scholarly journals Extreme Precipitation Indices over China in CMIP5 Models. Part II: Probabilistic Projection

2016 ◽  
Vol 29 (24) ◽  
pp. 8989-9004 ◽  
Author(s):  
Wei Li ◽  
Zhihong Jiang ◽  
Jianjun Xu ◽  
Laurent Li
Keyword(s):  
Extreme Precipitation ◽  
High Reliability ◽  
First Century ◽  
Western China ◽  
Cmip5 Models ◽  
Huai River ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Twenty First Century ◽  
Probabilistic Projection

Abstract The present article is the second part of a study on the extreme precipitation indices over China in CMIP5 models that perform a probabilistic projection of future precipitation indices with reference to the period 1986–2005. This is realized with a rank-based weighting method. The ranking of the 25 models is done according to their performance in simulating rainfall indices in present-day climate. Such weights are used to form a weighted ensemble for future climate projection. Results show that, compared to the unweighted raw ensemble, the projection with the weighted scheme is more credible, as the signal-to-noise ratio (SNR) of indices is larger from the weighted ensemble. From the beginning of the mid-twenty-first century, changes of wet indices with probability >0.5 increase significantly, especially over western China and the Yellow–Huai River basin, where the changes of all wet indices are in excess of 10%, the increase of total precipitation (PRCPTOT) can reach up to 20% over western China at the end of twenty-first century, and the SNR of PRCPTOT and precipitation intensity (SDII) is the highest at those two regions. This indicates that the precipitation in those regions has a high reliability to become more extreme. The maximum consecutive dry days (CDD) decreases throughout the north of 30°N, which shows that drought conditions in northern China would be reduced, and they are more likely to increase in southern China. However, the SNR for projection of CDD is less than 1.0 almost everywhere. Such a situation seems related to a strengthening of the East Asian summer monsoon and the associated northward shift of the monsoon front.

scholarly journals Extreme Precipitation Indices over China in CMIP5 Models. Part I: Model Evaluation

2015 ◽  
Vol 28 (21) ◽  
pp. 8603-8619 ◽  
Author(s):  
Zhihong Jiang ◽  
Wei Li ◽  
Jianjun Xu ◽  
Laurent Li
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Eastern China ◽  
Northern China ◽  
Western China ◽  
Cmip5 Models ◽  
The West ◽  
Southeastern China ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices

Abstract Compared to precipitation extremes calculated from a high-resolution daily observational dataset in China during 1960–2005, simulations in 31 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been quantitatively assessed using skill-score metrics. Four extreme precipitation indices, including the total precipitation (PRCPTOT), maximum consecutive dry days (CDD), precipitation intensity (SDII), and fraction of total rainfall from heavy events (R95T) are analyzed. Results show that CMIP5 models still have wet biases in western and northern China. Especially in western China, the models’ median relative error is about 120% for PRCPTOT; the 25th and 75th percentile errors are of 70% and 220%, respectively. However, there are dry biases in southeastern China, where the underestimation of PRCPTOT reach 200 mm. The performance of CMIP5 models is quite different between western and eastern China. The simulations are more reliable in the east than in the west in terms of spatial pattern and interannual variability. In the east, precipitation indices are more consistent with observations, and the spread among models is smaller. The multimodel ensemble constructed from a selection of the most skillful models shows improved behavior compared to the all-model ensemble. The wet bias in western and northern China and dry bias over southeastern China are all decreased. The median of errors for PRCPTOT has a decrease of 69% and 17% in the west and east, respectively. The good reproduction of the southwesterlies along the east coast of the Arabian Peninsula is revealed to be the main factor explaining the improvement of precipitation patterns and extreme events.

