基于彭曼公式日均值时序分析的中国蒸发能力动态成因

Attribution Analysis on Changes in Evaporation Capacity Based on Mean Diurnal Time-series Analysis of Penman Equation in China

摘要:

蒸发能力是全球气候变化背景下水资源管理和水灾害防治的靶向性指标，其动态成因分析集中于年尺度，可靠性需多尺度验证。本文基于中国819个气象站1961—2015年的逐日数据，利用时间序列分析方法挖掘年潜在蒸发量趋势和突变；提出彭曼公式全微分日求积方法，计算年均日潜在蒸发量变化的气象要素累积贡献率，甄别区域驱动因子和成因。经分析，各站年潜在蒸发量倾向率均值为-3.3mm/（10a），东西部为负值、中部为正值；各站年潜在蒸发量突变年份均值为1987年；东部潜在蒸发量减少由地表净辐射量减少所致，相应区域累积贡献率为280；西部潜在蒸发量减少由相对湿度增加所致，相应区域累积贡献率为175；中部潜在蒸发量增加由温度和风速增加所致，相应区域累积贡献率分别为355和121。

Abstract:

Evaporation capacity is the targeting index of water resources management and water disaster control under the global climate change. Attribution analysis of evaporation capacity concentrates on the annual scale in most researches. The verification of the corresponding attribution needs multiscale analysis. Daily meteorological data were selected at 819 stations in China from 1961 to 2015, in addition to potential evaporation (ETp). The trend and change points of annual ETp were excavated according to the time series analysis method at stations. Another special method was proposed based on diurnalscale total differential quadrature of Penman equation. This method was directly applied for the contributions of meteorological variables on the first order difference of daily ETp. It was further used for the accumulative contributions of meteorological elements on the changes in mean daily ETp. According to the contributions, the driving forces and corresponding reasons of the changes in evaporation capacity were analyzed. It was concluded that the mean value of the tendency rates was -33mm/（10a） at all stations. It spatially presented negative in Western and Eastern China and positive in Central China. Mean value of change points was 1987 at all stations. The driving force of decreasing ETp was decreasing net radiation in Eastern China. Corresponding accumulative contribution rate was 280. The driving force of decreasing ETp was increasing relative humidity in Western China. Corresponding accumulative contribution rate was 175. The driving forces of increasing ETp were increasing temperature and wind speed in Central China. Corresponding accumulative contribution rates were 355 and 121, respectively.