1

NC-CSC Science Workshop 2013

NC-CSC pilot: Delivering

climate projections on regional scales

to support adaptation planning

Andrea J. Ray, Ph.D., NOAA Earth System Research LabThanks to: Amy Symstad, Dominique Bachelet, P. Shafroth, L Perry, Max Post van der Burg, R. Sojda, Brant Liebmann, Joe Barsugli, Bob

Means, Jeffrey T. Morisette, Dennis Ojima

Joint Pilot withNorth Central Climate Science Center

Overarching goal • To explore together the “best available climate information” to support key land

management questions and how to provide that information. • To develop a deliberate, ongoing interaction to prototype how NCPP will work

with CSCs to develop and deliver needed climate information products. • Build capacity in the NC CSC by providing NCPP’s translational information for

climate data used as input to USGS‐based ecological modeling• 4 projects funded summer 2012. Will discuss two:

– Riparian Corridors– Grasslands & Forests– Plains & Prairie Potholes– Sage Grouse

• Wyoming Basin REA• Discussions with other LCC, CSCs, NOAA Fisheries, etc

APPROACH: How are they currently using climate projections and what choices have they made? what evaluation and comparisons are the ecologists interested in, what do we think they should be interested in?

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Indices from the Ecology literatureBioClim Indices• Annual Mean Temperature/Annual Precipitation• Mean Diurnal Range (Mean of monthly (max temp - min temp))• Isothermality (BIO2/BIO7) (* 100)• Temperature Seasonality (standard deviation *100)• Max Temperature of Warmest Month• Min Temperature of Coldest Month• Temperature Annual Range (BIO5-BIO6)• Mean Temperature of Wettest Quarter/ Driest Quarter• Mean Temperature of Warmest Quarter/Coldest Quarter• Precipitation of Wettest Month/Driest Month• Precipitation Seasonality (Coefficient of Variation)• Precipitation of Wettest Quarter/Precipitation of Driest Quarter• Precipitation of Warmest Quarter/Coldest QuarterOthers: • Humidity• Growing degree days, Chilling & forcing units• Annual dryness index: (DD5)0.5/Mean Annual Ppt• Palmer Drought Index, Std Precip Index (SPI)• Ratio of growing season ppt to mean annual ppt• Stream temperature e.g. July avg temp for trout

Regional Climate FuturesChallenge #1 – RCM historical climate may be too wet to use as is

Interpolation of met. data

RegCM3 – Northern R.M. tile

From A. Symstad, USGS/Wind Cave, & D. Bachelet

Regional Climate FuturesChallenge #3 – boundary conditions cause edge effects

From A. Symstad, USGS/Wind Cave, & D. Bachelet

Regional Climate FuturesChallenge #2 – not all RCM tiles are equal

The five RegCM3 model domains: Pacific Northwest (PNW), Pacific Southwest (PSW), Northern Rocky Mountains (NRM), Southern Rocky Mountains (SRM), and Eastern North America (ENA).

PACIFIC SOUTHWEST TILE

SOUTHERN ROCKIES TILE

From A. Symstad, USGS/Wind Cave & D. Bachelet

PACIFIC SOUTHWEST TILE SOUTHERN ROCKIES TILE

Precipitation Precipitation

Temperature Temperature

From A. Symstad, USGS/Wind Cave & D. Bachelet

0.0 1.0 2.0 3.0 4.0 5.0-25-20-15-10

-505

10152025

Other 109 GCM runsECHAM5 A2 Runs 2 & 3

Change in annual temperature, deg C

% C

hang

e in

ann

ual p

reci

pita

tion

Projected annual temperature and precipitation change

Colorado Plateau REA region 112 downscaled runs from Maurer et al.

