The Tibetan Plateau (TP), which is also known as "The Third Pole," is the highest land area in the world and has widespread seasonal snow cover. In the past 50 years, the TP has undergone dramatic changes characterized by imbalances in the warming climate, such as accelerated glacier retreats, permafrost degradation, lake expansions, and snow cover change (S.
<p>Atmospheric aerosols can scatter and absorb the incident solar radiation, and thus impact the land carbon cycle by perturbating the radiation required for photosynthesis. Atmospheric aerosols inhibit the carbon uptake by terrestrial ecosystems through reducing the total amount of incident radiation, while the increased proportion of diffuse irradiance is known to promote photosynthesis. In the past few decades, with the rapid industrialization and urbanization, China has suffered from frequent haze pollution episodes, which have brought up severe environmental problems and ecological impacts. Here, we use a regional climate model, WRF-Chem, along with the offline driven Simplified Simple Biosphere Model (SSiB4) to investigate the impact of aerosol radiation effects on land biosphere carbon uptake capacity. The results show that the current aerosol loading has led to significant decrease in the incident solar radiation in China, which severely suppresses the gross primary production (GPP) and net primary production (NPP). Then, we assessed the influences of stringent emission and pollution control policies on terrestrial ecosystem carbon fluxes. By comparing the simulation results based on China&#8217;s ambitious carbon neutrality policies with the reference scenario with negligible emission control, we found that the carbon neutrality scenario with rigorous pollution control increases the incident solar radiation and thereby enhancing the carbon uptake of land biosphere. Under the current state of aerosol loading, the decrease of total amount of incident radiation dominates the suppression of terrestrial carbon uptake, while aerosol diffuse fertilization effect can only partly offset the inhibition of decreased solar radiation on plant photosynthesis. Our findings improve the understanding of the interactions between aerosol pollution and the land carbon cycle, and suggest an appreciable ecological benefit and a potential terrestrial carbon sink enhancement of stringent emission and pollution control actions.</p>
<p>The Tibetan Plateau snow cover is characterized by rapid changes on a weekly time-scale, which can cause rapid changes in surface albedo. Using snow and surface albedo data from satellite observations, we find that changes in snow coverage on the Tibetan Plateau dominate the rapid changes in surface albedo. However, snow depth also has a distinct effect on rapid changes in surface albedo in some areas especially with unstable snow cover. We test the snow depth-dependent snow albedo parameterization scheme in the land surface model. The results show that whether or not the variation of snow albedo with snow depth is considered directly affects the rapidly changing characteristics of the simulated snow cover on the Tibetan Plateau, which further affects the simulation of surface albedo. These results highlight the rapid response of surface albedo to both snow coverage and depth over the Tibetan Plateau.</p>
<p>The Tibetan Plateau (TP) is the highest plateau in the world and has complex topography. On the TP, seasonal snow cover is widespread in different topographic areas, but the influence of topography on snow cover simulations is often ignored in most land surface models. In this study, the relationships among the snow cover fraction (SCF) and complex topography are investigated over the TP based on satellite observations. The standard deviation of topography is used as an index to describe the topographic complexity. We conduct 12 numerical experiments using the Simplified Simple Biosphere Model version 3 (SSiB3) to investigate the influence of topography on the snow cover simulations. Our results show that ignoring topography leads to significant SCF simulation biases. By adding a topographic factor to the original scheme, the SCF simulations are greatly improved. Compared with the simulation results of the default SCF scheme, the annual mean SCF bias at location at CMA stations is reduced from 3.833% to -0.097% by adding a topographic factor. The improved SCF simulations further lead to reduced biases in winter surface albedo and land surface temperature simulations. Compared with in situ observations, the winter surface albedo bias over the TP is reduced from 0.02 to 0.007 compared with GLASS albedo data, and the winter land surface temperature bias is reduced from -3.43 K to -3.04 K. This study highlights the importance of the topographic effect in simulating snow and energy exchanges between the land and atmosphere over the TP, and it can contribute to reducing the &#8220;cold bias&#8221; in winter climate simulations over the TP.</p>
Extreme precipitation events have posed a threat to global terrestrial ecosystems in recent decades. However, the response of terrestrial ecosystems to extreme precipitation in areas with various vegetation types and complex topography remains unclear. Here, we used satellite-based solar-induced chlorophyll fluorescence (SIF) measurements, a direct proxy of photosynthetic activity, to assess the response of vegetation to the record-breaking extreme precipitation event during the East Asia monsoon season in eastern China in 2020. Our results demonstrate that vegetation was adaptable to moderate increases in precipitation, but photosynthetic activity was significantly inhibited by exposure to extreme precipitation because of insufficient PAR and waterlogging. The responses of vegetation photosynthesis to extreme precipitation were regulated by both vegetation type and topography. Crops in the lowland areas in eastern China were severely damaged due to their higher vulnerability and exposure to extreme precipitation. The topography-induced redistribution of precipitation accounts for the modulation of vegetation response to extreme precipitation. Our research highlights the urgent need for effective management and adaptive measures of croplands under the elevated risk of extreme precipitation in the future.
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