高原气象

高原气象 >

2019 , Vol. 38 >Issue 1: 101 - 113

DOI: https://doi.org/10.7522/j.issn.1000-0534.2018.00110

论文

三套再分析资料在青藏高原湖泊模拟研究中的适用性分析

  • 杜娟 ,
  • 文莉娟 ,
  • 苏东生
展开
  • 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

收稿日期: 2018-07-18

  网络出版日期: 2019-02-28

基金资助

国家自然科学基金项目（91637107，41475011，41811530387）；中德科学中心国际合作项目（GZ1259）

收起

Reliability of Three Reanalysis Datasets in Simulation of Three Alpine Lakes on the Qinghai-Tibetan Plateau

  • DU Juan ,
  • WEN Lijuan ,
  • SU Dongsheng
Expand
  • 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

Received date: 2018-07-18

  Online published: 2019-02-28

Fold

摘要

湖泊模式为青藏高原湖-气相互作用研究提供了有效方法，而驱动数据对模拟结果影响显著，但目前用来驱动模式的再分析资料对高原不同地区湖泊的适用性依然不够清楚。利用野外观测数据、MODIS地表温度数据和WRF耦合的一维湖泊模式，对比分析了中国区域高时空分辨率地面气象要素驱动数据集（简称ITPCAS）、ERA-Interim和NCEP/NCAR三套再分析资料在青藏高原地区纳木错、班公错和鄂陵湖三个不同深度湖泊的适用性，并对三套再分析资料的准确性进行了初步验证，进一步分析了不同校正方式后的再分析资料对模拟结果的影响。结果表明，用三套不同再分析资料作为模式驱动数据时，WRF耦合的一维湖泊模型均能够较好地模拟出高原湖泊表面温度的变化，但仍然与MODIS观测结果存在偏差。三套再分析资料中ITPCAS数据集的各气象要素与站点观测更为接近，ERA-Interim数据的向下长波和短波辐射比观测值偏大，NCEP/NCAR数据中的向下长波较观测值偏小而风速偏大。利用站点观测对再分析资料进行校正，ITPCAS数据进行全要素校正前后模拟结果差别不大，ERA-Interim和NCEP/NCAR进行全要素校正后模拟结果准确性显著提高；对于实地观测资料匮乏的地区，单独对ERA-Interim向下短波辐射数据进行校正以及同时对NCEP/NCAR气温和向下长波辐射数据进行校正均能优化湖表面温度的模拟结果。

关键词： 一维湖泊模型; 高原湖泊; 湖表面温度; 再分析资料校正

本文引用格式

杜娟 , 文莉娟 , 苏东生 . 三套再分析资料在青藏高原湖泊模拟研究中的适用性分析[J]. 高原气象, 2019 , 38(1) : 101 -113 . DOI: 10.7522/j.issn.1000-0534.2018.00110

Abstract

Lake model is considered as a high-efficiency method to research lake-air interaction. However, few studies focus on reliability of reanalysis data driving model in the lake area on the Qinghai-Tibetan Plateau (QTP). This study explores the applicability of a one-dimensional lake model coupled into WRF at three lakes with different depths, i. e. Nam Co, Bangong Co and Ngoring on the QTP by using the China Meteorological Forcing Dataset (ITPCAS), ERA-Interim reanalysis data, NCEP/NCAR reanalysis data and MODIS LST data. Based on comparing three reanalysis datasets with observational data from weather stations near the lakes during the same period, we evaluate the reliability of reanalysis data in the lake area and further analyze the correction parameters of each reanalysis dataset. The outcomes of the study show that lake model has good ability to simulate the variations of the lake surface temperature on the QTP. Each meteorological element between the stations observation and ITPCAS data is closest among the three reanalysis datasets. The downward longwave radiation and the shortwave radiation of ERA-Interim and the wind speed of NCEP/NCAR are significantly larger, but the downward longwave of NCEP/NCAR is less than the observations. When reanalysis data used to be forcing data of the lake model, the simulation results before and after correction are not obviously different for ITPCAS data. But significantly improved simulation results after full parameters correction for ERA-Interim and NCEP/NCAR. Correcting the downward shortwave radiation only for ERA-Interim data and correcting the air temperature and the downward longwave radiation simultaneously for NECP/NCAR data in areas lacking observational data can improve the simulation of the lake surface temperature.

