Chapter 5: The Ocean Heat Budget
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Transcript Chapter 5: The Ocean Heat Budget
Chapter 5
The Ocean Heat Budget
Physical oceanography
Instructor: Dr. Cheng-Chien Liu
Department of Earth Sciences
National Cheng Kung University
Last updated: 16 October 2003
Introduction
The sunlight reaching Earth
• 1/2 oceans and land
• 1/5 atmosphere
The heat stored by the ocean
• Evaporation and infrared radiation
atmosphere
• Transported by current ameliorate Earth’s
climate development of ice age
The oceanic heat budget
Heat budget
• The sum of the changes in heat fluxes into or out of a
volume of water
• QT = QSW + QLW + QS + QL + QV
The resultant heat gain or loss QT [wm-2]
Insolation QSW, the flux of sunlight into the sea
Net Infrared Radiation QLW, net flux of infrared radiation from the sea
Sensible Heat Flux QS, the flux of heat out of the sea due to conduction
Latent Heat Flux QL, the flux of heat carried by evaporated water
Advection QV, heat carried away by currents
Change in energy
• DE = CpmDT
Cp 4.0 103 J kg-1 0C-1
The oceanic heat budget (cont.)
Importance of the ocean
• During an annual cycle
Cp(Rock) 800 J kg-1 0C-1 0.2Cp(water)
• Exchange heat depth
Water: 100m
Land: 1m
• Exchange heat mass
Water: 1001000 = 100,000 kg
Land: 13000 = 3,000 kg
• Typical change in temperature
Water: 100C
Land: 200C
• Ratio of seasonal heat storage: DEoceans / DEland 100
Heat budget terms
QSW
• Factors influencing QSW
qs = fn(latitude, season, time of day)
Length of day = fn(latitude, season)
The cross-sectional area
The surface absorbing sunlight = fn(qs)
Attenuation
k = fn(clouds, path length, gas molecules, aerosol, dust)
Reflectivity
fn(qs, surface roughness)
• Fig 5.2: surface solar insolation
• Average annual range (Fig 5.3)
30 < QSW < 260 Wm-2
Heat budget terms (cont.)
QLW
• Fig 5.4: Atmospheric transmittance
Greenhouse effect
Greenhouse gasses
• Factors influencing QLW
The clarity of the atmospheric window
fn(clouds thickness, cloud height, atmospheric water-vapor content)
Changes in water vapor and clouds are more important than changes in Tsurface
Water Temperature
Ice and snow cover
• Average annual range
-60 < QLW < -30 Wm-2
Heat budget terms (cont.)
QL
• Factors influencing QL
Vwind
Relative humidity
• Average annual range
-130 < QL < -10 Wm-2
QS
• Factors influencing QS
Vwind
Air-sea temperature difference
• Average annual range
-42 < QS < -2 Wm-2
Direct calculation of fluxes
Gust-Probe Measurements of Turbulent
Fluxes the only method
• Characteristics
On low-flying aircraft or offshore platforms
Usually at 30m height
Need fast-response instruments
Measure u, v, humidity, T
Expensive
Measurements large space or longer time
Only for calibration
• Calculation (Table 5.1: Notation Describing Fluxes)
T = <ru'w'> = r<u'w'> ru*2
QS = Cp<rw't'> = rCp<w't'>
QL = LE <w'q'>
Indirect calculation of fluxes: Bulk
formulas
Bulk formulas
• The observed correlations between fluxes and
variables
T = rCDU102
QS = rCpCSU10 (Ts - Ta)
QL = rLECLU10 (qs - qa)
Ta thermometers on ships
Ts thermometers on ships or AVHRR
qa relative humidity made from ships
qs Ts (assuming saturated air on surface)
CD, CS, CL correlating gust-probe measurements with the variables in the
bulk formulas (Table 5.1: suggested values)
Indirect calculation of fluxes: Bulk
formulas (cont.)
Calculations of each variable
• Wind stress and speed
See chapter 4
Sources of error
Sampling error (insufficient measurements in time and space)
CD
• Insolation
QSW = S(1-A) – C
S = 1365 W m-2
A: albedo
C: constant including absorption by ozone, other gasses and cloud droplets
Sources of error
Angular distribution of sunlight reflected from clouds and surface
Daily variability of QSW
Indirect calculation of fluxes: Bulk
formulas (cont.)
Calculations of each variable (cont.)
