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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]

The main portion of Tibetan Plateau has experienced statistically significant warming over the past 50 years, especially in cold seasons. This paper aims to identify and characterize the dynamics of inland lakes that located in the hinterland of Tibetan Plateau responding to climate change. We compared satellite imageries in late 1970s and early 1990s with recent to inventory and track changes in lakes after three decades of rising temperatures in the region. It showed warm and dry trend in climate with significant accelerated increasing annual mean temperature over the last 30 years, however, decreasing periodically annual precipitation and no obvious trend in potential evapotranspiration during the same period. Our analysis indicated widespread declines in inland lake's abundance and area in the whole origin of the Yellow River and southeastern origin of the Yangtze River. In contrast, the western and northern origin of the Yangtze River revealed completely reverse change. The regional lake surface area decreased by 11,499 ha or 1.72% from the late 1970s to the early 1990s, and increased by 6,866 ha or 1.04% from the early 1990s to 2004. Shrinking inland lakes may become a common feature in the discontinuous permafrost regions as a consequence of warming climate and thawing permafrost. Furthermore, obvious expanding were found in continuous permafrost regions due to climate warming and glacier retreating. The results may provide information for the scientific recognition of the responding events to the climate change recorded by the inland lakes. [ABSTRACT FROM AUTHOR]

This paper describes 2007/2008 inter-annual changes in runoff from the Zhadang Glacier located on the northern slope of Nyainqêntanglha Range, Tibet, and analyzes their causes. Precipitation increased by 17.9% in summer months of 2008 compared with the same period in 2007, drainage basin runoff decreased by 33.3%, and glacial meltwater decreased by 53.8%. Change in positive accumulated air temperature explained approximately half of the inter-annual difference in glacial meltwater using a degree-day model. This suggests that the glacier is extremely sensitive to changes in air temperature. Energy balance analysis showed that change in glacier surface albedo, considered to be caused by difference in precipitation form, resulted in the large inter-annual difference in glacial meltwater. It was shown statistically that precipitation form in the summer months of 2007 was mainly rainfall which comprised 71.5% of total precipitation, while during the same period in 2008 rainfall accounted for 30.7%, with the majority of precipitation falling as snow. Precipitation form should be considered an independent factor when analyzing glacier sensitivity to climate change or forecasting the runoff from certain glaciers. [ABSTRACT FROM AUTHOR]