Post on 17-Dec-2015
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