scholarly journals Future projection of extreme precipitation indices over the Indochina Peninsula and South China in CMIP6 models

2021 ◽  
pp. 1-63
Author(s):  
Bin Tang ◽  
Wenting Hu ◽  
Anmin Duan

AbstractA future projection of four extreme precipitation indices over the Indochina Peninsula and South China (INCSC) region with reference to the period 1958–2014 is conducted through the application of multimodel ensemble approach and rank-based weighting method. The weight of each model from phase 6 of the Coupled Model Intercomparison Project (CMIP6) is calculated depending on its historical simulation skill. Then, the weighted and unweighted ensembles are used for future projections. The results show that all four extreme precipitation indices are expected to increase over the INCSC region, both in the middle (2041–2060) and at the end (2081–2100) of the 21st century, under three Shared Socioeconomic Pathway (SSP) scenarios. The increases in total extreme precipitation (R95p), extreme precipitation days (R95d), and the fraction of total rainfall from events exceeding the extreme precipitation threshold (R95pT) in the Indochina Peninsula are more significant than those in South China. The occurrence of extreme rainfall events may become more frequent in the future over the INCSC region, since the probability that R95pT increases is larger than 0.7 in the whole INCSC region. A comparison between the weighted and unweighted ensemble means shows that the uncertainty over South China is almost always reduced after applying the weighted scheme to future probabilistic projection, while the reductions in uncertainty over the Indochina Peninsula may depend on SSPs. The more extreme precipitation over the INCSC region in the future may be related to the larger water vapor supply and the more unstable local atmospheric stratification.

2017 ◽  
pp. 63-76
Author(s):  
Nattapon Mahavik

Rainfall intensity and frequency are important parameters in agricultural development and water resource management. The middle of the Indochina peninsula climate is characterized by rainfall variability associated with complex terrains. The present study focuses on spatial seasonal extreme precipitation trends over the middle of the Indochina Peninsula for the 30 year period from 1978-2007. Daily gridded precipitation data obtained at 0.5° horizontal grid resolution from APHRODITE (Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources) was used to detect the spatial trends with the use of the Man-Kendall and Theil-Sen approach. Extreme precipitation indices were selected from the WMO–CCL/CLIVAR list of extreme precipitation indices focusing on intensity and frequency. The study shows a consistently increasing upward trend at 10.04 dfrom the WDAY index. In seasonal analysis, the pre-monsoon trend shows a significant upward trend in the PRCTOT index, while the WDAY index for pre-monsoon season has the highest correlation coefficient in downward trend. Spatial analysis of extreme precipitation indices shows that the PRCTOT index of the pre-monsoon season has the largest percentage change in significant upward trend over the northern Basins that are consistent with MAX and Mean but not for WDAY. In addition, the inter-annual relationship between the Oceanic Nino Index and PRCTOT is shown in relation with the La Niña phase for both April and May.


2021 ◽  
pp. 1-59
Author(s):  
Bin Tang ◽  
Wenting Hu ◽  
Anmin Duan

AbstractPrecipitation extremes over the Indochina and South China (INCSC) region simulated by 40 global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) were quantitatively assessed based on the skill score metrics of four extreme precipitation indices when compared with observational results from a high-resolution daily precipitation dataset for 1958–2014. The results show that it is difficult for most of the CMIP6 models to reproduce the observed spatial pattern of extreme precipitation indices in the INCSC region. The interannual variability of the extreme precipitation indices is relatively better simulated for South China than for Indochina. In general, most of the CMIP6 models perform better in South China compared with Indochina when taking both the simulations of spatial pattern and interannual variability into consideration. Only three models (EC-Earth3, EC-Earth3-Veg, and NorESM2-MM) can successfully reproduce both the spatial pattern and the interannual variability for the INCSC region. Through model ranking, the multi-model ensemble generated by a selection of the most skillful models leads to a more realistic simulation of the extreme precipitation indices both in South China and Indochina. Better simulation of the meridional wind component over South China and the water vapor convergence over Indochina can partly reduce the wet biases, resulting in a more realistic simulation of extreme precipitation indices over the INCSC region.


