
Cloud Regime Variability over the Azores and Its Application to Climate Model Evaluation
Author(s) -
Jasmine Rémillard,
George Tselioudis
Publication year - 2015
Publication title -
journal of climate
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.315
H-Index - 287
eISSN - 1520-0442
pISSN - 0894-8755
DOI - 10.1175/jcli-d-15-0066.1
Subject(s) - climatology , environmental science , climate model , middle latitudes , international satellite cloud climatology project , cloud computing , cloud cover , climate change , atmospheric sciences , meteorology , geology , geography , oceanography , computer science , operating system
From its location on the subtropics–midlatitude boundary, the Azores is influenced by both the subtropical high pressure and the midlatitude baroclinic storm regimes and therefore experiences a wide range of cloud structures, from fair-weather scenes to stratocumulus sheets and deep convective systems. This work combines three types of datasets to study cloud variability in the Azores: a satellite analysis of cloud regimes, a reanalysis characterization of storminess, and a 19-month field campaign that occurred on Graciosa Island. Combined analysis of the three datasets provides a detailed picture of cloud variability and the respective dynamic influences, with emphasis on low clouds that constitute a major uncertainty source in climate model simulations. The satellite cloud regime analysis shows that the Azores cloud distribution is similar to the mean global distribution and can therefore be used to evaluate cloud simulation in global models. Regime analysis of low clouds shows that stratocumulus decks occur under the influence of the Azores high pressure system, while shallow cumulus clouds are sustained by cold-air outbreaks, as revealed by their preference for postfrontal environments and northwesterly flows. An evaluation of climate model cloud regimes from phase 5 of CMIP (CMIP5) over the Azores shows that all models severely underpredict shallow cumulus clouds, while most models also underpredict the occurrence of stratocumulus cloud decks. It is demonstrated that the regime analysis can assist in the selection of case studies representing specific climatological cloud distributions. With all the tools now in place, a methodology is suggested to better understand cloud–dynamics interactions and attempt to explain and correct climate model cloud deficiencies.