Responses of Lake Ice Phenology to Climate Change at Tibetan Plateau

Abstract

Lake ice phenology is a sensitive indicator reflecting global warming. In this paper, the long-term changes of lake ice phenology of the second largest lake at Tibetan Plateau (i.e., the Nam Co) in response to climate change are investigated based on mathematical modelling. The model has been testified capable of reproducing daily surface temperature of the lake in both frozen and unfrozen seasons. The lake ice phenology determined according to the simulated lake surface temperature is found consistent with that derived from satellite observation. For the Nam Co during the period 1978-2017, the freezing date has been delayed (reached up to 0.57days/year) whereas the thawing date became earlier (-0.23days/year). The trend of lake ice phenology is significantly correlated to the annual minimal lake surface and air temperature. Modelling experiment suggests that lake ice phenology of the Nam Co is very sensitive to a warmer climate. Under warmer future, much later freezing date and earlier thawing date are expected, hence the ice-covering duration would be significantly shortened.

Review on the Change Trend, Attribution Analysis, Retrieval, Simulation, and Prediction of Lake Surface Water Temperature

“…In lakes with ice cover, LSWT has been rising and the duration of seasonal ice cover has been decreasing [109]. It has been shown in the literature that the average rate of decrease in lake ice cover duration shows an apparent agreement with the average rate of LSWT warming [55], [109], [298]. Guo et al (2020) investigated the long-term changes in lake ice phenology of Nam Co, the second largest lake on the Tibet Plateau and found that the rate of increase in LSWT minimum temperature of 0.12°C /a with warming of the AT during 1978-2017 was the main cause of its ice phenology changes, which resulted in a reduction in the duration of complete ice cover by 0.72 days per year, and predicted that the duration of complete ice cover would be reduced by 60 days if the AT warms by 2°C in the future [298].…”

“…Assuming that the lake is completely covered by ice, the heat exchange between air and water is blocked and the surface energy balance will be replaced by the land surface energy balance without the mixing depth of water. Based on this, Guo et al (2020) introduced the state of the lake (open water, ice cover, water and ice mixing) to modify the air2water model, which has 15 parameters (A2W-15) to be calibrated. It is worth noting that the model simulates a large bias in the very high/very low lake surface temperatures, which may be due to the uncertainty of the input model parameterization inheritance and the bias of the MODIS LST products [298].…”

“…Based on this, Guo et al (2020) introduced the state of the lake (open water, ice cover, water and ice mixing) to modify the air2water model, which has 15 parameters (A2W-15) to be calibrated. It is worth noting that the model simulates a large bias in the very high/very low lake surface temperatures, which may be due to the uncertainty of the input model parameterization inheritance and the bias of the MODIS LST products [298]. In addition, Zhu et al ( 2022) used an improved A2W-8 model for SST prediction and showed that the forecast performed well and could be migrated at unknown sites and is a promising tool for predicting SST, but it still needs to be justified by comparing its performance with other SST models using data from other regions [299].…”

Novel Air2water Model Variant for Lake Surface Temperature Modeling With Detailed Analysis of Calibration Methods

“…However, it is very difficult to define the bounds of this surface layer [24]. Recently Guo et al [25] introduced a variant of air2water model with 15 parameters developed for thermal surface conditions of frozen lakes. Basing on the idea introduced in [25], in the present paper we propose a new version of air2water model that has 12 parameters but is much more flexible in capturing interrelationships between a cold or frozen lake surface, and the water body.…”

“…Recently Guo et al [25] introduced a variant of air2water model with 15 parameters developed for thermal surface conditions of frozen lakes. Basing on the idea introduced in [25], in the present paper we propose a new version of air2water model that has 12 parameters but is much more flexible in capturing interrelationships between a cold or frozen lake surface, and the water body. The variant uses different parameterization for cold and warm water periods (basically, those with classical thermal stratification and inversion of water temperatures), and considers a situation of a mix of both of them.…”