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Extreme precipitation (EP) often has a significant impact on
economic and social development as well as on human life.
According to the emergency database, between 1992 and 2022, floods and landslides accounted for 56.
55% of natural disasters in Central Asia, affecting more than 1.
28 million people and causing losses of more than $1.
31 billion
.
The latest research shows that future heavy precipitation events change more intensely, which is directly related to
global warming.
Therefore, estimating changes in extreme precipitation as accurately as possible is particularly critical
to coping with and mitigating the resulting impacts.
In view of this problem, the team of researcher Chen Yaning of the State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, based on the deviation correction of the FGOALS-g3 model developed by the State Key Laboratory of Atmospheric Science and Earth Fluid Dynamics Numerical Simulation, based on multi-source precipitation datasets and multiple statistical indicators, quantitatively evaluated the correction effect and its application
in the study of extreme precipitation in the Tianshan region of Central Asia.
The results show that: (1) FGOALS-g3 products can identify the spatial distribution pattern of multi-year average precipitation in the Tianshan region of Central Asia, but there is a significant overestimation in terms of magnitude, especially in the western and central regions
of the Tianshan Mountains.
After downscaling and deviation correction, the deviation is significantly reduced, and the square-by-grid error is controlled between
7.
64% and 10%.
(2) In the simulation of EP changes, the corrected FGOALS-g3 product reasonably reproduces the spatial distribution pattern of EP; In terms of magnitude, except for R99.
9, R99.
95 and other strong EP indicators, the overall relative error is between -34.
93% and 29.
70%.
(3) Limiting the temperature rise to 1.
5 °C can well constrain the change
in the intensity and frequency of EP.
(4) 30hPa latitude wind, the relative number of sunspots, the summer wind index of South Asia, and the average surface temperature are the main factors
affecting the EP change in the Tianshan region of Central Asia.
The results were published in Atmospheric Research under the title "Application of bias corrected FGOALS-g3 model products for detecting changes in extreme precipitation in the Tienshan Mountains, Central Asia
.
" The first author of the paper is Dr.
Zhang Xueqi of the Xinjiang Institute of Birth.
The research was funded by the National Natural Science Foundation of China
.
Article link: https://authors.
elsevier.
com/c/1fqK8cd3SFH6w
Figure 1.
Year-over-year distribution of annual mean daily precipitation for observations (obs), FGOALS-g3 simulations (raw), and FGOALS-g3 correction (cor) (a) and empirical accumulation distributions (b).
Figure 2.
Spatial variation of extreme precipitation as reflected in observational data and FGOALS-g3 correction data: (a, b) CDD, (c, d) CWD, (e, f) PRCP, (g, h) Rx1day, (i, j) Rx5day, and (k, l) SDII.
