NOAA Rapid-Response Climate Assessment to Inform the FWS Status Review of the American Pika
Andrea J. Ray1,2, Joseph J. Barsugli 2, Klaus E. Wolter2, Jon K. Eischeid 2
NOAA Earth System Research Lab, Boulder, CO 1; NOAA-University of Colorado Cooperative Institute for Research in Environmental Sciences2, Download report from: http://www.esrl.noaa.gov/psd/news/
3. The Toolkit
Introduction
In 2009, the Fish and Wildlive Service asked us to assess and synthezise the “best available science” to inform their decision on
whether to move forward in a listing process for the American pika, this poster is an overview of the report and some new results
Context for the report:
• Rapid assessment w/in FWS “12 month finding” time frame
• Steep learning curve for us about pika biology -- but a lot of effort to connect climate to
biology; Specific biological impacts were beyond the scope of the report
• Experience with hydroclimatology and water applications helped as an analogue
• Legal framework and terms: “foreseeable future,” “best available science,” time frame,
• Background on observations & climate models -- help FWS and readers to be able to think
about them in an informed way and work more effectively with climate scientists
• Extensive discussions & iterations with FWS & others -- but we didn’t know the ruling until
the release date -- we informed, iterated, answered questions.
Climate Context:
• U.S. West has warmed ~1°C (2°F) during the past 30 years -- about half attributed to CC
• Magnitudes of trends vary locally and with season: e.g., 1｡-2.4｡C warming (1.7｡-4.3｡F) for
areas in the Sierra Nevada and western Great Basin and in Oregon
5. Same downscaled projections: the seasonality and spread of the models
On the Climate side:
Annual
IPCC projections from 2007 4th Assessment, aka “CMIP-3” (right ) a
coordinated large set of climate model runs performed at modelcenters
worldwide using 22 global climate models. A 200-km grid is common -- limited
use for directly use to assess impacts on pika. (
right)
and subsequent statistical and dynamical downscaled datasets
20+ global climate models (GCMs), A 200-km grid is common –
limited use for directly use to assess impacts on pika.
Observations from NWS COOP, NRCS SNOTEL
Gridded observational dataset @ 4km: PRISM
Ongoing research
Analysis of recent trends
New climate divisions
Research analyzing the CMIP model runs, and using them to force other
models,e.g., hydroclimate, snow
Research on extremes in the projections; dynamical downscaling (e.g.
NARCCAP, WACCIA)
Recent published papers and assessments
E.g. Washington & California Climate Impacts Assessments
Recent literature on hydroclimatic changes forced by IPCC projections
Mostly by river basin, focussed on water supply, but with cross-over
Winter
Summer
Figure 8. Seasonality of Projections & Model spread
Figure 4: Temperature (°F) and Precipitation Changes over North America 2040–60
average, projections from 22 CMIP3 models, relative to the 1950–99 baseline
average. The top row is the multi-model average temperature change for the annual
mean (left), winter (center), and summer (right). For Colorado, e.g., the average
projected temperature changes are about 4°F (2.2°C) (annual), 3°F (1.7°C) (winter),
and 5°F (2.7°C) (summer). Data from CMIP3 multi-model archive, IPCC AR4 WG1,
2008. (From Ray et al. 2008)
On the biology side:
 Challenge to relate FWS location data to climate data sets - GIS, UTM
 Only a few sites with long term, consistent monitoring of pikas
Connection between pikas & climate not well documented…
some not published or in the review process
Pikas thought to be sensitive to changes in the mean summer temperature,
summer maximum temperatures, and to winter minimum temperatures when
combined with an absence of insulating snow cover
• Natural variability is and will continue to be a factor in the climate of the western U.S.
• Summer average temperatures where pikas currently live range from ~9°C (48°F) in the
Sierras to ~14°C (57°F) at Warner and Ruby Mountain sites (1950-1999 climatology)
• Scaling temperature for elevation ranges suggests that they experience temperatures of ~+/3°C (5.4°F) around this for a 1000m vertical range.
