Understanding the sensitivity of Understanding the sensitivity of WA snowpacks to climate changeWA snowpacks to climate change

By: Ben LivnehBy: Ben Livneh

Joe Casola and Dennis LettenmaierJoe Casola and Dennis LettenmaierSource www.wta.orgSource www.wta.org

OverviewOverview

• Motivation and scopeMotivation and scope

• What has been done What has been done so far…so far…

• Current workCurrent work

• Implications on future Implications on future snowpack / future snowpack / future work…work…

MotivationMotivation• Snowpacks have been projected to Snowpacks have been projected to

decline as temperature warms; decline as temperature warms; • Snow acts as a natural reservoir/buffer, Snow acts as a natural reservoir/buffer,

to redistribute winter precipitation later to redistribute winter precipitation later into spring and summer when it is into spring and summer when it is needed, important for water-supply, needed, important for water-supply, wildlife, etc…wildlife, etc…

• Quantifying storage is critical for water Quantifying storage is critical for water managers, allocating man-made reservoir managers, allocating man-made reservoir capacity if needed…capacity if needed…

Source Source www.waterencyclopedia.comwww.waterencyclopedia.comSourceSource

www.wunderground.comwww.wunderground.com

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*Uncertainties exist in *Uncertainties exist in future temperatures / future temperatures / snowpacks;snowpacks;

Question:Question:

How sensitive are How sensitive are WA snowpacks to WA snowpacks to temperature temperature change?change?

Seasonal ReservoirSeasonal Reservoir Man-made ReservoirMan-made Reservoir

Scope & MethodsScope & Methods• Estimate snowpack sensitivity to temperature Estimate snowpack sensitivity to temperature

change:change:

1.1. 3 methods employed by *Casola et al (~2008):3 methods employed by *Casola et al (~2008):

-Geometric approach-Geometric approach

-Regression analysis-Regression analysis

-SNOTEL observations-SNOTEL observations

2.2. Present work using coupled and offline large-Present work using coupled and offline large-scale atmospheric models (GCM) and land scale atmospheric models (GCM) and land models (LSM).models (LSM).

*Casola J., L. Cuo, B. Livneh, D.P. Lettenmaier, M. Stoelinga , P. Mote, *Casola J., L. Cuo, B. Livneh, D.P. Lettenmaier, M. Stoelinga , P. Mote, and J.M. Wallace. and J.M. Wallace. “Assessing the Impacts of Global Warming on “Assessing the Impacts of Global Warming on Snowpack in the Washington Cascades”Snowpack in the Washington Cascades”. Journal of Climate; . Journal of Climate; in in presspress

Sensitivity AnalysisSensitivity Analysis

• SWE affected by SWE affected by both changes in both changes in temp. and precip. temp. and precip. Focus on temp. Focus on temp. changes:changes:SWE = (T)

λ = sensitivity

Q: How much snow water equivalent Q: How much snow water equivalent (SWE) reduction will be caused by 1(SWE) reduction will be caused by 1° C ° C warming?warming?

DomainDomain

Geometric ApproachGeometric ApproachEle

vati

on

(m

)

=23% mean Apr 1 SWE lost for +1°C

warming

Snow storage Volume (S(z) x A(z))

Variation of SWE with heightVariation of SWE with height Hypsometric distribution of land area with Hypsometric distribution of land area with heightheight

Simply shifting Simply shifting the snow-line the snow-line upwards in upwards in response to response to warming causes warming causes loss in SWE…loss in SWE…

Regression ApproachRegression Approach

• Using April 1 SWE measurements at 24 snow courses in the Cascades for 1970-2006, The basin-integrated SWE is regressed upon winter temperature

SNOTEL ApproachSNOTEL Approach

~ 20% April1 SWE/°C

RAINSNOW

Ollalie MeadowsElev. 1128m

1. Casola et al. findings1. Casola et al. findings

2. Sensitivity using a coupled 2. Sensitivity using a coupled and uncoupled Atmospheric-and uncoupled Atmospheric-Land ModelLand Model• Atmospheric models (general circulation models – GCMs) use Atmospheric models (general circulation models – GCMs) use

a land scheme to predict moisture fluxes, partition radiation, a land scheme to predict moisture fluxes, partition radiation, snow, etc.snow, etc.

• The Noah land surface model (LSM) is the land scheme for The Noah land surface model (LSM) is the land scheme for the atmospheric model (MM5-ECHAM-5) used here.the atmospheric model (MM5-ECHAM-5) used here.

• Major issue is to establish climate baseline (current Major issue is to establish climate baseline (current climate) for sensitivity testing, to make future climate) for sensitivity testing, to make future predictions…predictions…

• Problem: the GCM used (MM5-ECHAM-5), has an older version Problem: the GCM used (MM5-ECHAM-5), has an older version of Noah LSM snow model (ver. 2.0), with generally poor of Noah LSM snow model (ver. 2.0), with generally poor snowpack physics producing low biased SWE estimates snowpack physics producing low biased SWE estimates (compared with obs.).(compared with obs.).

