**1. Introduction**

The Tibetan Plateau (abbreviated as TP, see Abbreviation List at the end of the text) is known as "the Third Pole", with an average altitude of 4000 m above sea level. The TP, with a total area of about 50,000 km2, contains 1424 lakes (≥1 km<sup>2</sup> each) [1], most of which

**Citation:** Wen, L.; Wang, C.; Li, Z.; Zhao, L.; Lyu, S.; Leppäranta, M.; Kirillin, G.; Chen, S. Thermal Responses of the Largest Freshwater Lake in the Tibetan Plateau and Its Nearby Saline Lake to Climate Change. *Remote Sens.* **2022**, *14*, 1774. https://doi.org/10.3390/ rs14081774

Academic Editor: Monica Rivas Casado

Received: 25 January 2022 Accepted: 4 April 2022 Published: 7 April 2022

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are saline, accounting for more than half of the total lake coverage in China. The specific TP climatic environment (low air density, pressure, and temperature, all-year intensive solar radiation) creates unique lake–atmosphere interactions [2–8]. TP lakes significantly influence the local and regional climate by heat and mass exchanges between lakes and the atmosphere, and resonate with the adjacent and remote regions [9,10].

Lakes are sentinels of large-scale climate variability which interact strongly with the atmosphere and respond fast and widely to climate change, especially in the TP. The TP is influenced by elevation-dependent intensive warming, at up to three times the global warming rate [8,11]. The lake surface water temperature (LSWT) has rapidly increased globally, with a mean increasing trend of 0.34 ◦C/decade in summer averaged over 235 lakes worldwide between 1985 and 2009 [12]. However, TP lakes have shown an overall warming trend of 0.37 ◦C/decade, based on data from 374 inland lakes [13]. This rate was slightly higher than the global mean, because the TP climate and the warming of TP lakes are highly heterogeneous [14]. The majority of the TP lakes are warming at a higher rate of 0.76 ◦C/decade primarily due to the increasing air temperature, downward longwave radiation, and decreasing wind speeds, while some lakes are cooling due to glacier meltwater inflow or reduced salinity [3,13–17]. Changes in thermal conditions profoundly influence a lake's biological and chemical processes [18–20]. These processes may undergo substantial alterations, even with relatively small changes in lake temperature [21]. Moreover, the changing thermal characteristics of lakes further modulate local air–lake interactions, with significant impacts on the local climate. Therefore, a comprehensive investigation of the response of the thermal structure in TP lakes to climate change is needed to predict changes in lake ecosystems and the regional climate.

Most previous studies about the thermal responses of TP lakes were based on remote sensing data, which only reflected LSWT changes and the correlation between LSWT and possible driving factors. Additionally, results were mainly derived from statistical methods. However, this approach does not reveal the changes of internal phenomena in lakes, the quantitative contribution of driving factors, and the detailed mechanisms in lake processes. Numerical simulations appear to be the efficient method to reveal these key processes. A series of lake models, such as the Lake model, Flake (Freshwater lake) model, WRF (Weather Research and Forecast)-Lake, CLM (Community Land model)-Lake, CLM4-LISSS (the Lake, Ice, Snow, and Sediment Simulator), and the General Lake Model have been applied to studies of the TP lakes [2,4,7,15,16], with results showing that the vertically integrated mean lake water temperature (MLT) has been consistently changing corresponding to the increasing LSWT, while the bottom lake temperature (BLT) has varied in different ways depending on the lake depth [16,18]. However, with a scarcity of data, the development of TP lake models and numerical studies about the thermal responses of lakes to climate change have been focused solely on several large lakes, such as Nam Co Lake, Qinghai Lake, Ngoring Lake (NL) and Gyraing Lake [3,4,15], etc. In the absence of sufficient observational data and accurate forcing datasets, a previous long-term NL study employed the NCEP (National Centers for Environmental Prediction) and ERA-Interim (European Centre for Medium-Range Weather Forecasts Re-Analysis) data, in which the solar radiation was too grea<sup>t</sup> and decreasing quickly compared to the observations [22]. This resulted in predictions of insignificant NL warming in the simulations, whereas NL was actually warming, as shown by remote sensing data [14,23]. As such, the response of NL to climate warming should be restudied based on more accurate forcing data.

Most TP lakes are saline, but their responses to climate warming have been less studied than those of large lakes in the TP, mostly because of their small areas and the scarcity of observational data. Studies of saline lakes should be strengthened. The Hajiang Salt Pond (HSP, rich in soluble salts) is a paleo-saline lake which was formed by the joint action of traceability development of the Yellow River and climate change due to evaporation and condensation resulting from strong wind and sun. The pond is only about 11.2 km from NL and provides an ideal contrast as a saline lake to a freshwater lake NL with a similar climate.

The effects of salinity on responses of saline lakes to climate warming were poorly understood because of the lack of salinity parameterizations in commonly used models. Salinity could affect lake temperature, evaporation and ice appearance, etc. As such, a lake model considering salinity parameterizations is necessary for numerical studies of the majority of TP lakes.

Therefore, the CLM4-LISSS lake model, parameterized with salinity effects on several lake water characteristics and developed by ourselves and applied to the Great Salt Lake in USA, was introduced. Our previous saline lake model ignored the temperature of the maximum density (Tmaxd) of saline water that decreases with increased salinity and could affect the vertical thermal structure during the cold season in the TP [2,24]. To further improve our lake model, Tmaxd was further parameterized.

In the present study, we applied the CLM4-LISSS lake model developed with salinity parameterizations, in situ lake data, remote sensing data, and an assimilated meteorological dataset to study the thermal response of the largest freshwater lake NL in the TP and its nearby saline lake to climate change. The aim of the study is:


### **2. Study Area, Data and Methods**

### *2.1. Study Area*

2.1.1. Freshwater Ngoring Lake

Ngoring Lake (NL), with a surface area of 610 km<sup>2</sup> and mean depth of 17 m, is the largest freshwater lake in the TP (Figure 1, 97.5~97.92◦E, 34.75~35.08◦N, 4274 m a.s.l.). Mineralization is low. A cold, semi-arid continental climate prevails in the NL basin. The monthly mean air temperature varies from 11.6 ◦C (August 2016) to −26.6 ◦C (January 1978), the annual average air temperature is −3.5 ◦C (1953–2016), and the annual precipitation is 322.4 mm (Data from China's National Climate Center) at Maduo meteorological station (Figure 1, 34.91◦N, 98.22◦E, 4272 m a.s.l.). The lake is covered with ice from early December to early April.

**Figure 1.** Map of the research area, locations of the Ngoring Lake (NL) and Hajiang Salt Pond (HSP), and three observation sites (marked by red stars).

### 2.1.2. Hajiang Salt Pond

Hajiang Salt Pond (HSP, 97.88–97.92◦E, 35.02–35.05◦N) is a small and shallow saline lake with less than 1 m depth and about 220 g L−<sup>1</sup> salinity [25]. The freezing point caused by the salinity is low enough to prevent the lake from freezing normally. It is located approximately 11.2 km east from NL at an altitude of 4240 m. The lake developed from the large Hajiang paleo-lake and currently covers an area of about 10 km2.
