Title : Building a Cornell Climate Model to Broaden Stakeholder Participation in the Validation , Use , and Development of Seasonal Forecast Tools Hosts :

Content Provider	Semantic Scholar
Author	Chatrchyan, Allison Morrill
Copyright Year	2014
Abstract	Extreme weather is a serious threat to agriculture, human safety, and economic development throughout the world. Climate change is likely to increase the risk of severe weather, particularly heat waves, droughts, and floods. To flourish in spite of these hazards, societies will require a toolkit of infrastructural, technological, and policy adaptations to manage the risk of extremes. Numerical models of weather and climate will be among the most important of these tools because they empower decision makers with information to anticipate and prepare for consequential events. Historically, large national research labs have been the centers for numerical climate model design, development, and validation(1,2,3). Such institutions have made astonishing advancements in simulating global climate processes, biogeochemical cycles, and the role of human activity in warming the planet. Despite these contributions, the existing models are not yet adequate for making accurate seasonal to decadal forecasts(4,5). Although it is not completely understood why these time horizons are so difficult to forecast, two factors likely play a role. First, even the most powerful supercomputers are insufficient for directly simulating weather phenomena on the smallest to the largest geographic scales, yet variations across this continuum may be important for climate prediction(6,7). Second, most of the existing models are exclusively deterministic, meaning that very large ensembles are needed to estimate likely future outcomes from a set of initial conditions. Because model development has not taken advantage of explicitly probabilistic methods for representing unresolvable phenomena(7,8), hybridizing the existing deterministic methods with more probabilistic ones presents an opportunity to develop a new generation of models that are computationally faster and better at representing the full range of future possibilities. Existing model limitations also severely restrict their utility for stakeholders making decisions on a week-to-week or seasonal timeframe. An equally serious shortcoming found in the current generation of models is that the people whose lives and livelihoods are most directly impacted by severe weather and climate change have been left out of the development and evaluation of global climate models. This has led to distrust of climate models and the science of climate change by a large percentage of the general population in the United States(9).
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://www.atkinson.cornell.edu/Assets/ACSF/docs/events/attachments/20140911-CornellClimateModel.pdf
Alternate Webpage(s)	http://www.acsf.cornell.edu/Assets/ACSF/docs/events/attachments/20140911-CornellClimateModel.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article