Yanan Duan, Sanjiv Kumar, Montasir Maruf, Thomas M. Kavoo, Imtiaz Rangwala, Jadwiga H. Richter, Anne A. Glanville, Teagan King, Musa Esit, Brett Raczka, Kevin Raeder
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引用次数: 0
Abstract
We assess the relative contributions of land, atmosphere, and oceanic initializations to the forecast skill of root zone soil moisture (SM) utilizing the Community Earth System Model version 2 Sub to Seasonal climate forecast experiments (CESM2-S2S). Using eight sensitivity experiments, we disentangle the individual impacts of these three components and their interactions on the forecast skill for the contiguous United States. The CESM2-S2S experiment, in which land states are initialized while atmosphere and ocean remain in their climatological states, contributes 91 ± 3% of the total sub-seasonal forecast skill across varying soil moisture conditions during summer and winter. Most SM predictability stems from the soil moisture memory effect. Additionally, land-atmosphere coupling contributes 50% of the land-driven soil moisture predictability. A comparative analysis of the CESM2-S2S SM forecast skills against two other climate models highlights the potential for enhancing soil moisture forecast accuracy by improving the representation of soil moisture-precipitation feedback.
期刊介绍:
npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols.
The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.