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Changes in patterns of meteorological parameters, like precipitations, temperature, wind, etc., are causing significant increases in various extreme events. And these extreme events, i.e., floods, heatwaves, hurricanes, droughts, etc., lead to a shortage of water resources, crop failures, wildfires, and economic losses. However, Global Circulation Models (GCMs) are considered the most important tools for quantifying climate change. Therefore, we selected 20 different GCMs of precipitation in our research, as the frequency of extreme events, like drought and flood, is highly related to changes in precipitation patterns. However, this research introduced a new weighting scheme — MCFSAWS-Ensemble: Monte Carlo Feature Selection Adaptive Weighting Scheme to Ensemble multiple GCMs, whereas, Monte Carlo Feature Selection (MCFS) is one of the most popular algorithms for discovering important variables. However, the proposed weighting scheme (MCFSAWS-Ensemble) is mainly based on two sources. Initially, it evaluates the prior performance of each GCM model to define their relative importance using MCFS. Then, it computes value by value difference between the observed and simulated model. In addition, the application of this paper is based on the monthly time series data of precipitation in the Tibet Plateau region of China. In addition, we used twenty GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to analyze the implications of the MCFSAWS-Ensemble. Further, we compared the performance of the MCFSAWS-Ensemble scheme with Simple Model Averaging (SMA) through Mean Average Error (MAE) and correlation statistics. The results of this research indicate that the proposed weighting scheme (MCFSAWS-Ensemble) is more accurate than the SMA approach. Consequently, we recommend the use of advanced machine learning algorithms such as MCFS for making accurate multi-model ensembles. [ABSTRACT FROM AUTHOR]

Historical records truthfully document human life and environment associated with climate changes. We quantify official historical records of China dating back last 2000 years to examine the disasters due to anomalous temperatures of cold or hot, irregular precipitations of wet or dry, and floods in inland/coastal or Northern/Southern areas in four seasons that possibly linked to solar activities during 1-1825 CE (Common Era). It is found that the proportion of disaster years is positively associated with the time periods, and therefore, both the cases with high and low solar activity (HSA and LSA) leading are under study. Statistical results show that extreme cold weather occurs particularly in the Winter and Spring during LSA periods. Irregularities precipitations, including heavy rain/hail/snow and severe drought are significantly frequent during LSA periods, while floods on inland and coastal river basins tend to occur more frequently in LSA and HSA periods, respectively. The disasters owing to irregularities precipitations and floods frequently happen in Summer and Autumn, which suggests that the irregular precipitations could cause the floods. All the disasters occur significantly in the Northern China, which suggests the climate boundary of the Qinling–Huaihe Line along at about 33°N being essential. In total, all the disasters due to the anomalously cold temperatures, irregular precipitations, and floods tend to occur during the LSA periods. [ABSTRACT FROM AUTHOR]

Projection of future climate changes and their regional impact is critical for long-term planning at the national and regional levels aimed at adaptation and mitigation. This study assesses the future changes in precipitation in China and the associated atmospheric circulation patterns using the Couple Model Intercomparison Project 5 Phase (CMIP5) simulations under the RCP4.5 and RCP8.5 scenarios. The results consistently indicate that the annual precipitation in China is projected to significantly increase at the end of the 21st century compared to the present-day levels. The number of days and the intensity of medium rain, large rain and heavy rain are obviously increased, while the number of trace rain days is projected to decrease over the entire area of China. Further analysis indicates that the significant increase of annual precipitation in Northwest China is primarily due to the increase of light rain and the increases in North and Northeast China are primarily due to the increase of medium rain. In the region of southern China, the increases of large rain and heavy rain play an important role in the increase of annual precipitation, while light rain events play a negative role. Analysis of the changes in atmospheric circulation indicates that the East Asian summer monsoon circulation is projected to be considerably stronger, and the local atmospheric stratification is projected to be more unstable, all of which provide a background benefit for the increase of precipitation and extreme rainfall events in China under global warming scenarios. [ABSTRACT FROM AUTHOR]

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature (SAT) has increased at a rate ranging from 0.03°C (10 yr) to 0.12°C (10 yr). This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period (1000-1300 AD). Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas (GHG) concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events. [ABSTRACT FROM AUTHOR]