Influence of local and remote sea surface temperatures on precipitation as inferred from changes in boundary‐layer moisture convergence and moist thermodynamics over global oceans

Abstract

A comprehensive method of estimating the influences of local versus remote sea surface temperatures (SSTs) on precipitation is developed. The method was applied to two ten-year simulations made with a general circulation model (GCM) and forced with prescribed SSTs. The simulation period spanned from 1 January 1982 to 31 December 1991. The first simulation (called Cs) was forced with naturally varying SSTs taken from the analysis of observations and the second simulation (called Cc) was forced with monthly mean climatology of SSTs used in Cs. Monthly data of evaporation, precipitation, mean vertical velocity and atmospheric moisture convergence were binned by 1°C SST intervals and plotted as bin means and within-bin standard deviations. The plots showed that (i) binning captured the averaged trend of SST influences on the monthly fields, but with large standard deviations; (ii) all bin-averaged SST dependences were remarkably similar in the two simulations as well as in the single El Niño Southern Oscillation year of 1987; (iii) evaporation increased monotonically with SST up to about 27°C after which it plateaued; and (iv) precipitation correlated much more with the vertical velocity than with the local SST.Monthly precipitation fields were doubly binned with respect to SSTs and boundary-layer moisture convergence (BLqC); data binned in this way were used to compute the partial derivatives of precipitation with respect to SST and BLqC. Together with the total rate of change of BLqC with local SSTs, the rate of change of precipitation with local SST was computed. The remaining precipitation differences were lumped together as all other remote effects. Simulation Cc was used to infer the natural variability of the precipitation required for the statistical significance of the local SST and/or remotely caused changes in precipitation. This analysis categorized all precipitation anomalies into four types: (i) where the local SST influences were significant, (ii) where the remote SSTs influences were significant, (iii) where both influences were significant, and (iv) where the natural variability was larger than both influences. Most of the precipitation responses to SSTs were as expected, while their seasonal behaviour revealed that local SSTs contribute to a number of features of the Intertropical Convergence Zone (ITCZ) including the double ITCZ in March-April-May. Published in

Recent trends of the tropical hydrological cycle inferred from Global Precipitation Climatology Project and International Satellite Cloud Climatology Project data

“…These simulation results are consistent with heuristic arguments suggesting that whereas the atmospheric moisture at fixed relative humidity increases at ∼7% °C −1 (following the Clausius‐Clapeyron relation) [ Held and Soden , 2006], the global mean precipitation, governed by radiative‐convective balance, increases at less than half this rate. Therefore, a weaker overturning circulation must occur in response to the warming environment to match the radiative constraints on evaporation and precipitation [ Betts and Ridgway , 1989; Betts , 1998; Knutson and Manabe , 1995; Allen and Ingram , 2002; Held and Soden , 2006; Sud et al , 2008]. Locally, precipitation and moist convection could be enhanced in convective (wet) regions following the “rich‐get‐richer mechanism” because gross moist stability is reduced when the increase of moisture is concentrated mainly in the lower troposphere [ Chou and Neelin , 2004; Chou et al , 2009].…”

A Comparative Analysis of the Impacts of Two Types of El Niño on the Central and Eastern Pacific ITCZ

“…In general, the increased SST extent of the EP-El Niño is much larger than that of the CP-El Niño. The higher SST indicates stronger sea surface evaporation [34], and the CEP-ITCZ precipitation intensity should be much stronger as well. However, this is not consistent with the above statistical conclusions.…”