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

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.

Keywords

• air temperature
• precipitation
• aridity index
• land-atmosphere feedbacks