Capacity of Satellite-Based and Reanalysis Precipitation Products in Detecting Long-Term Trends across Mainland China

Sun, Shurong; Shi, Wanrong; Zhou, Shujia; Chai, Rongfan; Chen, Haishan; Wang, Guojie; Zhang, Yang; Shen, Huayu

doi:10.3390/rs12182902

Cited by 15 publications

(4 citation statements)

References 120 publications

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“…Further replacement of the underground ice by rainwaters is observed. However, this conclusion is based The assessment of accuracy of ERA5 P linear trend (Sun et al 2020) showed minor (about 1 mm/year) bias for northeastern part of China, that is near BC.…”

Section: Discussionmentioning

confidence: 93%

Climate Change Impact On Flood Runoff Over Lake Baikal Catchment

Grigorev¹,

Kharlamov²,

Semenova³

et al. 2021

Preprint

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Water level and distribution of dissolved and suspended matter of Lake Baikal are strongly affected by river inflow during rain-driven floods. This study analyses river flow changes at 44 streamflow gauges and related precipitation, evaporation, potential evaporation and soil moisture obtained from ERA5-Land dataset. Based on Sen-Slope trend estimator, Mann–Kendall non-parametric test, and using dominant analyses we estimated influence of meteorological parameters on river flow during 1979-2019. Using ridge-regression we found significant relationships between precipitation elasticity of river flow and catchments features. Half of the gauges in eastern part of Selenga river basin showed a significant decreasing trend of average and maximum river flow (up to -2.9%/year). No changes in central volume date of flood flow have been found. A reduction in rainfall amounts explains more than 60% of runoff decline. Decrease in evaporation is observed where precipitation decrease is 0.8%/y or more. Catchments where the precipitation trends are not as substantial are associated with increasing evaporation as a result of the increase of potential evaporation. Negative trends of precipitation are accompanied by negative trends of soil moisture. Finally, the study reveals sensitivity of the catchments with steep slopes in humid area to precipitation change.

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Section: Discussionmentioning

confidence: 93%

Climate Change Impact On Flood Runoff Over Lake Baikal Catchment

Grigorev¹,

Kharlamov²,

Semenova³

et al. 2021

Preprint

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show abstract

“…An improved topography is used in the MERRA‐2 model and can better capture the topography variations at different pressure levels over the TP (figures not shown). Many studies have used these reanalysis data and documented their reliability in climate studies (Reichle et al., 2017; S. Sun et al., 2020).…”

Section: Methodsmentioning

confidence: 99%

Diagnosing Potential Impacts of Tibetan Plateau Spring Soil Moisture Anomalies on Summer Precipitation and Floods in the Yangtze River Basin

et al. 2023

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Soil moisture as a key variable of land processes greatly influences the weather and climate. This study investigates the observed linkage between Tibetan Plateau (TP) spring soil moisture and summer precipitation and floods in the Yangtze River basin during 1988–2008 using satellite and in‐situ observations. A significant (p = 1%) proportion of interannual variations of summer precipitation (about 25%) in the Yangtze River basin can be attributed to spring TP soil moisture anomalies which show a dipole pattern. When spring soil moisture anomalies are positive (negative) over eastern (western) TP, there is more summer precipitation and consequently river discharge in the Yangtze River basin, or vice versa. The possible mechanisms can be explained from the perspectives of surface energy balance and atmospheric thermodynamics. More (less) spring soil moisture over the eastern (western) plateau enhances summer diabatic heating, which may be related to soil moisture memory. The enhanced summer diabatic heating stimulates vigorous ascending motions over TP, which diverge in the upper troposphere (200 hPa) and descend over the western Pacific. This is conducive to the enhancement and mutual proximity of the South Asian High (SAH) and the Western Pacific Subtropical High (WPSH). As a result, the warm and humid air flows from the Bay of Bengal and the western Pacific and the cold and dry air flows from the boreal continent converge in the Yangtze River basin, causing excessive summer precipitation. Therefore, TP spring soil moisture can be considered a seasonal predictor of summer precipitation and possible subsequent floods in the Yangtze River basin.

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“…For example, how good is the overall performance (e.g., Kling-Gupta Efficiency (KGE), which integrates impacts of bias, variability, and correlation coefficient on the overall performance [33]) of the PERSIANN-CDR in detecting extreme precipitation, and does this product reproduce linear trends of extreme precipitation? Particularly, the latter issue has been paid more and more attention in recent years (e.g., [34,35]) because the assessments regarding precipitation trends are the necessary foundation on which to accurately explore precipitation long term changes, especially for the regions with limited and even no observations. Therefore, this study aimed to: (1) comprehensively validate the PER-SIANN-CDR performance in detecting different extreme precipitation indices (e.g., the precipitation amount-, duration-, and intensity-based indices) over the HRB, based on four validation metrics (i.e., three continuous validation metrics and one overall performance metric), and (2) detect the PERSIANN-CDR capacity to reproduce linear trends of various extreme precipitation indices.…”

Section: Study Region and Datamentioning

confidence: 99%

Capacity of the PERSIANN-CDR Product in Detecting Extreme Precipitation over Huai River Basin, China

et al. 2021

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Assessing satellite-based precipitation product capacity for detecting precipitation and linear trends is fundamental for accurately knowing precipitation characteristics and changes, especially for regions with scarce and even no observations. In this study, we used daily gauge observations across the Huai River Basin (HRB) during 1983–2012 and four validation metrics to evaluate the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) capacity for detecting extreme precipitation and linear trends. The PERSIANN-CDR well captured climatologic characteristics of the precipitation amount- (PRCPTOT, R85p, R95p, and R99p), duration- (CDD and CWD), and frequency-based indices (R10mm, R20mm, and Rnnmm), followed by moderate performance for the intensity-based indices (Rx1day, R5xday, and SDII). Based on different validation metrics, the PERSIANN-CDR capacity to detect extreme precipitation varied spatially, and meanwhile the validation metric-based performance differed among these indices. Furthermore, evaluation of the PERSIANN-CDR linear trends indicated that this product had a much limited and even no capacity to represent extreme precipitation changes across the HRB. Briefly, this study provides a significant reference for PERSIANN-CDR developers to use to improve product accuracy from the perspective of extreme precipitation, and for potential users in the HRB.

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Capacity of Satellite-Based and Reanalysis Precipitation Products in Detecting Long-Term Trends across Mainland China

Cited by 15 publications

References 120 publications

Climate Change Impact On Flood Runoff Over Lake Baikal Catchment

Climate Change Impact On Flood Runoff Over Lake Baikal Catchment

Diagnosing Potential Impacts of Tibetan Plateau Spring Soil Moisture Anomalies on Summer Precipitation and Floods in the Yangtze River Basin

Capacity of the PERSIANN-CDR Product in Detecting Extreme Precipitation over Huai River Basin, China

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