Search

Actual evaporation in the Yangtze River basin is calculated by the complementary relationship approach-that is, the advection-aridity (AA) model with parameter validation from 1961 to 2007-and simulated by the general circulation model (GCM) ECHAM5-Max Planck Institute Ocean Model (MPI-OM) from 1961 to 2000. Trends of annual and seasonal estimated actual evaporation and air temperature, net radiation, saturation vapor pressure deficit, wind speed, and precipitation are examined by the linear regression method and nonparametric Mann-Kendall test. The stepwise regression method is used to analyze the significance to reference evapotranspiration of independent variables. Results show that a significant decreasing trend in annual reference evaporation is caused by a significant decline in wind speed. The annual actual evaporation decreases in the upper and midlower Yangtze reaches; more significantly in the AA model [-9.3 mm (10 yr)−1] than in the GCM [−3.6 mm (10 yr)−1]. Significant negative trends are found in spring and autumn, but they show reverse trends in summer and winter within the two methods, which is caused by the different contributors to the seasonal actual evaporation in the two methods. Decreasing net radiation is the main contributor to annual and spring actual evaporation in the two methods. Decreasing precipitation and net radiation are the main contributors to decreasing autumn actual evaporation in the AA model and the GCM. Increasing net radiation and decreasing precipitation are the main contributors to summer and winter actual evaporation in the GCM. Decreasing net radiation and increasing precipitation are the main contributors to decreasing summer and increasing winter actual evaporation in the AA model. [ABSTRACT FROM AUTHOR]

Spatial and temporal characteristics of precipitation trends in the Zhujiang River basin, South China, are analyzed. Nonparametric trend tests are applied to daily precipitation data from 192 weather stations between 1961 and 2007 for the following indices: annual, monthly, and daily precipitation; annual and monthly number of rain days and precipitation intensity; annual and monthly maximum precipitation; 5-day maximum precipitation, number of rainstorms with >50 mm day−−1, and peaks over thresholds (90th, 95th, and 99th percentile). The results show that few stations experienced trends in the precipitation indices on an annual basis. On a monthly basis, significant positive and negative trends above the 90%% confidence level appear in all months except December. Trends in the indices of monthly precipitation, rain intensity, rain days, and monthly maximum precipitation show very similar characteristics. They experience the most distinct negative (positive) trends in October (January). A change of the mean wind direction by 50°° from east-southeast to east-northeast explains the downward trend in precipitation in October. Dry October months (months with low precipitation indices) can be observed when the mean wind direction is east-northeast (arid) instead of the prevailing mean wind direction, east-southeast (moist). The former is typical for the East Asian winter monsoon (EAWM). Nearly 90%% of the driest October months can be explained by wind directions typical for the EAWM. The upward trend in precipitation indices in January cannot be explained by changes in large-scale circulation. The analysis of the precipitation indices delivers more detailed information on observed changes than other studies in the same area. This can be attributed to the higher station density, the quality of daily data, and the focus on monthly trends in the current study. [ABSTRACT FROM AUTHOR]