Article Were Partially Covered by the Open Access Fund of the Largest Freshwater Lakes of the Tibetan Plateau

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Article Were Partially Covered by the Open Access Fund of the Largest Freshwater Lakes of the Tibetan Plateau Hydrol. Earth Syst. Sci., 21, 1895–1909, 2017 www.hydrol-earth-syst-sci.net/21/1895/2017/ doi:10.5194/hess-21-1895-2017 © Author(s) 2017. CC Attribution 3.0 License. Seasonal thermal regime and climatic trends in lakes of the Tibetan highlands Georgiy Kirillin1, Lijuan Wen2, and Tom Shatwell1 1Department of Ecohydrology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), 12587 Berlin, Germany 2Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 73000, China Correspondence to: Georgiy Kirillin ([email protected]) Received: 28 November 2016 – Discussion started: 23 December 2016 Revised: 21 February 2017 – Accepted: 13 March 2017 – Published: 4 April 2017 Abstract. The hydrology of the lake-rich Tibetan Plateau is that the increase in air temperature was offset by the decrease important for the global climate, yet little is known about the in radiation, probably due to increasing humidity. This study thermal regime of Tibetan lakes due to scant data. We (i) in- demonstrates that air temperature trends are not directly cou- vestigated the characteristic seasonal temperature patterns pled to lake temperatures and underscores the importance of and recent trends in the thermal and stratification regimes shortwave radiation for the thermal regime of high-altitude of lakes on the Tibetan Plateau and (ii) tested the perfor- lakes. mance of the one-dimensional lake parameterization scheme FLake for the Tibetan lake system. For this purpose, we com- bined 3 years of in situ lake temperature measurements, sev- eral decades of satellite observations, and the global reanal- 1 Introduction ysis data. We chose the two largest freshwater Tibetan lakes, Ngoring and Gyaring, as study sites. The lake model FLake The hydrological regime of the Tibetan highlands is ex- faithfully reproduced the specific features of the high-altitude tremely complex and highly sensitive to climate changes (Gu lakes and was subsequently applied to reconstruct the ver- et al., 2005; Ma et al., 2012; Yang et al., 2014). The Ti- tically resolved heat transport in both lakes during the last betan Plateau plays a crucial role in the global water cycle 4 decades. The model suggested that Ngoring and Gyaring because it directly affects the monsoon system and is the were ice-covered for about 6 months and stratified in summer origin of major Asian rivers (Su et al., 2015) including the for about 4 months per year with a short spring overturn and a Yellow, Yangtze, Mekong, Salween, Brahmaputra (Yarlung longer autumn overturn. In summer the surface mixed bound- Tsangpo), and Indus (Fig. 1). The plateau contains thou- ary layer extended to 6–8 m of depth and was about 20 % sands of lakes, the hydrological regime of which is closely shallower in the more turbid Gyaring. The thermal regime connected to glaciers, permafrost, and influent and effluent of the transparent Ngoring responded more strongly to at- (Zheng, 2011; Zhang et al., 2013). The particular climatic en- mospheric forcing than Gyaring, where the higher turbid- vironment of the Tibetan Plateau, with low air pressure and ity damped the response. According to the reanalysis data, intense solar radiation, creates a unique land–atmosphere in- air temperatures and humidity have increased, whereas so- teraction (Ma et al., 2009) where the lake system is a crucial lar radiation has decreased, since the 1970s. Surprisingly, the component of the regional heat and mass balance (Liu et al., modeled mean lake temperatures did not change, nor did the 2009; Gerken et al., 2013; Li et al., 2015; Wen et al., 2015; phenology of the ice cover or stratification. Lake surface tem- Dai et al., 2016). Therefore, changes in the regional water peratures in summer increased only marginally. The reason is budget of the Tibetan Plateau driven by global warming are of key importance for climatic changes on continental scales. Published by Copernicus Publications on behalf of the European Geosciences Union. 1896 G. Kirillin et al.: Thermal regime and climatic trends in Tibetan lakes A major problem in resolving the energy and moisture budget of high-altitude lakes is the lack of long-term obser- vations. Observational data on the physics of Tibetan Plateau lakes are scarce and mostly confined to remote-sensing data on lake surface characteristics, such as lake surface temper- ature (Lin et al., 2011; Zhang et al., 2014). Observations of air–lake fluxes using eddy covariance methods over Tibetan Plateau lakes are too fragmentary to estimate the seasonal variations (Biermann et al., 2014; Li et al., 2015). Further- more, lack of knowledge of the heat transport within the lake water column, including the seasonal formation of thermal stratification and the thermal dynamics under the ice cover, have limited our understanding of lake–atmosphere interac- tions on climatic