A Clustering-Assisted Regression (CAR) approach for developing spatial climate data sets in China

Environmental Modelling and Software

Volumn 38, Issue , 2012, Pages 122-128

  Tang, Lina ^a   Su, Xiaodan ^a   Shao, Guofan ^a,b   Zhang, Hao ^b,c   Zhao, Jingzhu ^a  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b PURDUE UNIVERSITY   (United States)

^c PURDUE UNIVERSITY   (United States)

Author keywords

CAR; GIDS; Monthly mean temperature; Monthly precipitation; Spatial interpolation

Indexed keywords

CAR; CLIMATE DATA; CLIMATE VARIABLES; FIXED NUMBERS; GIDS; INTERPOLATION METHOD; INVERSE DISTANCE SQUARED; LOCAL CLIMATE; MEAN TEMPERATURE; METEOROLOGICAL STATION; MOUNTAINOUS REGIONS; MOVING WINDOW; OBSERVATION DATA; SPATIAL DATA; SPATIAL FEATURES; SPATIAL INTERPOLATION; SPATIAL RESOLUTION;

CLUSTER ANALYSIS;

INTERPOLATION;

ACCURACY ASSESSMENT; CLIMATE MODELING; DATA SET; INTERPOLATION; MOUNTAIN REGION; PRECIPITATION (CLIMATOLOGY); REGIONAL CLIMATE; REGRESSION ANALYSIS; SEASONALITY; SPATIAL DATA; SPATIAL RESOLUTION; TEMPERATURE PROFILE; WEATHER STATION;

CHINA;

EID: 84862201868     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2012.05.008     Document Type: Article

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