Reanalysis is now an indispensable dataset for climate studies. It provides analysis of a variety of variables, which are internally consistent within the framework of the numerical model used in the data assimilation. However, its coarse spatial resolution has been problematic for various application studies. As pointed out by von Storch et al. (2000), dynamical downscaling with the spectral nudging technique is considere
Statistical downscaling techniques based on a perfect prognosis approach often rely on reanalyses to...
The analogue method is a statistical downscaling method for precipitation prediction. It uses simila...
In this paper, we compare the retained and added variability obtained using the regional climate mod...
Continuous data assimilation (CDA) is successfully implemented for the first time for efficient dyna...
AbstractThis study analyzes a method to construct a homogeneous, high-resolution global atmospheric ...
To overcome the problem that the horizontal resolution of global climate models may be too low to re...
As an extreme demonstration of regional climate model capability, a dynamical downscaling of NCEP-NC...
High-resolution, bias-corrected climate data is necessary for climate impact studies and modeling ef...
International audienceA novel climate downscaling methodology that attempts to correct climate simul...
Global reanalyses provide the most consistent atmospheric circulation datasets for many dynamical pr...
Statistical downscaling and bias correction are becoming standard tools in climate impact studies. T...
Abstract. Dynamical downscaling has been extensively used to study regional climate forced by large-...
Lateral and lower boundary conditions derived from a suitable global reanalysis data set form the ba...
Dynamical downscaling has been extensively used to study regional climate forced by large-scale glob...
In this study, a worldwide overview on the expected sensitivity of downscaling studies to reanalysis...
Statistical downscaling techniques based on a perfect prognosis approach often rely on reanalyses to...
The analogue method is a statistical downscaling method for precipitation prediction. It uses simila...
In this paper, we compare the retained and added variability obtained using the regional climate mod...
Continuous data assimilation (CDA) is successfully implemented for the first time for efficient dyna...
AbstractThis study analyzes a method to construct a homogeneous, high-resolution global atmospheric ...
To overcome the problem that the horizontal resolution of global climate models may be too low to re...
As an extreme demonstration of regional climate model capability, a dynamical downscaling of NCEP-NC...
High-resolution, bias-corrected climate data is necessary for climate impact studies and modeling ef...
International audienceA novel climate downscaling methodology that attempts to correct climate simul...
Global reanalyses provide the most consistent atmospheric circulation datasets for many dynamical pr...
Statistical downscaling and bias correction are becoming standard tools in climate impact studies. T...
Abstract. Dynamical downscaling has been extensively used to study regional climate forced by large-...
Lateral and lower boundary conditions derived from a suitable global reanalysis data set form the ba...
Dynamical downscaling has been extensively used to study regional climate forced by large-scale glob...
In this study, a worldwide overview on the expected sensitivity of downscaling studies to reanalysis...
Statistical downscaling techniques based on a perfect prognosis approach often rely on reanalyses to...
The analogue method is a statistical downscaling method for precipitation prediction. It uses simila...
In this paper, we compare the retained and added variability obtained using the regional climate mod...