We quantified the combined effects of mineral dust nonsphericity and size on snow albedo reduction using the MOPSMAP (Modeled optical properties of ensembles of aerosol particles) package and SAMDS (Spectral Albedo Model for Dirty Snow) with the consideration of dust from Sahara, Greenland, San Juan Mountains, and Tibetan Plateau. Results indicate that the dust-induced albedo reduction decreases by up to 30% as the effective radii of dust particles increase in 1-5 mu m. Nonspherical dust enhances snow albedo reduction relative to spherical dust by up to 20%. Stronger enhancements are obtained for higher dust concentration and larger dust size. Furthermore, the dust nonsphericity-induced enhancement of snow albedo reduction is more pronounced for more-absorptive dust. Finally, we develop a new parameterization for quantifying the dependence of snow albedo reduction on dust nonsphericity and size, and provide a convenient way for assessing the climate impacts of dust in snow.

Dynamical downscaling generally performs poorly on the Tibetan Plateau (TP), due to the region's complex topography and several aspects of model physics, especially convection and land surface processes. This study investigated the effects of the cumulus parameterization scheme (CPS) and land-surface hydrology scheme (LSHS) on TP climate simulation during the wet season using the RegCM4 regional climate model. To address these issues and seek an optimal simulation, we conducted four experiments at a 20 km resolution using various combinations of two CPSs (Grell and MIT-Emanuel), two LSHSs (the default TOPMODEL [TOP], and Variable Infiltration Capacity [VIC]). The simulations in terms of 2-m air temperature, precipitation (including large-scale precipitation [LSP] and convective precipitation [CP]), surface energy-water balance, as well as atmospheric moisture flux transport and vertical motion were compared with surface and satellite-based observations as well as the ERA5 reanalysis dataset for the period 2006-2016. The results revealed that the model using the Grell and TOP schemes better reproduced air temperature but with a warm bias, part of which could be significantly decreased by the MIT scheme. All schemes simulated a reasonable spatial distribution of precipitation, with the best performance in the experiment using the MIT and VIC schemes. Excessive precipitation was produced by the Grell scheme, mainly due to overestimated LSP, while the MIT scheme largely reduced the overestimation, and the simulated contribution of CP to total precipitation was in close agreement with the ERA5 data. The RegCM4 model satisfactorily captured diurnal cycles of precipitation amount and frequency, although there remained some differences in phase and magnitude, which were mainly caused by the CPSs. Relative to the Grell scheme, the MIT scheme yielded a weaker surface heating by reducing net radiation fluxes and the Bowen ratio. Consequently, anomalous moisture flux transport was substantially reduced over the southeastern TP, leading to a decrease in precipitation. The VIC scheme could also help decrease the wet bias by reducing surface heating. Further analysis indicated that the high CP in the MIT simulations could be attributed to destabilization in the low and mid-troposphere, while the VIC scheme tended to inhibit shallow convection, thereby decreasing CP. This study's results also suggest that CPS interacts with LSHS to affect the simulated climate over the TP.

Borehole-measured soil temperatures have been routinely used to calibrate soil parameters in permafrost modeling, although they are sparse in the Qinghai-Tibet Plateau (QTP). A feasible alternative is to calibrate models using land surface temperatures. However, the quantitative impacts of various soil parameterizations on permafrost modeling remain unexplored. To quantify these impacts, two sets of soil parameters (denoted as Psoil and Psurf) were obtained via calibration using borehole temperature measurement and ERA5-Land (the land component of the fifth generation of European Re-Analysis) skin temperature, respectively, and applied to the Geophysical Institute Permafrost Laboratory Version 2 (GIPL 2.0) model. Comparing against the borehole -measured soil temperatures of 4 soil layers, the ERA5-Psurf simulation (with Root Mean Squared Error, i.e., RMSE from 1.4 degrees C to 3.9 degrees C) outperform ERA5-Psoil simulation (RMSE from 1.4 degrees C to 3.9 degrees C) during 2006-2014. The obtained Psoil and Psurf were then utilized as soil parameters in GIPL 2.0 to model permafrost dynamics for a long period from 1983 to 2019, respectively, using ERA5-Land as forcing data. Simulations revealed significant disparities. In comparison to the simulation using Psurf results using Psoil show that the mean annual soil tem-perature at 1 m depth was 2.72 degrees C lower with a 0.01 degrees C/a (50.0%) lower trend; the active layer thickness was 0.81 m (35.7%) less with a 2.16 cm/a (82.1%) lower trend; the duration of the thawing season at 1 m depth was underestimated by about one month, and the zero-curtain period was about 23 days (37.7%) shorter. The change rates of the zero-curtain period, however, were comparable. This study implies that choosing soil parameteri-zations is critical for model evaluation against observations and long-term model prediction.

