Abstract
As global warming continues to intensify, the problems of climate anomalies and deterioration of the water environment in East Asia are becoming increasingly prominent. In order to assist decision-making to tackle these problems, it is necessary to conduct in-depth research on the water environment and water resources through applying various hydrological and environmental models. To this end, the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) has been applied to East Asian regions where environmental issues are obvious, but the stations for monitoring meteorological variables are not uniformly distributed. The dataset contains all of the meteorological variables for SWAT, such as temperature, air pressure, humidity, wind, precipitation, and radiation. In addition, it includes a range of variables relevant to the Earth’s surface processes, such as soil temperature, soil moisture, and snowfall. Although the dataset is used mainly to drive the SWAT model, a large number of users worldwide for different models have employed CMADS and it is expected that users will not continue to limit the application of CMADS data to the SWAT model only. We believe that CMADS can assist all the users involved in the meteorological field in all aspects. In this paper, we introduce the research and development background, user group distribution, application area, application direction, and future development of CMADS. All of the articles published in this special issue will be mentioned in the contributions section of this article.
Highlights
The China Meteorological Assimilation Driving Datasets for the Soil and Water AssessmentTool (SWAT) (CMADS) is a product employed before the start of the intensive coupling process of model-driven research of atmospheric science and hydrology [1]
We evaluated the areas in East Asia to which researchers have applied the CMADS data most often; this analysis is a rough estimation because some users did not reveal the application purpose when applying for the data (Figure 2)
The results showed that the SUFI2 method was more efficient than ParaSol and GLUE, all three methods can yield good performance for Soil and Water Assessment Tool (SWAT) through using the CMADS
Summary
The China Meteorological Assimilation Driving Datasets for the Soil and Water AssessmentTool (SWAT) (CMADS) is a product employed before the start of the intensive coupling process of model-driven research of atmospheric science and hydrology [1]. These verification results demonstrate that the performance of CMADS products in East Asia can be trusted, especially in mountainous and highland areas with high altitudes and large differences of land use and geography, where meteorological stations are sparse.
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