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A Spatial Downscaling Method for Remote Sensing Soil Moisture Based on Random Forest Considering Soil Moisture Memory and Mass Conservation

open access: yesRemote Sensing, 2022
Remote sensing soil moisture (SM) has been widely used in various earth science studies and applications, but their low resolution limits their usage and downscaling of them is needed.
Taoning Mao   +8 more
doaj   +2 more sources

A Comparison of ETKF and Downscaling in a Regional Ensemble Prediction System [PDF]

open access: goldAtmosphere, 2015
Based on the operational regional ensemble prediction system (REPS) in China Meteorological Administration (CMA), this paper carried out comparison of two initial condition perturbation methods: an ensemble transform Kalman filter (ETKF) and a dynamical
Hanbin Zhang   +3 more
doaj   +2 more sources

Impacts of Horizontal Resolution of the Lateral Boundary Conditions and Downscaling Method on the Performance of RegCM4.6 in Simulating the Surface Climate Over Central‐Eastern China

open access: yesEarth and Space Science, 2022
This study investigated the impacts of horizontal resolution of lateral boundary condition (LBC) and downscaling method on the performance of RegCM4.6 in simulating the 2 m air temperature and precipitation over central eastern China.
Xiaoke Xu   +7 more
doaj   +1 more source

Statistical Learning-Based Spatial Downscaling Models for Precipitation Distribution

open access: yesAdvances in Meteorology, 2022
The downscaling technique produces high spatial resolution precipitation distribution in order to analyze impacts of climate change in data-scarce regions or local scales.
Yichen Wu   +3 more
doaj   +1 more source

An Improved Approach for Downscaling Coarse-Resolution Thermal Data by Minimizing the Spatial Averaging Biases in Random Forest

open access: yesRemote Sensing, 2020
Land surface temperature (LST) plays a fundamental role in various geophysical processes at varying spatial and temporal scales. Satellite-based observations of LST provide a viable option for monitoring the spatial-temporal evolution of these processes.
Sammy M. Njuki   +2 more
doaj   +1 more source

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

open access: yesJournal 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   +6 more
doaj   +1 more source

Downscaling approach to develop future sub-daily IDF relations for Canberra Airport Region, Australia [PDF]

open access: yesProceedings of the International Association of Hydrological Sciences, 2015
Downscaling of climate projections is the most adopted method to assess the impacts of climate change at regional and local scale. In the last decade, downscaling techniques which provide reasonable improvement to resolution of General Circulation ...
H. M. S. M. Herath   +2 more
doaj   +1 more source

BDIS: Balanced Training Architecture for Dual Image Scaler Using Origin Referenceable Losses

open access: yesIEEE Access, 2022
Deep neural network (DNN)-based research on image scaling has mostly focused on super-resolution (SR) rather than image downscaling. Specifically, most existing DNN-based methods for image downscaling are used as auxiliary modules to improve the quality ...
Eun Su Kang   +4 more
doaj   +1 more source

Simulations of the Holocene climate in Europe using an interactive downscaling within the iLOVECLIM model (version 1.1) [PDF]

open access: yesClimate of the Past, 2023
This study presents the application of an interactive downscaling in Europe using iLOVECLIM (a model of intermediate complexity), increasing its atmospheric resolution from 5.56 to 0.25∘ kilometric.
F. Arthur   +5 more
doaj   +1 more source

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