ECHAM in pink

• A strength of dynamical downscaling is in the regional processes represented

• A “con” is that its computationally expensive, so few models and runs are downscaled

• Hostetler (USGS) downscaled one run each from ECHAM and GFDL

• Solution? At least look at the model runs in the context of many models

• Know – how does the GCM run selected compare- warmer/cooler/drier

Concerns with few model runs dynamically downscaled

Difference between 1968-99 climatology and 2015-30 (top) and 2045-2060 (lower)

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5-30-20-10

0102030

Other 109 GCM runs

Change in annual temperature, deg C

% C

hang

e in

ann

ual p

reci

pita

tion

• From Daniels, FAQs, “Figure 5—Scatterplot of change in annual average temperature (°C) and precipitation (%) projected by different GCMs for the 2040s (2030-2059) in the Upper Missouri River Basin. Triangles represent GCM simulations of the B1 emissions scenario; circles = A1B; and squares = A2. Large bold symbols represent multi-model averages for each emissions scenario (source: Littell and other 2011).”

Concerns with few model runs downscaled

Basic & Evaluating; WWA/RISA

“Time series”

• Ecologists say that the sequence of years is important for many systems & interest in runs of wet/dry years

• Neither ensemble means or simply selecting one or a few runs is a good choice

• Poor choice to use just one model run from one GCM – GCM’s aren’t intended as “predictions” of a sequence, but intended to generate a new “climatology”

• false sense of “reality” from only one or a few model runs

• Solution???? We’re working on it….

The model chosen matters… often arbitrary

• Regional studies may select GCMs based on some evaluation of how the represent

• However…often “arbitrary” choices of models*** e.g. b/c a colleague has used it, or another

• Issue: ***

• Solution???? They’re not wrong…different representations of future; KNOW which you’re picking – could intentionally pick different climates.

APPROACH: How are they currently using climate projections and what choices have they made? what evaluation and comparisons are the ecologists interested in, what do we think they should be interested in?

• Downscale to very fine resolution, 1km – tempting b/c a lot of ecological variation/observations are at this scale -- but is the fine scale actually adding value? Meaningful?

• Bioclim indices – widely used, but do the 30 year averages “wash out” extremes and variability that’s an important feature driving the ecology?? • Are there better indices?

• Potential pitfalls for comparing studies based on one set of GCMs downscaled to studies based on another set

Many different downscaling projects use different GCMs, often not easily comparted

Hostetler, Rehfeldt, Mauerer, MACA/Abatzoglu/JohnA, Stamm etc and with models downscaled –

Initial solution: look at the data, see how they compare to a common downscaling or each other (As with observations)

Dynamic processes

storm tracks, high pressure/blocking, great plains low level jet, etc

Some observations

My list: climate science guidance & translational info1) “Downscaling,” how low can you go? What meaningful information at different

resolutions down, what’s meaningful at 1km?• Scales appropriate to regions and phenomena – and how to communicate the limits of

downscaling • Temperature broader scale, so likely represented better at 4-12-15km– climatology/statistics• PPT varies more spatially, but statistics might be OK at those scales, and no better represented

at small downscaling• How do different downscaling products compare??? Maurer-Hostetler-NARCCAP

2) “Time series,” sequencing of years -- many ecological questions sensitive to sequence

3) “Decadal” outlook: what’s more/less likely over in 10-20-30 years, given natural variability and trend (vs just trend)• How to take advantage of new CMIP5 decadal runs, statistical methods (LIM), etc• Triangulate among methods?• Are we passing thresholds?

4) ET/PET & drought indicators – and projections of these• Improving PET/ET in MCI ecological model• Need soil moisture/dryness for vegetation type/structure/succession, fire, transition, invasives

• Multi-year problem Katherine discussed

5) Seasonal-interannual outlooks – for management actions in the next seasons & year or two – and how might these change in the future. Many applications, likely builds capacity for adaptation, but has been a bit “left behind” in CC interest

Challenge: Comparing results from different GCMs & their downscaling

• Many ecological and hydrological studies published – the basis for land & ecosystem management plans, REAs• Need to know

• Each have made choices, sometimes arbitrary -- but how to compare results• WY REA, for example wants to use Rehfeldt, but he downscaled different GCMs from

Hostetler, which they’re required to consider• Solution?

