Japan Third Reanalysis Conference 28 January to 1 February 2008.

The flow of Energy through the Earth’s Climate System:
Land and Ocean Exchanges
Kevin E Trenberth and John T. Fasullo
NCAR, Boulder, CO, USACorrespondence: Contact trenbert@ucar.edu
INTRODUCTION
Weather and climate on Earth is determined by the amount and distribution of incoming radiation from the sun.
For an equilibrium climate, outgoing longwave radiation (OLR) necessarily balances the incoming absorbed solar
radiation (ASR), although there is a great deal of fascinating atmosphere, ocean and land phenomena that couple thetwo. Incoming radiant energy may be scattered and reflected by clouds and aerosols or absorbed in the atmosphere.
The transmitted radiation is then either absorbed or reflected at the Earth’s surface. Radiant solar or shortwave energy
is transformed into sensible heat, latent energy (involving different water states), potential energy and kinetic energy
before being emitted as longwave radiant energy. Energy may be stored for some time, transported in various forms,
and converted among the different types, giving rise to a rich variety of weather or turbulent phenomena in theatmosphere and ocean. Moreover, the energy balance can be upset in various ways, changing the climate andassociated weather.
In this paper, the mean and annual cycle of energy flowing into the climate system and its storage, release, andtransport in the atmosphere, ocean, and land surface are estimated with recent observations. The variability is also
considered. An emphasis is placed on establishing internally consistent quantitative estimates with discussion andassessment of uncertainty. At the top-of-atmosphere (TOA), adjusted radiances from Earth Radiation BudgetExperiment (ERBE) and Clouds and the Earth’s Radiant Energy System (CERES) are used. In the atmosphere,reanalyses from the National Centers for Environmental Prediction/NCAR reanalysis (NRA) (Kalnay et al. 1996) andthe second generation European Centre for Medium Range Weather Forecasts (ECMWF) Reanalysis (ERA-40)(Uppala et al. 2005) and recent Japanese Reanalysis (JRA) (Onogi et al. 2007) are used as they contain the mostcomprehensive estimates of global atmospheric temperature and moisture fields. Vertically-integrated quantities forenergy components, the transports, and divergences have been computed and archived.
The net upward surface flux (FS) over ocean is derived as the residual of TOA and atmospheric energy budgets,and is compared with direct calculations of ocean heat content (OE) and its tendency (δOE/δt) from several ocean
temperature datasets. The ocean datasets used to diagnose T include the World Ocean Atlas 2005 (WOA, Locarini etal. 2006), the ocean analysis of the Japanese Meteorological Agency Version 6.2 (JMA, Ishii et al. 2006), and therecently corrected Global Ocean Data Assimilation System (GODAS, Behringer 2006), along with someconsideration of the ECCO (Estimating the Circulation and Climate of the Ocean) analyses (Stammer et al. 2004).
Over land FS from a stand-alone simulation of the Community Land Model forced by observed fields is used.
Comprehensive depiction of the energy budget during the ERBE (February 1985 to April 1989) and CERES (Mar.
2000 to May 2004) periods are constructed that match estimates of the global, global-ocean, and global-land
imbalances. In addition, the annual cycle of the energy budget during both periods is examined and compared withδOE/δt.
The near balance between net TOA radiation (RT) and FS over ocean and thus with OE, and between RT andatmospheric total energy divergence over land, are documented both in the mean and for the annual cycle. However,there is an annual mean transport of energy by the atmosphere from ocean to land regions of 2.2±0.1 PW (1015 watts)
primarily in the northern winter when the transport exceeds 5 PW. The global albedo is dominated by a semiannualJapan Third Reanalysis Conference 28 January to 1 February 2008.

cycle over the oceans, but combines with the large annual cycle in solar insolation to produce a peak in absorbed solar
and net radiation in February, somewhat after the perihelion, and with the net radiation 4.3 PW higher than the annualmean, as it is enhanced by the annual cycle of outgoing long-wave radiation that is dominated by land regions. In situ
estimates of the annual variation of OE are found to be unrealistically large. Challenges in diagnosing interannual
variability in the energy budget and its relationship to climate change are identified in the context of the episodic andinconsistent nature of observations.
RESULTS

Figure1:CERES-period
March 2000 to May 2004
mean
best-estimate
TOAfluxes [PW] globally (centergrey) and for global-land(right,lightgrey)
andglobal-ocean (left) regions. SI
is the solar irradiance and thenet downward radiation
RT =ASR-OLR.
In the figure, the arrows show
the direction of the flow. The
net surface flux is also given
along with the energy flowfrom ocean to land.

