The direct perturbation of anthropogenic aerosols on Earth's energy balance [i.e., direct aerosol radiative forcing (DARF)] remains uncertain in climate models. In this study, we investigate the uncertainty of DARF associated with aerosol vertical distribution, using simulation results from 14 global models within phase 6 of the Coupled Model Intercomparison Project (CMIP6). The column mass loading for each aerosol species is first normalized to the multimodel average for each model, which is called the mass-normalization process. The unified radiative transfer model and aerosol optical parameter are used, so that the differences in the calculated DARF are solely attributed to the difference in aerosol vertical profiles. The global mean DARF values in 2014 with respect to 1850 before and after mass normalization are -0.77 +/- 0.52 and -0.81 +/- 0.12 W m(-2) respectively, assuming external mixing, which indicates that the intermodel difference in aerosol vertical distribution accounts for similar to 20% of the total DARF uncertainty. We further conduct two separate experiments by normalizing aerosol optical depth (AOD) and aerosol single scattering albedo (SSA) profiles, respectively, and find that the vertical distribution of SSA results in larger DARF uncertainty (0.17 W m(-2)) than that of AOD (0.10 W m(-2)). Finally, compared with CALIPSO observation, CMIP6 models tend to produce higher aerosol layers. The bias in modeled aerosol profile with respect to CALIPSO leads to stronger DARF, especially for land regions.

Fire is an endemic process at high latitudes, connected to a range of other land surface properties, such as land cover, biomass, and permafrost, and intimately linked to the carbon balance of the high-latitude land surface. Much of our current understanding of these links and their climate consequences is through land surface models, so it is important to ensure that for their credibility, these models should be consistent with available data. Over the vast panboreal region, a key source of information on fire is satellite data. Comparisons between satellite-based burned area data from the Global Fire Emissions Database and three dynamic vegetation models (LPJ-WM, CLM4CN, and SDGVM) indicate that all models fail to represent the observed spatial and temporal properties of the fire regime. Although the three dynamic vegetation models give comparable values of the boreal net biome production (NBP), fire emissions are found to differ by a factor 4 between the models, because of widely different estimates of burned area and because of different parameterizations of the fuel load and combustion process. Including a more realistic representation of the fire regime in the models shows that for northern high latitudes, (i) severe fire years do not coincide with source years or vice versa, (ii) the interannual variability of fire emissions does not significantly affect the interannual variability of NBP, and (iii) overall biomass values alter only slightly, but the spatial distribution of biomass exhibits changes. We also demonstrate that it is crucial to alter the current representations of fire occurrence and severity in land surface models if the links between permafrost and fire are to be captured, in particular, the dynamics of permafrost properties, such as active layer depth. This is especially important if models are to be used to predict the effects of a changing climate, because of the consequences of permafrost changes for greenhouse gas emissions, hydrology, and land cover.

Large differences in future climatic scenarios found when different global circulation models (GCMs) are employed have been extensively discussed in the scientific literature. However, differences in hydrological responses to the climatic scenarios resulting from the use of different hydrological models have received much less attention. Therefore, comparing and quantifying such differences are of particular importance for the water resources management of a catchment, a region, a continent, or even the globe. This study investigates potential impacts of human-induced climate change on the water availability in the Dongjiang basin, South China, using six monthly water balance models, namely the Thornthwaite-Mather (TM), Vrije Universitet Brussel (VUB), Xinanjiang (XAJ), Guo (GM), WatBal (WM), and Schaake (SM) models. The study utilizes 29-year long records of monthly streamflow and climate in the Dongjiang basin. The capability of the six models in simulating the present climate water balance components is first evaluated and the results of the models in simulating the impact of the postulated climate change are then analyzed and compared. The results of analysis reveal that (1) all six conceptual models. have similar capabilities in reproducing historical water balance components; (2) greater differences in the model results occur when the models are used to simulate the hydrological impact of the postulated climate changes; and (3) a model without a threshold in soil moisture simulation results in greater changes in model-predicted soil moisture with respect to alternative climates than the models with a threshold soil moisture. The study provides insights into the plausible changes in basin hydrology due to climate change, that is, it shows that there can be significant implications for the investigation of response strategies for water supply and flood control due to climate change. (c) 2007 Elsevier B.V. All rights reserved.