• Rainfall (water flux)
Difficulties of ship measurements
Rain falls horizontally and its path is distorted by the ship’s superstructure
Most rain at sea is drizzle difficult to detect or measure
TRMM (Tropical rain measurement mission 1997 –) (Fig 5.5)
Infrared observations height of cloud tops
Microwave radiometer
Re-analyses of the output from numerical weather forecast models
Ship observations
Combinations
Sources of error
Rain rate cumulative rain fall (Sampling error)
Miss storm
Indirect calculation of fluxes: Bulk
formulas (cont.)
Calculations of each variable (cont.)
• Net long-wave radiation
F = <e> (Fd –ST4)
<e> : average emissivity of the surface
Fd : downward flux (from satellite, microwave radiometer data or numerical models)
S : Stefan-Boltzmann constant
F tends to be constant over space and time not necessary to improve
• Latent heat flux
QL = rLECLU10 (qs - qa)
Difficult to measure from satellite (not sensitive to qs)
Two indirect ways to use satellite measurements
Monthly averages of surface humidity water vapor in the air column
SST from AVHRR + water vapor and wind from SSM/I
Indirect calculation of fluxes: Bulk
formulas (cont.)
Calculations of each variable (cont.)
• Sensible heat flux
Ship observations of air-sea temperature difference and
wind speed
Numerical models output
Almost small everywhere
Global data sets for fluxes
COADS NOAA
• Two releases
The first COADS release: 70 million reports (1854 – 1979)
The second COADS release (1980 – 1986)
• 28 elements
Weather, position, …
• Summaries
14 statistics for each of eight observed variables
Ta, Ts, Vwind, Psurface, q, cloudiness
11 derived variables
• Three principal resolutions
Individual reports
Year-month summaries in 20 by 20 boxes
Decade-month summaries
Global data sets for fluxes (cont.)
Satellite data (Table 5.3: levels)
• Operational meteorological satellites
NOAA series of polar-orbiting, meteorological satellites
SSM / I
Geostationary meteorological satellites
NOAA (GOES), Japan (GMS) and ESA (METEOSTATS)
• Experimental satellites
Nimbus-7, Earth Radiation Budget Instruments
Earth Radiation Budget Satellite, Earth Radiation Budget Experiment
The European Space Agency's ERS-1 & 2
The Japanese Advanced Earth Observing System (ADEOS)
Quicksat
The Earth-Observing System satellites Terra, Aqua, and Envisat
Topex/Poseidon and its replacement Jason-1.
Global data sets for fluxes (cont.)
International Satellite Cloud
Climatology Project
• Collect observations of clouds
by dozens of meteorological satellites (1985 – 1995)
Using visible-light instruments on polar-orbiting and
geostationary satellites
• Goals
Calibrate the the satellite data
Calculate cloud cover using carefully verified techniques
Calculate surface insolation
Global data sets for fluxes (cont.)
Global Precipitation Climatology Project
• Three sources of data rain rate
Infrared observations (GOES) the height of cumulus clouds
The basic idea: the more rain produced by cumulus clouds, the higher the cloud top, and
the colder the top appears in the infrared. Thus rain rate at the base of the clouds is related
to infrared temperature
Measurements by rain gauges on islands and land.
Radio-frequency emissions (SSM/I) from atmospheric water droplets
• Accuracy: 1 mm/day
• Data available:
2.50 2.50 grid from July 1987 to December 1995 (NASA GSFC)
• Xie and Arkin (1997)
A 17-year data set based on seven types of satellite and rain-gauge data
combined with the output from the NCEP/NCAR reanalyzed data from
numerical weather models
Global data sets for fluxes (cont.)
Reanalyzed Data From Numerical Weather
Models
• Calculated from weather data using numerical
weather models by various reanalysis projects
• Recent suggestions on the data
Biased fluxes, The time-mean model outputs ship observations
More accurate in the northern hemisphere
Zonal means differences > 40 Wm-2 between model and COADS data
ECMWF data set averaged over 15 years gives a net flux of 8 Wm-2 into
the ocean
• Summary
Reanalyzed fluxes forcing ocean, GCM
COADS data calculating time-mean fluxes
Geographic distribution of terms in
the heat budget
Figure 5.6
• The mean annual radiation and heat balance
Top of the atmosphere: Insolation = infrared radiation
342 = 107 + 235
At the surface, latent heat flux + net infrared radiation =
insolation
168 + 324 = 390 + 24 + 78
Sensible heat flux is small
The sunlight reaching Earth
1/2 (168 / 342) oceans and land
1/5 (67 / 342) atmosphere
Driving of the atmospheric circulation
Thunderstorms are large heat engines converting the energy of latent heat into
kinetic energy of winds
Geographic distribution of terms in
the heat budget (cont.)
