i. introduction ii. a simple energy balance model for the seasonal cycle of energy fluxes
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The Seasonality and Partitioning of Atmospheric Heat Transport in a Myriad of Different Climate States. I. Introduction II. A simple energy balance model for the seasonal cycle of energy fluxes III. Dynamical heat transport partitioning - PowerPoint PPT PresentationTRANSCRIPT
The Seasonality and Partitioning of Atmospheric Heat Transport in a
Myriad of Different Climate States
I. Introduction II. A simple energy balance model for the seasonal cycle of energy fluxesIII. Dynamical heat transport partitioningIV. Atmospheric heat transport in aquaplanet simulationsV. Atmospheric Heat Transport in Simulations with
Land-Ocean Contrast and TopographyVI. Conclusions
I. Introduction a. The energy budget frameworkb. The dynamical framework
II. A simple energy balance model for the seasonal cycle of energy fluxes
III. Dynamical heat transport partitioningIV. Atmospheric heat transport in aquaplanet simulationsV. Atmospheric Heat Transport in Simulations with Land-
Ocean Contrast and TopographyVI. Conclusions
5.7 PW 5.9 PW
I. Introduction / a. The energy budget framework
ERBE DATA
Zonal and Annual Averaged Energy Flux (global mean removed)
• All signs defined wrt the atmosphere (e.g., negative OLR is an energy flux deficit for the atmosphere)
Surface heat flux = the total energy flux (radiative plus turbulent) through the surface/atmosphere interface
In the annual mean, positive SHF is equal to oceanic heat flux convergence
ASR = Absorbed solar
SHF = Surface heat flux
(-)OLR = Outgoing longwave
MHT = Meridional Heat Transp.
CTEN = (-) Atmos Column tendency
Observed NH
I. Introduction / a. The energy budget framework
ERBE/NCEP
Annual mean of energy budget poleward of 300N
(Departures from global annual mean)
AbsorbedSolar (ASR)
Surface HeatFlux (SHF)
Negative OLR
MeridionalHeat Transport(MHT)
2.2 PW
4.3 PW
1.4 PW
Tropics North Polar Region
7.9 PW
I. Introduction / a. The energy budget framework
(-) OLR
ASR
SHF
MHT
CTEN (-) Atmospheric Column tendency
Zonal and Seasonal Averaged Energy Flux (zonal, annual average removed)
Observed NH
I. Introduction / a. The energy budget framework
ERBE/NCEPDATA
Seasonal Extratropical Energy Budget
I. Introduction / a. The energy budget framework
Temp.Anom. (K)
Meridional Wind Anomaly
STATIONARY WAVES
Mean MeridionalCirculations (MMC)
Transient Eddies (Storm Tracks)Heat Transport
W/m
I. Introduction / b. The dynamical framework
PW
PW
PWPW
I. Introduction / b. The dynamical framework
Partitioning of heat transport from NCEP reanalysis
I. Introduction / b. The dynamical framework
Heat transport partitioning at latitude of maximum heat transport
I. Introduction
II. A simple energy balance model for the seasonal cycle of energy fluxes
III. Dynamical heat transport partitioningIV. Atmospheric heat transport in aquaplanet
simulationsV. Atmospheric Heat Transport in Simulations with
Land-Ocean Contrast and TopographyVI. Conclusions
II. A simple energy balance model for the seasonal cycle of energy fluxes
TROPICS EXTRATROPICS
TS’ BOCE
ASR’
MHT’ = BMHT(T’A,T – T’A,E)
OLR’ = BOLR T’A,E
T’A,E
BCTENTA,E
T’A,T
Primes denote anomaly from global annual mean
Annual mean extratropical energy balance• Global mean energy balance requires:
OLR’ = 0 or T’T = - T’E = ΔT
ΔT -ΔT
TROPICS EXTRATROPICS
•MHT = BMHT2ΔT
•OLR’ = BOLRΔT
•MHT / OLR = 2BMHT/BOLR = 2.3
•Real world ratio is 2.6 (including ocean); we shouldn’t be surprised
ASR’
MHT’
OLR’
II. A simple energy balance model for the seasonal cycle of energy fluxes
II. A simple energy balance model for the seasonal cycle of energy fluxes
Seasonal cycle of extratropical energy fluxes
Asterisks = AGCM simulation
Solid = EBM
Dotted = theoryBased on “B” coefficients
• The seasonal amplitude of extratropical energy fluxes is partitioned into ocean storage (SHF), heat transport (MHT), OLR, and atmospheric storage (CTEN) in the approximate ratio:
lSHF’l : lMHT’l : lOLR’l : lCTEN’l ≈
BOCE : BMHT:BOLR : BCTEN
I. Introduction II. A simple energy balance model for the seasonal cycle of energy fluxes
III. Dynamical heat transport partitioninga. Methodologyb. Spatial and Temporal patterns of variability
IV. Atmospheric heat transport in aquaplanet simulationsV. Atmospheric Heat Transport in Simulations with
Land-Ocean Contrast and TopographyVI. Conclusions
III. Dynamical heat transport partitioning b. Spatial and Temporal patterns of variability
ANNUAL MEAN VERTICALLY INTEGRATED HEAT TRANSPORT
Transient Eddies
Transient Eddies
Stationary Eddies
Stationary Eddies
SEASONAL REGRESSION MAP VERTICALLY INTEGRATED HEAT TRANSPORT
PW
PW
•Units are PW, if the local heat flux existed at all zonal locations
•Seasonal regression takes the zonal mean transient or stationary eddy time series at the latitude of maximum heat transport and regresses it against the spatial map
