Buda Su

Effects of the land-surface heterogeneities in temperature and moisture from the ''combined approach'' on regional climate: a sensitivity study

In order to better understand the land–atmosphere interactions and increase the predictability of climate models, it is very important to investigate the effects of land-surface heterogeneities, in which the temperature and moisture heterogeneities are very significant. In this paper, the land-surface scheme BATS [Dickinson, R.E., Henderson-Sellers, A., Kennedy, P.J., Wilson, M.F., 1993. Biosphere /Atmosphere Transfer Scheme (BATS) Version 1e as Coupled to the NCAR Community Climate Model. NCAR Tech. Note TN-387+STR, National Center for Atmospheric Research, Boulder, CO], in the NCAR regional climate model RegCM2, was treated with a ‘‘combined approach’’ that is computationally effective to represent land-surface heterogeneities in temperature and moisture, and was tested by using real data of China during the summer monsoon in 1991 as initial and boundary conditions. Different from the results of the off-line simulations for warm season in Giorgi [Mon. Weather Rev. 125 (1997b) 1900], as for temperature, we used a cosine probability density function (PDF), which is more effective in computation and different from the linear PDF applied by Giorgi [Mon. Weather Rev. 125 (1997a) 1885]; we can see that the summer monsoon climate is generally sensitive to the temperature heterogeneity (e.g., precipitation is sensitive to the temperature heterogeneity). Similar to the results in Giorgi [Mon. Weather Rev. 125 (1997b) 1900], the regional climate seems to be very sensitive to the moisture heterogeneity, which shows a regularity as changing with the heterogeneity, i.e., with the heterogeneity increasing, the mean sensible heat flux is generally increased, while the mean latent heat flux is generally decreased. So, the capability of simulation for summer monsoon climate may be improved via the appropriate representation of the heterogeneities in temperature and moisture. In addition, other results reveal the limitations of off-line experiments, and therefore the coupling of the land-surface scheme (with the inclusion of heterogeneity representation) to the atmospheric model is necessary for the study on land–atmosphere interactions. D 2002 Elsevier Science B.V. All rights reserved.

Impacts of climate change on streamflow in the upper Yangtze River basin

The impacts of climate change on streamflow in the upper Yangtze River basin were studied using four hydrological models driven by bias-corrected climate projections from five General Circulation Models under four Representative Concentration Pathways. The basin hydrological responses to climate forcing in future mid-century (2036–2065) and end-century (2070–2099) periods were assessed via comparison of simulation results in these periods to those in the reference period (1981–2010). An analysis of variance (ANOVA) approach was used to quantify the uncertainty sources associated with the climate inputs and hydrological model structures. Overall, the annual average discharge, seasonal high flow, and daily peak discharge were projected to increase in most cases in the twenty-first century but with considerable variability between models under the conditions of increasing temperature and a small to moderate increase in precipitation. Uncertainties in the projections increase over the time and are associated with hydrological model structures, but climate inputs represent the largest source of uncertainty in the upper Yangtze projections. This study assessed streamflow projections without considering water management practices within the basin.

Drought losses in China might double between the 1.5 °C and 2.0 °C warming

Significance We project drought losses in China under global warming of 1.5 °C and 2.0 °C. To assess future drought losses, we project the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration patterns. With increasing drought intensity and areal coverage across China, drought losses will increase considerably. The estimated losses in a sustainable development pathway at 1.5 °C warming will be 10 times higher than in the reference period 1986–2005 and three times higher than in 2006–2015. Yet, climate change mitigation, limiting the temperature increase to 1.5 °C, can considerably reduce the annual drought losses in China, compared with 2.0 °C warming. We project drought losses in China under global temperature increase of 1.5 °C and 2.0 °C, based on the Standardized Precipitation Evapotranspiration Index (SPEI) and the Palmer Drought Severity Index (PDSI), a cluster analysis method, and “intensity-loss rate” function. In contrast to earlier studies, to project the drought losses, we predict the regional gross domestic product under shared socioeconomic pathways instead of using a static socioeconomic scenario. We identify increasing precipitation and evapotranspiration pattern for the 1.5 °C and 2.0 °C global warming above the preindustrial at 2020–2039 and 2040–2059, respectively. With increasing drought intensity and areal coverage across China, drought losses will soar. The estimated loss in a sustainable development pathway at the 1.5 °C warming level increases 10-fold in comparison with the reference period 1986–2005 and nearly threefold relative to the interval 2006–2015. However, limiting the temperature increase to 1.5 °C can reduce the annual drought losses in China by several tens of billions of US dollars, compared with the 2.0 °C warming.