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 simulation of intraseasonal precipitation variability over China in extendedsummer (May–October) is evaluated based on six climate simulations of theMet Office Unified Model. Two simulations use the Global Atmosphere 6.0 (GA6)and four the Global Coupled 2.0 (GC2) configuration. Model biases are largesuch that mean precipitation and intraseasonal variability reach twice theirobserved values, particularly in southern China. To test the impact ofair–sea coupling and horizontal resolution, GA6 and GC2 at horizontalresolutions corresponding to ∼25 , 60, and 135 km at 50 ∘  N areanalyzed. Increasing the horizontal resolution and adding air–sea couplinghave little effect on these biases. Pre-monsoon rainfall in the Yangtze Riverbasin is too strong in all simulations. Simulated rainfall amounts in Juneare too high along the southern coast and persist in the coastal regionthrough July, with only a weak northward progression. The observed northwardpropagation of the Meiyu–Baiu–Changma rainband from spring to late summeris poor in all GA6 and GC2 simulations. To assess how well the MetUMsimulates spatial patterns of temporally coherent precipitation, empiricalorthogonal teleconnection (EOT) analysis is applied to pentad-meanprecipitation. Patterns are connected to large-scale processes by regressingatmospheric fields onto the EOT pentad time series. Most observed patterns ofintraseasonal rainfall variability are found in all simulations, includingthe associated observed mechanisms. This suggests that GA6 and GC2 mayprovide useful predictions of summer intraseasonal variability despite theirsubstantial biases in mean precipitation and overall intraseasonal variance.

Intraseasonal summer rainfall variability over China in the MetUM GA6 and GC2 configurations