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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The methodology for dynamical climate downscaling is studied using the second-generation regional climate model (RegCM2). The question addressed is, in order to simulate high-resolution details as accurately as possible, what strategy should be taken: continuous long-term integration in climate prediction mode or consecutive shortterm integrations in weather forcasting mode? To investigate this problem, the model was run for 5 months in three different ways: 1) a 5-month continuous simulation, 2) monthly reinitialized simulations, and 3) 10-day reinitialized simulations. Compared to the observed precipitation, the 10-day reinitialized simulation results in the smallest error, while the continuous run shows larger error. Analysis shows that the long-term continuous simulation is contaminated by the systematic errors associated with the steep Andes Mountains and the uncertainties in the moisture processes in the planetary boundary layer near the coast. The method of 10-day reinitialization effectively mitigates the problem of systematic errors and makes a difference in the subtle precipitation processes in the regional climate model, therefore improving the accuracy in dynamic downscaling.

Reinitialized versus Continuous Simulations for Regional Climate Downscaling