•OTHER ANAYLSIS- seasonal eofs, inter-annual eofs, interannual variability
I. Introduction II. A simple energy balance model for the seasonal cycle of energy fluxesIII. Dynamical heat transport partitioning
IV. Atmospheric heat transport in aquaplanet simulations
a. Ocean mixed layer depth experimentsb. Longwave emissivity (CO2) experimentsc. Planetary rotation rate experiments
V. Atmospheric Heat Transport in Simulations with Land-Ocean Contrast and Topography
VI. Conclusions
a. Ocean mixed layer depth experimentsIV. Aquaplanet simulations
METHOD: GFDL 2.1 atmosphere (seasonal insolation) coupled to a slab ocean - Vary mixed ocean depth (Dargan)
HYPOTHESIS: Annual mean is unaffected, as the ocean depth increase more seasonal energy goes into ocean storage and the seasonal amplitude of MHT, OLR, and CTEN decrease
Asterisks = AGCM simulation
Lines = EBM simulations
Dotted Lines =B pseudo-steadystate theory
Donohoe and Battisti 2010
b. Longwave emissivity (CO2) experimentsIV. Aquaplanet simulations
METHOD: Vary CO2 from LGM (180 ppm) to 4 times PI (1280ppm) [Dargan]
HYPOTHESIS: - The efficiency of energy export by longwave radiation (BOLR) goes down, in the annual mean and seasonal cycle the ratio of MHT to OLR decreases (infrared opacity)- The efficiency of MHT (BMHT) increases in a warmer world (more moist transport)
b. Longwave emissivity (CO2) experimentsIV. Aquaplanet simulations
Annual Mean Heat Transport
Hea
t T
rans
port
(P
W)
Latitude
QUADPI
180 ppm
c. Planetary Rotation Rates IV. Aquaplanet simulations
METHOD: Vary Earth’s rotation rate from 0.5X to 2.0X the current rotation rate
HYPOTHESIS: With a faster rotation rate, the eddy length scale and efficiency of meridional heat transport (BMHT) will decrease- less heat transport and larger temperature gradient
Dry TransientEddy Heat Transport (1014 W)
Latitude
0.25 Ω
1.0 Ω
EDDY HEAT TRANSPORT AS A FUNCTION OF Ω[Perpetual Annual Mean Insolation, Realistic Topography]
(Del Genio andSuozzo 1986)
I. Introduction II. A simple energy balance model for the seasonal cycle of energy fluxesIII. Dynamical heat transport partitioningIV. Atmospheric heat transport in aquaplanet simulations
V. Atmospheric Heat Transport in Simulations with Land-Ocean Contrast and Topography
a. Land fraction experimentsb. Topography experimentsc. The full gauntlet (realistic climate states)
VI. Conclusions
V. Land-Ocean Contrast and Topographya. Land Fraction Experiments
METHOD: A single extratropical continent with North-South Coastlines and varying zonal width – NO TOPOGRAPHY
HYPOTHESIS: - ENERGETICS: As land mass increases, more seasonal energy goes into the atmosphere, and the seasonal cycle of heat transport increases- DYNAMICS: Zonal heating anomalies induce stationary waves, heat transport partitioning changes, total heat transport (BMHT)?
Solid = EBM simulations
Dashed = Pseudo-steady state theory
V. Land-Ocean Contrast and Topographyb. Topography experiments --- IDEALIZED
METHOD: Aquaplanet with a single idealized mid-latitude topographic feature ofvarying height, meridional location, and zonal width
HYPOTHESIS: - Topography induces stationary wave heat transport - Storm tracks become localized, transient eddy heat transport goes down (seeding?)-Partitioning will change, TOTAL HEAT TRANSPORT?
Mountain Height (km)
Edd
y H
eat
Tra
nspo
rt (
K m
/s)
E
quiv
alen
tly =
0.2
5 P
W
•Dry model, T21
•Newtonian cooling to equilibrium temperature
(Yu and Hartmann, 1995)
V. Land-Ocean Contrast and Topographyb. Topography experiments --- Realistic topography
METHOD: Aquaplanet with flat topography, present day topography, and LGM topography (ICE – 5G, Peltier )
HYPOTHESIS: The partitioning between transient and stationary eddies will change– total heat transport?
Stationary Eddy DRY Heat Transport Transient Eddy DRY Heat Transport
LGM
MODERN
MOD - LGM
Latit
ude 50
5050
50
50 50
-50-50
-50 -50
-50-50
Jan Apr Jul Oct Jan Apr Jul Oct
Jan Apr Jul Oct
Jan Apr Jul Oct
Jan Apr Jul Oct
Jan Apr Jul Oct
PW-2 0 2
PW-1 10
V. Land-Ocean Contrast and Topographyc. The Full Gauntlet (Realistic Climate States)
Method: AGCM (CAM3) simulations of LGM, PI, 4XCO2 forced byprescribed SST and sea ice (from CCSM coupled runs), land ice topography, greenhouse gases, and solar insolation
Hypothesis: (almost) Everything we’ve learned becomes important:1. CO2 experiments2. Land Fraction Experiments (sea ice is like land)3. Topography4. Additionally, the absorbed solar radiation changes, we’ll treat this as a forcing
(CAMILLE LI)
c. The Full Gauntlet (Realistic Climate States)
V. Land-Ocean Contrast and Topography
I. Introduction II. A simple energy balance model for the seasonal cycle of energy fluxesIII. Dynamical heat transport partitioningIV. Atmospheric heat transport in aquaplanet simulationsV. Atmospheric Heat Transport in Simulations with
Land-Ocean Contrast and Topography
VI. Conclusions
QUESTIONS ?