高原气象

高原气象 >

2018 , Vol. 37 >Issue 2: 394 - 405

DOI: https://doi.org/10.7522/j.issn.1000-0534.2017.00069

论文

青海湖热力状况对气候变化响应的数值研究

  • 苏东生 ,
  • 胡秀清 ,
  • 文莉娟 ,
  • 赵林 ,
  • 李照国
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  • 中国科学院西北生态环境资源研究院寒旱区陆面过程与气候变化重点实验室, 甘肃 兰州 730000;中国科学院大学, 北京 100049;国家卫星气象中心, 北京 100081

收稿日期: 2017-07-04

  网络出版日期: 2018-04-28

基金资助

国家自然科学基金项目（91637107，41475011）；中德中心国际合作项目（GZ1259）

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Simulation of the Response of Qinghai Lake Thermal Conditions to Climate Change

  • SU Dongsheng ,
  • HU Xiuqing ,
  • WEN Lijuan ,
  • ZHAO Lin ,
  • LI Zhaoguo
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  • Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Region, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, Gansu, China;University of Chinese Academy of Science, Beijing 100049, China;National Satellite Meteorological Centre, Beijing 100081, China

Received date: 2017-07-04

  Online published: 2018-04-28

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摘要

湖泊对气候变化非常敏感，是气候变化的指示器。青藏高原湖泊众多，但由于观测数据的缺乏，目前对全球变暖背景下高原湖泊热力状况的研究依然不足且多为短期研究。利用中国科学院青藏高原研究所（ITPCAS）开发的中国区域高时空分辨率地面气象要素驱动数据集、MODIS地表温度数据、青海湖浮标观测数据，分析了Freshwater Lake Model（简称Flake模式）在青海湖的适用性，揭示了青海湖热力状况对气候变化的响应。结果表明，Flake模式能够很好的模拟出青海湖的热力状况，但对夏季与秋季的湖表面水温（特别是夜间）模拟偏高，部分是驱动数据误差造成的，修正驱动数据后模拟效果得到改善。对1989-2012年Flake模拟的湖表面温度与ITPCAS数据不同驱动要素之间的年际变化趋势与相关性进行分析，发现青海湖表面温度呈现上升趋势，与气温、向下长波辐射有较好的正相关性，而与风速负相关。内部热力状况的模拟结果显示，青海湖混合层温度基本全年呈上升趋势，其中5、6月及12月增温最显著；湖泊底层温度在5月以及12月的两次季节性翻转时期呈上升趋势，在6-10月湖水分层期呈下降趋势，分层期湖泊上层温度升高会加强湖水层结稳定性，使湖水混合减弱，导致底层温度下降。

关键词： 青藏高原; Flake模式; 青海湖; 数值模拟; 气候变化

本文引用格式

苏东生 , 胡秀清 , 文莉娟 , 赵林 , 李照国 . 青海湖热力状况对气候变化响应的数值研究[J]. 高原气象, 2018 , 37(2) : 394 -405 . DOI: 10.7522/j.issn.1000-0534.2017.00069

Abstract

Lake is a very sensitive indicator to climate change. There are thousands of lakes on Qinghai-Tibetan Plateau, about 1 200 of them have an area larger than 1 km2, but few observation data of lakes are available, which makes the thermal condition of plateau lakes under the background of climate warming far from well understood, at the same time, most of the studies on plateau lakes focused on short-term research. In this study, the China Meteorological Forcing Dataset developed by Institute of Tibetan Plateau Research, Chinese Academy of Sciences (ITPCAS), MODIS LST data and buoy observation data were used to analysis the applicability of Freshwater Lake Model (Flake) at Qinghai Lake and reveal the response of thermal condition of Qinghai Lake to climate change. The results show that Flake have good abilities to capture the thermal characteristics of Qinghai Lake and have a good simulation to the seasonal variations of the lake surface temperature. But some positive deviation was found in summer and autumn (especially in nighttime), part of the deviation was caused by the bias of forcing data, after a simple correction to temperature and wind speed of the forcing data, the deviation of the simulation result was partly reduced. The comparison and analysis of interannual variation trend and correlation between lake surface temperature simulated by Flake and meteorological factors of ITPCAS forcing data from 19892012 found there is a warming trend in lake surface temperature, which have a positive correlation with air temperature and downward longwave radiation, and a negative correlation with wind speed, indicating that the air temperature warming plays a key role in lake surface temperature increase. The simulation of inner lake thermal condition revealed that the mixed-layer temperature of Qinghai Lake presents an increase trend almost all the year round, which is most obviously in May and June. For the bottom of the lake, the increase trend only happens in May and December, it is also the seasonal overturn period of the lake, and a decrease trend happens from June to October when the lake is in stratification period. This pattern may caused by the increase of stratified stability due to the temperature increase of the up-layer water in stratification period.

Key words： Qinghai-Tibetan Plat; Flake model; Qinghai Lake; numerical simulation; climate change

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