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

This study investigates the changes in annual and seasonal maximum daily rainfall (RX1day) in Southeast Asia, obtained from gauge-based gridded precipitation data, to address the increasing concerns about climate change in the region. First, the nonparametric Mann–Kendall test was employed to detect significant trends in RX1day. Then, maximum likelihood modeling, which allows the incorporation of covariates in the location parameter of the generalized extreme value (GEV) distribution, was conducted to determine whether the rising global mean temperature, as well as El Nino–Southern Oscillation (ENSO), is influencing extreme rainfall over the region. The findings revealed that annual and seasonal RX1day is significantly increasing in Indochina and east-central Philippines while decreasing in most parts of the Maritime Continent during the past 57 yr (1951–2007). The trends in RX1day were further linked to the rising global mean temperature. It was shown that the location parameter of the GEV—and he...

Significant Influences of Global Mean Temperature and ENSO on Extreme Rainfall in Southeast Asia