The Relative Contribution of Large-Scale Circulation and Land Surface to Summer Precipitation Over Asian Mid-Low Latitudes

Understanding the contributions of large-scale atmospheric circulation and local land surface processes to precipitation is essentially important for the climate prediction. This study adopts a dynamic adjustment (DA) approach based on constructed circulation analogs to quantitatively isolate the contribution of atmospheric circulation to summer land precipitation (Pr) over Asian mid-low latitudes during 1980-2019. The atmospheric circulation factor is represented by the 500 hPa geopotential height (Z500) from the fifth generation ECMWF reanalysis (ERA5), and the land surface factors, including soil moisture (SM) and net radiation and heat fluxes are from the products of the Global Land Data Assimilation System (GLDAS). The residual component after DA is regarded as the contribution from land surface processes via evaporation mainly resulting from SM. The results indicate that the key SM-Pr feedback areas are mainly located in northeast China and the northern Indian Peninsula. The key influencing area of Z500 on the land Pr anomaly shows a “-+-” tripole pattern in the mid-latitude region. Atmospheric circulation determines the magnitude of summer land Pr, while the residual components reflect the land-atmosphere coupling effect and dominate Pr trend. This conclusion is helpful for better understanding the evolution mechanism of summer climate over Asia mid-low latitudes and may also have application value for climate prediction.

High-Resolution WRF Simulation of Extreme Heat Events in Eastern China: Large Sensitivity to Land Surface Schemes

Regional climate models with high-resolution simulation are particularly useful for providing a detailed representation of land surface processes, and for studying the relationship between land surface processes and heat events. However, large differences and uncertainties exist among different land surface schemes (LSSs). This study comprehensively assesses the sensitivity to different LSSs based on two extreme heat events in eastern China using the Weather Research and Forecasting (WRF) model. Among the five LSSs (i.e., 5TD, CLM4, Noah, Noah-MP and RUC), Noah is closest to observations in reproducing the temperatures and energy fluxes for both two heat events. The modeled warm biases result mainly from the underestimation of evapotranspirative cooling. Our results show that how each LSS partitions the evapotranspiration (ET) and sensible heat largely determines the relationship between the temperature and turbulent fluxes. Although the simulated two extreme heat events manifest similar biases in the temperatures and energy fluxes, the land surface responses (ET and soil moisture) are different.

The Influence of Natural and Anthropogenic Forcing on Water and Energy Balance and on Photosynthesis

Land surface processes are rarely studied in Detection and Attribution Model Inter-comparison Project (DAMIP) experiments on climate change. We analyzed a CMIP6 DAMIP historical experiment by using multi-linear regression (MLRM) and analysis of variance methods. We focused on energy and water budgets, including gross primary productivity (GPP). In MLRM, we estimated each forcing’s contribution and identified the role of natural forcing, which is usually ignored. Contributions of the forcing factors varied by region, and high-ranked variables such as net radiation could receive multiple influences. Greenhouse gases (GHG) accelerated energy and water cycles over the global land surface, including evapotranspiration, runoff, GPP, and water-use efficiency. Aerosol (AER) forcing displayed the opposite characteristics, and natural forcing accounted for short-term changes. A long-term analysis of total soil moisture and water budget indicated that as the AER increases, the available water on the global land increases continuously. In the recent past, an increase in net radiation (i.e., a lowered AER) reduced surface moisture and hastened surface water cycle (GHG effect). The results imply that aerosol emission and its counterbalance to GHG are essential to most land surface processes. The exception to this is GPP, which was overdominated by GHG effects.

On the similarity of hillslope hydrologic function: a process-based approach

Hillslope similarity is an active topic in hydrology because of its importance to improve our understanding of hydrologic processes and enable comparisons and paired studies. In this study, we propose a holistic bottom-up hillslope similarity classification based on a region’s integrative hydrodynamic response quantified by the seasonal changes in groundwater levels. The main advantage of the proposed classification is its ability to describe recharge and discharge processes. We test the performance of the proposed classification by comparing it to seven other common hillslope similarity classifications. These include simple classifications based on the aridity index, topographic wetness index, elevation, land cover, and more sophisticated machine-learning classifications that jointly integrate all these data. We assess the ability of these classifications to identify and categorize hillslopes with similar static characteristics, hydroclimatic behaviors, land surface processes, and subsurface dynamics in a mountainous watershed, the East River, located in the headwaters of the Upper Colorado River Basin. The proposed classification is robust as it reasonably identifies and categorizes hillslopes with similar elevation, land cover, hydroclimate, land surface processes, and subsurface hydrodynamics (and hence hillslopes with similar hydrologic function). In general, the other approaches are good in identifying similarity in a single characteristic, which is usually close to the selected variable. We further demonstrate the robustness of the proposed classification by testing its ability to predict hillslope responses to wet and dry hydrologic conditions, of which it performs well when based on average conditions.

Cryogenic land surface processes shape vegetation biomass patterns in northern European tundra

Tundra ecosystems have experienced changes in vegetation composition, distribution, and productivity over the past century due to climate warming. However, the increase in above-ground biomass may be constrained by cryogenic land surface processes that cause topsoil disturbance and variable microsite conditions. These effects have remained unaccounted for in tundra biomass models, although they can impact multiple opposing feedbacks between the biosphere and atmosphere, ecosystem functioning and biodiversity. Here, by using field-quantified data from northern Europe, remote sensing, and machine learning, we show that cryogenic land surface processes substantially constrain above-ground biomass in tundra. The three surveyed processes (cryoturbation, solifluction, and nivation) collectively reduced biomass by an average of 123.0 g m−2 (−30.0%). This effect was significant over landscape positions and was especially pronounced in snowbed environments, where the mean reduction in biomass was 57.3%. Our results imply that cryogenic land surface processes are pivotal in shaping future patterns of tundra biomass, as long as cryogenic ground activity is retained by climate warming.

Experimental Study on Thermal Conductivity of Organic-Rich Soils under Thawed and Frozen States

Thermal properties are important for featuring the water-heat transfer capacity of soil. They are also key to many processes in earth sciences, such as the land surface processes and ecological and geoenvironmental dynamics and their changes in permafrost regions. With loose and porous structures, the organic matter layer in soil strata substantially influences soil thermal conductivity. So far, thermal conductivity of mineral soils has been explored extensively and in depth, but there are only limited studies on that of organic soils. In this study, influences of soil temperature, soil moisture saturation (SMS), and soil organic matter (SOM) content on soil thermal conductivity were analyzed on the basis of laboratory experiments on the silt-organic soil mixtures of varied mixing ratios. Results show that soil thermal conductivity declines slowly with the lowering temperatures from 10 to 0°C; however, it increases and finally stabilizes when temperature further lowers from 0 to -10°C. It is important to note that thermal conductivity peaks in the temperature range of -2~0°C (silty and organic-poor soil) and -5~0°C (organic-rich soil), possibly due to phase changes of ice/water in warm permafrost. Under both thawed and frozen states, soil thermal conductivity is positively related with SMS. However, with rising SOM content, the growth rate of soil thermal conductivity with SMS slows gradually. Given the same SMS, soil thermal conductivity declines exponentially with increasing SOM content. Based on the experimental and theoretical analyses, a new empirical computational formula of soil thermal conductivity is established by taking into account of the SOM content, SMS, and soil temperature. The results may help better parameterize in simulating and predicting land surface processes and for optimizing frozen soil engineering designs and provide theoretical bases for exploring the dynamic mechanisms of environmental changes in cold regions under a changing climate.