Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target

被引:321
作者
McColl, Kaighin A. [1 ]
Vogelzang, Jur [2 ]
Konings, Alexandra G. [1 ]
Entekhabi, Dara [1 ,3 ]
Piles, Maria [4 ,5 ]
Stoffelen, Ad [2 ]
机构
[1] MIT, Dept Civil & Environm Engn, Cambridge, MA 02139 USA
[2] KNMI, De Bilt, Netherlands
[3] MIT, Dept Earth Atmospher & Planetary Sci, Cambridge, MA USA
[4] Univ Politecn Cataluna, Remote Sensing Lab, Dept Teoria Senyal & Comunicac, Barcelona, Spain
[5] SMOS Barcelona Expert Ctr, Barcelona, Spain
关键词
triple collocation; signal-to-noise ratio; model validation; model calibration; correlation coefficient; SOIL-MOISTURE; MICROWAVE OBSERVATIONS; SURFACE TEMPERATURE; AMSR-E; VALIDATION; SATELLITE; RETRIEVALS; AFRICA; EUROPE; MODEL;
D O I
10.1002/2014GL061322
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Calibration and validation of geophysical measurement systems typically require knowledge of the true value of the target variable. However, the data considered to represent the true values often include their own measurement errors, biasing calibration, and validation results. Triple collocation (TC) can be used to estimate the root-mean-square-error (RMSE), using observations from three mutually independent, error-prone measurement systems. Here, we introduce Extended Triple Collocation (ETC): using exactly the same assumptions as TC, we derive an additional performance metric, the correlation coefficient of the measurement system with respect to the unknown target, rho(t,Xi). We demonstrate that rho(2)(t,Xi) is the scaled, unbiased signal-to-noise ratio and provides a complementary perspective compared to the RMSE. We apply it to three collocated wind data sets. Since ETC is as easy to implement as TC, requires no additional assumptions, and provides an extra performance metric, it may be of interest in a wide range of geophysical disciplines.
引用
收藏
页码:6229 / 6236
页数:8
相关论文
共 30 条
[1]   Towards an integrated soil moisture drought monitor for East Africa [J].
Anderson, W. B. ;
Zaitchik, B. F. ;
Hain, C. R. ;
Anderson, M. C. ;
Yilmaz, M. T. ;
Mecikalski, J. ;
Schultz, L. .
HYDROLOGY AND EARTH SYSTEM SCIENCES, 2012, 16 (08) :2893-2913
[2]  
[Anonymous], 1993, INTRO BOOTSTRAP
[3]   Validation of ocean wind and wave data using triple collocation [J].
Caires, S ;
Sterl, A .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2003, 108 (C3)
[4]  
CORNBLEET PJ, 1979, CLIN CHEM, V25, P432
[5]   An improved approach for estimating observation and model error parameters in soil moisture data assimilation [J].
Crow, W. T. ;
van den Berg, M. J. .
WATER RESOURCES RESEARCH, 2010, 46
[6]   Intercomparison of fraction of absorbed photosynthetically active radiation products derived from satellite data over Europe [J].
D'Odorico, Petra ;
Gonsamo, Alemu ;
Pinty, Bernard ;
Gobron, Nadine ;
Coops, Nicholas ;
Mendez, Elias ;
Schaepman, Michael E. .
REMOTE SENSING OF ENVIRONMENT, 2014, 142 :141-154
[7]  
Deming WE., 1943, Statistical adjustment of data
[8]  
Dorigo W. A., 2010, HYDROL EARTH SYST SC, V7, P5621, DOI DOI 10.5194/HESSD-7-5621-2010
[9]   Estimating root mean square errors in remotely sensed soil moisture over continental scale domains [J].
Draper, Clara ;
Reichle, Rolf ;
de Jeu, Richard ;
Naeimi, Vahid ;
Parinussa, Robert ;
Wagner, Wolfgang .
REMOTE SENSING OF ENVIRONMENT, 2013, 137 :288-298
[10]   Performance Metrics for Soil Moisture Retrievals and Application Requirements [J].
Entekhabi, Dara ;
Reichle, Rolf H. ;
Koster, Randal D. ;
Crow, Wade T. .
JOURNAL OF HYDROMETEOROLOGY, 2010, 11 (03) :832-840