Evaluating and Improving the Performance of Three 1-D Lake Models in a Large Deep Lake of the Central Tibetan Plateau

Fine-scale monitoring of lake ice phenology by synthesizing remote sensed and climatologic features based on high-resolution satellite constellation and modeling

Lake ice, as a crucial component of the cryosphere, serves as a sensitive indicator of climate change. Fine-scale monitoring of spatiotemporal patterns in lake ice phenology holds significant importance in scientific research and environmental management. However, the rapid and dynamic nature of the freeze-thaw process of lake ice poses challenges to existing methods, resulting in their limited application in small lakes. In this study, we propose a novel approach of investigating ice phenology of lakes in various sizes. We conducted a case study in Hoh Xil, known for its vulnerability to climate change and a wide distribution of small lakes, to analyze the ice phenology of 372 lakes (>1 km2) during 2017-2021. Firstly, ensemble machine-learning model was developed for lake ice identification from Landsat-8/9 and Sentinel-2 A/B imagery. The accuracy evaluation reveals the overall good performance for ice extraction results based on Landsat-8/9 (97.03 %) and Sentinel-2 A/B (96.89 %). Next, the XGBoost models were employed to reconstruct ice coverages on unobserved dates for the freezeup and breakup periods, respectively. Totally, 744 XGBoost models were constructed for the study lakes, and the majority of them perform well. Based on the reconstructed daily ice coverage, phenology parameters could be extracted for examining the spatiotemporal characteristics of ice cover and possible relationships with lake sizes and terrains. From early-October to early-November, the Hoh Xil lakes freeze from the northwest to the southeast, while the breakup period starts in late-March and lasts until late-June. Moreover, the results indicate relatively small variability in freezeup-end dates among lakes, but significant differences in breakup dates, showing a greater sensitivity to temperature variations. Furthermore, ice phenology in small lakes exhibit stronger consistency with subtle climatic fluctuations. The results highlight the significant role of ice phenology in small lakes, as they dominate the overall tendency of ice phenology in Hoh Xil.

Climate change drives rapid warming and increasing heatwaves of lakes

Climate change could seriously threaten global lake ecosystems by warming lake surface water and increasing the occurrence of lake heatwaves. Yet, there are great uncertainties in quantifying lake temperature changes globally due to a lack of accurate large-scale model simulations. Here, we integrated satellite observations and a numerical model to improve lake temperature modeling and explore the multifaceted characteristics of trends in surface temperatures and lake heatwave occurrence in Chinese lakes from 1980 to 2100. Our model-data integration approach revealed that the lake surface waters have warmed at a rate of 0.11 °C 10a-1 during the period 1980-2021, being only half of the pure model-based estimate. Moreover, our analysis suggested that an asymmetric seasonal warming rate has led to a reduced temperature seasonality in eastern plain lakes but an amplified one in alpine lakes. The durations of lake heatwaves have also increased at a rate of 7.7 d 10a-1. Under the high-greenhouse-gas-emission scenario, lake surface temperature and lake heatwave duration were projected to increase by 2.2 °C and 197 d at the end of the 21st century, respectively. Such drastic changes would worsen the environmental conditions of lakes subjected to high and increasing anthropogenic pressures, posing great threats to aquatic biodiversity and human health.

Mitigation Effect of Dense "Water Network" on Heavy PM2.5 Pollution: A Case Model of the Twain-Hu Basin, Central China

The influence of the underlying surface on the atmospheric environment over rivers and lakes is not fully understood. To improve our understanding, this study targeted the Twain-Hu Basin (THB) in central China, with a unique underlying surface comprising a dense "water network" over rivers and lakes. In this study, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) was used to simulate the impact of this dense "water network" on a wintertime heavy PM_2.5 pollution event in the THB. On this basis, the regulating effects of density and area of the lake groups, with centralized big lakes (CBLs) and discrete small lakes (DSLs), on PM_2.5 concentrations over the underlying surface of the dense "water network" in the THB were clarified, and the relative contributions of thermal factors and water vapor factors in the atmospheric boundary layer to the variation of PM_2.5 concentrations were evaluated. The results show that the underlying surface of dense "water networks" in the THB generally decreases the PM_2.5 concentrations, but the influences of different lake-group types are not uniform in spatial distribution. The CBLs can reduce the PM_2.5 concentrations over the lake and its surroundings by 4.90-17.68% during the day and night. The ability of DSLs in reducing PM_2.5 pollution is relatively weak, with the reversed contribution between -5.63% and 1.56%. Thermal factors and water vapor-related factors are the key meteorological drivers affecting the variation of PM_2.5 concentrations over the underlying surface of dense "water networks". The warming and humidification effects of such underlying surfaces contribute positively and negatively to the "purification" of air pollution, respectively. The relative contributions of thermal factors and water vapor-related factors are 52.48% and 43.91% for CBLs and 65.96% and 27.31% for DSLs, respectively. The "purification" effect of the underlying surface with a dense "water network" in the THB on regional air pollution highlights the importance of environmental protection of inland rivers and lakes in regional environmental governance. In further studies on the atmospheric environment, long-term studies are necessary, including fine measurements in terms of meteorology and the environment and more comprehensive simulations under different scenarios.

