climate change projections for the hudson valley

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7/15/2010

Climate Change Projections for the Hudson Valley

Art DeGaetanoDepartment of Earth & Atmospheric Science

Cornell UniversityDirector, NOAA Northeast Regional Climate Center

Hudson Valley Climate Change Workshop

July 14, 2010

ClimAID:

Adaptation Strategies in New York State

To provide New York State with cutting ‐edge information on its vulnerability to climate change and to facilitate the development of adaptation policies informed by both local

exper ence an s a e ‐o ‐ e‐ar sc en c now e ge.



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Sectors‐ Agriculture/Ecosystems‐ Coastal Zones‐ Energy‐ Public Health‐ Transportation/ Communication‐ Water Resources

Key Themes‐ Climate Risks‐ Vulnerability‐ Adaptation

Cross Cutting Elements‐ Science/Policy Linkages‐ Economic Policy Linkages‐ Environmental Justice

ClimateClimate

Economics

Economics

Adaptation Adaptation Vulnerability Vulnerability

Science‐Policy Linkages

Science‐Policy Linkages

CLIMATE‐PROTECTED NYSReduced Vulnerability and Enhanced Adaptive Capacity



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Key Climate Products

• uantitative and qualitative projections, statewide and by region

• Sector ‐specific climateproducts

• Re ional climate modeling and statistical

downscaling

Basis of Climate Products

16 Global climate models 3 Emissions Scenarios Statistical Downscaling to 22 stations grouped into 7 regions



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Emissions Scenarios



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Climate Model Ensembles ClimAID (NYS Climate Adaptation Assessment)

67%

What is Downscaling?

200 x 300 km

75 km



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Global View

Regional or Local View



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Smoothed topography

Downscaling

Resolves the mismatch in scale between the coarse spatial resolution of climate model output and the need for weather and climate information at a higher resolution

Extreme rainfall estimates Impact Assessment Models



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Two main types...

Statistical Em irical Uses a statistical model to link large ‐scale climate variables to local climate characteristics

Dynamical Most common type uses a mesoscale, physically ‐based regional climate model (RCM)

Both have their origins in operational weather prediction.

Delta Method Downscaling

Average change in model projections from base to future period are applied to observed data from base period



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Other Statistical Downscaling Relationships derived between large ‐scale atmospheric variables (predictors) and observed local weather

.

These relationshi s are then a lied to e uivalent

Temperature = f(500 mb Height)Albany Temperature= f(large ‐scale 500 mb height)

variables in the GCM.

Used in CLIMAID for extreme precip, snow

SDSM Output



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Dynamical Downscaling

T ical rid ~20‐50km

Regional climate models work like numerical weather prediction (NWP) models, except that they run for a much longer time

North American Regional Climate Change Assessment Program (NARCCAP)

Nested RCMs need boundary conditions from GCMs or Reanalysis

The World Ends Here

e W o r l d E n d s H e r e T h e

W o r l d E n d s H e r

The World Ends Here

T e



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Quantitative Projections by Region: Mean Changes

4

23

1 56

7

Utica, Yorktown Heights, Saratoga Springs, Hudson Correctional Facility

Region 6 Baseline

Region 5 Baseline 1

1971-2000 2020s 2050s 2080s

Air temperatureMin (Central Range) Max 2

50° F 0.5 (1.5 to 3.0) 3.5 ° F 2.5 (3.0 to 5.5) 7.5 ° F 3.0 (4.0 to 8.0) 10.0 ° F

PrecipitationMin (Central Range) Max 51 in -5 (0 to + 5) 10 % -5 (0 to + 10) 10 % 0 (5 to 10) 15%

Boonville, Watertown

1971-2000 Air temperatureMin (Central Range) Max

44° F + 0.5 (1.5 to 3.0) 4.0 ° F + 2.5 (3.5 to 5.5) 7.5 ° F + 3.0 (4.5 to 9.0) 10.5 ° F

PrecipitationMin (Central Range) Max 51 in -5 (0 to + 5) 15 % -5 (0 to + 10) 15% -5 (+ 5 to 15) 20%



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Sea level rise

• • Thermal expansion• Glacier melt• Ice cap/ice sheet melt• Local land sinking/subsidence• Local water surface elevation

Source: CCSR

Sea level rise

• • based on paleoclimate data• 20,000 – 10,000 0.39‐0.47 in/yr

• Local modeling for Hudson to Troy river has low topographic gradient

Source: CCSR

change at Battery = change at Albany



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New York City Baseline(1971-2000) 2020s 2050s 2080s

Sea level rise

Sea level rise

NYC

Troy

(central range) + o n + o n + o n

Rapid Ice-MeltSea level rise NA ~ 5 to 10 in ~ 19 to 29 in ~ 41 to 55 in

Troy Baseline(1971-2000) 2020s 2050s 2080s

Sea level rise(Central range) NA + 1 to 4 in + 5 to 9 in + 8 to 18 in

Rapid Ice-Melt NA ~ 4 to 9 in ~ 17 to 26 in ~ 37 to 50 in

Source: CCSR



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Vulnerabilities: Water

Water Supply Across New York

Category Sensitivity to

Climate ChangePopulation Served

1 Draw from Large Waterbodies Low 2,000,000

2 NYC System Moderate 8,300,000

3 Other Reservoir Systems Moderate 1,300,000

4 Run ‐of ‐the ‐river on small drainage High 62,000

5 Long Island GW Moderate 3,200,000

6 Other Primary Aquifers Moderate 650,000 , ,

8 Other Small Water Supply Systems (GW or

SW) Moderate to High 1,600,000

Total = 19,000,000



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23% Heavy Rain

1

3%

31%15%

67%

20%

100 ‐year storm has become the 65 year storm!



