Hurricanes and Climate Change Kerry Emanuel Massachusetts Institute of Technology

Hurricanes and Climate Change

Hurricanes and Climate Change

Kerry EmanuelMassachusetts Institute of Technology

ProgramProgram

• Effect of climate change on hurricane activityEffect of climate change on hurricane activity

• Hurricanes in the climate systemHurricanes in the climate system

Effect of Climate Change on Effect of Climate Change on HurricanesHurricanes

No Obvious Trend in Global TC Frequency, 1970-2006No Obvious Trend in Global TC Frequency, 1970-2006

Data Sources: NOAA/TPC and NAVY/JTWC

Better Intensity Metric:Better Intensity Metric:

The Power Dissipation IndexThe Power Dissipation Index

0

3maxPDI V dt

A measure of the total frictional dissipation of kinetic A measure of the total frictional dissipation of kinetic energy in the hurricane boundary layer over the energy in the hurricane boundary layer over the

lifetime of the stormlifetime of the storm

Power Dissipation Based on 3 Data Sets for Power Dissipation Based on 3 Data Sets for the Western North Pacificthe Western North Pacific(smoothed with a 1-3-4-3-1 filter)

aircraft recon

Data Sources: NAVY/JTWC, Japan Meteorological Agency, UKMO/HADSST1, Jim Kossin, U. Wisconsin

Years included: 1949-2004

Atlantic Storm Maximum Power DissipationAtlantic Storm Maximum Power Dissipation(Smoothed with a 1-3-4-3-1 filter)

Po

wer

Dis

sip

atio

n In

dex

(P

DI)

Years included: 1870-2006

Data Source: NOAA/TPC

Atlantic Sea Surface Temperatures and Atlantic Sea Surface Temperatures and Storm Max Power DissiaptionStorm Max Power Dissiaption

(Smoothed with a 1-3-4-3-1 filter)

Sca

led

Tem

per

atu

re

Po

wer

Dis

sip

atio

n In

dex

(P

DI)

Years included: 1870-2006

Data Sources: NOAA/TPC, UKMO/HADSST1

Energy ProductionEnergy Production

Distribution of Entropy in Hurricane Inez, 1966

Source: Hawkins and Imbembo, 1976

Theoretical Upper Bound on Theoretical Upper Bound on Hurricane Maximum Wind Speed:Hurricane Maximum Wind Speed:

*2| |0

C T Tk s oV k kpot TC

oD

Air-sea enthalpy disequilibrium

Surface temperature

Outflow temperature

Ratio of exchange coefficients of enthalpy and momentum

Heat Engine Theory Predicts Heat Engine Theory Predicts Maximum Hurricane WindsMaximum Hurricane Winds

MPH

Combine with Ocean Surface Energy Combine with Ocean Surface Energy BalanceBalance

2

| |entrains o

poto D s

F F FT TV

T C

V

Net outgoing radiation

Surface Trade Wind speed

Ocean mixed layer entrainment

Sea Surface Temperature

Temperature at top of storm

Incoming solar radiation

Derived by combining potential intensity expression with ocean surface energy balance

Observed Tropical Atlantic Potential IntensityObserved Tropical Atlantic Potential Intensity

Data Sources: NCAR/NCEP re-analysis with pre-1979 bias correction, UKMO/HADSST1

What is Causing Changes in What is Causing Changes in Tropical Atlantic Sea Surface Tropical Atlantic Sea Surface

Temperature?Temperature?

10-year Running Average of Aug-Oct NH Surface T and 10-year Running Average of Aug-Oct NH Surface T and MDR SSTMDR SST

Tropical Atlantic SST(blue), Global Mean Surface Tropical Atlantic SST(blue), Global Mean Surface Temperature (red), Temperature (red),

Aerosol Forcing (aqua)Aerosol Forcing (aqua)

Mann, M. E., and K. A. Emanuel, 2006. Atlantic hurricane trends linked to climate change. EOS, 87, 233-244.

Global mean surface temperature

Tropical Atlantic sea surface temperature

Sulfate aersol radiative forcing

Best Fit Linear Combination of Global Warming Best Fit Linear Combination of Global Warming and Aerosol Forcing (red) versus Tropical Atlantic and Aerosol Forcing (red) versus Tropical Atlantic

SST (blue)SST (blue)

Mann, M. E., and K. A. Emanuel, 2006. Atlantic hurricane trends linked to climate change. EOS, 87, 233-244.