Fig 5.7
• The zonal average of the oceanic heat-budget terms
Zonal average: an average along lines of constant latitude
QSW = max at EQ
QS is small
The areal-weighted integral 0
errors in the various terms in the heat budget
Can be reduced by using additional information (constraint)
Heat and fresh water transport
Fig 5.8: annual-mean QSW and QLW
Fig 5.9: annual-mean QL
Fig 5.10: annual-mean QS
Meridional heat transport
Meridional transport
• North-south transport
Meridional heat transport
• the divergence of the zonal average of the
heat budget measured at the top of the
atmosphere
• satellite
• Assumption: steady state
Meridional heat transport (cont.)
Heat Budget at the top of the Atmosphere
• Measurement
Insolation meteorological satellites and by special satellites (e.g. the
Earth Radiation Budget Experiment Satellite)
Back radiation infrared radiometers
The net heat flux across the top of the atmosphere = insolation - net
infrared radiation
• Calculation
Average the satellite observations zonally zonal average
Calculate their meridional derivative the north-south flux divergence
Divergence = the heat transport by the atmosphere and the ocean
• Errors
Calibration of instruments
Inaccurate angular distribution of reflected and emitted radiation
Meridional heat transport (cont.)
Oceanic Heat Transport
• Three methods
Surface Flux Method
Measurements: wind, insolation, air, and sea temperature, and cloudiness
Bulk formulas the heat flux through the sea surface
Integration the zonal average of the heat flux (Figure 5.7)
the meridional derivative the flux divergence = heat transport in the ocean
Direct Method
Measurements: current velocity and temperature from top to bottom along a zonal section
spanning an ocean basin the heat transport
The flux = northward velocity heat content
Residual Method
Measurements: atmospheric measurements or the output of numerical weather models
the atmospheric heat transport
The oceanic contribution = the top-of-the-atmosphere heat flux (satellite) - the
atmospheric transport (Figure 5.11)
Meridional fresh water transport
The Earth's water budget
• Dominated by evaporation (86%) and
precipitation (78%) over the ocean
• A map of the net evaporation (Fig 5.12)
• Meridional transport of fresh water by the
Atlantic (Fig 5.13)
Same calculation as the heat transport
• Significance
Understanding the global hydrological cycle, ocean
dynamics, and global climate
Variation in solar constant
Solar constant constant
• Sunspots and faculae (bright spots)
the output varied by ± 0.2% over centuries
the changes in global mean temperature of Earth's
surface of ± 0.4°C (Fig 5.14)
• A small 12yr, 22yr, and longer-period
variations of SST
measured by bathythermographs and ship-board
thermometers over the past century
• Solar variability climate change ?
Important concepts
• Sunlight is absorbed primarily in the tropical ocean.
The amount of sun-light changes with season, latitude,
time of day, and cloud cover.
• Most of the heat absorbed by the oceans in the tropics
is released as water vapor which heats the atmosphere
when water is condenses as rain. Most of the rain falls
in the tropical convergence zones, lesser amounts fall
in mid-latitudes near the polar front.
• Heat released by rain and absorbed infrared
radiation from the ocean are the primary drivers for
the atmospheric circulation.
Important concepts (cont.)
• The net heat flux from the oceans is largest in midlatitudes and offshore of Japan and New England.
• Heat fluxes can be measured directly using fast
response instruments on low-flying aircraft, but this is
not useful for measuring heat fluxes over oceanic
areas.
• Heat fluxes through large regions of the sea surface
can be calculated from bulk formula. Seasonal,
regional, and global maps of fluxes are available
based on ship and satellite observations.
Important concepts (cont.)
• The most widely used data sets for studying heat
fluxes are the Comprehensive Ocean-Atmosphere
Data Set and the reanalysis of meteorological data by
numerical weather prediction models.
• The oceans transport about one-half of the heat
needed to warm higher latitudes, the atmosphere
transports the other half.
• Solar output is not constant, and the observed small
variations in output of heat and light from the sun
seem to produce the changes in global temperature
observed over the past 400 years.