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Flooding ‐‐ relative contribution of rain vs pet will lead to floods or droughts, and uncertainty

Years

less snow / more rainlarger storm rainfall amounts

longer growing season+ + more ET/

drier soils+ = ?

Clinton

Essex

Franklin

Fulton

Hamilton

H e r k i m e r

Jefferson

Lewis

MonroeNiagara OneidaO n Orleans

Oswego

Wayne a s h i n g t o n

St. Lawrence

Warren

S a r a t o g

Flood events percounty from1994-2006

(FEMA disaster designation)

Clinton

Essex

Franklin

Fulton

Hamilton

H e r k i m e r

Jefferson

Lewis

MonroeNiagara OneidaO n Orleans

Oswego

Wayne a s h i n g t o n

St. Lawrence

Warren

S a r a t o g

Flood events percounty from1994-2006

(FEMA disaster designation)

A l b a n y

AlleganyBroome C a t

t a r a u g u

s

C a y u g

a

C h a u

t a u q u a

Chemung

C h e n

a n g o

C o l u m

b i a C o r t l a n d

Delaware

D u t c h e s s

Erie

Genesee

Greene

L i v i n g s t o n

Madison Montg.

NassauNY City

o n d a g a Ontario

Orange

SteubenTioga

T o m p k i n

s

S c h u y

l e r

Ulster

Westchester

Putnam

Sullivan

RocklandSuffolk

Otsego Rensselaer

Schenectady

S c h o

h a r i

e

W y o m i n g Yates S

e n e c a

a

0x

1x

2x

3x

4x

6x

7x

A l b a n y

AlleganyBroome C a t

t a r a u g u

s

C a y u g

a

C h a u

t a u q u a

Chemung

C h e n

a n g o

C o l u m

b i a C o r t l a n d

Delaware

D u t c h e s s

Erie

Genesee

Greene

L i v i n g s t o n

Madison Montg.

NassauNY City

o n d a g a Ontario

Orange

SteubenTioga

T o m p k i n

s

S c h u y

l e r

Ulster

Westchester

Putnam

Sullivan

RocklandSuffolk

Otsego Rensselaer

Schenectady

S c h o

h a r i

e

W y o m i n g Yates S

e n e c a

a

0x

1x

2x

3x

4x

6x

7x



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Water Quality



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• CSO IncreasesGreater relative increase on systems that meet EPA Fourdischarge per year regulation

Other Issues

• Run off from urban/agriculture surfacesMight be limited by available pollutant load

• Increased water temperaturePathogens (some better some worse)Increases algal growth

SPDES permit implications especially in combo with lowsummer flows

• Potentially power plant cooling issues

• Ex ansion of irri ated a riculture ma lace

Other Issues

further demands on water supply

• Potentially local demand increases due to gas well drilling

• Population migration from drier regions



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Coastal



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Rapid ice



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ECWS Frequency

Hurricane Frequency



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•Rising sea level

Salt Front Migration

•slope of the river 2 ft/150 mi•sea level rise 1 in/decade •0.6 mi up river/ year

•Reduced precip

Figure 5.6. Hudson River Estuary withlocation of salt front on 10/30/2009,approximate distance is 53 river miles from theBattery at New York City (USGS).

•Increased temp (more evap)

Marsh Survival0.1 in/yr 0.2 in/yr 0.3 in/yr

Negative = drowned marshes Positive = marsh survivalIgnores subsurface compaction, subsidence and other causes of marsh loss



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A Significant land loss and break up of

reviousl conti uous

Udalls Cove Park Preserve Queens, NY

marsh

B Eroding embankments

C Widening of channels

• Increase water temp 0.220F per decade between 1920 and 1990 on Hudson

Other Coastal Impacts

Blue claw crabs flourish lobster declines

• Increases in ocean acidity Detrimental effects on the growth, development, and survival of hard clams, bay scallops, and Eastern oysters

• Coastal erosion



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• Flooding of water ‐side facilities (sea level rise, storm surge, extreme rainfall events)

Energy Supply

• Water ‐cooling related impacts (drought, turbidity from storm events, water temperature)

• Air temperature (equipment breakdown during extreme heat events, decreased power plant output or transmission/distribution line throughput capacity, snow vs. rain = timing of hydro availability)

• Drought (hydro availability)

• Resource availability (hydro, solar, wind availability)

• Changes in seasonal and diurnal load patterns

Energy Demand

summer peaking = increases demand length of extreme heat

waves + changing air conditioning saturation rates



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Public Health• Increased heat related mortality and morbidity

• Changes in vector‐borne disease prevalence

• Air quality declinesmogpollen wildfire?

• Consequences from flooding events

• Potential risks to water supply and food production

EcosystemsShifts in plant species composition in forest and other natural landscapes

Lose: Spruce fir boreal plant communities Win: Oak Hickory Pine

Changes in mammal communitiesLose: Snowshoe hare, fisher Win: White ‐tailed deer, northern cardinal Canadian goose

Expansion of invasive species Weeds: KutzuInsects: Hemlock wooly adelgid

Negative impacts on brook trout and other native cold water fishBass might benefit

Loss of winter recreation opportunities



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EFFECTIVE ADAPTATION IS ITERATIVE

INTEGRATING CLIMATE INTO LOCAL ADAPTATION DECISIONS



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Questions?

climate change projections for the hudson valley

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