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Estimating pros and cons of statistical downscaling based on EQM bias adjustment as a complementary method to dynamical downscaling [PDF]

Scientific Reports
The increasing availability of coarse-scale climate simulations and the need for ready-to-use high-resolution variables drive the climate community to the challenge of reducing computational resources and time for downscaling purposes.
Alfredo Reder, Giusy Fedele, Ilenia Manco, Paola Mercogliano   +3 more
doaj   +2 more sources

Evaluation of statistical downscaling model's performance in projecting future climate change scenarios

Journal of Water and Climate Change, 2023
Statistical downscaling (SD) is preferable to dynamic downscaling to derive local-scale climate change information from large-scale datasets. Many statistical downscaling models are available these days, but comparison of their performance is still ...
Rituraj Shukla, Deepak Khare, Anuj Kumar Dwivedi, Ramesh Pal Rudra, Santosh S. Palmate, C. S. P. Ojha, Vijay P. Singh   +6 more
doaj   +1 more source

Uncovering the shortcomings of a weather typing method [PDF]

Hydrology and Earth System Sciences, 2020
In recent years many methods for statistical downscaling of the precipitation climate model outputs have been developed. Statistical downscaling is performed under general and method-specific (structural) assumptions but those are rarely evaluated ...
E. Van Uytven, J. De Niel, P. Willems, P. Willems   +3 more
doaj   +1 more source

Projected Changes in Temperature and Precipitation over Kashafrood Basin Based on Statistical and Dynamical Downscaling Methods [PDF]

مخاطرات محیط طبیعی, 2021
It is well-known that climate is changing continuously under the intricate influences of natural and artificial factors at global and regional scales. The global Coupled Model Intercomparison Project (CMIP) already provides multi model data resources in ...
Hooshmand Ataei, Mansoureh Kouhi, Rahele Modirian, Bahare Bazrafshan   +3 more
doaj   +1 more source

Climate change scenarios generated by using GCM outputs and statistical downscaling in an arid region [PDF]

Desert, 2015
Two statistical downscaling models, the non-homogeneous hidden Markov model (NHMM) and the Statistical Down–Scaling Model (SDSM) were used to generate future scenarios of both mean and extremes in the Tarim River basin,which were based on nine combined ...
Zhaofei Liu, Zongxue Xu
doaj   +1 more source

How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections?

Earth's Future, 2022
We present an intercomparison of a suite of high‐resolution downscaled climate projections based on a six‐member General Circulation Model (GCM) ensemble from Coupled Models Intercomparison Project (CMIP6).
Deeksha Rastogi, Shih‐Chieh Kao, Moetasim Ashfaq   +2 more
doaj   +1 more source

Repeatable high-resolution statistical downscaling through deep learning [PDF]

Geoscientific Model Development, 2022
One of the major obstacles for designing solutions against the imminent climate crisis is the scarcity of high spatio-temporal resolution model projections for variables such as precipitation.
D. Quesada-Chacón, K. Barfus, C. Bernhofer   +2 more
doaj   +1 more source

Wavelet-based predictor screening for statistical downscaling of precipitation and temperature using the artificial neural network method

Hydrology Research, 2022
One of the challenging issues in statistical downscaling of climate models is to select dominant large-scale climate variables (predictors). Correlation-based methods have been revealed to be efficacious to select the predictors; however, traditional ...
Aida Hosseini Baghanam, Ehsan Norouzi, Vahid Nourani   +2 more
doaj   +1 more source

A Hybrid Statistical Downscaling Framework Based on Nonstationary Time Series Decomposition and Machine Learning

Earth and Space Science, 2022
Downscaling techniques are effective to bridge the scale gap between global circulation models and regional studies. Statistical downscaling methods are prevalent due to their advantages in high computational efficiency and accuracy. However, an implicit
Xintong Li, Xiaodong Zhang, Shuguang Wang   +2 more
doaj   +1 more source

Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0) [PDF]

Geoscientific Model Development, 2019
In this paper I present new methods for bias adjustment and statistical downscaling that are tailored to the requirements of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP).
S. Lange
doaj   +1 more source