Ecosystems Working Group

1. Ecosystems Working Group • Adrienne Wootten • Amy Symstad • Laura Perry • Valerie Steen • Jennie Hoffman • Brian Beckage • Jeff Morisette • Justin Schuetz • Amy Daniels • John Gross • Colin Talbert • Andrea Ray • Linda Mearns, Bill Gutowski, Keith Dixon, John Lanzante, Carlos Gaitan, Laura Briley

2. What’s the goal??? • Description to help make choices, interpret existing products • Support learning about the products, & support thoughtful, informed use • Raise the level of conversations btw ecologists and climate scientists – does **not** replace, but facilitates those conversations, • Link to other sources of info for more detail, & also to guide people to other efforts • Nutrition labels in tiered levels, crosslinked • “ingredients” vs “processed food” – need info on both • SRES/RCP emissions scenarios • GCM/RCM/ESMs • Many groups do their own statistical downscaling want to decide which GCMs to use, or to evaluate the models used in an available downscaling • Downscaling products, e.g. NARCCAP, Maurer, • Indiv variables?? • Link back to detailed/high level information at portals, e.g. PCMDI Narrative, summary, visualizations • Narrative, summary, visualizations • Turbotax– alternate/additional way to provide translational information • Series of questions that leads thru what to consider for a particular kind of applications – build on the other translational information • Publication in an ecological journal Translational Information -- overview

3. Top level info: emissions scenario (s), GCM(s), RCM(s), • who produced it, and portals available from (data formats) • spatial resolution & extent (e.g. SE or N.Am); temporal resolution, time period covered, & continuous/time slice • run #(s) downscaled, method (stat vs. dynamical, bias correction • historic climatology used, regridding/reprojected, • probabilistic vs. individual #s, stochastic vs. deterministic approach • Pointer to portal (s), or original dataset • Might include maps or other visual/graphic info • What are the top 10 or 15 evaluation to characterize a dataset? – different for dynamic vs statistical • Model sensitivity, “equilibrium climate sensitivity” • Measure/index of stationarity • RMSE, mean absolute error, mean abs. difference • Root mean square error/index of agreement (Wilmot)– not as widely known, so might be in against an observational dataset. • Map the bias per grid cellor other appropriate area/region • How well different processes are represented (may also be narrative) • relative performance, like the energy efficiency slider bars – could do this for ECS • **Need evaluation for geographic area, user-oriented regions • (if not user-defined regions) *** Nutrition label

4. “Biography” of GCM/RCM/ESMs and downscaling product • More info and detail than in the nutrition label • Description, including what purpose it was developed for, • how its being used • By agencies for planning/regulatory purposes • By ecologists for kinds of studies • Experiential information on use • Narrative of evaluation, summaries/excerpts from published evaluations, e.g for a region (even if not available for all regions) • Citations/links to key work on the product • Visualizations (slider scale, scatterplot) of how the GCM falls in the context • Link to video/audio, presentation from a meeting or developed for this page • Glossary • Definitions, significance, distinctions (e.g. how are ESMs different from AOGCM, not just definitions of each) • Draw on & point to existing glossaries (AMS glossary, USFS FAQ) • Strengths/weaknesses, advantages/disadvantages of downscaling techniques • Comparisons & context eg: CMIP3 vs CMIP5 what’s new, different, significant for ecological context; How statistiscal & dynamical DS are evaluated differently Translational information: Narratives

5. Extension agents & Connect to extension groups • Assn of Natural Resource Extension Professionals (meeting next summer), Climate Science Initiative • NOAA/NWS Climate Coordinators & Climate services focal points • Train the trainer strategy • Discussion about balance between summary stats and detailed data. • Make it easy for advanced, intermediate, & novice users to get to the right level; learning at every level • Alternate evaluations: evaluation by users – e.g. Yelp-type eval by users • Expert opinion evaluation by climate scientists – rate on a scale?? • Upgrade/democratize the technology used -- ability to code/tag models for processes, “product” comparisons. Interface (compare products) for given user, etc. • How to deal with user-defined regions ?? Options, both may be needed for different uses: • GUI, e.g. put in your shapefile and GUI gives relevant skill, evaluation • Script file, easy to revise choices • TurboTax as an alternate/addition to nutrition label—maybe better way to manage this amount of information. • Answer to first question directs you to subsequent questions Other discussion

6. Product: Article • Choosing better practices, avoiding bad practices • “Translate” from many best practices documents intended for climate science community to the ecological community + other • IPCC tables, CLIVAR to be more useful / have ecological relevance • Illustrate with a few case studies • Submit to an ecological journal, e.gFrontiers in Ecology and Evolution • Use this as the peer- reviBased on peer-reviewed journal, related summaries, short pieces in other publications, posters/talks at professional society meeting,

7. What’s the goal??? • Description to help make choices, interpret existing products • Support learning about the products, & support thoughtful, informed use • Raise the level of conversations btw ecologists and climate scientists – does **not** replace, but facilitates those conversations, • Link to other sources of info for more detail, & also to guide people to other efforts • Nutrition labels in tiered levels, crosslinked • “ingredients” vs “processed food” – need info on both • SRES/RCP emissions scenarios • GCM/RCM/ESMs • Many groups do their own statistical downscaling want to decide which GCMs to use, or to evaluate the models used in an available downscaling • Downscaling products, e.g. NARCCAP, Maurer, • Indiv variables?? • Link back to detailed/high level information at portals, e.g. PCMDI Narrative, summary, visualizations • Narrative, summary, visualizations • Turbotax– alternate/additional way to provide translational information • Series of questions that leads thru what to consider for a particular kind of applications – build on the other translational information • Publication in an ecological journal Translational Information -- overview

9. Types of Translational Information Applications Global Regional Local Basic Data Digital Information Indices Downscaled GIS Formats Seasonality Assessments IPCC NCA Local Narratives What has happened? What will happen? What are the impacts? Guidance Judgment Model Output Fact Sheets Summaries Images Figures Observations Quality Assessment Homogeneity Uncertainty Descriptions Risk Assessments

10. Can we create a “nutrition label” for downscaled data? Product: Downscaled Temperature (min) Data Frequency: Daily Data Coverage: 1950-2100 What measure(s) of “skill” to use? Extremes ? Accumulated values? Stationarity? What are the top 10 or 15 evaluation to characterize a dataset? Would it be nationwide? Regional? Or tailored to a location?

12. What’s appropriate trend measurement, variance / confidence? • What ‘ensemble’ or models to use? • Some variables or metrics of interest ‘unpopular’ (e.g. wind)