A framework to quantify the inter-annual variation in near-surface air temperature due to change in precipitation in snow-free regions

Dongqin Yin*, Michael L. Roderick

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    A negative correlation between near-surface air temperature (T a) and precipitation (P) has long been recognized over many land regions, but a predictive quantitative relationship has not yet been established. In this study, we examine inter-annual variations in T a with P and investigate how the T a-P relationship varies with aridity in regions without snow coverage. The wetness index is used as a measure of aridity (defined as the ratio of mean annual P to E o, with E o the net radiation expressed as an equivalent depth of water), with wetness index more (less) than 1.0 used to define the wet (dry) regions. Results show that variations in T a are independent of P in wet environments, while in dry environments the variations in T a with P increase with aridity. We use that relationship to establish a quantitative framework to a priori predict the T a-P relation based on aridity. The results highlight the importance of inter-annual variations in P in changing T a in dry environments, since it has similar magnitude with the decadal global warming signals over land.

    Original languageEnglish
    Article number114028
    JournalEnvironmental Research Letters
    Volume15
    Issue number11
    DOIs
    Publication statusPublished - Nov 2020

    Fingerprint

    Dive into the research topics of 'A framework to quantify the inter-annual variation in near-surface air temperature due to change in precipitation in snow-free regions'. Together they form a unique fingerprint.

    Cite this