Key words： One-dimensional lake; alpine lakes; the lake surface tem; correction of the re

参考文献

[1]Bonan G B, 1995. Sensitivity of a GCM simulation to inclusion of inland water surfaces[J]. Journal of Climate, 8(11):2691-2704.
[2]Doberschütz S, Frenzel P, Haberzettl T, et al, 2014. Monsoonal forcing of Holocene paleoenvironmental change on the central Tibetan Plateau inferred using a sediment record from Lake Nam Co (Xizang, China)[J]. Journal of Paleolimnology, 51(2):1-14.
[3]Hostetler S W, Bartlein P J, 1990.Simulation of lake evaporation with application to modeling lake level variation of Harney-Malheur Lake, Oregon[J]. Water Resource Research, 26(10):2603-2613.
[4]Hostetler S W, Bates G T, Giorgi F, 1993. Interactive coupling of a lake thermal model with a regional climate model[J]. Journal of Geophysical Research, 98(D3):5045-5057.
[5]Hostetler S W, Giorgi F, Bates G T, 1994. Lake-atmosphere feedbacks associated with Paleolakes Bonneville and Lahontan[J]. Science, 263(5417):665.
[6]Huang L, Wang J B, Zhu L P, et al, 2017. The warming of large lakes on the Tibetan Plateau:Evidence from a lake model simulation of Nam Co, China, during 1979-2012[J]. Journal of Geophysical Research:Atmospheres, 122(24):13095-13107.
[7]Hulley G C, Hook S J, 2012. A radiance-based method for estimating uncertainties in the Atmospheric Infrared Sounder (AIRS) land surface temperature product[J], J. Geophys. Res., 117:D20117. DOI:10.1029/2012JD018102.
[8]Gu H P, Jin J M, Wu Y H, et al, 2015. Calibration and validation of lake surface temperature simulations with the coupled WRF-lake model[J]. Climatic Change, 129(3/4):471-483.
[9]Kalnay E, Kanamitsu M, Kistler R, et al, 1996. The NCEP/NCAR 40 years reanalysis project[J]. Bulletin of the American Meteorological Society, 77(3):437-471.
[10]Ke C Q, Tao A Q, J X. 2013. Variability in the ice phenology of Nam Co Lake in central Tibet from scanning multichannel microwave radiometer and special sensor microwave/imager:1978 to 2013[J]. Journal of Applied Remote Sensing, 7(1):073477. https://doi.org/10.1117/1.Jrs.7.073477.
[11]Lei Y B, Yang K, Wang B B, et al, 2014. Response of inland lake dynamics over the Tibetan Plateau to climate change[J]. Climatic Change, 125(2):281-290.
[12]Li Z G, Lv S H, Ao Y H, et al, 2015. Long-term energy flux and radiation balance observations over Lake Ngoring, Tibetan Plateau[J]. Atmospheric Research, 155:13-25.
[13]La Z, Yang K, Wang J B, et al, 2016. Quantifying evaporation and its decadal change for Lake Nam Co, central Tibetan Plateau[J]. Journal of Geophysical Research:Atmosphere, 121:7578-579.
[14]Wan Z, 2008. New refinements and validation of the MODIS Land-Surface Temperature/Emissivity products[J]. Remote Sensing of Environment, 112(1):59-74.
[15]Wan Z, Zhang Y, Zhang Q, et al, 2004. Quality assessment and validation of the MODIS global land surface temperature[J]. International Journal Remote Sensing, 25(1):261-274.
