Results 81 to 90 of about 2,660,815 (249)
13th International Conference on Urban Drainage (ICUD 2014)
Selection of predictors for statistical downscaling is crucial as the relationship between the predictors (temperature, humidity and geopotential height) and predictands (local scale meteorological variables such as rainfall) forms the basis of ...
Rashid, Md Mamunur +5 more
core +1 more source
The Galápagos Archipelago's near‐surface climate is primarily influenced by interannual El Niño‐Southern Oscillation variability, with no statistical evidence for long‐term trends in air temperature, humidity, or precipitation. While tropospheric warming and increased atmospheric stability are observed, these trends are largely decoupled from near ...
Benjamin Schmidt +6 more
wiley +1 more source
A Zonal‐Meridional Projection Method for Quantifying Global Land‐Ocean Moisture Transport
We present a physically consistent and computationally efficient method to quantify global coastal moisture transport by projecting vertically integrated moisture flux onto signed land–ocean boundary segments. The signed projection naturally distinguishes ocean‐to‐land inflow and land‐to‐ocean outflow without explicit directional classification ...
Chong Zhang +2 more
wiley +1 more source
Downscaling of Temperatures Over the Eastern Mediterranean for the 21st Century
We developed an analogue‐based statistical downscaling method, using a K‐nearest‐neighbour framework, to project daily maximum temperature (Tmax) and minimum temperature (Tmin) at 32 homogenized meteorological stations. Late twenty‐first‐century (2080–2100) temperature projections obtained using the method, show robust warming across all stations and ...
Anton Gelman +4 more
wiley +1 more source
Statistical downscaling, including machine learning based downscaling, is widely used to produce high spatiotemporal resolution air temperatures for monitoring extreme heat events. However, coarse baseline data often exhibit sharp discontinuities at grid
Zitong Wen +5 more
doaj +1 more source
A genetic programming (GP)-based logistic regression method is proposed in the present study for the downscaling of extreme rainfall indices on the east coast of Peninsular Malaysia, which is considered one of the zones in Malaysia most vulnerable to ...
Sahar Hadi Pour +2 more
doaj +1 more source
Extreme precipitation trends detected in Paraná, Southern Brazil (1983–2024), are strongly conditioned by the dataset used, with reanalyses indicating coherent inland drying and longer dry spells, observations retaining stronger mesoscale heterogeneity, and satellite products often showing declines in short‐duration extremes. Monthly diagnostics reveal
Paulo Miguel de Bodas Terassi +2 more
wiley +1 more source
Evaluating historical precipitation trends is complicated by interactions between variability in atmospheric circulation and thermodynamic forcing. This study assesses 1901–2023 UK winter precipitation trends in UK Climate Projections 2018 (UKCP18) global climate models using dynamical adjustment to separate circulation‐driven and non‐dynamical ...
James G. Carruthers +3 more
wiley +1 more source
Evaluating downscaled products with expected hydroclimatic co-variances [PDF]
There has been widespread adoption of downscaled products amongst practitioners and stakeholders to ascertain risk from climate hazards at the local scale (e.g., ∼ 5 km resolution).
S. H. Baek +3 more
doaj +1 more source
Automated regression-based statistical downscaling tool.
Many impact studies require climate change information at a finer resolution than that provided by Global Climate Models (GCMs). In the last 10 years, downscaling techniques, both dynamical (i.e. Regional Climate Model) and statistical methods, have been
Ouarda, Taha B. M. J. +3 more
core +1 more source

