Fine‐resolution climate projections enhance regional climate change impact studies
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.153 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
A new data set enhances the abilities of researchers and decision‐makers to assess possible future climates, explore societal impacts, and approach policy responses from a risk‐based perspective. The data set, which consists of a library of 112 fine‐resolution climate projections, based on 16 climate models and three greenhouse gas emissions scenarios, is now publicly available. Monthly climate projections from 1950 to 2099 were downscaled to a spatial resolution of ⅛° (about 140 square kilometers per grid cell) covering the conterminous United States and portions of Canada and Mexico. For the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, climate modeling groups produced hundreds of simulations of past and future climates. The colocation of these simulations in a single archive (at the Program for Climate Model Diagnosis and Intercomparison at Lawrence Livermore National Laboratory (LLNL), established to facilitate assessment of general circulation models, or GCMs) and the conversion of all results to a common data format have made probabilistic, multi‐model projections and impact assessments practical. A remaining issue is that the spatial scale of climate model output is typically too coarse for regional impact studies. Multiple downscaling approaches exist for deriving regional climate from coarse‐resolution model output; these approaches are typically applied on an ad hoc basis to a particular region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Eos
- Topic
- demographic modeling and climate adaptation
- Field
- Decision Sciences
- Canadian institutions
- —
- Funders
- —
- Keywords
- DownscalingClimate modelClimate changeGeneral Circulation ModelEnvironmental scienceGreenhouse gasProbabilistic logicClimatologyScale (ratio)MeteorologyGridRepresentative Concentration PathwaysComputer scienceGeographyPrecipitationCartography
- Has abstract in OpenAlex
- yes