High sensitivity of tropical precipitation to local sea surface temperature.

Precipitation and atmospheric circulation are the coupled processes through which tropical ocean surface temperatures drive global weather and climate1-5. Local sea surface warming tends to increase precipitation, but this local control is difficult to disentangle from remote effects of conditions elsewhere. As an example of such a remote effect, El Niño Southern Oscillation (ENSO) events in the equatorial Pacific Ocean alter precipitation across the tropics. Atmospheric circulations associated with tropical precipitation are predominantly deep, extending up to the tropopause. Shallow atmospheric circulations6-8 affecting the lower troposphere also occur, but the importance of their interaction with precipitation is unclear. Uncertainty in precipitation observations9,10 and limited observations of shallow circulations11 further obstruct our understanding of the ocean's influence on weather and climate. Despite decades of research, persistent biases remain in many numerical model simulations12-18, including excessively wide tropical rainbands14,18, the 'double-intertropical convergence zone problem'12,16,17 and too-weak responses to ENSO15. These biases demonstrate gaps in our understanding, reducing confidence in forecasts and projections. Here we use observations to show that seasonal tropical precipitation has a high sensitivity to local sea surface temperature. Our best observational estimate is an 80 per cent change in precipitation for every gram per kilogram change in the saturation specific humidity (itself a function of the sea surface temperature). This observed sensitivity is higher than in 43 of the 47 climate models studied, and is associated with strong shallow circulations. Models with more realistic (closer to 80%) sensitivity have smaller biases across a wide range of metrics. Our results apply to both temporal and spatial variation, over regions where climatological precipitation is about one millimetre per day or more. Our analyses of multiple independent observations, physical constraints and model data underpin these findings. The spread in model behaviour is further linked to differences in shallow convection, thus providing a focus for accelerated research to improve seasonal forecasts through multidecadal climate projections.

Changes in the MJO under greenhouse gas-induced warming in CMIP5 models.

This study investigates changes to the Madden-Julian Oscillation (MJO) in response to greenhouse-gas induced warming during the 21st century. Changes in the MJO's amplitude, phase speed, and zonal scale are examined in five Coupled Model Intercomparison Project Phase 5 (CMIP5) models that demonstrate superior MJO characteristics. Under warming, the CMIP5 models exhibit a robust increase in the spectral power of planetary-scale, intraseasonal, eastward-propagating (MJO) precipitation anomalies (~10.9 %K-1). The amplification of MJO variability is accompanied by an increase of the spectral power of the corresponding westward traveling waves at a similar rate. This suggests that enhanced MJO variability in a warmer climate is likely caused by enhanced background tropical precipitation variability, not by changes in the MJO's stability. All models examined show an increase in the MJO's phase speed (1.8 - 4.5 %K-1) and a decrease in the MJO's zonal wavenumber (1.0 - 3.8 %K-1). Using a linear moisture mode framework, this study tests the theory-predicted phase speed changes against the simulated phase speed changes. It is found that the MJO's acceleration in a warmer climate is a result of enhanced horizontal moisture advection by the steepening of the mean meridional moisture gradient and the decrease in zonal wavenumber, which is partially offset by the lengthening of the convective moisture adjustment timescale and the increase in gross dry stability. While the ability of the linear moisture mode framework to explain MJO phase speed changes is model dependent, the theory can accurately predict the phase speed changes in the model ensemble.