Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

The Climate Response to Global Forest Area Changes under Different Warming Scenarios in China

Human activities have notably affected the Earth’s climate through greenhouse gases(GHG), aerosol, and land use/land cover change(LULCC). To investigate the impact of forest changes on regional climate under different shared socioeconomic pathways(SSPs), changes in surface air temperature and precipitation over China under low and medium/high radiative forcing scenarios from 2021 to 2099 are analyzed using multimodel climate simulations from the Coupled Model Intercomparison Project Phase 6(CMIP6). Results show that the climate responses to forest changes are more significant under the low radiative forcing scenario. Deforestation would increase the mean, interannual variability, and the trend of surface air temperature under the low radiative forcing scenario, but it would decrease those indices under the medium/high radiative forcing scenario. The changes in temperature show significant spatial heterogeneity. For precipitation, under the low radiative forcing scenario, deforestation would lead to a significant increase in northern China and a significant decrease in southern China, and the effects are persistent in the near term(2021–40), middle term(2041–70), and long term(2071–99). In contrast, under the medium/high radiative forcing scenario, precipitation increases in the near term and long term over most parts of China, but it decreases in the middle term, especially in southern, northern,and northeast China. The magnitude of precipitation response to deforestation remains comparatively small.

Effects of irrigation on precipitation in the arid regions of Xinjiang,China

Soil moisture is an important parameter for the interaction between soil and atmosphere. It is the sec- ond important factor that influences climate change, next to sea surface temperature （SST）. Most previous studies focused on the monsoon regions in East China, and only a few laid emphases on arid environments. In Xinjiang, which is located in Northwest China, the climate is typically arid and semi-arid. During the past 20 years, the pre- cipitation in Xinjiang has shown a significant increasing trend, and it is closely related to oasis irrigation. This paper aims at discussing whether abnormal soil moisture in spring can be the signal to forecast summer precipitation. The effects of abnormal soil moisture due to farm irrigation in spring in arid environments on regional climate are inves- tigated by using a regional climate model （RegCM3）. The results indicate that positive soil moisture anomaly in irrigated cropland surface in May led to an increase in precipitation in spring as well as across the whole summer. The impact could last for about four months. The effects of soil moisture on the surface air temperature showed a time-lagging trend. The summer air temperature declined by a maximum amplitude of 0.8℃. The increased soil moisture could enhance evaporation and ascending motion in the low troposphere, which brought in more precipi- tation. The soil moisture affected regional weather and climate mainly by altering the surface sensible and latent heat fluxes.

Relationship between thermal anomalies in Tibetan Plateau and summer dust storm frequency over Tarim Basin,China

The dust storm is the most important and frequent meteorological disaster over Tarim Basin, which causes huge damages on local social economics. How to predict the springtime and summertime dust storm oc- currence has become a hot issue for meteorologists. This paper employed the data of dust storm frequency and 10-m wind velocity at 35 stations over Tarim Basin and the reanalysis data from the National Center for Environ- mental Prediction and the National Center for Atmospheric Research （NCEP/NCAR） during 1961-2007 to study the relationship between dust storm frequency （DSF） in summer over Tarim Basin and the thermal anomalies in Tibetan Plateau in May by using the statistical methods, such as Empirical Orthogonal Function （EOF）, correlation and binomial moving average. The results show when negative anomalies in Tibetan Plateau and positive anomalies in its southern region are present along 30~N （the second mode of surface temperature anomalies by EOF decomposition） in May, the time coefficient （PC2） plays an important role in summer DSF variation and has a close relation with the summer DSF at both inter-annual and decadal time scales. When negative anomalies in Tibetan Plateau and positive anomalies are present in its southern region （PC2 in positive phase）, there is an anomalous anticyclone in North China, which weakens the northwest wind and is not beneficial for cold air moving from high latitude to the Tarim Basin, and the circulation pattern is hard to result in dust storm weather. Furthermore, the sea level pressure （SLP） increased over Tarim Basin and the direction of SLP gradient reversed, which resulted in the 10-m wind velocity slowing down, so the DSF decreased. From above all, it can be conclude that the thermal anomalies in Tibetan Plateau in May has important effects on the summertime dust storm frequency over Tarim Basin and the PC2 can be used as a prediction factor for the summertime dust storm occurrence.

Development of Land Surface Model BCC＿AVIM2.0 and Its Preliminary Performance in LS3MIP/CMIP6

The improvements and validation of several parameterization schemes in the second version of the Beijing Climate Center Atmosphere–Vegetation Interaction Model(BCC_AVIM2.0) are introduced in this study. The main updates include a replacement of the water-only lake module by the common land model lake module(Co LM-lake) with a more realistic snow–ice–water–soil framework, a parameterization scheme for rice paddies added in the vegetation module, renewed parameterizations of snow cover fraction and snow surface albedo to accommodate the varied snow aging effect during different stages of a snow season, a revised parameterization to calculate the threshold temperature to initiate freeze(thaw) of soil water(ice) rather than being fixed at 0°C in BCC_AVIM1.0, a prognostic phenology scheme for vegetation growth instead of empirically prescribed dates for leaf onset/fall, and a renewed scheme to depict solar radiation transfer through the vegetation canopy. The above updates have been implemented in BCC_AVIM2.0 to serve as the land component of the BCC Climate System Model(BCC_CSM). Preliminary results of BCC_AVIM in the ongoing Land Surface, Snow, and Soil Moisture Model Intercomparison Project(LS3 MIP) of the Coupled Model Intercomparison Project Phase 6(CMIP6) show that the overall performance of BCC_AVIM2.0 is better than that of BCC_AVIM1.0 in the simulation of surface energy budgets at the seasonal timescale. Comparing the simulations of annual global land average before and after the updates in BCC_AVIM2.0 reveals that the bias of net surface radiation is reduced from-12.0 to-11.7 W m-2 and the root mean square error(RMSE) is reduced from 20.6 to 19.0 W m-2;the bias and RMSE of latent heat flux are reduced from 2.3 to-0.1 W m-2 and from 15.4 to14.3 W m-2, respectively;the bias of sensible heat flux is increased from 2.5 to 5.1 W m-2 but the RMSE is reduced from 18.4 to 17.0 W m-2.