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Risbey, James S.

Publications and source records attributed to Risbey, James S..

Advances in the Application and Utility of Subseasonal-to-Seasonal Predictions

The subseasonal-to-seasonal (S2S) predictive time scale, encompassing lead times ranging from 2 weeks to a season, is at the frontier of forecasting science. Forecasts on this time scale provide opportunities for enhanced application-focused capabilities to complement existing weather and climate services and products. There is, however, a “knowledge–value” gap, where a lack of evidence and awareness of the potential socioeconomic benefits of S2S forecasts limits their wider uptake. To address this gap, here we present the first global community effort at summarizing relevant applications of S2S forecasts to guide further decision-making and support the continued development of S2S forecasts and related services. Focusing on 12 sectoral case studies spanning public health, agriculture, water resource management, renewable energy and utilities, and emergency management and response, we draw on recent advancements to explore their application and utility. These case studies mark a significant step forward in moving from potential to actual S2S forecasting applications. We show that by placing user needs at the forefront of S2S forecast development—demonstrating both skill and utility across sectors—this dialogue can be used to help promote and accelerate the awareness, value, and cogeneration of S2S forecasts. We also highlight that while S2S forecasts are increasingly gaining interest among users, incorporating probabilistic S2S forecasts into existing decision-making operations is not trivial. Nevertheless, S2S forecasting represents a significant opportunity to generate useful, usable, and actionable forecast applications for and with users that will increasingly unlock the potential of this forecasting time scale.

54 ENVIRONMENTAL SCIENCES↗

On the limitations of General Circulation Climate Models

General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change.

Stone, Peter H.↗

Observations of the 30-60 day oscillation in zonal mean atmospheric angular momentum and high cloud cover

Zonally averaged momentum and high-cloud data were analyzed for the periods of April-October 1979 and November 1982-October 1983 periods. The analysis yielded belt correlation fields implying a symmetry and propagation of momentum out of the tropics in the momentum data and an asymmetrical oscillation across the equatorial zone in the high-cloud data. The 30-60 day oscillation was found to be the dominant periodicity in tropical and subtropical belts in both the momentum and cloud fields, with variation of time spectra evident between 1979 and 1983. The lag correlations between high cloud belts and momentum belts showed strong correlations with the 30-60 day oscillation present. Anomalously high/low zonal mean high cloudiness in the tropics was accompanied by anomalously high/low zonal mean momentum in the tropics, with the latter anomalies subsequently propagating into midlatitudes.

Risbey, James S.↗