• We’re comparing Hostetler & Rehfeldt downscaling for particular variables, comparing both to Maurer

• If the variables themselves have differences, e.g. warmer/cooler/drier, we’ll have documented the source

Climate projections & gridded observational data are widely available from multiple sites -- need overall guidance, vs from each data provider However, little consistent information on evaluations, guidance on

use, or “translational information” Many different downscaling projects use different GCMs, often not easily

comparted With Hostetler, Rehfeldt, Mauerer, MACA/Abatzoglu/JohnA, Stamm etc and

with models downscaled – see TABLE How to handle tis? Downscale to very fine resolution, 1km – but is the fine scale

actually adding value? Meaningful? Bioclim indices – widely used, but do the 30 year averages “wash

out” extremes and variability that’s an important feature in the How to put the climate info in context relevant for the managers?

Give them the same critical eye as ecological data you use – PLOT & explore the data just as you would biological data {GRAPHIC from daymet and from Laura

Climate scientists need to do a better job of explaining what different products should and shouldn’t be used for. Results of objective & quantitative evaluation Narratives, which may include qualitative and quantitative aspects of

data use; e.g., expert guidance on the suitability of the data for an application; also narratives that provide summary information of how the climate has changed or how it will change

Guidance on appropriate uses & interpretation Characterize & interpret uncertainty

General observations across the projects

Next steps??

• Many ecological and hydrological studies published – the basis for work like REAs• Each have made choices, sometimes arbitrary -- but how to compare results• WY REA, for example wants to use Rehfeldt, but he downscaled different GCMs from

Hostetler, which they’re required to consider• We’re comparing Hostetler & Rehfeldt downscaling for particular variables• If the variables themselves have differences, e.g. warmer/cooler/drier, we’ll have

documented the source

• Many sources of climate data, but most don’t provide guidance or translational info

Climate projections & gridded observational data are widely available from multiple sites However, little consistent information on evaluations, guidance on use, or “translational

information” Give them the same critical eye as ecological data you use – PLOT & explore the

data just as you would biological data {GRAPHIC from daymet and from Laura} Climate scientists need to do a better job of explaining what different products

should and shouldn’t be used for. Results of objective & quantitative evaluation Narratives, which may include qualitative and quantitative aspects of data use; e.g.,

expert guidance on the suitability of the data for an application; also narratives that provide summary information of how the climate has changed or how it will change

Guidance on appropriate uses & interpretation Characterize & interpret uncertainty

“Time series” data into the future, using the projections as “predictions” The sequence of events matters for a lot of ecological studies -- Neither ensemble means

or simply selecting one or a few runs is a good choice GRAPHIC

Hostetler/USGS Dynamical Downscaling – being used a lot in ecological studies how do the 3 GCM selected runs compare {GRAPHIC} Consider this for any GCMS your project is using Comparing results among available analysis projects

“situate” one or more models in the context of others (Lukas’ Mauer plots)

General questions/needs across the projects

Challenge: Comparing results from different GCMs & their downscaling

• Many ecological and hydrological studies published – the basis for work like REAs• Each have made choices, sometimes arbitrary -- but how to compare climate results to

inform ecological questions?• WY REA, for example wants to use Rehfeldt, but he downscaled different GCMs from

Hostetler, which they’re required to consider• Solution?

