Shanhu Bao

The supercooled layer thickness (SLT), defined as the vertical distance between the 0°C isotherm and cloud top within clouds, presents distinct retrieval challenges over the Mongolian Plateau because of its unique environmental and topographic characteristics, which are significantly different from those of plains and other regions. Currently, SLT estimation accuracy in this region is constrained by insufficient retrieval precision of key parameters including the cloud top height (CTH), cloud top temperature (CTT), and cloud base height (CBH). To address this issue, we integrate data from the Advanced Himawari Imager (AHI), Advanced Geostationary Radiation Imager (AGRI), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), employing multiple advanced machine learning (ML) algorithms to retrieve CTH, CTT, and CBH. Using the optimal ML algorithm's retrieval results, we precisely estimate SLT. Validation reveals significant correlations between geostationary satellite SLT estimates and radiosonde data (Himawari-8/AHI: R² = 0.806; FY-4A/AGRI: R² = 0.817). Comparisons with CALIPSO products reveal moderate correlations for both Himawari-8/AHI (R² = 0.703) and FY-4A/AGRI (R² = 0.718). Furthermore, the CTH, CTT, and CBH retrievals from both satellites are highly consistent with the CALIOP products. Building upon these results, we systematically analyze the spatial variations in the SLT at different temporal scales across the Mongolian Plateau. The proposed SLT framework is formulated and validated primarily for single-layer cloud conditions.

The distribution and variation of top-of-atmosphere longwave cloud radiative forcing (LCRF_TOA) has drawn a significant amount of attention due to its importance in understanding the energy budget. Advancements in sensor and data processing technology, as well as a new generation of geostationary satellites, such as the FengYun-4A (FY-4A), allow for high spatiotemporal resolutions that are crucial for real-time radiation monitoring. Nevertheless, there is a distinct lack of official top-of-atmosphere outgoing longwave radiation products under clear-sky conditions (OLR_clear). Consequently, this study addresses the challenge of constructing LCRF_TOA data with high spatiotemporal resolution over the full disk region of FY-4A. After simulating the influence of atmospheric parameters on OLR_clear based on the SBDART radiation transfer model (RTM), we developed a model for estimating OLR_clear using infrared channels from the advanced geosynchronous radiation imager (AGRI) onboard the FY-4A satellite. The OLR_clear results showed an RMSE of 5.05 W/m² and MBE of 1.59 W/m² compared to ERA5. The corresponding RMSE and MBE value compared to CERES was 6.52 W/m² and 2.39 W/m². Additionally, the calculated LCRF_TOA results were validated against instantaneous, daily average, and monthly average ERA5 and CERES LCRF_TOA products, supporting the validity of the algorithm proposed in this paper. Finally, the changes in LCRF_TOA due to varied cloud heights (high, medium, and low cloud) were analyzed. This study provides the basis for comprehensive studies on the characteristics of top-of atmosphere radiation. The results suggest that high-height clouds exert a greater degree of radiative forcing more frequently, while low-height clouds are more frequently found in the lower forcing range.

The distribution and variation of top-of-atmosphere longwave cloud radiative forcing (LCRFTOA) has drawn a significant amout of attention due to its importance in understanding the energy budget. Advancements in sensor and data processing technology, as well as a new generation of geostationary satellites, such as the FengYun-4A (FY-4A), allow for high spatial resolutions that are crucial for real-time radiation monitoring. Nevertheless, there is a distinct lack of official top-of-atmosphere outgoing longwave radiation products under clear-sky conditions (OLRclear). Consequently, this study addresses the challenge of constructing LCRFTOA data with high spatiotemporal resolution over the full disk region of FY-4A. After simulating the influence of atmospheric parameters on OLRclear based on SBDART radiation transfer model (RTM), we developed a model for estimating OLRclear using infrared channels from the advanced geosynchronous radiation imager (AGRI) onboard the FY-4A satellite. The OLRclear results showed an RMSE of 5.05 W/m2 and MBE of 1.59 W/m2 compared to ERA5. Besides, the calculated LCRFTOA results were validated against instantaneous, daily average, and monthly average ERA5 and CERES LCRFTOA products, supporting the validity of the algorithm proposed in this paper. Finally, the changes in LCRFTOA due to variaty cloud heights (high, medium, and low cloud) were analyzed. This study provides the basis for comprehensive studies on the characteristics of top-of atmosphere radiation.

