Add to ORKGWe present a statistical approach to study time-varying, multivari-ate climate data sets. Aided by domain expertise from the NOAA scientists, we have developed a solution for correlation analysis of multivariate spatial-temporal climate data sets.
Global warming and the associated climate changes are being the subject of intensive research due t...
A multivariate statistical approach is presented that allows a systematic search for relationships b...
Typescript (photocopy).The focus of this work is to contribute to the enhancement of the relationshi...
We present a correlation study of time-varying multivariate volu-metric data sets. In most scientifi...
Understanding atmospheric phenomena involves analysis of large-scale spatiotemporal multivariate dat...
Abstract — Climate change has been a challenging and urgent research problem for many related resear...
This paper discusses multivariate spatio-temporal dependence between extremes or abrupt change and u...
This paper discusses multivariate spatio-temporal dependence between extremes or abrupt change and u...
In this paper, a unique approach to the problem of spatio-temporal pattern detection is discussed in...
Modeling and prediction multivariate geostatistical techniques can be successfully applied to study ...
Modeling and prediction multivariate geostatistical techniques can be successfully applied to study ...
A large number of hydrological phenomena may be regarded as realizations of space-time random functi...
The wavelet local multiple correlation (WLMC) is introduced for the first time in the study of clima...
[1] The analysis of univariate or multivariate time series provides crucial information to describe,...
In this paper we briefly illustrate some exploratory techniques born in the geostatistical framework...
Global warming and the associated climate changes are being the subject of intensive research due t...
A multivariate statistical approach is presented that allows a systematic search for relationships b...
Typescript (photocopy).The focus of this work is to contribute to the enhancement of the relationshi...
We present a correlation study of time-varying multivariate volu-metric data sets. In most scientifi...
Understanding atmospheric phenomena involves analysis of large-scale spatiotemporal multivariate dat...
Abstract — Climate change has been a challenging and urgent research problem for many related resear...
This paper discusses multivariate spatio-temporal dependence between extremes or abrupt change and u...
This paper discusses multivariate spatio-temporal dependence between extremes or abrupt change and u...
In this paper, a unique approach to the problem of spatio-temporal pattern detection is discussed in...
Modeling and prediction multivariate geostatistical techniques can be successfully applied to study ...
Modeling and prediction multivariate geostatistical techniques can be successfully applied to study ...
A large number of hydrological phenomena may be regarded as realizations of space-time random functi...
The wavelet local multiple correlation (WLMC) is introduced for the first time in the study of clima...
[1] The analysis of univariate or multivariate time series provides crucial information to describe,...
In this paper we briefly illustrate some exploratory techniques born in the geostatistical framework...
Global warming and the associated climate changes are being the subject of intensive research due t...
A multivariate statistical approach is presented that allows a systematic search for relationships b...
Typescript (photocopy).The focus of this work is to contribute to the enhancement of the relationshi...