Superensemble Regional Climate Modeling for the Western United States

Abstract

Volunteers contributing idle computing time are helping to create an unprecedented combination of high-spatial and high-statistical resolution in simulations of climate in the C limate system modeling has made tremendous advancements in recent decades. Rapidly expanding computational capabilities and scientific research on fundamental processes have allowed simultaneous progress on a variety of fronts, such as expansion of the processes represented in climate models including interactive carbon cycles represented by biogeochemical models (e.g., Flato 2011), increases in spatial resolution (global models now providing century-long runs at grid spacing as low as ~50 km), and the number of simulations possible with a given model.One area of research currently at the crossroads of basic research and applications is the description of present and future climate at spatial scales that are meaningful both scientifically and for management applications (e.g., Means et al. 2010). Regional climate models (RCMs; e.g., Giorgi 1990) have been implemented over specific areas of interest with resolutions as high as 500 m (Wang et al. 2013) compared to 50-300 km for a GCM. Typically, such studies run the RCM one or at most a handful of times. The problem with having a very small number of simulations is that differences between past and future simulations can stem from several sources, not just the change in greenhouse gases: uncertainty is not well quantified. As O'Brien et al. (2011) note, some studies tacitly assume "that differences between model simulations are entirely due to a physical forcing" and show that internal variability can be larger than the signal in some instances; they

Perspectives on the causes of exceptionally low 2015 snowpack in the western United States

“…We generated different initial conditions using the state of the atmosphere and land surface from 50 simulations ending the prior year and perturbing the global atmospheric potential temperature field; details are provided in Mote et al . [] and Massey et al . [].…”

Thirty Years of Regional Climate Modeling: Where Are We and Where Are We Going next?

“…To date, no rigorous RCM‐based studies are available in the context of attribution of long‐term regional climate changes and trends. A series of papers have explored the issue of the anthropogenic warming contribution to the occurrence of observed extreme events using very large ensembles (up to thousands of members) of short RCM simulations completed as part of the http://climateprediction.net/weather@home project (Massey et al, ; Mote et al, ; Otto et al, ; Schaller et al, ; Sparrow et al, ). Indeed, the weather@home approach can be especially useful for this type of problems, which will undoubtedly receive increasing attention in the future because of its socioeconomic implications.…”

Parametric Sensitivity of Vegetation Dynamics in the TRIFFID Model and the Associated Uncertainty in Projected Climate Change Impacts on Western U.S. Forests

“…Simulations of western U.S. climate and vegetation were generated on the Weather@home distributed volunteer climate modeling system (Guillod et al, ; Massey et al, ; Mote et al, ). The vast computational capacity of Weather@home enables large ensembles of short simulations to be generated rapidly lending to its popularity as an event attribution tool (e.g., Mera et al, ; Mote et al, ), but it has also been used to make statistically robust projections of regional climate change (Rupp et al, ; Rupp & Li, ).…”