The effect of Arabian Sea optical properties on SST biases and the South Asian summer monsoon in a coupled GCM

This study examines the effect of seasonally varying chlorophyll on the climate of the Arabian Sea and South Asian monsoon. The effect of such seasonality on the radiative properties of the upper ocean is often a missing process in coupled general circulation models and its large amplitude in the region makes it a pertinent choice for study to determine any impact on systematic biases in the mean and seasonality of the Arabian Sea. In this study we examine the effects of incorporating a seasonal cycle in chlorophyll due to phytoplankton blooms in the UK Met Office coupled atmosphere-ocean GCM HadCM3. This is achieved by performing experiments in which the optical properties of water in the Arabian Sea - a key signal of the semi-annual cycle of phytoplankton blooms in the region - are calculated from a chlorophyll climatology derived from Sea-viewing Wide Field-of-View Sensor (SeaWiFS) data. The SeaWiFS chlorophyll is prescribed in annual mean and seasonally-varying experiments. In response to the chlorophyll bloom in late spring, biases in mixed layer depth are reduced by up to 50% and the surface is warmed, leading to increases in monsoon rainfall during the onset period. However when the monsoons are fully established in boreal winter and summer and there are strong surface winds and a deep mixed layer, biases in the mixed layer depth are reduced but the surface undergoes cooling. The seasonality of the response of SST to chlorophyll is found to depend on the relative depth of the mixed layer to that of the anomalous penetration depth of solar fluxes. Thus the inclusion of the effects of chlorophyll on radiative properties of the upper ocean acts to reduce biases in mixed layer depth and increase seasonality in SST

Impacts of Atlantic multidecadal variability on the tropical Pacific: a multi-model study

Atlantic multidecadal variability (AMV) has been linked to the observed slowdown of global warming over 1998-2012 through its impact on the tropical Pacific. Given the global importance of tropical Pacific variability, better understanding this Atlantic-Pacific teleconnection is key for improving climate predictions, but the robustness and strength of this link are uncertain. Analyzing a multi-model set of sensitivity experiments, we find that models differ by a factor of 10 in simulating the amplitude of the Equatorial Pacific cooling response to observed AMV warming. The inter-model spread is mainly driven by different amounts of moist static energy injection from the tropical Atlantic surface into the upper troposphere. We reduce this inter-model uncertainty by analytically correcting models for their mean precipitation biases and we quantify that, following an observed 0.26°C AMV warming, the equatorial Pacific cools by 0.11°C with an inter-model standard deviation of 0.03°C

Prediction from Weeks to Decades

This white paper is a synthesis of several recent workshops, reports and published literature on monthly to decadal climate prediction. The intent is to document: (i) the scientific basis for prediction from weeks to decades; (ii) current capabilities; and (iii) outstanding challenges. In terms of the scientific basis we described the various sources of predictability, e.g., the Madden Jullian Ocillation (MJO); Sudden Stratospheric Warmings; Annular Modes; El Niño and the Southern Oscillation (ENSO); Indian Ocean Dipole (IOD); Atlantic “Niño;” Atlantic gradient pattern; snow cover anomalies, soil moisture anomalies; sea-ice anomalies; Pacific Decadal Variability (PDV); Atlantic Multi-Decadal Variability (AMV); trend among others. Some of the outstanding challenges include how to evaluate and validate prediction systems, how to improve models and prediction systems (e.g., observations, data assimilation systems, ensemble strategies), the development of seamless prediction systems