An appraisal of downscaling methods used in climate change research
The term 'downscaling'refers to the process of translating information from global climate
model simulations to a finer spatial resolution. There are numerous methods by which this …
model simulations to a finer spatial resolution. There are numerous methods by which this …
Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model
A drought forecasting model is a practical tool for drought-risk management. Drought models
are used to forecast drought indices (DIs) that quantify drought by its onset, termination, and …
are used to forecast drought indices (DIs) that quantify drought by its onset, termination, and …
Long-term rainfall prediction using atmospheric synoptic patterns in semi-arid climates with statistical and machine learning methods
J Diez-Sierra, M Del Jesus - Journal of Hydrology, 2020 - Elsevier
In this paper, we evaluate the performance of 8 statistical and machine learning methods,
driven by atmospheric synoptic patterns, for long-term daily rainfall prediction in a semi-arid …
driven by atmospheric synoptic patterns, for long-term daily rainfall prediction in a semi-arid …
[HTML][HTML] Influence of rainfall scenario construction methods on runoff projections
FS Mpelasoka, FHS Chiew - Journal of Hydrometeorology, 2009 - journals.ametsoc.org
Influence of Rainfall Scenario Construction Methods on Runoff Projections in: Journal of
Hydrometeorology Volume 10 Issue 5 (2009) Jump to Content Jump to Main Navigation …
Hydrometeorology Volume 10 Issue 5 (2009) Jump to Content Jump to Main Navigation …
A multivariate quantile-matching bias correction approach with auto-and cross-dependence across multiple time scales: Implications for downscaling
R Mehrotra, A Sharma - Journal of Climate, 2016 - journals.ametsoc.org
A novel multivariate quantile-matching nesting bias correction approach is developed to
remove systematic biases in general circulation model (GCM) outputs over multiple time …
remove systematic biases in general circulation model (GCM) outputs over multiple time …
High‐resolution multisite daily rainfall projections in India with statistical downscaling for climate change impacts assessment
Climate change impacts assessment involves downscaling of coarse‐resolution climate
variables simulated by general circulation models (GCMs) using dynamic (physics‐based) …
variables simulated by general circulation models (GCMs) using dynamic (physics‐based) …
Do derived drought indices better characterize future drought change?
Current methods for climate change assessment ignore the significant differences in
uncertainty in model projections of the two key constituents of drought, precipitation, and …
uncertainty in model projections of the two key constituents of drought, precipitation, and …
A nonparametric kernel regression model for downscaling multisite daily precipitation in the Mahanadi basin
Hydrologic impacts of global climate change are usually assessed by downscaling large‐
scale climate variables, simulated by general circulation models (GCMs), to local‐scale …
scale climate variables, simulated by general circulation models (GCMs), to local‐scale …
Prediction of daily rainfall state in a river basin using statistical downscaling from GCM output
Conventional statistical downscaling techniques for prediction of multi-site rainfall in a river
basin fail to capture the correlation between multiple sites and thus are inadequate to model …
basin fail to capture the correlation between multiple sites and thus are inadequate to model …
A comparison of three stochastic multi-site precipitation occurrence generators
R Mehrotra, R Srikanthan, A Sharma - Journal of Hydrology, 2006 - Elsevier
This paper presents a comparison of three multi-site stochastic weather generators for
simulation of point rainfall occurrences at a network of 30 raingauge stations around …
simulation of point rainfall occurrences at a network of 30 raingauge stations around …