Tropical Atlantic sea surface temperature

Global Surface T + Aerosol Forcing

Pushing Back the Record of Pushing Back the Record of Tropical Cyclone Activity:Tropical Cyclone Activity:

PaleotempestologyPaleotempestology

barrier beach

backbarrier marshlagoon

barrier beach

backbarrier marshlagoon

a)

b)

Source: Jeff Donnelly, WHOI

upland

upland

flood tidal delta

terminal lobes

overwash fan

overwash fan

Paleotempestology

Source: Jeff Donnelly, Jon Woodruff, Phil Lane; WHOI

Source: Jeff Donnelly, Jon Woodruff, Phil Lane; WHOI

Source: Jeff Donnelly, Jon Woodruff, Phil Lane; WHOI

Projecting into the Future: Projecting into the Future: Downscaling from Global Downscaling from Global

Climate ModelsClimate Models

Today’s global climate Today’s global climate models are far too coarse to models are far too coarse to simulate tropical cyclonessimulate tropical cyclones

Our ApproachOur Approach• Step 1: Randomly seed ocean basins with weak

(25 kt) warm-core vortices

• Step 2: Determine tracks of candidate storms using a beta-and-advection model

• Step 3: Run a deterministic coupled tropical cyclone intensity model along each synthetic track, discarding all storms that fail to achieve winds of at least 35 kts

• Step 4: Assess risk using statistics of surviving events

Synthetic Track Generation,Synthetic Track Generation,Using Synthetic Wind Time SeriesUsing Synthetic Wind Time Series

• Postulate that TCs move with vertically averaged environmental flow plus a “beta drift” correction (Beta and Advection Model, or “BAMS”)

• Approximate “vertically averaged” by weighted mean of 850 and 250 hPa flow

Synthetic wind time series

• Monthly mean, variances and co-variances from NCEP re-analysis data

• Synthetic time series constrained to have the correct mean, variance, co-variances and an power series

3

Track:Track:

850 2501 ,track V V V V

Empirically determined constants:

0.8, 10 ,u ms

12.5v ms

• Run coupled deterministic model (CHIPS, Emanuel et al., 2004) along each track

• Use monthly mean potential intensity, ocean mixed layer depth, and sub-mixed layer thermal stratification

• Use shear from synthetic wind time series

• Initial intensity specified as

• Tracks terminated when v <

Tropical Cyclone IntensityTropical Cyclone Intensity

112 ms

117 ms

Example: 200 Synthetic TracksExample: 200 Synthetic Tracks

6-hour zonal displacements in region bounded by 6-hour zonal displacements in region bounded by 1010oo and 30 and 30oo N latitude, and 80 N latitude, and 80oo and 30 and 30oo W W

longitude, using only post-1970 hurricane datalongitude, using only post-1970 hurricane data

Present Climate: Spatial Present Climate: Spatial Distribution of Genesis PointsDistribution of Genesis Points

Observed

Synthetic

CalibrationCalibration

• Absolute genesis frequency calibrated Absolute genesis frequency calibrated to North Atlantic during the period to North Atlantic during the period 1980-20051980-2005

Genesis ratesGenesis rates

Seasonal CyclesSeasonal Cycles

AtlanticAtlantic

Seasonal CyclesSeasonal Cycles

Western North PacificWestern North Pacific

Cumulative Distribution of Storm Lifetime Cumulative Distribution of Storm Lifetime Peak Wind Speed, with Sample of 2946Peak Wind Speed, with Sample of 2946

Synthetic TracksSynthetic Tracks

Atlantic ENSO InfluenceAtlantic ENSO Influence

Year by Year Comparison with Best Track Year by Year Comparison with Best Track and with Knutson et al., 2007and with Knutson et al., 2007

Simulated vs. Observed Power Dissipation Trends, 1980-2006Simulated vs. Observed Power Dissipation Trends, 1980-2006

Now Use Daily Output from IPCC Now Use Daily Output from IPCC Models to Derive Wind Models to Derive Wind

Statistics, Thermodynamic State Statistics, Thermodynamic State Needed by Synthetic Track Needed by Synthetic Track

TechniqueTechnique

1. Last 20 years of 20Last 20 years of 20thth century century simulationssimulations

2.2. Years 2180-2200 of IPCC Years 2180-2200 of IPCC Scenario A1b (COScenario A1b (CO22 stabilized at stabilized at

720 ppm)720 ppm)

Compare two simulations each Compare two simulations each from 7 IPCC models:from 7 IPCC models:

Model Institution Atmospheric Resolution

Designation in this paper

Potential Intensity

Multiplicative Factor

Community Climate System Model, 3.0

National Center for Atmospheric Research

T85, 26 levels CCSM3 1.2

CNRM-CM3 Centre National de Recherches Météorologiques, Météo-France

T63, 45 levels CNRM 1.15

CSIRO-Mk3.0 Scientific and Research Organization

T63, 18 levels CSIRO 1.2

ECHAM5 Max Planck Institution T63, 31 levels ECHAM 0.92GFDL-CM2.0 NOAA Geophysical Fluid

Dynamics Laboratory2.5o X 2.5 o , 24 levels

GFDL 1.04

MIROC3.2 CCSR/NIES/FRCGC, Japan T42, 20 levels MIRO 1.07

mri_cgcm2.3.2a Meteorological Research Institute,

T42, 30 levels MRI 0.97

Genesis Distributions

Basin-Wide Percentage Change Basin-Wide Percentage Change in Power Dissipationin Power Dissipation

Basin-Wide Percentage Change Basin-Wide Percentage Change in Storm Frequencyin Storm Frequency

7 Model Consensus Change in 7 Model Consensus Change in Storm FrequencyStorm Frequency

Why does frequency decrease?Why does frequency decrease?