2021 ◽  
Author(s):  
Shakti Suryavanshi ◽  
Nitin Joshi ◽  
Hardeep Kumar Maurya ◽  
Divya Gupta ◽  
Keshav Kumar Sharma

Abstract This study examines the pattern and trend of seasonal and annual precipitation along with extreme precipitation events in a data scare, south Asian country, Afghanistan. Seven extreme precipitation indices were considered based upon intensity, duration and frequency of precipitation events. The study revealed that precipitation pattern of Afghanistan is unevenly distributed at seasonal and yearly scales. Southern and Southwestern provinces remain significantly dry whereas, the Northern and Northeastern provinces receive comparatively higher precipitation. Spring and winter seasons bring about 80% of yearly precipitation in Afghanistan. However, a notable declining precipitation trend was observed in these two seasons. An increasing trend in precipitation was observed for the summer and autumn seasons, however; these seasons are the lean periods for precipitation. A declining annual precipitation trend was also revealed in many provinces of Afghanistan. Analysis of extreme precipitation indices reveals a general drier condition in Afghanistan. Large spatial variability was found in precipitation indices. In many provinces of Afghanistan, a significantly declining trends were observed in intensity-based (Rx1-day, RX5-day, SDII and R95p) and frequency-based (R10) precipitation indices. The duration-based precipitation indices (CDD and CWD) also infer a general drier climatic condition in Afghanistan. This study will assist the agriculture and allied sectors to take well-planned adaptive measures in dealing with the changing patterns of precipitation, and additionally, facilitating future studies for Afghanistan.


Agromet ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 41-51
Author(s):  
. Misnawati ◽  
Mega Perdanawanti

Extreme climate events have significant impacts on various sectors such as agriculture, ecosystem, health and energy. The issue would lead to economic losses as well as social problems. This study aims to investigate the trend of extreme precipitation in Sumatera Island based on observed data during 30-year period, 1981–2010. There are ten indices of climate extreme as defined by ETCCDMI, which were tested in this study, including PRCPTOT, SDII, CDD, CWD, R10, R50, R95p, R99p, Rx1day and Rx5day. Then, the trend was analyzed based on the Mann-Kendall statistic, performed on the time series of precipitation data. The result shows that there was positive trend of extreme precipitation found in most stations over Sumatera, either statistically significant or insignificant. In each extreme precipitation indices, the number of observed stations indicating the insignificant change is higher than the significant one. This research also found that some indices including SDII, Rx1day, R50, R95p and R99p, showed a significantly-positive trend followed by a higher intensity of wetter and heavier events of extreme precipitation over Sumatera. On the other hand, the wet spell (CWD) index shows a negative trend (α=0.05).


Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1453 ◽  
Author(s):  
Junnan Xiong ◽  
Zhiwei Yong ◽  
Zegen Wang ◽  
Weiming Cheng ◽  
Yi Li ◽  
...  

The Tibetan Plateau is one of the most vulnerable areas to extreme precipitation. In recent decades, water cycles have accelerated, and the temporal and spatial characteristics of extreme precipitation have undergone dramatic changes across the Tibetan Plateau, especially in its various ecosystems. However, there are few studies that considered the variation of extreme precipitation in various ecosystems, and the impact of El Niño-Southern Oscillation (ENSO), and few researchers have made a quantitative analysis between them. In this study, we analyzed the spatial and temporal pattern of 10 extreme precipitation indices across the Tibetan Plateau (including its four main ecosystems: Forest, alpine meadow, alpine steppe, and desert steppe) based on daily precipitation from 76 meteorological stations over the past 30 years. We used the linear least squares method and Pearson correlation coefficient to examine variation magnitudes of 10 extreme precipitation indices and correlation. Temporal pattern indicated that consecutive wet days (CWD) had a slightly decreasing trend (slope = −0.006), consecutive dry days (CDD), simple daily intensity (SDII), and extreme wet day precipitation (R99) displayed significant increasing trends, while the trends of other indices were not significant. For spatial patterns, the increasing trends of nine extreme precipitation indices (excluding CDD) occurred in the southwestern, middle and northern regions of the Tibetan Plateau; decreasing trends were distributed in the southeastern region, while the spatial pattern of CDD showed the opposite distribution. As to the four different ecosystems, the number of moderate precipitation days (R10mm), number of heavy precipitation days (R20mm), wet day precipitation (PRCPTOT), and very wet day precipitation (R95) in forest ecosystems showed decreasing trends, but CDD exhibited a significant increasing trend (slope = 0.625, P < 0.05). In the other three ecosystems, all extreme precipitation indices generally exhibited increasing trends, except for CWD in alpine meadow (slope = −0.001) and desert steppe (slope = −0.005). Furthermore, the crossover wavelet transform indicated that the ENSO had a 4-year resonance cycle with R95, SDII, R20mm, and CWD. These results provided additional evidence that ENSO play an important remote driver for extreme precipitation variation in the Tibetan Plateau.


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