Lake ice thickness(LIT)is important for regional hydroclimate systems,lake ecosystems,and human activities on the ice,and is thought to be highly susceptible to global warming.However,the spatiotemporal variability in...Lake ice thickness(LIT)is important for regional hydroclimate systems,lake ecosystems,and human activities on the ice,and is thought to be highly susceptible to global warming.However,the spatiotemporal variability in LIT is largely unknown due to the difficulty in deriving in situ measurements and the lack of an effective remote sensing platform.Despite intensive development and applications of lake ice models driven by general circulation model output,evaluation of the global LIT is mostly based on assumed“ideal”lakes in each grid cell of the climate forcing data.A method for calculating the actual global LIT is therefore urgently needed.Here we use satellite altimetry to retrieve ice thickness for 16 large lakes in the Northern Hemisphere(Lake Baikal,Great Slave Lake,and others)with an accuracy of~0.2 m for almost three decades.We then develop a 1-D lake ice model driven primarily by remotely sensed data and cross-validated with the altimetric LIT to provide a robust means of estimating LIT for lakes larger than 50 km^(2)across the Northern Hemisphere.Mean LIT(annual maximum ice thickness)for 1313 simulated lakes and reservoirs covering~840,000 km^(2)for 2003–2018 is 0.63±0.02 m,corresponding to~485 Gt of water.LIT changes are projected for 2071–2099 under RCPs 2.6,6.0,and 8.5,showing that the mean LIT could decrease by~0.35 m under the worst concentration pathway and the associated lower ice road availability could have a significant impact on socio-economic activities.展开更多
基金supported by the National Natural Science Foundation of China(92047301,91547210,and 51722903)the Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(2019QZKK0105)。
文摘Lake ice thickness(LIT)is important for regional hydroclimate systems,lake ecosystems,and human activities on the ice,and is thought to be highly susceptible to global warming.However,the spatiotemporal variability in LIT is largely unknown due to the difficulty in deriving in situ measurements and the lack of an effective remote sensing platform.Despite intensive development and applications of lake ice models driven by general circulation model output,evaluation of the global LIT is mostly based on assumed“ideal”lakes in each grid cell of the climate forcing data.A method for calculating the actual global LIT is therefore urgently needed.Here we use satellite altimetry to retrieve ice thickness for 16 large lakes in the Northern Hemisphere(Lake Baikal,Great Slave Lake,and others)with an accuracy of~0.2 m for almost three decades.We then develop a 1-D lake ice model driven primarily by remotely sensed data and cross-validated with the altimetric LIT to provide a robust means of estimating LIT for lakes larger than 50 km^(2)across the Northern Hemisphere.Mean LIT(annual maximum ice thickness)for 1313 simulated lakes and reservoirs covering~840,000 km^(2)for 2003–2018 is 0.63±0.02 m,corresponding to~485 Gt of water.LIT changes are projected for 2071–2099 under RCPs 2.6,6.0,and 8.5,showing that the mean LIT could decrease by~0.35 m under the worst concentration pathway and the associated lower ice road availability could have a significant impact on socio-economic activities.
