Soils containing gravel (particle size ≥2 mm) are widely distributed over the Qinghai-Tibet Plateau (QTP). Soil mixed with gravel has different thermal and hydrological properties compared with fine soil (particle size <2 mm) and thus has marked impacts on soil water and heat transfer. However, the most commonly used land models do not consider the effects of gravel. This paper reports the development of a new scheme that simulates the thermal and hydrological processes in soil containing gravel and its application in the QTP. The new scheme was implemented in version 4 of the Community Land Model, and experiments were conducted for two typical sites in the QTP. The results showed that (1) soil with gravel tends to reduce the water holding capacity and enhance the hydraulic conductivity and drainage; (2) the thermal conductivity increases with soil gravel content, and the response of the temperature of soil mixed with gravel to air temperature change is rapid; (3) the new scheme performs well in simulating the soil temperature and moisture-the mean biases of soil moisture between the simulation and observation reduced by 25-48 %, and the mean biases of soil temperature reduced by 9-25 %. Therefore, this scheme can successfully simulate the thermal and hydrological processes in soil with different levels of gravel content and is potentially applicable in land surface models.
in the Sahel climate system at seasonal to decadal scales. The project's strategy is to apply prescribed observationally based anomaly forcing, i.e., "idealized but realistic" forcing, in simulations by climate models. The goal is to assess these forcings' effects in producing/amplifying seasonal and decadal climate variability in the Sahel between the 1950s and the 1980s, which is selected to characterize the great drought period of the last century. This is the first multi-model experiment specifically designed to simultaneously evaluate such relative contributions. The WAMME II models have consistently demonstrated that SST forcing is a major contributor to the twentieth century Sahel drought. Under the influence of the maximum possible SST forcing, the ensemble mean of WAMME II models can produce up to 60 % of the precipitation difference during the period. The present paper also addresses the role of SSTs Abstract The second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedbacks of sea surface temperature (SST), land use land cover change (LULCC), and aerosols forcings This paper is a contribution to the special issue on West African climate decadal variability and its modeling, consisting of papers from the West African Monsoon Modeling and Evaluation (WAMME) and the African Multidisciplinary Monsoon Analyses (AMMA) projects, and coordinated by Yongkang Xue, Serge Janicot, and William Lau. Provided Funding information has to be tagged. Electronic supplementary materialThe online version of this article (doi:10.1007/s00382-016-3224-2) contains supplementary material, which is available to authorized users. 3in triggering and maintaining the Sahel drought. In this regard, the consensus of WAMME II models is that both Indian and Pacific Ocean SSTs greatly contributed to the drought, with the former producing an anomalous displacement of the Intertropical Convergence Zone before the WAM onset, and the latter mainly contributes to the summer WAM drought. The WAMME II models also show that the impact of LULCC forcing on the Sahel climate system is weaker than that of SST forcing, but still of first order magnitude. According to the results, under LULCC forcing the ensemble mean of WAMME II models can produces about 40 % of the precipitation difference between the 1980s and the 1950s. The role of land surface processes in responding to and amplifying the drought is also identified. The results suggest that catastrophic consequences are likely to occur in the regional Sahel climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought.Keywords Sahel seasonal and decadal climate variability · Sahel drought, SST and land forcings · GCM
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