tropical cyclones in a warming world kerry emanuel massachusetts institute of technology
TRANSCRIPT
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TROPICAL CYCLONES IN A WARMING WORLD
TROPICAL CYCLONES IN A WARMING WORLD
Kerry EmanuelMassachusetts Institute of Technology
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Issues
• What processes control rates of formation of tropical cyclones?
• What processes control the actual and potential intensity of TCs?
• What have TCs been like in the past, and how will they be affected by global warming?
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The Genesis Puzzle
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Global Tropical Cyclone Frequency, 1970-2008
Data Sources: NOAA/TPC and NAVY/JTWC
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Tropical Cyclones Often Develop from Cloud Clusters:
When/Why Does Convection Form Clusters?
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Monsoonal Thunderstorms, Bangladesh and India July 1985
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Simplest Statistical Equilibrium State:
Radiative-Convective Equilibrium
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Vertically integrated water vapor at 4 days (Nolan et al., QJRMS, 2007)
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Vertically integrated water vapor at 4 (a), 6 (b), 8 (c), and 10 (d) days (Nolan et al., QJRMS, 2007)
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Nolan et al., QJRMS, 2007
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Empirical Necessary Conditions for Self-Aggregation (after Held et al., 1993; Bretherton et al., 2005; Nolan et al.; 2007)
• Small vertical shear of horizontal wind• Interaction of radiation with clouds and/or
water vapor• Feedback of convective downdraft surface
winds on surface fluxes• Sufficiently high surface temperature
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Self-Aggregation is Temperature-Dependent (Nolan et al., 2007; Emanuel and Khairoutdinov, in preparation, 2010)
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Extension to f-plane
Distance between vortex
centers scales as
Vpot/f
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Intensity:Some Empirical Results
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Atlantic Sea Surface Temperatures and Storm Max Power Dissipation
(Smoothed with a 1-3-4-3-1 filter)
Scal
ed T
empe
ratu
re
Pow
er D
issi
patio
n In
dex
(PD
I)
Years included: 1870-2006
Data Sources: NOAA/TPC, UKMO/HADSST1
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Tropical cyclone power dissipation has nearly tripled since the 1980s, though there has been an increase
of only 0.5o C in sea surface temperature
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Analysis of satellite-derived tropical cyclonelifetime-maximum wind speeds
Box plots by year. Trend lines are shownfor the median, 0.75 quantile, and 1.5
times the interquartile range
Trends in global satellite-derived tropical cyclone maximum wind
speeds by quantile, from 0.1 to 0.9 in increments of 0.1.
Elsner, Kossin, and Jagger, Nature, 2008
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The Importance of Potential Intensity for Genesis and for
Storm Intensity
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Energy Production Cycle
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Theoretical Upper Bound on Hurricane Maximum Wind Speed:
2 *| | 0s b
C T Tk s oV T s spot C TD o
Air-sea enthalpy disequilibrium
Surface temperature
Outflow temperature
Ratio of exchange coefficients of enthalpy and momentum
s0* = saturation entropy of sea surfacesb = actual entropy of subcloud layer
0 0
** ln ln v
p
L qT ps C R
T p T
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Condition of convective neutrality:
sb = s* of free troposphere
Also, s* of free troposphere is approximately spatially uniform (WTG approximation)
*2 *| | 0s
C T Tk s oV T s spot C TD o
approximately constant
What matters, apparently, is the SST (s0*) relative to the tropospheric temperature (s*)
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0o 60oE 120oE 180oW 120oW 60oW
60oS
30oS
0o
30oN
60oN
0 10 20 30 40 50 60 70 80
Annual Maximum Potential Intensity (m/s)
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Empirical Evidence for the Importance of Potential Intensity to TC Genesis: A Genesis Potential Index (GPI)
• 850 hPa absolute vorticity (h)• 850 – 250 hPa shear (S)• Potential intensity (PI)• Non-dimensional subsaturation of the middle
troposphere:
Base choice of predictors on physics, intuition, past experience
600
0
*
* *
s s
s s
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New Genesis Potential Index:
23 1
3 1 44
| | 45
(10 )
PI msGPI
ms S
• 850 hPa absolute vorticity (h)• 850 – 250 hPa shear (S)• Potential intensity (PI)• Non-dimensional subsaturation of the middle
troposphere: 600
0
*
* *
s s
s s
5 1| | 10 s
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Performance
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Basin Frequencies
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Spatial Distribution
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Climate Control of Potential Intensity
* *0
* *0
* *0
| | ( )
| |
| |
k a s rad ocean
rad ocean
k a s
rad ocean
k a s
C T s s F h F
F h Fs s
C T
and
F h Fs s
C T
10
10
10
V
V
V
Ocean Surface Energy Balance:
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• Potential intensity is determined by local radiative balance, local convergence of ocean heat flux, local surface wind speed, and local outflow temperature only
• Remote influences limited to remote effects on surface wind surface radiation ocean heat flux and, in marginal zones, on outflow temperature
• SST cannot vary independently of free atmospheric temperature on long time scales
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Interpretation of Recent Trends in Potential Intensity
North Indian
Western North Pacific
Southern Hemisphere North Atlantic
Eastern North Pacific
From NCAR/NCEP reanalysis data, 1980-2008
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Potential intensity has been increasing by about 12 ms-1K-1,
compared to accepted value of 4 ms-1K-1. What is the source of this
discrepancy?