Old snow model Old snow model Noah 2.0Noah 2.0

ObservationsObservationsNew snow model New snow model Noah 2.8Noah 2.8

Improvments: Improvments: Melt water refreezeMelt water refreeze

More realistic solar More realistic solar radiation absorptionradiation absorption

SNOTEL, WASNOTEL, WA SNOTEL, CASNOTEL, CA

Coupled Model Approach…Coupled Model Approach…• First: Attempt to isolate snow sensitivity to temperature change, given potential bias sources:First: Attempt to isolate snow sensitivity to temperature change, given potential bias sources:

i. Biased snow model;i. Biased snow model;

ii. Biases in atmospheric simulation.ii. Biases in atmospheric simulation.

• MethodMethod::

Remove land model, Noah 2.0, from the coupled mode and run it separtely (offline) to make Remove land model, Noah 2.0, from the coupled mode and run it separtely (offline) to make snow simulations, and do the same with the improved land model, Noah 2.8 to test snow snow simulations, and do the same with the improved land model, Noah 2.8 to test snow model bias; both under the following conditions:model bias; both under the following conditions:

(1) Using spatially gridded *observations (Tmax, Tmin., Precip, Wind) for the 1990s;(1) Using spatially gridded *observations (Tmax, Tmin., Precip, Wind) for the 1990s;

(2) Using the extracted GCM forcings (Tmax, Tmin., Precip, Wind) for the 1990s; (2) Using the extracted GCM forcings (Tmax, Tmin., Precip, Wind) for the 1990s;

(3) Shifting observed temperatures to equal GCM temperatures for the 1990s;(3) Shifting observed temperatures to equal GCM temperatures for the 1990s;

(4) Manually increase the observed forcing temperatures (warming scenario), and (4) Manually increase the observed forcing temperatures (warming scenario), and

(5) Run with increased GCM temperatures (warming scenario for the 2020s).(5) Run with increased GCM temperatures (warming scenario for the 2020s).

• Compare these results with the coupled model SWE output:Compare these results with the coupled model SWE output:

(6) the 1990s; and(6) the 1990s; and

(7) the 2020s.(7) the 2020s.

*Maurer, E.P., A.W. Wood, J.C. Adam, D.P. Lettenmaier, and B. Nijssen, 2002, *Maurer, E.P., A.W. Wood, J.C. Adam, D.P. Lettenmaier, and B. Nijssen, 2002, A Long-Term Hydrologically-A Long-Term Hydrologically-Based Data Set of Land Surface Fluxes and States for the Conterminous United StatesBased Data Set of Land Surface Fluxes and States for the Conterminous United States , , J. Climate J. Climate 15, 15, 3237-3251 3237-3251

All simulations at spatial resolution: 1/8All simulations at spatial resolution: 1/8° ° ≈ 12 ≈ 12 kmkmBaselineBaseline

Noah 2.0

Noah 2.8

Δ: Noah 2.8 – Noah 2.0

Seasonal Snow water storage

April 1 SWEApril 1 SWE

Monthly snow Monthly snow storage volume:storage volume:

∫∫SWE(A)SWE(A)··A dAA dA

Mean temperature (Nov-Mean temperature (Nov-Mar):Mar):

~ 1~ 1° C° C

(1) Observed Forcing (1) Observed Forcing 1990s1990s

0

10

20

30

40

50

60

70

Nov Dec Jan Feb Mar Apr May Jun Jul

Sn

ow

Wat

er S

tora

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(km

**3

/ WA

) Noah 2.8

Noah 2.0

Noah 2.0

Noah 2.8

Δ: Noah 2.8 – Noah 2.0

Seasonal Snow water storage

0

10

20

30

40

50

60

70

Nov Dec Jan Feb Mar Apr May Jun Jul

Sn

ow

Wat

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(km

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) Noah 2.8

Noah 2.0

Mean temperature (Nov-Mean temperature (Nov-Mar):Mar):

~ -1.5~ -1.5° C° C(2) GCM Forcings (2) GCM Forcings 1990s1990s

Noah 2.0

Noah 2.8 Seasonal Snow water storage

Δ: Noah 2.8 – Noah 2.0

0

10

20

30

40

50

60

70

Nov Dec Jan Feb Mar Apr May Jun Jul

Sn

ow

Wat

er S

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(km

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) Noah 2.8

Noah 2.0

Mean temperature Mean temperature (Nov-Mar): -1.5(Nov-Mar): -1.5° C° C(3) Obs. forcings with GCM (3) Obs. forcings with GCM

tempstemps

Noah 2.0

Noah 2.8

Δ: Noah 2.8 – Noah 2.0

Seasonal Snow water storage

Mean temperature (Nov-Mean temperature (Nov-Mar):Mar):

~ 2~ 2° C° C(4) Obs. forcings +1(4) Obs. forcings +1°C °C 1990s1990s

0

10

20

30

40

50

60

70

Nov Dec Jan Feb Mar Apr May Jun Jul

Sn

ow

Wat

er S

tora

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(km

**3

/ WA

) Noah 2.8

Noah 2.0

Noah 2.0

Noah 2.8

Δ: Noah 2.8 – Noah 2.0

Seasonal Snow water storage

Mean temperature (Nov-Mean temperature (Nov-Mar):Mar):