Global warming and human activities are complicating the spatial and temporal relationships between basin hydrologic processes and ecosystem quality (EQ), especially in arid and semi-arid regions. Knowledge of the synergy between hydrological processes and ecosystems in arid and semi-arid zones is an effective measure to achieve ecologically sustainable development. In this study, the inland river basin Ulagai River Basin (URB), a typical arid and semi-arid region in Northern China, was used as the study area; based on an improved hydrological model and remote-sensing and in situ measured data, this URB-focused study analyzed the spatial and temporal characteristics of hydrological process factors, such as precipitation, evapotranspiration (ET), surface runoff, lateral flow, groundwater recharge, and EQ and the synergistic relationships between them. It was found that, barring snowmelt, the hydrological process factors such as precipitation, ET, surface runoff, lateral flow, and groundwater recharge had a rising trend in the URB, since the 20th century. The rate of change was higher in the downstream areas when compared with what it was in the upstream and midstream areas. The multi-year average of EQ in the basin is 53.66, which is at a medium level and has an overall improving trend, accounting for 95.14% of the total area, mainly in the upstream, downstream southern, and downstream northern areas of the basin. The change in relationship between the hydrological process factors and EQ was found to have a highly synergistic effect. Temporally, EQ was consistent with the interannual trends of precipitation, surface runoff, lateral flow, and groundwater recharge. The correlation between the hydrological process factors and EQ was found to be higher than 0.7 during the study period. Spatially, the hydrological process factors had a synergistic relationship with EQ from strong to weak upstream, midstream, and downstream, respectively. In addition, ecosystem improvements were accelerated by government initiatives such as the policy of Returning Grazing Land to Grassland Project, which has played an important role in promoting soil and water conservation and EQ. This study provides theoretical support for understanding the relationship between hydrological processes and ecological evolution in arid and semi-arid regions, and it also provides new ideas for related research.

Drought in the Mongolian Plateau (MP) has gradually intensified in recent decades. The energy and water cycles are key factors affecting drought. However, there are few quantitative studies on the mechanism of aridity change in this region. This study uses the ERA5, Moderate Resolution Imaging Spectroradiometer (MODIS) and Himawari 8 datasets and investigated the mechanism of drought change over the MP. The aridity index (the ratio of potential evaporation and total precipitation) is employed to detect drought changes. The results showed that the annual mean of aridity index increased by 0.73% per year (increased significantly since 1999) during the period 1979–2020. Moreover, the drought was most severe in the January to April of 2016–2020, mainly concentrated in the central and western parts of the MP. The potential evaporation increased (0.72% per year) and total precipitation decreased (0.16% per year) from 1979 to 2020. However, the surface temperature continued increasing from August to December in the period 2016–2020 (1.67% per year). This may result in an increase in potential evaporation and a decrease in volumetric soil water from August to December last year. The decrease of volumetric soil water resulted in the decrease of total cloud cover (0.25% per year) and total precipitation from January to April. The surface net radiation (increased by 0.42% per year) and the potential evaporation increased, which may aggravate the drought from January to April. The evaporation paradox is studied over the MP. The results show that the variation in evaporation is consistent with that of total precipitation, and the surface temperature will promote an increase in evaporation and potential evaporation. This study reveals that global warming, desertification and increased surface net radiation contribute to the increase in potential evaporation and reduced volumetric soil water, which together contribute to drought.