• Promote and move forward the dialogue with ecologists and ecosystem scientists interested
in climate; Document a report publically available when FWS finding released; MS in prep
for peer-reviewed pub
• Create a report that is accessible to non-experts interested in climate; climate literacy goal
Figure 5: With FWS, we selected 22 representative pika habitat areas to analyze,
which include all subbspecies
Climate Observation Challenge: Utah example (left, Figure 6)
• Few long-term, quality-controlled meteorological observations exist at pika locations, especially in
higher elevation habitat
• Climate averages and trends may be inferred from nearby observations, from large-scale climate
patterns, and by adjusting for elevation
• In the absence of detailed site-specific studies, gridded observational datasets (PRISM) are the best
source to infer the climate where pikas live. However, gridding should be thought of as a “ model”
of what happens between the observation sites. Resolution does not necessarily mean reliability!
• Consider what source data goes into the dataset? For the western US at high elevations … Does it
include SNOTEL data? And, how is the temperature and precipitation dependence on elevation
handled (see Daly, 2006 for one view)
Figure 1: Temperature projections for scenario
B1 start to diverge appreciably from A1B and A2
by the middle of the 21st century. A2 and A1B
diverge in the latter quarter of the century. (From
IPCC AR4 WGI, 2007, Figure TS.32).
“Forseeable Future”
• We were asked to provide an expert opinion on the foreseeable future
•The IPCC provides projections to 2100 and beyond, based on several emissions scenarios.
However, until ~2050, emissions scenarios result in a quantitatively similar range of projections
of global and regional temperature changes (Figure 1)
• WACCIA report (left) shows a similar story for the Pacific Northwest: considerable overlap in
the model projections for temperature & precipitation out to ~2050
Therefore, we suggested mid-century, around 2050, as a “foreseeable future” for climate for
Figure 2: Temperature projections for the Pacific Northwest,
the pika -- although we reported results out to 2100
similar to the IPCC plot above. Mean warming rates for the
21st century diverge in this region after 2020 (Mote &
Salathe, 2009, Figure 7).
2. Challenge: Connecting the science to biology in a meaningful and scientifically defensible way
Challenge to synthesize the available science and make sense
of some potentially conflicting results (e.g. temp and elevation)
Figure 6 Pika & climate observations.
4. Projections for the report
Framework for synthesizing climate projection information:
For the report, we generated:
• Emphasize mean summertime temperature, known climate stressor that
orrelates will with other stressors such as hot spells
• Statistically downscaled projections as westwide as maps (below) and
• More agreement among climate models on warming than on
precipitation changes
• Graphics and tables for 22 habitat areas for around 2025, 2050, and
2090 (actually 10- or 20- year avgs around the year indicated), see #s 5
and 6.
• Use simple downscaling from existing online dataset
(LLNL/Reclamation)
• Scaled to pika elevations (tables in panel 5& 6)
• Broad range of climate models sampled
• For 3 emissions scenarios, with focus on A1B, aka “middle”
• Report focussed on 2050 b/c of foreseeable future chosen
• Data available for entire range of pika habitat in the Western US
Key issues
Observational data: how to best use in situ data? Sparse
observations at elevation
–What can we say about precipitation?
• Determined need to adjust the data to reflect the PRISM
climatology
• Dynamically downscaled output used as a “ reality check” on the
temperature trends – are there any clear systematic differences in the
mountainous regions during summer?. Results only available for some
regions, not the entire West
–What about the literature that suggests accelerated
warming at higher elevations?
–How do we account for elevation ranges of habitat & scale
obs and projections at lower elevation to higher elevation?
local/regional/elevation scale
–Intercomparison issues: different time periods, spatial
scales, definitions of “spring,” what’s represented by “April
1st,” etc
• Beyond 2050, IPCC projections indicate continued global and regional warming into the second half of this
century; if emissions follow the higher scenarios (e.g. A2), warming in 2090 could be double that in 2050.
• Figure 9 shows the same projections for three emissions scenarios: If emissions follow the higher scenarios (e.g.
A2), warming in 2090 could be double that in 2050.
The synthesis: GCM data shows widespread summertime warming that is
reflected in the simple downscaling. The range shown in the GCMs and
simple downscaling is not contradicted by any systematic findings of the
dynamical downscaling results.
Report Conclusions
• GCMs project larger summer warming over the
western U.S. than elsewhere North Am, +5°C in
summer and +3°C in winter for the mid 21st
century Statistically downscaling these broad
patterns, statistical we find a pattern of ~+3°C for
22 representative pika habitats
• But there is a range of projections from individual
GCMs, with low-end model projections ~1°C
cooler and high-end ~1°C warmer than the
ensemble average
• Due to the impacts of temperature increase,
projections show a precipitous decline in lowerelevation snowpack (below 8200 ft) by ~2050,
with more modest declines at elevations above
8200 ft where some pika populations live.
