Evaluation of CHIRPS and its application for drought monitoring over the Haihe River Basin, China

Gao, Feng; Zhang, Yuhu; Ren, Xiulin; Yao, Yunjun; Hao, Zengchao; Cai, Wanyuan

doi:10.1007/s11069-018-3196-0

Cited by 85 publications

(46 citation statements)

References 37 publications

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“…For example, the Palmer Drought Index, which was proposed by Palmer in 1965, has become the semi-official drought index of the United States [4]. The Standardized Precipitation Index (SPI) established by McKee in 1993 is based on long-term precipitation records and has been used widely to analyze the characteristics of drought in various regions [5][6][7][8]. For monitoring meteorological drought, relevant indices include the relative humidity index [9] and the Standardized Precipitation Evapotranspiration Index [10].…”

Section: Introductionmentioning

confidence: 99%

Performance of Two Long-Term Satellite-Based and GPCC 8.0 Precipitation Products for Drought Monitoring over the Yellow River Basin in China

et al. 2019

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This study investigated the accuracy and drought monitoring application of two newly-released long-term satellite precipitation products (i.e., the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record, PERSIANN-CDR and the Climate Hazards Group Infrared Precipitation with Station data version 2.0 CHIRPS) and the latest reanalysis precipitation product (i.e., the Global Precipitation Climatology Centre full data monthly version 2018, GPCC 8.0). Satellite- and reanalysis-based precipitation sequences and standardized precipitation indices (SPIs) were compared comprehensively with background estimates of the China Gauge-based Daily Precipitation Analysis (CGDPA) dataset at spatial and multiple temporal scales over the Yellow River Basin (YRB) in China during 1983–2016. Results indicated the PERSIANN-CDR, CHIRPS and GPCC 8.0 precipitation products generally had good consistency with CGDPA (correlation coefficient, CC > 0.78). At spatial, monthly and seasonal scales, the consistency between GPCC 8.0 and CGDPA precipitation was found to be better than that of the two satellite products. Due to their good performance at the spatiotemporal scale, the satellite with long-time record and GPCC 8.0 products were evaluated and compared with CGDPA to derive SPI-1 (1-month SPI), SPI-3 (3-month SPI), and SPI-12 (12-month SPI) for drought monitoring in the YRB. The results showed that they had good application in monitoring droughts (CC > 0.65 at spatial scale, CC > 0.84 at temporal scale). The historical drought years (i.e., 1997, 1999, and 2006) and the spatial distribution of drought area in August 1997 were captured successfully, but the performance of GPCC 8.0 was found to be the best. Overall, GPCC 8.0 is considered best suited to complement precipitation datasets for long-term hydrometeorological research in the YRB.

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Section: Introductionmentioning

confidence: 99%

Performance of Two Long-Term Satellite-Based and GPCC 8.0 Precipitation Products for Drought Monitoring over the Yellow River Basin in China

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%

“…A wide range of satellite-derived precipitation products have emerged in the last decades, providing a spatial coverage that is superior to gauge products, considering that rain gauges had the obvious queries such as the density of site networks, the continuous time series, and the financial limitation [1]. Some of these products are the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) [2], the Climate Prediction Center Morphing (CMORPH) technique [3], the Global Satellite Mapping of Precipitation (GSMaP) [4], the TRMM Multisatellite Precipitation Analysis (TMPA) 3B42RT [5], and the Multisource Weighted-Ensemble Precipitation (MSWEP) [6].…”

Section: Introductionmentioning

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%

“…Zambrano et al [12] concluded that, in order to use the CHIRPS dataset to monitor drought intensity conditions, the product should be calibrated to adjust for the overestimation/underestimation of rainfall geographically. Recently, Gao et al [1] and Zhong et al [28] indicated that CHIRPS successfully captured the spatial patterns of drought over China.…”

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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Spatio‐Temporal Variations and El Niño Modulation of Meteorological Droughts in Malaysia

Zakaria,

Tangang,

Salimun

et al. 2024

Intl Journal of Climatology

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Meteorological droughts in Malaysia have significantly impacted critical sectors such as agriculture, water resources, health, the environment, tourism and various socio‐economic sectors, affecting the population's livelihood and well‐being. This study analyses drought characteristics over a 39‐year period, from 1982 to 2021, using the Standardised Precipitation Index (SPI) derived from 5‐km resolution Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). The droughts were assessed on 3‐, 6‐, 9‐ and 12‐month timescales to investigate spatio‐temporal variations in characteristics such as frequency, duration, peak, severity and intensity. The study also provides an in‐depth analysis of large‐scale drought modulation, particularly associated with the El Niño phenomenon and its teleconnection in the Maritime Continent. Depending on the location and timescale, the number of meteorological drought occurrences varied from 10 to 22 for the 3‐month timescale and 4 to 14 for the 12‐month timescale. Generally, as the timescale of a drought increases, the peak intensity decreases, while the duration and severity increase. Additionally, drought intensity decreases over longer timescales. These characteristics show significant spatial variations. Results indicate that meteorological droughts in Malaysia were almost entirely modulated by the El Niño phenomenon through its induced teleconnection over the Maritime Continent. Drought characteristics exhibit a strong seasonality linked to changes in the Walker circulation and the strengthening and weakening of anticyclonic circulations associated with Rossby waves induced by heating in the Pacific Ocean. Very strong El Niño events had the most significant influence on the droughts. The positive Indian Ocean Dipole (pIOD) strengthened the effects of El Niño but it itself had no significant influence on the droughts. In most regions, there were no significant trends in the characteristics of meteorological droughts. However, in northeast Peninsular Malaysia and some scattered areas along the west coast of the peninsula, significant trends are observed in peak, duration and severity.

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Evaluation of CHIRPS and its application for drought monitoring over the Haihe River Basin, China

Cited by 85 publications

References 37 publications

Performance of Two Long-Term Satellite-Based and GPCC 8.0 Precipitation Products for Drought Monitoring over the Yellow River Basin in China

Performance of Two Long-Term Satellite-Based and GPCC 8.0 Precipitation Products for Drought Monitoring over the Yellow River Basin in China

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

Spatio‐Temporal Variations and El Niño Modulation of Meteorological Droughts in Malaysia

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