How does lake water clarity affect lake thermal processes?

The objective of this study was to determine the effects of water clarity changes on thermal processes in Lake Poyang, the largest freshwater lake in China, using a physically based lake model embedded in the Community Land Model. A water extinction coefficient (K d ) describing water clarity and controlling radiation penetration in the lake model was used to conduct controlled simulations. Three sets of simulations were conducted for Lake Poyang over the period from 2000 to 2015: DEFAULT with the K d = 0.45 m-1; CTL with the K d = 1.68 m-1 based on a water clarity of 0.85 m; and DARK with the K d = 1.68 m-1 from 2000 to 2005 and K d = 3.44 m-1 based on a water clarity of 0.41 m observed from 2005 to 2015. The simulation results showed that compared with the DEFAULT simulation, the temperature simulations were closer to the observations using the more accurate K d values for the CTL and DARK simulations. Due to decreased water clarity, radiation absorbed in the top 1 m of the water body was larger for the DARK simulation and lower at greater depths than that observed for the CTL simulation. Such changes in radiation penetration in the DARK simulation generated a higher lake water surface temperature (LWST) and thus stronger lake-air interactions from February to July and lower LWST and turbulent fluxes from August to the following January than in the CTL simulation. The temperature inside the lake water body declined markedly, with a significant reduction from June to August that exceeded 5 °C. The results of this study provide an additional reference regarding lake water clarity effects on inland freshwater systems and theoretical support for lake water system management.

Thermal Responses of the Largest Freshwater Lake in the Tibetan Plateau and Its Nearby Saline Lake to Climate Change

There are thousands of lakes in the Tibetan Plateau (TP), and most are saline. However, little is known about the responses of TP lakes to climate change, especially saline ones. We investigated the thermal responses of the largest freshwater lake (Ngoring Lake) in the TP and its nearby small saline lake (Hajiang Salt Pond) to climate change using the improved lake scheme in the Community Land model (CLM4-LISSS), in which we primarily developed the salinity parameterizations previously evaluated in the Great Salt Lake in USA and further considered the effect of salinity on the temperature of the maximum density of saline water in the present study. The improved lake model with salinity parameterizations was first applied to a saline lake in the TP, where saline lakes make up the majority of water bodies. The CLM4-LISSS model could effectively simulate lake surface water temperature (LSWT), lake water temperature (LT) and ice thickness in Ngoring Lake. Additionally, the model including our salinity parameterizations significantly improved simulations of LSWT and LT in Hajiang Salt Pond, especially in winter. The LSWT of the two completely opposite lakes were warming in the simulations at a rate above 0.6 °C/decade. Meteorological forces were the main driving factor, with increasing downward longwave radiation, air temperature and air humidity, as well as weakening winds contributing to LSWT increase. Compared to a hypothetical shallow freshwater lake, the greater depth of Ngoring Lake made its surface warm faster, and salinity slightly accelerated the warming of Hajiang Salt Pond. Monthly mean LSWT differences between the two lakes were induced by salinity effects in cold periods and lake depth in the unfrozen period. In response to a warming climate, the LSWT in the ice-free Hajiang Salt Pond rapidly increased from January to April due to the warming climate, whereas the LSWT of Ngoring Lake increased faster in the first and last month of the ice-cover period due to later ice-on and earlier ice-off. This study will provide a useful tool for saline lakes in the TP and help deepen our knowledge about the responses of TP lakes, especially the saline lakes, to climate change, as well as response differences between freshwater and saline lakes and the reasons for these differences.