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Answer: Potential Intensity is not a function of SST per se
Showing potential intensity vs. SST, varying mean surface wind (blue) and CO2 content (green)
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2
| |s o rad
maxo D
T T F dV
T C
ocean
s
F
V
Combine expression for potential intensity, Vmax, with energy balance of ocean mixed layer:
Valid on time scales > thermal equilibration time of ocean mixed layer (~ 2 years)
SST Outflow T
Net surface radiative flux
Ocean mixed layer depth Mixed layer heat flux
Drag coefficient Mean surface wind speed
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Surface wind speeds have not changed much since 1980. Key variable: Outflow
temperature, which in general decreases with:
• Increasing SST
• Decreasing temperature of lower stratosphere and/or troposphere transition layer
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Importance of Trends in Outflow Temperature
From NCEP Reanalysis
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Outflow Temperature, September, 1995
0o 60oE 120oE 180oW 120oW 60oW
60oS
30oS
0o
30oN
60oN
200 210 220 230 240 250 260 270 280
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Does NCEP Reanalysis Capture Lower Stratospheric Cooling?
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Yes, Pretty Much
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Do AGCMs Capture Lower Stratospheric Cooling?
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But AGCMs, driven by observed SSTs, do not get the cooling!
August-October outflow temperatures averaged over the Atlantic MDR from the ECHAM 5 simulation (green), the NOAA/CIRES 20th Century reanalysis, version 2
(red) and the NCAR/NCEP reanalysis (blue)
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As a result, they miss the recent increase in potential intensity
# 31: ECHAM without aerosols
#32: ECHAM with aerosols
NCEP
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1979-1999 Temperature Trends, 30S-30N. Red: Radiosondes; Solid Black: Mean of Models with Ozone; Dashed Black: Mean of
Models without Ozone (Cordero and Forster, 2006)
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Ozone may not explain spatial pattern of cooling(Fu and Wallace, Science, 2006)
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Stratospheric Compensation
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Our Approach to TC Downscaling
• Step 1: Seed each ocean basin with a very large number of weak, randomly located vortices
• Step 2: Vortices are assumed to move with the large scale atmospheric flow in which they are embedded
• Step 3: Run a coupled, ocean-atmosphere computer model for each vortex, and note how many achieve at least tropical storm strength; discard others
• Step 4: Using the small fraction of surviving events, determine storm statistics.
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New Downscaling Technique: 200 Synthetic U.S. Landfalling tracks (color coded by S-S Scale)
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Cumulative Distribution of Storm Lifetime Peak Wind Speed, with Sample of 2946 Synthetic Tracks
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Year by Year Comparison with Best Track and with Knutson et al., 2007
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Application to Re-analyses and AGCMs
Annual Atlantic tropical cyclone counts: Unadjusted best-track data (black); and downscaled from the NCAR/NCEP reanalysis, 1980-2008 (blue), the ECHAM 5
simulation, 1870-2005 (green), and the NOAA/CIRES reanalysis, 1891-2008 (red). Thin lines show annual values, thick lines show 5-year running means
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Application to the Climate of the Pliocene
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Explicit (blue dots) and downscaled (red dots) genesis points for June-October for Control (top) and Global Warming (bottom) experiments using the 14-km resolution NICAM model. Collaborative work with K. Oouchi.