[16]Wang B B, Ma Y M, Chen X L, et al, 2015. Observation and simulation of lake-air heat and water transfer processes in a high-altitude shallow lake on the Tibetan Plateau[J]. Journal of Geophysical Research:Atmosphere, 120(24):12327-12344. DOI:10.1002/2015JD023863.
[17]Wen L J, Lü S H, Zhao L, et al, 2015. Impacts of the two biggest lakes on local temperature and precipitation in the Yellow River Source Region on the Tibetan Plateau[J]. Advances in Meteorology, 2015(D14). http://dx.doi.org/10.1155/2015/248031.
[18]Wen L J, Lü S H, Kirillin G, et al, 2016. Air-lake boundary layer and performance of a simple lake parameterization scheme over the Tibetan highlands[J]. Tellus A, 68:31091.
[19]Yang K, He J, Tang W J, et al, 2010.On downward shortwave and longwave radiations over high altitude regions:Observation and modeling in the Tibetan Plateau[J]. Agricultural and Forest Meteorology, 150(1), 38-46.
[20]Zhang G Q, Yao T D, Piao S L, et al, 2017. Extensive and drastically different alpine lake changes on Asia's high plateaus during the past four decades[J]. Geophysical Research Letters, 44:252-260.
[21]Zhang G Q, Yao T D, Xie H J, et al, 2014a. Lakes' state and abundance across the Tibetan Plateau[J]. Chinese Science Bulletin, 59(24):3010-3021.
[22]Zhang G Q, Yao T D, Xie H J, et al, 2014b. Estimating surface temperature changes of lakes in the Tibetan Plateau using MODIS LST data[J], Journal of Geophysical Research:Atmosphere, 119(14):8552-8567.
[23]方楠, 阳坤, 拉珠, 等, 2017. WRF湖泊模型对青藏高原纳木错湖的适用性研究[J].高原气象, 36(3):610-618. DOI:10.7522/j. issn. 1000-0534.2016.00038.
[24]古红萍, 沈学顺, 金继明, 等, 2013.一维热扩散湖模式在太湖的应用研究[J].气象学报, 71(4):719-730.
[25]韩熠哲, 马伟强, 王炳赟, 等, 2017.青藏高原近30年降水变化特征分析[J].高原气象, 36(6):1477-1486. DOI:10.7522/j. issn. 1000-0534.2016.00125.
[26]何杰, 2010.中国区域高时空分辨率气象要素数据集的建立[D].北京: 中国科学院大学, 1-77.
[27]李建, 宇如聪, 陈昊明, 等, 2010.对三套再分析资料中国大陆地区夏季降水量的评估分析[J].气象, 36(12):1-9.
[28]闵文彬, 李跃清, 周纪, 2015.青藏高原东侧MODIS地表温度产品验证[J].高原气象, 34(6):1511-1516. DOI:10.7522/j. issn. 1000-0534.2014.00082.
[29]苏东生, 胡秀清, 文莉娟, 等, 2018.青海湖热力状况对气候变化响应的数值研究[J].高原气象, 37(2):394-405. DOI:10.7522/j. issn. 1000-0534.2017.00069.
[30]唐恬, 王磊, 文小航, 2013.黄河源鄂陵湖地区辐射收支和地表能量平衡特征研究[J].冰川冻土, 35(6):1462-1473.
[31]王苏民, 窦鸿身, 1998.中国湖泊志[M].北京:科学出版社, 398-476.
[32]王明达, 侯居峙, 类延斌, 2014.青藏高原不同类型湖泊温度季节性变化及其分类[J].科学通报, 59(31):3095-3103. DOI10.1007/s11434-014-0588-8.
[33]肖宇, 谢淑云, 王明达, 等, 2015.青藏高原班公错与达则错水温时间序列分形特征[J].地质科技情报, 34(6):200-206.
[34]谢爱红, 秦大河, 任贾文, 等, 2007. NCEP/NCAR再分析资料在珠穆朗玛峰-念青唐古拉山脉气象研究中的可信性[J].地理学报, 62(3):268-278.
[35]许鲁君, 刘辉志, 2015.云贵高原洱海湖泊效应的数值模拟[J].气象学报, 73(4):789-802.
[36]游庆龙, 康世昌, 李潮流, 等, 2009. NCEP/NCAR再分析资料在纳木错流域湖泊/冰川区适用性分析[J].气象, 35(5):66-73.
[37]朱智, 师春香, 张涛, 等, 2018.四套再分析土壤湿度资料在中国区域的适用性分析[J].高原气象, 37(1):240-252. DOI:10.7522/j. issn. 1000-0534.2017.00033.
[38]赵天保, 符淙斌, 2009.几种再分析地表气温资料在中国区域的适用性评估[J].高原气象, 28(3):594-606.
Options
文章导航

/

〈 〉

本系统由北京玛格泰克科技发展有限公司设计开发 技术支持：support@magtech.com.cn