Daily floods including event, characteristic, extreme and inundation in the Lancang-Mekong River Basin (LMRB), crucial for flood projection and forecasting, have not been adequately modeled. An improved hydrological-hydrodynamic model (VIC and CaMa-Flood) considering regional parameterization was developed to simulate the flood dynamics over the basin from 1967 to 2015. The flood elements were extracted from daily time series and evaluated at both local and regional scales using the data collected from in-situ observations and remote sensing. The results show that the daily discharge and water level are both well simulated at selected stations with relative error (RE) less than 10% and Nash-Sutcliffe efficiency coefficient (NSE) over 0.90. Half of the flood events have NSE exceeding 0.76. The peak time and flood volume are well reproduced while both peak discharge and water level are slightly underestimated. The results tend to worsen when the characteristics of flood events are extended to annual extremes. These extremes are generally underestimated with NSE less than 0.5 but RE is within 20%. The simulated rainy season inundation area generally agrees with observations from remote sensing, with about 86.8% inundation occurrence frequency captured within the model capacity. Ignoring the regional parameterization and reservoir regulation can both deteriorate flood simulation performance at the local scale, resulting in lower NSE. Specifically, systematically higher water levels and up to 27% overestimation of peak discharge are found when ignoring regional parameterization, while ignoring reservoir regulation would cause up to 23% overestimation for flood extremes. It is expected that these findings would contribute to the regional flood forecasting and flood management.

We extend a stochastic aerosol-snow albedo model to explicitly simulate dust internally/externally mixed with snow grains of different shapes and for the first time quantify the combined effects of dust-snow internal mixing and snow nonsphericity on snow optical properties and albedo. Dust-snow internal/external mixing significantly enhances snow single-scattering coalbedo and absorption at wavelengths of <1.0 mu m, with stronger enhancements for internal mixing (relative to external mixing) and higher dust concentrations but very weak dependence on snow size and shape variabilities. Compared with pure snow, dust-snow internal mixing reduces snow albedo substantially at wavelengths of <1.0 mu m, with stronger reductions for higher dust concentrations, larger snow sizes, and spherical (relative to nonspherical) snow shapes. Compared to internal mixing, dust-snow external mixing generally shows similar spectral patterns of albedo reductions and effects of snow size and shape. However, relative to external mixing, dust-snow internal mixing enhances the magnitude of albedo reductions by 10%-30% (10%-230%) at the visible (near-infrared) band. This relative enhancement is stronger as snow grains become larger or nonspherical, with comparable influences from snow size and shape. Moreover, for dust-snow external and internal mixing, nonspherical snow grains have up to similar to 45% weaker albedo reductions than spherical grains, depending on snow size, dust concentration, and wavelength. The interactive effect of dust-snow mixing state and snow shape highlights the importance of accounting for these two factors concurrently in snow modeling. For application to land/climate models, we develop parameterizations for dust effects on snow optical properties and albedo with high accuracy.