*0

,m bm

b

s s

s s

Critical control parameter in Critical control parameter in CHIPS:CHIPS:

** ( 1) *lnv

m b m v

L qs s s s R q

T H H H,

Entropy difference between boundary layer Entropy difference between boundary layer and middle troposphere and middle troposphere increasesincreases with with temperature at constant relative humiditytemperature at constant relative humidity

Change in Frequency when T held constant in m

Feedback of Global Tropical Feedback of Global Tropical Cyclone Activity on the Cyclone Activity on the

Climate SystemClimate System

The wake of Hurricane Emily (July 2005).

Hurricane Dennis(one week earlier)

Source: Rob Korty, CalTech

Direct mixing by tropical cyclones

Source: Rob Korty, CalTech

Emanuel (2001) estimated global rate of heat input as

1.4 X 1015 Watts

Response of Ocean to Point Mixing:

Scott, J. R. and J. Marotzke, 2002: The location of diapycnal mixing and the meridional overturning circulation. J. Phys. Ocean., 32, 3578–3595

TC Mixing May Induce Much or Most of the Observed Poleward Heat Flux by the Oceans

Trenberth and Caron, 2001Trenberth and Caron, 2001

Results from EPIC 2001

“…motions below the thermocline were very weak, but they intensified…as energy from a strong storm worked its way downward. The accompanying mixing accounted for most of what little mixing there was between depths of 100-200 m. Mixing in the thermocline…appears to respond mostly to wind stress.

“…the strongest atmospheric disturbances are likely to cause an inordinately large fraction of the total mixing. Profound errors could occur in climate models, which fail to take this into account.”

50

100

200

September 2001, 10oN, 95oW

Raymond et al. (2004) report that background mixing is essentially zero in the tropical eastern Pacific.

Slide courtesy of Rob Korty, CalTech

Diffusivity Estimated from Analysis of ERA-40 Wake Recoveries

Figure courtesy of Ron Sriver and Matt Huber, Purdue University

Linear trend (1955–2003) of the zonally integrated heat content of the world ocean by one-degree latitude belts for 100-m thick layers. Source: Levitus et al., 2005

Zonally averaged temperature trend due to global warming in a coupled climate model. Source: Manabe et al, 1991

TC-Mixing may explain difference between

observed and modeled ocean warming

TC-Mixing may be Crucial for High-Latitude Warmth and Low-Latitude Moderation During Warm Climates,

such as that of the Eocene

SST: elevated mixing to 360 meters – uniform

10 x CO2 in both experimentsSource: Rob Korty, CalTech

Interactive TC-Mixing Moderates Tropical Warming and Amplifies High-Latitude Warming in Coupled Climate Models

Climate Forcing

SST

Multiple Equilibria and Hysteresis in a Two-Column Coupled Model (Emanuel, JGR, 2002)

Summary:

• Tropical cyclones are sensitive to the climate state

• Observations together with detailed modeling suggest that TC power dissipation increases by ~65% for a 10% increase in potential intensity

• Storm-induced mixing of the upper tropical ocean may be the principal driver of the ocean’s thermohaline circulation

• Increased TC power dissipation in a warming climate will drive a larger poleward heat flux by the oceans, tempering tropical warming but amplifying the warming of middle and high latitudes

• This feedback between TCs and ocean heat flux is not included in any current climate model; its inclusion may change our understanding of climate dynamics and our predictions of the earth’s response to increased greenhouse gases

Transects of SSH Transects of SSH anomalies from passage anomalies from passage of Hurricane Edouard, of Hurricane Edouard, which passed through which passed through transect on Day 239. transect on Day 239. Scale of anomlies is 10 Scale of anomlies is 10 cm. (Analysis and figure cm. (Analysis and figure courtesy of Peter courtesy of Peter Huybers.) Height rise Huybers.) Height rise implies net heat input of implies net heat input of 2 X 102 X 102121 J. J.

Variations in Solar Output (IPCC, 2007)Variations in Solar Output (IPCC, 2007)

Variation with Time of Natural Climate Forcings:Variation with Time of Natural Climate Forcings:

Comparing 1980-1990 (quiet) to Comparing 1980-1990 (quiet) to 1995-2005 (active)1995-2005 (active)

104-156 HURDAT tracks 1000 Synthetic tracks

Cumulative distributions of storm lifetime maximum wind

Sensitivity to Shear and Potential Sensitivity to Shear and Potential IntensityIntensity

Examples of Annual Cycles of Storm Examples of Annual Cycles of Storm Counts by MonthCounts by Month

NCAR CCSM3 GFDL CM2.0

ATLANTIC

Examples of Annual Cycles of Storm Examples of Annual Cycles of Storm Counts by MonthCounts by Month

NCAR CCSM3 GFDL CM2.0

Western North Pacific

Examples of Shifts in Hurricane Track Examples of Shifts in Hurricane Track Density (GFDL CM2.0)Density (GFDL CM2.0)

1980-1999 2180-2199

Examples of Shifts in Hurricane Track Examples of Shifts in Hurricane Track Density (GFDL CM2.0)Density (GFDL CM2.0)

1980-1999 2180-2199