Based on the statistics of glacier area variation measured in the Chinese Tianshan Mountains since 1960, the response of glacier area variation to climate change is discussed systematically. As a result, the total area of the glaciers has been reduced by 11.5% in the past 50 years, which is a weighted percentage according to the glacier area variations of 10 drainage basins separated by the Glacier Inventory of China (GIC). The annual percentage of area changes (APAC) of glaciers in the Chinese Tianshan Mountains is 0.31% after the standardization of the study period. The APAC varies widely for different drainage basins, but the glaciers are in a state of rapid retreat, generally. According to the 14 meteorological stations in the Chinese Tianshan Mountains, both the temperature and precipitation display a marked increasing tendency from 1960 to 2009 at a rate of 0.34℃·(10a) −1 and 11 mm·(10a) −1 , respectively. The temperature in the dry seasons (from November to March) increases rapidly at a rate of 0.46℃·(10a) −1 , but the precipitation grows slowly at 2.3 mm·(10a) −1 . While the temperature in the wet seasons (from April to October) grows at a rate of 0.25 ·(10a) ℃ −1 , but the precipitation increases at 8.7 mm·(10a) −1 . The annual and seasonal climatic trends accelerate the retreat of glaciers.

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The heights of the atmospheric freezing level have increased over most glacierized areas of High Asia during 1971-2010, especially in the Altai Mountains, the eastern Tianshan Mountains, and the northeastern margins of the Tibetan Plateau. The systematic increase of freezing level heights (FLHs) is evidenced from both radiosonde and National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis data. Eleven glaciers with long-term observations are selected in typical high-elevation mountain ranges to examine the relationship between changes in FLHs and cryospheric response. Long-term trends in glacier mass balance and equilibrium line altitude (ELA) show significant correlations with changes in FLHs. A rise of 10 m in summer FLH causes mass balance of reference glaciers in High Asia to decrease by between 7 and 38 mm (water equivalent) and ELA to increase by between 3.1 and 9.8 m, respectively, depending on location. Both relationships are statistically significant (p < 0.01) for most reference glaciers. Thus, rapid deglaciation in these high mountain ranges during recent decades is related to the increase in FLH. Similar relationships may exist in other high-elevation glaciers of High Asia with changes in FLHs having significant ecological and social consequences, especially in arid and semiarid regions.

Many studies have examined the impacts of neighborhood characteristics on residential satisfaction. However, because their performance is not connected with their importance in residential choice, community planners have yet to know which characteristics need to be prioritized for neighborhood improvements. Using the 2014 data from Xi'an, China, to examine environmental correlates of residential satisfaction, this study pioneers the application of importance-performance analysis and three-factor theory for a joint evaluation of importance and performance. It classifies neighborhood characteristics into basic factors, performance factors, and excitement factors for urban, suburban, and exurban neighborhoods. By considering their performance, it further identifies development priorities for neighborhood self-improvement and the priorities for competition among different neighborhoods. These priorities allow local governments to deploy scarce resources to improve residential satisfaction of existing residents and attract more residents.

A new nonlinear artificial intelligence ensemble prediction (NAIEP) model has been developed for predicting typhoon intensity based on multiple neural networks with the same expected output and using an evolutionary genetic algorithm (GA). The model is validated with short-range forecasts of typhoon intensity in the South China Sea (SCS); results show that the NAIEP model is clearly better than the climatology and persistence (CLIPER) model for 24-h forecasts of typhoon intensity. Using identical predictors and sample cases, predictions of the genetic neural network (GNN) ensemble prediction (GNNEP) model are compared with the single-GNN prediction model, and it has been proven theoretically that the former is more accurate. Computation and analysis of the generalization capacity of GNNEP also demonstrate that the prediction of the ensemble model integrates predictions of its optimized ensemble members, so the generalization capacity of the ensemble prediction model is also enhanced. This model better addresses the "overfitting" problem that generally exists in the traditional neural network approach to practical weather prediction.