 0.86) and a smaller amount of noise, bias and error (NSE = 0.84, PBIAS = 0.98%, and RMSE = 46.99 mm) have been found between CHIRPS satellite‐based and the ground‐based rainfall products when compared. The overall results in this study also indicated the good performance of CHIRPS satellite‐based rainfall estimates in maintaining patterns of observed measurements at monthly, seasonal and annual time steps across the watersheds.

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Evaluating the accuracy of Climate Hazard Group (CHG) satellite rainfall estimates for precipitation based drought monitoring in Koshi basin, Nepal

Cited by 72 publications

References 17 publications

Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan

Comparing Multiple Precipitation Products against In-Situ Observations over Different Climate Regions of Pakistan

Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

Evaluation of Climate Hazards Group InfraRed Precipitation Station (CHIRPS) satellite‐based rainfall estimates over Finchaa and Neshe Watersheds, Ethiopia

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