A comprehensive validation for GPM IMERG precipitation products to detect extremes and drought over mainland China

Yu, Linfei; Leng, Guoyong; Python, André

doi:10.1016/j.wace.2022.100458

Cited by 20 publications

(12 citation statements)

References 60 publications

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“…The satellite‐based rainfall from the IMERG V06 precipitation rate (“precipitationCal”) data is used to explore the diurnal rainfall over Sumatra. The IMERG data set is currently the most advanced remote sensing precipitation product (G. Huffman, Bolvin, et al., 2019; G. Huffman, Stocker, et al., 2019; G. J. Huffman et al., 2020; Yu et al., 2022). The IMERG algorithm intercalibrates, merges, and interpolates microwave precipitation estimates from the Global Precipitation Measurement satellite constellation, integrating microwave‐calibrated infrared satellite estimates and precipitation gauge data to produce a global‐gridded data set with spatiotemporal resolutions of 0.1° and 30‐min resolution (G. Huffman, Bolvin, et al., 2019; G. Huffman, Stocker, et al., 2019; G. J. Huffman et al., 2020).…”

Section: Methodsmentioning

confidence: 99%

“…Huffman, Stocker, et al, 2019;G. J. Huffman et al, 2020;Yu et al, 2022). The IMERG algorithm intercalibrates, merges, and interpolates microwave precipitation estimates from the Global Precipitation Measurement satellite constellation, integrating microwave-calibrated infrared satellite estimates and precipitation gauge data to produce a global-gridded data set with spatiotemporal resolutions of 0.1° and 30-min resolution (G. G.…”

Section: Imerg Data Collectionmentioning

confidence: 99%

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The Diurnal Cycle of Rainfall and Deep Convective Clouds Around Sumatra and the Associated MJO‐Induced Variability During Austral Summer in Himawari‐8

Lopez‐Bravo,

Vincent,

Huang

et al. 2023

JGR Atmospheres

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The effects of the diurnal cycle and large‐scale atmospheric disturbances dominate rainfall and cloud variability in the Maritime Continent. This study examines the modulation of the Austral Summer diurnal cycle by the Madden–Julian Oscillation (MJO) using cloud populations through precipitation and deep convective cloud derived from satellite measurements. Using Rainfall Potential Areas from Himawari‐8 Advanced Himawari Imager as a proxy for deep convection, our analysis shows that convective clouds are present ∼55% of the time over land in Sumatra during the afternoon and night. Cloud signatures reveal semi‐diurnal structures of deep convective clouds off the West Coast of Sumatra. In contrast, the East Coast exhibits explicit sea‐ward propagation patterns of deep convective controlled by the coastal effects around the Strait of Malacca and Java Sea, together with the influence of synchronized diurnal forcing between islands. We show that the MJO drives the enhanced convective phases, changing the cloud top type distribution, moisture convergence, and moisture transport over the equatorial Indian Ocean. The cold cloud area also increases during the MJO active phases, which is linked to frequent deep convective cloud development near the mountain ranges of Sumatra and the adjacent ocean. The analyses of cloud variations based on the rainfall potential areas and cloud top type provide evidence of the effects of convective processes on the diurnal cycle of ice and water vapor distribution in the troposphere.

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Section: Methodsmentioning

confidence: 99%

Section: Imerg Data Collectionmentioning

confidence: 99%

The Diurnal Cycle of Rainfall and Deep Convective Clouds Around Sumatra and the Associated MJO‐Induced Variability During Austral Summer in Himawari‐8

Lopez‐Bravo,

Vincent,

Huang

et al. 2023

JGR Atmospheres

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“…Li The use of multiple sensors for the estimation of precipitation indicated promising results recently, in this context, (Brocca et al 2019) showed that a global daily satellite precipitation data works relatively well in data-poor regions of the world, such as Africa and South America. Several recent studies have focused on the use of different precipitation datasets due to data scarcity and lack of follow-up in poorly gauged or ungauged catchments such as in Blue Nile River sub-basin in the Sudan (Abd Elhamid et al 2020), in the north of Tunisia (Dhib et al 2017), in Taiwan (Hsu et al 2021), in Australia (Islam et al 2020), in Andalusia in Spain (Moreno et al 2022), in in the Sio Malaba Malakisi river basin of East Africa (Omonge et al 2022), in the Mainland China (Yu et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Assessing the variability of satellite and reanalysis rainfall products over a semiarid catchment in Tunisia

Gharnouki,

Aouissi,

Benabdallah

et al. 2024

Acta Geophys.