Impact of Interaction between Metropolitan Area and Shallow Lake on Daily Extreme Precipitation over Eastern China

Both cities and lakes have significant impacts on regional precipitation. With global warming, extreme precipitation events in Eastern China have increased significantly, and the single/joint influences of metropolises and lakes on extreme precipitation still need to be quantitatively evaluated. To reveal the impact of the single/joint influences of metropolises and lakes on the shear line torrential rain process, the Suzhou-Wuxi-Changzhou Metropolitan Area (SXCMA) and Lake Taihu in Eastern China were selected as the study area. Utilizing a WRF model, comparative studies of sensitivity simulations were conducted for the two typical extreme precipitation events caused by the low-level shear line (LLSL) on 27 June 2015 (EP627) and 25 September 2017 (EP925). Both results show that the existence of Lake Taihu and SXCMA will increase precipitation in the study area. SXCMA has a more obvious effect on enhancing precipitation, which is about twice the effect of Lake Taihu. SXCMA mainly strengthens the intensity and movement of the surface convergence line (SCL) in the study area and indirectly affects the shift of the LLSL, which finally affects the intensity and location of precipitation. Lake Taihu affects the intensity and movement of SCL, triggering ground vertical convections due to lower surface roughness, and acts as a land-lake breeze and water vapor source, which will affect the distribution and intensity of precipitation.

The Impact of Climate Warming on Lake Surface Heat Exchange and Ice Phenology of Different Types of Lakes on the Tibetan Plateau

Increasing air temperature is a significant feature of climate warming, and is cause for some concern, particularly on the Tibetan Plateau (TP). A lack of observations means that the impact of rising air temperatures on TP lakes has received little attention. Lake surfaces play a unique role in determining local and regional climate. This study analyzed the effect of increasing air temperature on lake surface temperature (LST), latent heat flux (LE), sensible heat flux (H), and ice phenology at Lake Nam Co and Lake Ngoring, which have mean depths of approximately 40 m and 25 m, respectively, and are in the central and eastern TP, respectively. The variables were simulated using an adjusted Fresh-water Lake (FLake) model (FLake_α_ice = 0.15). The simulated results were evaluated against in situ observations of LST, LE and H, and against LST data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) for 2015 to 2016. The simulations show that when the air temperature increases, LST increases, and the rate of increase is greater in winter than in summer; annual LE increases; H and ice thickness decrease; ice freeze-up date is delayed; and the break-up date advances. The changes in the variables in response to the temperature increases are similar at the two lakes from August to December, but are significantly different from December to July.

Impacts of the Desiccated Lake System on Precipitation in the Basin of Mexico City

Mexico City constitutes one of the largest concentrations of population on the planet and is settled in a valley that, before the 16th century, had a lake system. The lakes were desiccated artificially, and currently, only small lakes remain. The impact of the lake system desiccation on precipitation was studied by performing numerical experiments: with the ancient lake system and without it. The experiments were carried out with the Weather Research and Forecasting (WRF) model coupled with a lake model for two months, using identical initial and boundary conditions, where only the system and lake physics were changed. The mean daily accumulated precipitation reduced when the system was removed. Additionally, the hourly distribution of rainfall changed from a relatively small diurnal variability when there was a lake system to a larger variability with a peak in the afternoon when the system was removed. Extreme precipitation events became more intense in the simulations with lakes. When the lakes were removed, the diurnal temperature range increased, and the boundary layer height became more variable, with a higher daily maximum. The results presented here show that the WRF-Lake model leads to opposite results compared to those with a non-coupled lake.

Evaluating and Improving the Performance of Three 1-D Lake Models in a Large Deep Lake of the Central Tibetan Plateau

The ability of FLake, WRF-Lake, and CoLM-Lake models in simulating the thermal features of Lake Nam Co in Central Tibetan Plateau has been evaluated in this study. All the three models with default settings exhibited distinct errors in the simulated vertical temperature profile. Then model calibration was conducted by adjusting three (four) key parameters within FLake and CoLM-Lake (WRF-Lake) in a series of sensitive experiments. Results showed that each model's performance is sensitive to the key parameters and becomes much better when adjusting all the key parameters relative to tuning single parameter. Overall, setting the temperature of maximum water density to 1.1 °C instead of 4 °C in the three models consistently leads to improved vertical thermal structure simulation during cold seasons; reducing the light extinction coefficient in FLake results in much deeper mixed layer and warmer thermocline during warm seasons in better agreement with the observation. The vertical thermal structure can be clearly improved by decreasing the light extinction coefficient and increasing the turbulent mixing in WRF-Lake and CoLM-Lake during warm seasons. Meanwhile, the modeled water temperature profile in warm seasons can be significantly improved by further replacing the constant surface roughness lengths by a parameterized scheme in WRF-Lake. Further intercomparison indicates that among the three calibrated models, FLake (WRF-Lake) performs the best to simulate the temporal evolution and intensity of temperature in the layers shallower (deeper) than 10 m, while WRF-Lake is the best at simulating the amplitude and pattern of the temperature variability at all depths.