Freeze-thaw processes in soils, including changes in frost and thaw fronts (FTFs), are very sensitive to warming. However, the latest climate models do not predict changes in FTFs directly. In this study, a new frozen soil parameterization including changes in FTFs was incorporated into the Community Land Model version 4.5 for climate modeling, which we denote CLM4.5_FTF. A set of numerical experiments including single points, regions in China, and a global scale were conducted using the model to validate its performance. The simulated FTF depths compare well with observed data from both the D66 station (permafrost) and Hulugou station (seasonally frozen ground). The simulated active layer thickness, defined as the maximum thaw front depth in permafrost, is in general agreement but slightly greater than observations from the Circumpolar Active Layer Monitoring program. The simulated distributions of different types of frozen soil in China and permafrost in the northern hemisphere are in agreement with the frozen soil map of China and the International Permafrost Association map, respectively. The results confirm that the model performs well for FTF simulations. The model was also used for year-long simulations of soil temperature and freeze-thaw processes to check its applicability in continuous simulation. The results show that CLM4.5_FTF performed better than the original model, and the improvement was better for lower levels than for the upper level. Finally, we give simulated latent heat flux, sensible heat flux, and 10-cm soil temperature deviations determined via the couple model with and without the new scheme.

We quantify the effects of grain shape and multiple black carbon (BC)-snow internal mixing on snow albedo by explicitly resolving shape and mixing structures. Nonspherical snow grains tend to have higher albedos than spheres with the same effective sizes, while the albedo difference due to shape effects increases with grain size, with up to 0.013 and 0.055 for effective radii of 1,000m at visible and near-infrared bands, respectively. BC-snow internal mixing reduces snow albedo at wavelengths < similar to 1.5m, with negligible effects at longer wavelengths. Nonspherical snow grains show less BC-induced albedo reductions than spheres with the same effective sizes by up to 0.06 at ultraviolet and visible bands. Compared with external mixing, internal mixing enhances snow albedo reduction by a factor of 1.2-2.0 at visible wavelengths depending on BC concentration and snow shape. The opposite effects on albedo reductions due to snow grain nonsphericity and BC-snow internal mixing point toward a careful investigation of these two factors simultaneously in climate modeling. We further develop parameterizations for snow albedo and its reduction by accounting for grain shape and BC-snow internal/external mixing. Combining the parameterizations with BC-in-snow measurements in China, North America, and the Arctic, we estimate that nonspherical snow grains reduce BC-induced albedo radiative effects by up to 50% compared with spherical grains. Moreover, BC-snow internal mixing enhances the albedo effects by up to 30% (130%) for spherical (nonspherical) grains relative to external mixing. The overall uncertainty induced by snow shape and BC-snow mixing state is about 21-32%. Plain Language Summary Pure snow strongly reflects sunlight, the degree of which is regulated by grain size and shape. Observations have shown that snow can be significantly darkened by impurities, such as black carbon (BC), which is the most important light-absorbing aerosol. However, the combined effects of the two critical factors, snow grain shape and BC-snow mixing structure, have not been previously investigated, the neglect of which could introduce large uncertainties in the estimates of snow albedo in terms of BC-induced darkening. We have developed a snow model to quantify the impact of the preceding two factors on snow albedo by means of resolving the structures of BC-snow mixtures for different grain shapes. Both snow grain shape and multiple BC-snow internal mixing play important roles in their impacts on snow albedo. For application to climate models, we construct a scheme to parameterize snow albedo and its darkening in terms of snow grain size, shape, and BC content.

The reduction of snow spectral albedo by black carbon (BC) and mineral dust, both alone and in combination, is computed using radiative transfer modeling. Broadband albedo is shown for mass fractions covering the full range from pure snow to pure BC and pure dust, and for snow grain radii from 5 mu m to 2500 mu m, to cover the range of possible grain sizes on planetary surfaces. Parameterizations are developed for opaque homogeneous snowpacks for three broad bands used in general circulation models and several narrower bands. They are functions of snow grain radius and the mass fraction of BC and/or dust and are valid up to BC content of 10ppm, needed for highly polluted snow. A change of solar zenith angle can be mimicked by changing grain radius. A given mass fraction of BC causes greater albedo reduction in coarse-grained snow; BC and grain radius can be combined into a single variable to compute the reduction of albedo relative to pure snow. The albedo reduction by BC is less if the snow contains dust, a common situation on mountain glaciers and in agricultural and grazing lands. Measured absorption spectra of mineral dust are critically reviewed as a basis for specifying dust properties for modeling. The effect of dust on snow albedo at visible wavelengths can be represented by an equivalent BC amount, scaled down by a factor of about 200. Dust has little effect on the near-IR albedo because the near-IR albedo of pure dust is similar to that of pure snow.