Ecological and societal impacts of decadal climate variability
Contact: Gokhan Danabasoglu
gokhan@ucar.edu
A NSF EaSM II project led by Gokhan Danabasoglu on decadal climate variability includes investigations of ecological and societal impacts of near-term variability. The studies make use of decadal prediction (DP) simulations performed using the Community Earth System Model (CESM1), including a recent set of DPs with biogeochemistry (BGC) enabled in the ocean component.
In one study, the impacts of the Atlantic meridional overturning circulation on DP of Arctic winter sea-ice extent is investigated (Yeager et al. 2015), forecasting a slowdown in the rate of Atlantic-sector sea ice loss. The analysis shows that external radiative forcing contributes to the skill of retrospective decadal sea ice predictions, but the spatial and temporal accuracy is greatly enhanced by the more realistic representation of ocean heat transport anomalies afforded by initialization. Recent forecasts indicate that a spin-down of the thermohaline circulation that began near the turn of the century will continue, and this will result in near-neutral decadal trends in Atlantic winter sea ice extent in the coming years, with decadal growth in select regions.
Preliminary analysis of net primary productivity (NPP) in the DP experiments with BGC shows promising skill in predicting anomalous NPP in the Northeast Pacific sector between 1 to 2 years in advance. There is substantially lower skill in predicting NPP in the subpolar North Atlantic at multi-year lead times than there is in predicting upper-ocean heat content or sea surface temperatures (SST), but there is nevertheless a suggestion that decadal-scale regime shifts in productivity may in fact be predictable.
In another study, research on the predictability of extreme weather has focused on the identification of large-scale spatial SST patterns that control the variability of the number and intensity of winter cyclones in the Northwestern Atlantic, and hurricane tracks that make landfall at the U.S. Northeast coast. These SST patterns are important to define the critical information in the decadal forecasts that are most relevant to extreme weather events. For hurricanes making landfall around New York, significant large-scale SST patterns are found to be correlated with the number of annual landfall hurricanes: more landfall hurricanes are associated with a negative phase of the Pacific Decadal Variability, and a SST warm anomaly around 35°N in the North Atlantic that is sandwiched between two cold anomalies poleward and equatorward. This SST pattern has been used to construct a statistical-dynamical forecast model to predict the probability of landfall hurricanes.
We plan to expand use these CESM DP simulations to include studies on near-term changes in sea surface height; human population exposure to temperature extremes; and impacts on fisheries. We also plan to assess decadal predictability of SST patterns associated with hurricane activity and use them for WRF downscaling of extreme temperature, precipitation, and winds, making use of the results from the CESM DP experiments. We note that the CESM DP simulations are freely available to the community, and we encourage further use and analysis of the simulations.
This is a highly collaborative project, involving many colleagues from NCAR, WHOI, and SUNY.
Yeager, S., A. Karspeck, and G. Danabasoglu, 2015: Predicted slowdown in the rate of Atlantic sea ice loss. Geophysical Research Letters, 42, DOI: 10.1002/2015GL065364.