• We’re comparing Hostetler & Rehfeldt downscaling for particular variables – and comparing both to Maurer

• If the variables themselves have differences, e.g. warmer/cooler/drier, we’ll have documented the source

• Another solution: Consider products that have been used/evaluated in many projects• Statistical products:

“Maurer” – the basis for the Reclamation “SECURE Water Act” report,and extensively analyzed – IMHO the gold standard for now – downscaled many GCMS and ensemble members/GCM; has been run thru a hydrologic model, so available for hydroclimate variables; already being used in DOI policy & planning. Available from several portals, with visualization tools Climate Wizard, GeoDataPortal

Other options: Hayhoe’s downscaling to stations & other products, used in the National Climate Assessment; WorldClim – widely used, less evaluated

• Dynamical products covering North America NARCCAP, North American Regional Climate Change Assessment Program,

http://www.narccap.ucar.edu. IMHO the gold standard for now – 6 GCMs and multiple RCMs; used in the 2013 National Climate Assessment

Other options: Hostetler, aka “USGS Dynamical downscaling,” http://pubs.usgs.gov/of/2011/1238/; http://regclim.coas.oregonstate.edu; caveat: only 3 GCMs, 1RCM; BLM requiring its use in REAs*

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Climate Predictions Applications Workshop24 April 2013Logan, UT

Delivering climate

projections on regional scales

to support adaptation planning: ESRL/PSD activities

Andrea J. Ray, Ph.D., Jeffrey T. Morisette, Dennis Ojima

NOAA Earth System Research Lab, NC-CSC, CSU.

Thanks to: Amy Symstad, Donimique Bachelet, P. Shafroth, L Perry, Max Post Van der Berg, Brant Liebmann, Joe Barsugli, Jeff Morisette, Dennis

Ojima

EXTRAS

“Tiles”

• Ecologists • Edge effects• Solution????

Ecological Response

Models

DOI Management Objectives/Goals

• Climate data based on results of objective, quantitative evaluation

• Document challenges and decisions made in determining apppropriate information to use

• Develop translational information based on iteration with NC-CSC

Proposals are publicly available at: http://www.doi.gov/csc/northcentral/NCPP-Pilot-Project.cfm 23

• Precip run-off (PRMS)• Phenology (UniForc)• Seed recruitment (HEC EFM)‐• Landscape level (MC-1)• Habitat Niche modeling

• Adaptive management• Structure decision

making & value of information

Joint Pilot Climate and Ecological Integrated Modeling

242424

Grasslands & forests (Symstad, Bachelet, )• Much of the NGP is uncultivated, habitat for grassland specialists.• Woody encroachment is a serious issue on the edges of the region.• CO2 fertilization may make region more conducive to tree growth, especially in absence of

fire.• Climate projection issues

• availability and reliability of full time series• bias correction methods• RCM “tile” “inconsistencies”• PET calculation

• Downscaling RegCM3 output for Northern Great Plains area (Hostetler)• Comparisons of values for tile overlap areas

• Cottonwood and willow seed dispersal typically occurs during or just after snowmelt peak flows

• What are the chances that seeds will land on bare, moist surfaces along rivers - created by floods, and exposed by flood recession

Seed dispersal during or just after the spring flood =• exposed, bare, moist soil in the recruitment

band• Too high: dessicate• Too low, scoured away• “just right”

Base flow

Recruitment band

Too high – drought stress

Too low – ice and flood scour

Receding spring flood

Connecting the science to ecology/landscape in a meaningful and scientifically defensible way

• Key issues– Observational data: how to best use in situ data? – What can we say about precipitation?– How do we account for elevation ranges– Be explicit about what we’re confident about, and

unresolved issues

• Overall objective is to develop “Reasonably Foreseeable Climate Scenarios” (RFCS), based on analysis and comparison among several climate projection datasets and to compare the RFCS to the historic period for the region

• Goals:– Relate to conservation elements– Shifts vegetation classes, e.g. from semi-

desert shrub steppe to shrublands?– Assess Key Ecological Attributes

WY Basin REA

Fort Collins, ColoradoMarch 7, 2013EPA logo

Down-scaled climate data in current conditions

“DRAFT”

• Ecologists • Edge effects• Solution????

