<p>Initializing climate models for decadal prediction is a major challenge, in part due to the lack of long-term subsurface ocean observations and the changing nature of observing systems. In order to overcome these limitations, we have developed a novel method for initializing a climate model for decadal prediction. Using GFDL&#8217;s next-generation prediction system, we developed a coupled ensemble data assimilation system, which assimilated only surface pressure observations, since the surface pressure measurements have been made since the late 1800s. Physically, by assimilating high-frequency surface pressure observations we constrain the model to experience a sequence of wind and storms, and thus surface fluxes, that is very similar to what is observed. The hypothesis is that by having the ocean component of the coupled model experience a very similar sequence of surface fluxes as observations, the ocean component of the coupled model will gradually reproduce the same variations as the observed system.</p><p>We assimilated the observed surface pressure station data used in the latest 20-century reanalysis. A coupled simulation during 1960 to 2016 has been completed. In this talk, we will review how well the observed decadal climate variations (e.g., PDO and AMO) can be reproduced solely from the surface pressure observations.&#160; In addition, we will explore the multi-decadal variations of the Atlantic meridional overturning circulation (AMOC) and its connection with the North Atlantic sea surface temperature. The feasibility of using this method to initialize coupled climate models for realistic decadal predictions will be discussed in the talk.&#160; &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;</p>
Mapping Recent Decadal Climate Variations in Precipitation and Temperature across Eastern Africa and the Sahel