scales. While the first brief reports were recently presented (Wang et al., 2014; Wen et al., 2016) on the mixing conditions and vertical heat transport within the lake water bodies, there are no observational data covering the annual variability or the long-term trends in thermal conditions and stratification in Tibetan lakes. No regular lake monitoring was performed in Figure 1. The study site map and the points of the AVHRRPathfiner this area in the past. In this situation, the modeling of decadal grid used for estimation of the surface temperature from satellite data. The green shaded region is the Tibetan Plateau, shown as land variability in lake dynamics can provide insight into the on- above 2000 m a.s.l. going changes on seasonal to climatic time scales, provided that the model performance is tested against available obser- vational data for shorter periods. On the other hand, the vali- Recent evidence indicates that the number of lakes on the Ti- dation of models for parameterizing lakes in weather predic- betan Plateau is increasing, highlighting global warming ef- tion and climate studies is of significant value, particularly fects and local anthropogenic activity, such as infrastructure because it is crucial to properly account for the heat budget construction on permafrost (Cheng and Wu, 2007; Liu et al., of one of the largest lake systems worldwide to adequately 2009; Yang et al., 2010). Hence, to estimate how lakes may model heat and mass transport on a planetary level. affect the regional climate, it is necessary to quantify the sea- In view of these challenges, the present study aimed to sonal thermal dynamics of lakes and ponds with particular reference to the vertical thermal stratification, the ice regime, – characterize the seasonal stratification regime and ice and the lake interactions with the lower atmosphere. cover formation in lakes of the Tibetan Plateau using the Due to the importance of lakes for understanding the two largest freshwater lakes of the region as examples; global-scale changes on the Tibetan Plateau, several studies – test the ability of the lake model FLake (Mironov, 2008; have been performed in recent years on the lake dynamics Kirillin et al., 2011) to simulate the main features of and lake–atmosphere interactions. The amount of evapora- the lake thermodynamics in high-altitude conditions as tion and heat flux and their change was revealed in lakes in a potential tool to parameterize the Tibetan lake system the Tibetan Plateau during the pre- and post-monsoon peri- in regional climate modeling; ods (Haginoya et al., 2009; Xu et al., 2009). Biermann et al. (2014) measured the turbulent fluxes over wet grassland – and quantify the mean trends in the thermal and ice and a shallow lake with the eddy covariance method at the regime of Tibetan lakes during the last half-century shoreline of the Nam Co Lake basin. Li et al. (2015) recently to estimate the climate-driven changes in the seasonal studied the characteristics of the energy flux and the radi- stratification pattern. ation balance over Ngoring Lake. With the development of lake schemes and atmospheric models that include the lake For this purpose, we combine 3-year observations on the surface (Sun et al., 2007), other studies have investigated the surface heat budget from Ngoring Lake (Wen et al., 2016) effects of the Tibetan Plateau lakes on the local climate (Li with the surface temperatures from the AVHRR sea sur- et al., 2009; Wen et al., 2015; Yang et al., 2015). Neverthe- face temperature (SST) product (Casey et al., 2010), the less, compared to other lake-rich regions of the world, like one-dimensional lake temperature and mixing model FLake, Fennoscandia, northern Canada, or the eastern Siberian tun- and the long-term forcing from the ERA-Interim and dra, the lakes of the Tibetan Plateau are poorly studied, de- NCEP/NCAR global atmospheric reanalyses (Kalnay et al., spite their extraordinary thermal regimes due to strong sea- 1996; Dee et al., 2011). In situ and satellite data on the sur- sonal and synoptic variations. face temperatures are primarily used to validate the model Hydrol. Earth Syst. Sci., 21, 1895–1909, 2017 www.hydrol-earth-syst-sci.net/21/1895/2017/ G. Kirillin et al.: Thermal regime and climatic trends in Tibetan lakes 1897 performance at short and long time scales, respectively. The of 2011–2013 (Li et al., 2015, 2016; Wen et al., 2015, 2016). model is forced by reanalysis data in two different configura- The bulk surface temperatures obtained in these observations tions corresponding to the two neighboring large freshwater comprise the primary dataset for verifying the lake model in lakes located in the northeastern part of the plateau, Ngor- this study. The bulk temperatures of the lake surface water ing and Gyaring. Both lakes undergo virtually the same at- were recorded by 109 L probes (Campbell Scientific, Inc., mospheric forcing, but differ in mean depth and water trans- Logan, UT, USA) at water depths of 0.05, 0.20, 0.40, and parency.
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