ALBERT

Description: 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 in the Sahel climate system at seasonal to decadal scales. The WAMME II strategy is to apply prescribed observationally based anomaly forcing, i.e., idealized but realistic forcing, in simulations by climate models to test the relative impacts of such forcings in producingamplifying the Sahelian seasonal and decadal climate variability, including the great 20th century drought. This is the first multi-model experiment specifically designed to simultaneously evaluate relative contributions of multiple external forcings to the Sahel decadal precipitation anomalies between the 1980s and the 1950s that is used to characterize the Sahel 1980s drought in this study. The WAMME II models have consistently demonstrated that SST is the major contributor to the 20th century Sahel drought. Under the influence of the maximum possible SST forcing, WAMME II model ensemble mean can produce up to 60 of the precipitation difference between the 1980s and the 1950s. The present paper also delineated the role of SSTs in triggering and maintaining the Sahel drought. The impact of SSTs in individual oceans is also examined and consensus and discrepancies are reported. Among the different ocean basins, the WAMME II models show the consensus that the Indian Ocean SST has the largest impact on the precipitation temporal evolution associated with the ITCZ movement before the WAM onset while the Pacific Ocean SST greatly contributes to the summer WAM drought. This paper also compares the SST effect with the LULCC effect. Results show that with prescribed land forcing the WAMME II model ensemble mean produces about 40 of the precipitation difference between the 1980s and the 1950s, which is less than the SST contribution but still of first order in the Sahel climate system. The role of land surface processes 61 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. These preliminary WAMME results need to be further evaluated with different experimental designs and different models.

Description: Land-surface characteristics (LSCs) and land-soil moisture conditions can modulate energy partition at the land surface, impact near-surface atmosphere conditions, and further affect land–atmosphere interactions. This study investigates the effect of land-surface-characteristic parameters (LSCPs) including albedo, leaf-area index (LAI), and soil moisture (SM) on hot weather by in East China using the numerical model. Simulations using the Weather Research and Forecasting (WRF) Model were conducted for a hot weather event with a high spatial resolution of 1 km in domain 3 by using ERA-Interim forcing fields on 20 July 2017 until 16:00 UTC on 25 July 2017. The satellite-based albedo and LAI, and assimilation-based soil-moisture data of high temporal–spatial resolution, which are more accurate to match fine weather forecasts and high-resolution simulations, were used to update the default LSCPs. A control simulation with the default LSCPs (WRF_CTL), a main sensitivity simulation with the updated LSCP albedo, LAI and SM (WRF_CHAR), and a series of other sensitivity simulations with one or two updated LSCPs were performed. Results show that WRF_CTL could reproduce the spatial distribution of hot weather, but overestimated air temperature (Ta) and maximal air temperature (Tamax) with a warming bias of 1.05 and 1.32 °C, respectively. However, the WRF_CHAR simulation reduced the warming bias, and improved the simulated Ta and Tamax with reducing relative biases of 33.08% and 29.24%, respectively. Compared to the WRF_CTL, WRF_CHAR presented a negative sensible heat-flux difference, positive latent heat flux, and net radiation difference of the area average. LSCPs modulated the partition of available land-surface energy and then changed the air temperature. On the basis of statistical-correlation analysis, the soil moisture of the top 10 cm is the main factor to improve warming bias on hot weather in East China.