English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

There have been significant advances in our understanding of the climate system, but two major problems still exist in modeling atmospheric response during cold seasons: (a) lack of detailed physical description of snow and frozen soil in the land-surface schemes and (b) insufficient understanding of regional climate response from the cryosphere. A multilayer snow land-surface model based on the conservations of heat and water substance inside the soil and snow is coupled to an atmospheric RCM, to investigate the effect of snow, snowmelt, and soil frost on the atmosphere during cold seasons. The coupled RCM shows much improvement in moisture and temperature simulation for March-April of 1997 compared to simple parameterizations used in GCMs. The importance of such processes in RCM simulation is more pronounced in mid-to-high latitudes during the transition period (winter–spring) affected by changes in surface energy and the hydrological cycle. The effect of including cryosphere physics through snow-albedo feedback mechanism changes the meridional temperature gradients and in turn changes the location of weather systems passing over the region. The implications from our study suggest that, to reduce the uncertainties and better assess the impacts of climate change, RCM simulations should include the detailed snow and frozen soil processes

Atmosphere-Cryosphere Coupled Model for Regional Climate Applications