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Change in Power Dissipation with Global Warming
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Probability Density by Storm Lifetime Peak Wind Speed, Explicit and Downscaled Events
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Summary
• Potential intensity is an important (but not the only) control on tropical cyclone activity, including frequency and intensity
• On time scales long enough for the ocean mixed layer to be in thermal equilibrium, potential intensity is controlled largely by surface radiation, surface wind speed, ocean heat fluxes, and outflow temperature
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• Recent large, upward trends in potential intensity are partly and perhaps mostly attributable to cooling of the lower stratosphere
• Models forced with observed SSTs not very successful in capturing this cooling
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• Simple but high resolution coupled TC model can be used to ‘downscale” TC activity from global climate data sets
• Studies based on this downscaling suggest large sensitivity of TCs to climate state, and possibly important role for TC-induced ocean mixing and atmospheric drying/heating in regulating climate
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Feedback of Global Tropical Cyclone Activity on the Climate
System
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500hPa zonal mean meridional temperature flux (mK/s) of the stationary eddies for January through March. The dotted (solid) curve represents the composite mean of the winters following inactive (active) northern hemisphere TC seasons. Error bars
represent the standard error of the mean for datasets of size varying from N=9 to 13. Flux calculated using NCAR/NCEP reanalysis for the period 1960‐2008
Hart, 2010
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The wake of Hurricane Emily (July 2005)
Hurricane Dennis(one week earlier)
Source: Rob Korty, CalTech
Sea Surface Temperature in the Wakes of Hurricanes
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Wake Recovery
Hart, Maue, and Watson, Mon. Wea. Rev., 2007
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Direct mixing by tropical cyclones
Source: Rob Korty, CalTech
Emanuel (2001) estimated global rate of heat input as 1.4 X 1015 Watts
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TC Mixing May Induce Much or Most of the Observed Poleward Heat Flux by the Oceans
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Estimate of total heat uptake by tropical oceans
Estimate from satellite-derived wake recoveries
Extrapolation from detailed ocean
measurements of one storm
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TC-Mixing may be Crucial for High-Latitude Warmth and Low-Latitude Moderation During Warm Climates, such as that of the Eocene
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Our future?
Figure courtesy of Rob Korty, CalTech
Depiction of central North America, ~60 million years ago
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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
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What is Causing Changes in Tropical Atlantic Sea Surface Temperature?
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10-year Running Average of Aug-Oct Northern Hemisphere Surface Temp and Hurricane Region Ocean Temp
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Estimates of Global Mean Surface Temperature from the Instrumental Record
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Tropical Atlantic SST(blue), Global Mean Surface Temperature (red),
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 aerosol radiative forcing
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Best Fit Linear Combination of Global Warming and Aerosol Forcing (red) versus Tropical Atlantic
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
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Pushing Back the Record of Tropical Cyclone Activity:
Paleotempestology
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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
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Source: Jeff Donnelly, Jon Woodruff, Phil Lane; WHOI
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Source: Jeff Donnelly, Jon Woodruff, Phil Lane; WHOI
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Inferences from Modeling
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The Problem:
• Global models are far too coarse to simulate high intensity tropical cyclones
• Embedding regional models within global models introduces problems stemming from incompatibility of models, and even regional models are usually too coarse
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Histograms of Tropical Cyclone Intensity as Simulated by a Global Model with 50 km grid point spacing. (Courtesy Isaac Held, GFDL)
Category 3
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Probability Density of TC Damage, U.S. East Coast
Damage Multiplied by Probability Density of TC Damage, U.S. East Coast
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To the extent that they simulate tropical cyclones at all, global models simulate storms that are largely irrelevant to society and to the climate system itself, given that ocean stirring effects are heavily weighted towards the most intense storms
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Decomposition of PDI Trends
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Sensitivity to Shear and Potential Intensity
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Reminder: Problems with Potential Intensities
# 31: ECHAM without aerosols
#32: ECHAM with aerosols
NCEP
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*'
'' * ' '
' '
b
p s
T s T b
Ts s
p p p
T T s
Hydrostatic Compensation (following Holloway and Neelin)
Perturbations to moist adiabatic troposphere:
Stratospheric compensation:
'''
'ln ln ln
s T bTT
T T sRT
p p p
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' 'T sT T
For typical values of the parameters