• We provided projections westwide (maps) and
for 22 areas for around 2025, 2050, and 2090
for 3 emissions scenarios, & scaled to pika
elevations (graphics, tables)
6. The big picture and beyond the report to 2100
Below are the projections by area for 2080-2100. The GCM projections are the drivers for quantitative regional
projections. The large-scale warming seen in the GCMs and the agreement among GCMs builds confidence. This is
particularly relevant for pika because high temperature is a known stressor.
Because large-scale atmospheric temperatures are a good predictor for temperature trends in exposed areas of the
high mountains, particularly for daytime summer temperatures, free-atmosphere lapse rates were used to make
additional adjustments
Simple downscaling methods do not add any new information on climate processes, but help to relate the GCM
changes to a high-resolution climatology.
Regional climate models add climate processes as a finer scale, but still not at “pika” scales. They may be useful to
address a specific hypothesis. More comprehensive archive of regional climate projections are just coming online.
Comparing to the table above, note that in 2050, emissions not a big factor, there is not a large difference between
the low modeland high model, whereas the difference are substantial by 2090.
Figure 3a-b. Relationship of temperature and pika sites and implications, from the
report, figures 3 & 24..
Importance of Elevation
–Scientifically defensible projections at pika-relevant scales: Elevation is one of the most important determinants of temperature in mountainous
Spatial, temporal
terrain. Figure 3a shows elevation, temperature, and pika sites. PRISM dataset
temperatures used to compute the historical mean and percentiles represent the
–What’s the “foreseeable future”
average over an area roughly 3x4km, but at the elevation of the gridbox center,
whereas pikas live at a variety of elevations in a representative point or mountain
range. Therefore, when interpreting the temperature value for a grid box, consider
• Little “off the shelf” science -that a range of temperatures are represented by the single value, with lower
–Many potentially relevant studies aren’t at the appropriate elevations pika sites likely experiencing warmer temperatures.
–Ditto downscaled model projections, statistical or
dynamical
• Projected precipitation trends small compared to the variability.
Figure 8. Comparison of scenarios
• Spring has warmed more than other seasons in most of the Wes, and is 2-3 weeks earlier in
some places; snowpack is melting out earlier
NOAA Goals beyond informing FWS decision: Another experiment in “climate services”
• Crater Lake, OR, as an example: Summers warm more than winter; Average summer temperatures similar to
the hottest months in the past fifty years (Figure 8).
Elevation and temperaturee are related by lapse rate, T1 = T0– (z1 – z0)*L
where T0 and z0 are temperature and elevation of the gridcell or observation, T1
and z1 are the elevation of the minimum (or maximum) elevations in the range
given; L is the estimated lapse rate. This is good approximation of surface
conditions during the summer. A Standard Atmosphere temperature lapse rate of
6.5 C/km is used for this example. Note 14°C = 57°F, 2500m = 8200ft.
Westwide projections, 4-km statistical
downscaling (Figure 7)
By 2050 the projected changes in summer (JJA)
climate can be visualized as a shift of temperature
zones northward & upward in elevation
This shift of temperature zones continues through
the end of the 21st century
The projected changes, especially in summer, are
large compared to present-day climate variations
Next Steps: What variables are needed
-- a major limitation was the understanding of the links
between pikas and climate across the west and across subspecies.
–What temperature variable, e.g., # days above/below threshold temperature
–What else can we “coax out” from existing observations and projections
• Will take some effort to get from the 200-km daily model output to a reasonable daily dataset.
Due to the impacts of temperature increase, projections (Figure 3b) show a
precipitous decline in lower-elevation snowpack (below 8200 ft/2500 m) by the
mid-21st century and more modest declines at elevations above 8200 ft where
some pika populations live.
Figure 7. Westwide maps.
This report by the NOAA Earth System Research Lab was partially funded byt the Fish and Wildlife Service. To download the full report, see:
http://www.esrl.noaa.gov/psd/news/
–To design those analyses we need a better understanding – or at least clearer hypotheses – of what are
the critical environmental variables are connecting pikas and climate
–“Case studies” of extirpations -- could do attribution studies
–“critical habitat elements” wrt temperature, ppt