Predicting patterns of near-surface air temperature using empirical data

被引:9
|
作者
Anisimov, OA [1 ]
机构
[1] State Hydrol Inst, Dept Climatol, St Petersburg 199053, Russia
基金
美国国家科学基金会;
关键词
D O I
10.1023/A:1010658014439
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The signal of recent global warming has been detected in meteorological records, borehole temperatures and by several indirect climate indicators. Anthropogenic warming continues to evolve, and various methods are used to study and predict the changes of the global and regional climate. Results derived from GCMs, palaeoclimate reconstructions, and regional climate models differ in detail. An empirical model could be used to predict the spatial pattern of the near-surface air temperature and to narrow the range of regional uncertainties. The idea behind this approach is to study the correlations between regional and global temperature using century-scale meteorological records, and to evaluate the regional pattern of the future climate using regression analysis and the global-mean air temperature as a predictor. This empirical model, however, is only applicable to those parts of the world where regional near-surface air temperature reacts linearly to changes of the global thermal regime. This method and data from a set of approximately 2000 weather stations with continuous century-scale records of the monthly air temperature was applied to develop the empirical map of the regional climate sensitivity. Data analysis indicated that an empirical model could be applied to several large regions of the World, where correlations between local and global air temperature are statistically significant. These regions are the western United States, southern Canada, Alaska, Siberia, south-eastern Asia, southern Africa and Australia, where the correlation coefficient is typically above 0.9. The map of regional climate sensitivity has been constructed using calculated coefficients of linear regression between the global-mean and regional annual air temperature. As long as the correlations between the local and global air temperature are close to those in the last several decades, this map provides an effective tool to scale down the projection of the global air temperature to regional level. According to the results of this study, maximum warming at the beginning of the 21st century will take place in the continental parts of North America and Eurasia. The empirical regional climate sensitivity defined here as the response of the mean-annual regional temperature to 1 degreesC global warming was found to be 5-6 degreesC in southern Alaska, central Canada, and over the continental Siberia, 3-4 degreesC on the North Slope of Alaska and western coast of the U.S.A., and 1-2 degreesC in most of the central and eastern U.S.A. and eastern Canada. Regions with negative sensitivity are located in the southeastern U.S.A., north-western Europe and Scandinavia. The local tendency towards cooling, although statistically confirmed by modern data, could, however, change in the near future.
引用
收藏
页码:297 / 315
页数:19
相关论文
共 50 条
  • [41] Impacts of land surface temperature and ambient factors on near-surface air temperature estimation: A multisource evaluation using SHAP analysis
    Li, Songyang
    Wong, Man Sing
    Zhu, Rui
    Shi, Guoqiang
    Yang, Jinxin
    SUSTAINABLE CITIES AND SOCIETY, 2025, 122
  • [42] Modelling spatial patterns of near-surface air temperature over a decade of melt seasons on McCall Glacier, Alaska
    Troxler, Patrick
    Ayala, Alvaro
    Shaw, Thomas E.
    Nolan, Matt
    Brock, Ben W.
    Pellicciotti, Francesca
    JOURNAL OF GLACIOLOGY, 2020, 66 (257) : 386 - 400
  • [43] ANNUAL COURSE OF AIR TEMPERATURE AND NEAR-SURFACE SOIL TEMPERATURE IN A TROPICAL SAVANNAH ENVIRONMENT
    KALMA, JD
    AGRICULTURAL METEOROLOGY, 1971, 8 (4-5): : 293 - &
  • [44] Near-Surface Air Temperature Retrieval Derived from AMSU-A and Sea Surface Temperature Observations
    Jackson, Darren L.
    Wick, Gary A.
    JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY, 2010, 27 (10) : 1769 - 1776
  • [45] On the contribution of lakes in predicting near-surface temperature in a global weather forecasting model
    Balsamo, G.
    Salgado, R.
    Dutra, E.
    Boussetta, S.
    Stockdale, T.
    Potes, M.
    TELLUS SERIES A-DYNAMIC METEOROLOGY AND OCEANOGRAPHY, 2012, 64
  • [46] Assimilation of near-surface temperature using extended Kalman filter
    Kumar, P
    Kaleita, AL
    ADVANCES IN WATER RESOURCES, 2003, 26 (01) : 79 - 93
  • [47] A spatiotemporal analysis of the relationship between near-surface air temperature and satellite land surface temperatures using 17 years of data from the ATSR series
    Good, Elizabeth J.
    Ghent, Darren J.
    Bulgin, Claire E.
    Remedios, John J.
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2017, 122 (17) : 9185 - 9210
  • [48] Estimating Monthly Energy Fluxes Using Observations of Near-Surface Air Temperature, Humidity and Radiosonde Profiles
    Brondani, Daiane V.
    Acevedo, Otavio C.
    Tatsch, Jonatan D.
    Puhales, Franciano S.
    BOUNDARY-LAYER METEOROLOGY, 2019, 171 (02) : 271 - 288
  • [49] Estimating Monthly Energy Fluxes Using Observations of Near-Surface Air Temperature, Humidity and Radiosonde Profiles
    Daiane V. Brondani
    Otávio C. Acevedo
    Jônatan D. Tatsch
    Franciano S. Puhales
    Boundary-Layer Meteorology, 2019, 171 : 271 - 288
  • [50] Estimating near-surface air temperature across Israel using a machine learning based hybrid approach
    Zhou, Bin
    Erell, Evyatar
    Hough, Ian
    Rosenblatt, Jonathan
    Just, Allan C.
    Novack, Victor
    Kloog, Itai
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2020, 40 (14) : 6106 - 6121