Temperature projections over Iran during the twenty-first century using CMIP5 models

2021 ◽  
Author(s):  
David Francisco Bustos Usta ◽  
Maryam Teymouri ◽  
Uday Chatterjee ◽  
Bappaditya Koley
Keyword(s):  
First Century ◽  
Cmip5 Models ◽  
Twenty First Century

Understanding Precipitation Characteristics of Afghanistan at Provincial Scale

2021 ◽  
Author(s):  
Shakti Suryavanshi ◽  
Nitin Joshi ◽  
Hardeep Kumar Maurya ◽  
Divya Gupta ◽  
Keshav Kumar Sharma
Keyword(s):  
Extreme Precipitation ◽  
Asian Country ◽  
Annual Precipitation ◽  
Precipitation Pattern ◽  
Precipitation Trend ◽  
Extreme Precipitation Events ◽  
Changing Patterns ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Precipitation Events

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.

scholarly journals Trend of Extreme Precipitation over Sumatera Island for 1981-2010

Agromet ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 41-51
Author(s):  
. Misnawati ◽  
Mega Perdanawanti
Keyword(s):  
Extreme Precipitation ◽  
Ecosystem Health ◽  
The Other ◽  
Economic Losses ◽  
Positive Trend ◽  
Climate Extreme ◽  
Precipitation Data ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Climate Events

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).

scholarly journals Spatial and Temporal Patterns of the Extreme Precipitation across the Tibetan Plateau (1986–2015)

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1453 ◽  
Author(s):  
Junnan Xiong ◽  
Zhiwei Yong ◽  
Zegen Wang ◽  
Weiming Cheng ◽  
Yi Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Extreme Precipitation ◽  
Temporal Pattern ◽  
Alpine Meadow ◽  
The Tibetan Plateau ◽  
Desert Steppe ◽  
Trend Slope ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Increasing Trends

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.

Recent trends of extreme precipitation indices in the Iberian Peninsula using observations and WRF model results

2016 ◽  
Vol 94 ◽  
pp. 10-21 ◽  
Author(s):  
S. Bartolomeu ◽  
M.J. Carvalho ◽  
M. Marta-Almeida ◽  
P. Melo-Gonçalves ◽  
A. Rocha
Keyword(s):  
Iberian Peninsula ◽  
Extreme Precipitation ◽  
Wrf Model ◽  
Extreme Precipitation Indices ◽  
Recent Trends ◽  
Precipitation Indices

scholarly journals Probabilistic Projections of Climate Change over China under the SRES A1B Scenario Using 28 AOGCMs

2011 ◽  
Vol 24 (17) ◽  
pp. 4741-4756 ◽  
Author(s):  
Weilin Chen ◽  
Zhihong Jiang ◽  
Laurent Li
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
General Circulation ◽  
Regional Scale ◽  
First Century ◽  
Climate System Model ◽  
Huai River ◽  
Twenty First Century ◽  
The Impact ◽  
A1b Scenario

Probabilistic projection of climate change consists of formulating the climate change information in a probabilistic manner at either global or regional scale. This can produce useful results for studies of the impact of climate change impact and change mitigation. In the present study, a simple yet effective approach is proposed with the purpose of producing probabilistic results of climate change over China for the middle and end of the twenty-first century under the Special Report on Emissions Scenarios A1B (SRES A1B) emission scenario. Data from 28 coupled atmosphere–ocean general circulation models (AOGCMs) are used. The methodology consists of ranking the 28 models, based on their ability to simulate climate over China in terms of two model evaluation metrics. Different weights were then given to the models according to their performances in present-day climate. Results of the evaluation for the current climate show that five models that have relatively higher resolutions—namely, the Istituto Nazionale di Geofisica e Vulcanologia ECHAM4 (INGV ECHAM4), the third climate configuration of the Met Office Unified Model (UKMO HadCM3), the CSIRO Mark version 3.5 (Mk3.5), the NCAR Community Climate System Model, version 3 (CCSM3), and the Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2 (hires)]—perform better than others over China. Their corresponding weights (normalized to 1) are 0.289, 0.096, 0.058, 0.048, and 0.044, respectively. Under the A1B scenario, surface air temperature is projected to increase significantly for both the middle and end of the twenty-first century, with larger magnitude over the north and in winter. There are also significant increases in rainfall in the twenty-first century under the A1B scenario, especially for the period 2070–99. As far as the interannual variability is concerned, the most striking feature is that there are high probabilities for the future intensification of interannual variability of precipitation over most of China in both winter and summer. For instance, over the Yangtze–Huai River basin (28°–35°N, 105°–120°E), there is a 60% probability of increased interannual standard deviation of precipitation by 20% in summer, which is much higher than that of the mean precipitation. In general there are small differences between weighted and unweighted projections, but the uncertainties in the projected changes are reduced to some extent after weighting.

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