Towards a realistic simulation of boreal summer tropical rainfall climatology in state-of-the-art coupled models: role of the background snow-free land albedo
Abstract
State-of-the-art global coupled models used in seasonal prediction systems and climate projections still have important deficiencies in representing the boreal summer tropical rainfall climatology. These errors include prominently a severe dry bias over all the Northern Hemisphere monsoon regions, excessive rainfall over the ocean and an unrealistic double inter-tropical convergence zone (ITCZ) structure in the tropical Pacific. While these systematic errors can be partly reduced by increasing the horizontal atmospheric resolution of the models, they also illustrate our incomplete understanding of the key mechanisms controlling the position of the ITCZ during boreal summer. Using a large collection of coupled models and dedicated coupled experiments, we show that these tropical rainfall errors are partly associated with insufficient surface thermal forcing and incorrect representation of the surface albedo over the Northern Hemisphere continents. Improving the parameterization of the land albedo in two global coupled models leads to a large reduction of these systematic errors and further demonstrates that the Northern Hemisphere subtropical deserts play a seminal role in these improvements through a heat low mechanism.
Keywords
Tropical rainfall climatology Monsoons Global coupled models Surface albedo Heat low DesertsNotes
Acknowledgements
The authors gratefully acknowledge the financial support given by the Earth System Science Organization, Ministry of Earth Sciences, Government of India, to conduct this research under the National Monsoon Mission (Grant #MM/SERP/CNRS/2013/INT-10/002, Contribution #MM/PASCAL/RP/08). We sincerely thank Prof. Ravi Nanjundiah, Director, Indian Institute of Tropical Meteorology (IITM, India) and Dr. R Krishnan, executive Director, Centre for Climate Change Research (at IITM, India) for all the support during this research study. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in the Supplementary Materials) for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Inter-comparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. Computer resources from Indian Institute of Tropical Meteorology (India) and GENCI-IDRIS (France, Grants 2015, 2016, 2017–016895) are also acknowledged.
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