~ -0.4~ -0.4° C° C(5) GCM Forcings (5) GCM Forcings 2020s2020s

0

10

20

30

40

50

60

70

Nov Dec Jan Feb Mar Apr May Jun Jul

Sn

ow

Wat

er S

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(km

**3

/ WA

) Noah 2.8

Noah 2.0

MM5 SWE 2020s

MM5 – SWE 1990s

Δ: SWEMM5-1990s - SWEMM5-2020s

Seasonal Snow water storage

ΔΔ Mean temperature (Nov-Mean temperature (Nov-Mar): ~ 1.1Mar): ~ 1.1° C° C(6) GCM Outputs 1990s, (6) GCM Outputs 1990s,

2020s2020s

Baseline

0

10

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30

40

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Nov Dec Jan Feb Mar Apr May Jun Jul

Sn

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ter

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e (

km

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A)

MM5 SWE 1990s

MM5 SWE 2020s

Model sensitivities

Forcings Maurer: 1990sMM5 GCM output

forcing: 1990s

Mean air temp over snow season (Nov – Mar, °C)Std.Dev,Std.Err

1.0 1.02,0.32 -1.5 0.81,0.25

Sensitivity of Mean Apr1. Snow Water Storage to 1° C change

Noah 2.8 (over WA)

7.0 km3 / °C (17.3 %)

5.1 km3 / °C (9.5 %)12.8 km3 / °C (20.6 %)

Sensitivity of Mean Apr1. Snow Water Storage to 1° C change Noah 2.0 (over WA)

4.5 km3 / °C (25.9 %)

6.2 km3 / °C (18.8 %)4.4 km3 / °C (27.0 %)

Sensitivity of Mean Apr1. Snow Water Storage to 1° C change MM5 Snow Output (over WA)

XX.X 4.4 km3 / °C (28.2 %)

Asymmetric Asymmetric sensitivitiessensitivities

Summary of results

ForcingsMaurer: 1990s

Maurer: 1990s + 1°C

Maurer: 1990s +

2.5°C

MM5 ΔT applied to Maurer: 1990s

MM5: 1990s MM5: 2020s

Mean Seasonal Temperature (Nov-Jul / Mean air temp over snow season (Nov-Mar °C)

5.9 / 1.0 6.9 / 2.0 8.4 / 3.5 3.3 / -1.5 3.3 / -1.5 4.3 / -0.4

Mean Apr1. Snow Water Storage

Noah 2.8 (km3/WA)40.5 33.5 23.9 53.2 61.8 47.7

Mean Apr1. Snow Water Storage

Noah 2.0 (km3/WA)17.4 12.9 7.2 32.8 16.3 11.9

Mean Apr1 Snow Water Storage

MM5 Output (km3/WA)XX.X XX.X XX.X XX.X 15.6 11.2

BaselineBaseline BaselineBaseline

Conclusions…Conclusions…• Estimates of snowpack sensitivity to temperature change Estimates of snowpack sensitivity to temperature change

(excluding assumptions about precipitation changes) yield a range (excluding assumptions about precipitation changes) yield a range of potential sensitivities ~ 20 % with 1 outlier:of potential sensitivities ~ 20 % with 1 outlier:

1.1. 3 methods employed by *Casola et al (~2008):3 methods employed by *Casola et al (~2008):-Suggest snow water storage has roughly 20% sensitivity to -Suggest snow water storage has roughly 20% sensitivity to

11°C warming.°C warming.

2.2. Present work using coupled and offline large-scale GCM and LSM’s:Present work using coupled and offline large-scale GCM and LSM’s: -Caution must be taken in establishing the baseline, or current -Caution must be taken in establishing the baseline, or current climate, from which sensitivities are computed…climate, from which sensitivities are computed… -GCM has cold bias, inferior snow model, and distribution of -GCM has cold bias, inferior snow model, and distribution of precipitation differing from observed, exacerbate disparity in SWE precipitation differing from observed, exacerbate disparity in SWE predictionprediction -Preliminary results are generally in agreement with Casola et al. -Preliminary results are generally in agreement with Casola et al. sensitivities…sensitivities…

Ultimately, a snow model that can effectively reproduce current Ultimately, a snow model that can effectively reproduce current conditions conditions one one essential component to making realistic essential component to making realistic estimates of future climates and sensitivities.estimates of future climates and sensitivities.

Thank YouThank You

Low snow bias for old (coupled) Noah LSM (ver 2.0)

Cumulative Cumulative snow covered snow covered daysdays

IMS SatelliteIMS Satellite1/8° spatial 1/8° spatial resolutionresolution

Noah ver. 2.0Noah ver. 2.0

Model Improvements…• Improved SWE performance:

*Refreeze of melt water, more realistic absorption of solar radiation, turbulent exchange

Noah ver. 2.8Noah ver. 2.8½½° spatial ° spatial resolutionresolution

Noah ver. Noah ver. 2.02.0