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Precipitation is a key component in hydrologic processes. It plays an important role in hydrological modeling and water resource management. However, many regions suffered from limited and data scarcity due to the lack of ground-based rain gauge networks. The main objective of this study is to evaluate and compare three different satellite-based precipitation products (CHIRPS, PERSIANN and GPM) and a reanalysis (ERA5) in semi-arid catchment of Tunisia (Haffouz catchment) against rain-gauge stations records for the period between September 2000 and August 2018. Twelve rain-gauges and two different interpolation methods (Inverse Distance Weight and ordinary kriging) were used to compute a set of interpolated precipitation reference elds. The evaluation was performed at daily, monthly, and yearly time scales and at spatial scales, using different statistical metrics. The results showed that the two interpolation methods give similar and valid precipitation estimates at the catchment scale.According to the different statistical metrics, CHRIPS showed the most satisfactory results followed by PERSIANN which performed well in terms of correlation but overestimated precipitations spatially over the catchment. GPM underestimate the precipitation considerably, but it gives a satisfactory performance temporally. ERA5 shows a very good performance at daily, monthly, and yearly timescale, but it is unable to present the spatial variability distribution of precipitation for this catchment. This study concluded that satellite-based precipitation products can be useful in semi-arid regions and data-scarce catchments, and it may provide less costly alternatives for data-poor regions.

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“…With the continuous development of remote sensing technology, multisource satellite precipitation products have been widely used in hydrological research (Chen et al, 2014;Zhou et al, 2017), effectively making up for the problems of traditional monitoring, such as time consuming and power consumption and insufficient site observation data, etc., with the advantages of wide coverage, good space-time continuity, and strong timeliness of data acquisition. Yu et al (2022) used GPM data to complete the spatiotemporal monitoring of drought in mainland China. Alijanian et al (2022) combined MSWEP data to realize drought monitoring in the Zayandehrood Basin, a key area of the Iranian plateau, showing that remote sensing data can more accurately represent the temporal and spatial distribution of drought in the absence of site data.…”

Section: Introductionmentioning

confidence: 99%

Construction of high-resolution precipitation dataset and its implication to drought over the Tianshan Mountains, China

He²,

Li³

et al. 2023

Front. Earth Sci.

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Understanding the drought characteristics of mountainous areas in northwest China with sparse rainfall stations requires high precision, as well as high-resolution precipitation data. Considering the spatial relationship of precipitation and environmental factors, this study downscales Global Precipitation Measurement (GPM) and Multi-Source Weighted-Ensemble Precipitation (MSWEP) based on the geographically weighted regression (GWR) and multi-scale geographically weighted regression (MGWR) models integrated with interpolation. A high-resolution (1 km×1 km) precipitation dataset during 1979–2020 is reconstructed in the Tianshan Mountains, and the drought characteristics are analyzed by using the optimal dataset. The results show that: 1) Compared with GWR, MGWR model has higher downscaling accuracy; 2) The optimal MSWEP downscaling dataset (CC = 0.93, |BIAS| = 0.48%) compared to GPM (CC = 0.81, |BIAS| = 1.87%) is closer to the observed precipitation; 3) In the past 40 years, 71% and 9% of the Tianshan Mountains show significant wetting and drying trends respectively, and 16 drought events are identified. 4) The West subregion of the Tianshan Mountains is characterized by low frequency, long duration and high severity of drought events. The characteristics of the East are opposite to those of the West. Occasional extreme drought events occur in the North and South. This paper provides data support and method reference for the study of water-vapor balance and regional ecohydrological process in the arid area of Northwest China.

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A comprehensive validation for GPM IMERG precipitation products to detect extremes and drought over mainland China

Cited by 20 publications

References 60 publications

The Diurnal Cycle of Rainfall and Deep Convective Clouds Around Sumatra and the Associated MJO‐Induced Variability During Austral Summer in Himawari‐8

The Diurnal Cycle of Rainfall and Deep Convective Clouds Around Sumatra and the Associated MJO‐Induced Variability During Austral Summer in Himawari‐8

Assessing the variability of satellite and reanalysis rainfall products over a semiarid catchment in Tunisia

Construction of high-resolution precipitation dataset and its implication to drought over the Tianshan Mountains, China

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