The Mongolian Plateau (MP) is among the most sensitive areas to global climate change, and the clouds over the MP have a greater impact on regional and global radiation budgets by altering the atmospheric and surface radiative forcing. In this study, daily Cloud and Earth Radiation Energy System data are used to investigate spatiotemporal variation of cloud radiative forcing (CRF) at the top of atmosphere (TOA), surface and atmosphere over the MP from 2003 to 2017 and then combined with Moderate Resolution Imaging Spectroradiometer level 2 atmospheric data during the same period to analyse the cloud parameter impacts on CRF over the MP. At the TOA and surface, net radiative forcing (NRF) and shortwave radiative forcing (SRF) have cooling effects and longwave radiative forcing (LRF) have heating effects in all four seasons, and the NRF cooling effect in most areas of the MP decreases in summer and autumn and increases in spring and winter. In the atmosphere, SRF in spring and summer and NRF in summer reach larger values and heat the atmosphere, and LRF plays a strong cooling role in winter. The NRF change trend in the atmosphere over Mongolia is noteworthy in spring, its reduction slope is large, and most areas of Mongolia passed a significance test. As expected, a significant negative correlation was observed between cloud cover and NRF (as well as SRF) at the TOA and surface and a positive correlation was observed with NRF/SRF in the atmosphere and all LRF. With the increase in cloud optical thickness and cloud water path, the NRF and SRF cooling effects at the TOA and surface, the LRF cooling effect in the atmosphere, the LRF heating effect at the surface, and the SRF heating effect in the atmosphere all become stronger.

The Tibetan Plateau (TP) has important influences on regional and global climate change. Here, we perform an in‐depth study of the relationship between cloud parameters and meteorological factors over the TP. The spatiotemporal variations in cloud cover and cloud optical thickness over the TP during the daytime from 2003 to 2015 are analysed using the Aqua‐MODIS level 2 atmospheric product data MYD06. Results show that the annual average cloud cover over the TP decreases from the southeast to the northwest. The cloud cover of the western TP is highest in spring and lowest in autumn, while the cloud cover of the eastern TP is higher in spring and summer. The cloud covers in most areas of the TP exceed 30% in spring and summer, and the cloud optical thickness in the southeastern TP exceeds 10 in summer, with substantial cloud cover and cloud optical thickness changes. Compared to other seasons, the cooling effect of the near surface cloud net radiative forcing is greater during daytime in summer, which is likely associated with thick cloud optical thickness or large cloud cover. The results of the analysis of relationships among cloud cover, water vapour and air temperature show that positive correlations exist between cloud cover and water vapour, and that significantly negative correlations exist between cloud cover and air temperature over the TP. Combined with the analysis of variation features in the cloud parameters and meteorological factors, we find that water vapour variations during the daytime over the TP lead to cloud cover changes, which affect the air temperature variations over the TP by the cooling effects of clouds, especially in summer.

The Mongolian Plateau (MP) has important influences on regional and global climate change. The spatiotemporal variations in the cloud cover and cloud optical thickness of total, high, middle, and low clouds over the MP during the daytime from 2006 to 2015 are analyzed using MODIS level 2 atmospheric data. Results show that the annual average total cloud cover over the MP decreases from the forest area in the northeast to the desert area in the southwest. The total cloud cover over the MP is obviously higher in summer than in other seasons, in which high clouds have a largest proportion, with the substantial total cloud cover changes. The spatial distributions of the high, middle, and low cloud covers over the MP are highly variable. The cooling effect of the cloud net radiative forcing is greater during the daytime in summer than in other seasons, which is likely associated with thick cloud optical thickness or large cloud cover in summer. Combined with the analyses of relationships among cloud cover, cloud optical thickness, cloud radiative forcing, and air temperature, the results show that significantly negative correlations exist between cloud optical thickness and cloud radiative forcing, and between total cloud cover and air temperature in the MP. The decrease in air temperature in summer over the MP during daytime confirm that the increase in the daytime total cloud cover strengthen the cooling effects of clouds and decrease the air temperature, especially in the high-value area with cloud cover distribution over the northeast MP.