Basic & applied climate science: often at the “technical interface” between researchers and problems faced by managers

• Evaluating climate models – how well climate features are simulated & confidence e.g. seasonal snowpack, hydrology, storm tracks, changes in extremes

• Climate diagnostics: provide an explanation of evolving conditions, e.g. seasonal anomalies, heat waves, Hurricane Sandy, Texas drought, Missouri river flooding; Assess predictability

• “Use-inspired science”: Climate & Fisheries; Arctic Impacts Assessment; drought; Partners: NC-CSC, NMFS, FWS,NIDIS, universities, WWA/RISA, TNC

• Guidance & climate analysis: Sage brush/sage grouse, prairie potholes, grasslands; Wyoming Basin Rapid Ecoregional Assessment. BLM, NC-CSC, TNC

• Hydroclimate studies: climate & water management; projections of climate change on river flows/water supply, partners: Reclamation, Army Corps, Western Utility Climate Alliance; WWA/RISA

• Emerging topics: dust on snow; decadal predictionsSynthesis & Assessment: of existing science & often new analysis to inform specific policy & decisionmaking processes

• 2012 National Assessments for several regions/topics & 2009 CCSP

synthesis documents (SAPs) – as authors, contributors, reviewers• FWS Status review of the American pika, Ochotona sp, 2010• Climate change in Colorado to support Water Management,

2008• “Appendix U” hydroclimate science for the DOI EIS for Colorado River “Interim Guidelines” 2007

NOAA/PSD Climate Science in the Intermountain West

North Central Regional Example• What NOAA capabilities were applied?

– Evaluate &provide guidance on “best practices” on model use and downscaling approaches

– Efforts to translate & contextualize the climate information for various DOI & LCC decision contexts

– Builds on NOAA and NOAA-funded research at labs and universities; RISA experience on understanding climate needs

– The USGS Geodata portal is an NCPP partner

• Address common ground with the LCC mission by – Leverage resources and strategically target science to inform conservation

actions, in particular by supporting vulnerability assessment for climate change

– Three projects have landscape level focus risk framework, each directed at management goals identified by DOI and several LCC partners; 4th project assesses the value of climate information for supporting management decisions within the Plains and Prairie Potholes LCC

North Central Pilot Project with NOAA’s National Climate Projection program

Woody Encroachment, Riparian Corridors

Sage Brush/Sage Grouse

Plains & Prairie Potholes

Hadley Cells

• George Hadley, 1700s• Simple Theory Explains

– N-S movement of air near equator– Trade winds blow from NE/SE– Deserts at 30 N/S Latitude– Areas of heavy rain at Equator– Location of “Subtropical Jet”

• Note: major UK Modeling Center named after Hadley

• Hadley Cell projected to intensify and expand northward

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Joint Pilot Projects have landscape level focus, risk framework, directed at identified management goals of DOI & LCC partners:

• Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests (Shafroth et al., USGS Fort Collins Science Center)

• Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability: A collaboration for Greater Sage- Grouse and their habitats (Sojda et al., ‐USGS Northern Rockies Science Center)

• Grasslands & Forests: Projecting Future Effects of Land Management, Natural Disturbance, and CO2 on Woody Encroachment in the Northern Great Plains in a Changing Climate (Symstad et al., USGS Northern Prairie Wildlife Research Center & Oregon State )

• Assess the value of climate information for supporting management decisions within the Plains and Prairie Potholes LCC (Post van der Burg et al., USGS Northern Prairie Wildlife Research Center & Fort Collins Science Ctr.)

Scale – temporal and spatial

• Downscale to very fine resolution, 1km – but is the fine scale actually adding value? Meaningful?

• Bioclim indices – widely used, but do the 30 year averages “wash out” extremes and variability that’s an important feature in the

• Climate often used “uncritically”

• Table with hostetler, rehfeldt, mauerer, MACA/Abatzoglu,Stamm etc and whith models downscaled

Ecologist’s questions