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Seasonal variations in precipitation (P) and potential evapotranspiration (ET0) are critical for regional hydrometeorological studies and water resource management. The sinusoidal function is widely used to describe the seasonal pattern of P and ET0. However, high errors occur either in the arid places or in places with hyperseasonal precipitation. These limitations are intrinsic properties of the sinusoidal climate descriptor and remain a barrier to provide insight into regional water–energy partitions and hydrologic similarity and predictability. In this study, we used a Gaussian framework as an alternative to describe seasonal variations in P and ET0 regimes in the Yellow River basin (YRB). The results show that the Gaussian framework provides a good approximation to the seasonal pattern of P and has a strong regional applicability for reproducing the monthly P and ET0. This allows us to assess the climate seasonality characterizing the regional balance between water supply and energy availability using δP, δET0, and aridity index. The climate seasonality indicates that the balance between water supply and energy availability has a switch in about 32% of the grid cells during the seasonal cycle from 1982 to 2015. These grid cells are mostly located in regions with average annual precipitation above 550 mm. In the northwest region of the YRB, which has a dry climate, the amount of potential evapotranspiration always exceeds the precipitation. We argue that the Gaussian function provides a quantitative conceptual framework for accurate assessment of regional water supply and energy availability and offers a penetrating insight into hydrometeorology.

journal of hydrometeorology

Using a Gaussian Function to Describe the Seasonal Courses of Monthly Precipitation and Potential Evapotranspiration across the Yellow River Basin, China