Results 211 to 220 of about 782,810 (312)

What Do Latest CMIP6 Global Climate Models Say About Future Arctic Sea Ice Coverage Changes?

open access: yesInternational Journal of Climatology, EarlyView.
Modelling of sea ice dynamics has significantly improved between CMIP5 and CMIP6, with nearly three times as many models capturing realistic annual variability in sea ice extent (SIE). What we previously thought was a non‐linear pattern of low SIE observations in 2007–2010 that would continue throughout time now appears to be non‐record‐setting lows in
Jessica L. Matthews   +4 more
wiley   +1 more source

Three Generations of NARCliM: Evaluation of Precipitation, Temperature and Their Extremes Over the CORDEX Australasia Domain

open access: yesInternational Journal of Climatology, EarlyView.
The NSW and Australian Regional Climate Modelling Version 2.0 (NARCliM2.0) builds on NARCliM1.0 and 1.5 to deliver improved regional climate simulations. This study provides the first comprehensive evaluation of NARCliM2.0 against its predecessors, assessing individual model skill in reproducing mean and extreme climate.
Fei Ji   +12 more
wiley   +1 more source

Growing Degree‐Day Trends Associated With ‘False Springs’ in the Continental United States

open access: yesInternational Journal of Climatology, EarlyView.
Earlier spring warming has increased growing degree‐day (GDD) accumulation prior to the last freeze at some US locations (red circles = stat. sig. increases). However, after accounting for spatial autocorrelation using a false discovery rate approach, few trends remain significant, indicating no coherent continental‐scale increase in false spring risk.
Robert E. Davis   +3 more
wiley   +1 more source

Solar Geoengineering Effects on Malaria Transmission Risk in South Asia Under G6sulfur Scenario

open access: yesInternational Journal of Climatology, EarlyView.
Comparison of EIR (unit: No of infected bites per person per day) for each considered country in South Asia, under the considered scenarios, averaged over the period 2020–2090. A regression equation is shown for each country (for Bhutan EIRG = 0.1690 × 10−10 EIRS + 0.5968 × 10−12) to illustrate the projected trend.
Athar Hussain   +2 more
wiley   +1 more source

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