Results 111 to 120 of about 2,660,815 (249)

Statistical downscaling of air quality models using Principal Fitted Components [PDF]

, 2018
Statistical downscaling is a technique that is used to extract high-resolution information from regional scale variables produced by Chemical Transport Models (CTMs).
Alkuwari, Farha Ahmad Z. A.
core   +1 more source

Diffusion model-based probabilistic downscaling for 180-year East Asian climate reconstruction

npj Climate and Atmospheric Science
As our planet is entering into the “global boiling” era, understanding regional climate change becomes imperative. Effective downscaling methods that provide localized insights are crucial for this target.
Fenghua Ling, Zeyu Lu, Jing-Jia Luo, Lei Bai, Swadhin K. Behera, Dachao Jin, Baoxiang Pan, Huidong Jiang, Toshio Yamagata   +8 more
doaj   +1 more source

Breeding for multi‐stress resilience in crops: Myth or possibility?

PLANTS, PEOPLE, PLANET, EarlyView.
Climate change threatens millions of farmers worldwide by exposing crops to multiple concurrent or sequential environmental stresses such as drought, heat, waterlogging, and diseases. Although crops have long been selected under naturally occurring multi‐stress conditions, breeding pipelines largely focus on optimal or single‐stress environments ...
Hamid Khazaei, Ian C. Dodd, Rodomiro Ortiz   +2 more
wiley   +1 more source

REGRESI KUADRAT TERKECIL PARSIAL MULTI RESPON UNTUK STATISTICAL DOWNSCALING (Multi Response Partial Least Square for Statistical Downscaling) [PDF]

, 2011
In  climatology  partial  least  square  regression  (PLSR)  can  be  used  as  an alternative  technique  in  statistical  downscaling  based  on  global  circulation model  (GCM)  output.
Wigena, Aji Hamim
core  

The evaluation of boundary‐layer turbulence in high‐resolution numerical weather prediction simulations using Doppler lidar

Quarterly Journal of the Royal Meteorological Society, EarlyView.
A new method compares both kilometer and sub‐kilometre weather model simulations with Doppler lidar observations to assess the representation of boundary‐layer turbulence. While bulk boundary‐layer properties are well represented, vertical velocity variance is strongly underestimated in both simulations.
Natalie J. Harvey, Helen F. Dacre, Kirsty E. Hanley, Humphrey W. Lean, Christopher J. Walden, Michael Baidu, Steven Boeing, Andrew N. Ross   +7 more
wiley   +1 more source

Statistical downscaling with artificial neural networks

, 2008
Statistical downscaling methods seek to model the relationship between large scale atmospheric circulation, on say a European scale, and climatic variables, such as temperature and precipitation, on a regional or subregional scale.
Malcolm Haylock, Philip D. Jones, U. K. Nr Tj, Stephen R. Dorling, Clare Goodess, Gavin C. Cawley   +5 more
core  

Modéliser l'impact du changement climatique sur les écosystèmes aquatiques par approche de downscaling [PDF]

, 2009
L'objectif était d'évaluer l'impact du changement global sur les écosystèmes aquatiques au cours du 21ème siècle, dans le bassin Adour Garonne (S-O France). Une approche de " downscaling " a été développée à l'interface entre les sciences du climat, de l'
Tisseuil, Clément
core  

Increasing urban flash flood risk attributable to both climate and development

Quarterly Journal of the Royal Meteorological Society, EarlyView.
A new event impact attribution methodology that combines convection‐permitting climate model data with flood inundation modelling was used for a five‐hour flash‐flooding event in the suburbs of Leeds in 2014. The results show increased urban flood extent due to both climate change (+16%) and increased urbanisation (+29%).
Daniel F. Cotterill, Dann Mitchell, Peter A. Stott, Paul Bates, Youtong Rong, Leanne Archer   +5 more
wiley   +1 more source

Assessment of typhoon hazards under global warming: Case studies on severe typhoons with downscaling experiments [PDF]

, 2015
International Workshop on Issues in Downscaling of Climate Change Projection.
Ito, Rui, Arakawa, Osamu, Takemi, Tetsuya   +2 more
core  

Calibration of medium‐range temperature ensemble forecasts dependent on the time horizon: An assessment

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Numerical weather prediction output necessitates calibration, as weather model systems are unable to replicate the correct statistics of observations. Such processing is especially important when predicting extreme weather. Calibration methods function by learning from prediction inadequacies during a training phase and by exploiting this information ...
Dmitrij Japs, Oleksiy Boyko, Paolo Reggiani, Ezio Todini   +3 more
wiley   +1 more source