Figure 2: a) Global, b) global-ocean, and c) global-landmean annual cycles of albedo (%) and RT (PW) whereshading represents ±2σI of monthly means and theannual mean has been removed. σI is the standard
error from interannual sampling. Values plotted arefrom ERBE and the two CERES instruments on board
Terra (FM1 and FM2). The global albedo drops fromJanuary, which is when perihelion occurs, to February,
so that peak ASR and net radiation occurs in February.
The ocean values tend to follow those in the southernhemisphere which has more ocean, while the land
values follow the northern hemisphere. Over ocean, thealbedo undergoes a semiannual cycle associated withmonsoons and cloud changes. Over land, albedo ishighest in winter in association with snow covervariations and the changing irradiance over Antarctica.

Japan Third Reanalysis Conference 28 January to 1 February 2008.

Figure 3: a) Global, b) global-ocean, and c) global-landestimates of atmospheric total energy divergence (∇•FA) andtendency (δAE/δt) are shown in PW where shading represents±2σI of monthly means and the annual mean is shown (dotted).
Globally the atmospheric divergence is identically zero and theocean and land values are equal but opposite, with maximum
transport in northern winter from ocean to land. Atmosphericstorage variations are small but not negligible.

Figure 4 (right): Global, global-ocean, and global-land estimates of net upwards surface flux (FS) are shown in PW
where shading represents ±2σI of monthly means.
Figure 5: Ocean to land energy
transport in PW as 12-monthrunning means inferred fromERBE and CERES RT over landand NRA δAE/δt fields (see text,dark black). Transports from NRA(thin solid), ERA-40 (dashed) andJRA (dotted) fields are also shown.
Both ERA-40 and JRA experience
major drifts with introduction ofSSM/I observations in July 1987
and transitions of NOAA-9 toNOAA 11 in 1988. ERA-40 values
jump when Pinatubo erupted in1991. All values are influenced by
the TOVS to ATOVS transition in1998 (in JRA) to 2001. As isevident here, agreement is poor among the reanalyses both in absolute terms and for the low frequency variability.
The estimates from the satellite products are more realistic but highlight the errors in the changes from the ERBE toCERES periods in the reanalyses.

Japan Third Reanalysis Conference 28 January to 1 February 2008.

Figure 6. The annual cycle of
TOA radiation (heavy black) can
be compared with the rates ofchange in ocean heat content
storage (grey curves) from 4
different
products.
When
combined with the radiation andchange in land and atmosphericstorage, the residual should bezero (black curves).
The
residuals have a prominent
semiannual cycle and are largest
for the WOA and JMS products,
somewhat improved for GODAS
and best for ECCO. Residuals oforder 1 PW are not unexpectedowing to lack of consideration of sea-ice changes and different periods of the data.

Figure 7: ERBE-period zonal mean annual cycle of meridional energy transport by a) the atmosphere and ocean as
inferred from ERBE RT, NRA δAE/δt, and GODAS δOE/δt, b) the atmosphere based on NRA, and c) by the ocean as
implied ERBE+NRA FS and GODAS δOE/δt. Stippling and hatching in a) through c) represent regions and times ofyear in which the standard deviation of monthly mean values among estimates, some of which include the CERES
period exceeds 0.5 and 1.0 PW, respectively. Also shown (d) is the median annual mean transport by latitude for thetotal (solid), atmosphere (dashed) and ocean (dotted) accompanied with the associated ±2σ range (shaded).

Japan Third Reanalysis Conference 28 January to 1 February 2008.

Figure 8. Comparison of the ocean heat content
analyses from JMA (solid), GODAS (dotted) andECCO (dashed) from 1992 to 2006 when altimetry
estimates were available of sea level. The long-termmean is removed. An estimated imbalance at TOA of0.4 PW which goes into the ocean, implies a change of
1.26x1023 J/decade, similar to the ECCO changes after
1998. As shown here, the decadal variability is poorlyreplicated.

This paper is a summary of work mainly documented in three articles. Fasullo and Trenberth (2008a) provide
an assessment of the global energy budgets at TOA and the surface, for the global atmosphere, and ocean and landdomains based on a synthesis of satellite retrievals, reanalysis fields, a land surface simulation, and ocean temperature
estimates. The TOA budget is constrained to match estimates of the global imbalance during recent periods of satellite
coverage associated with changes in atmospheric composition and climate. There is an annual mean transport ofenergy by the atmosphere from ocean to land regions of 2.2±0.1 PW primarily in the northern winter when thetransport exceeds 5 PW. Fasullo and Trenberth (2008b) go on to evaluate the meridional structure and transports ofenergy in the atmosphere, ocean and land for the mean and annual cycle zonal averages over the ocean, land andglobal domains. Trenberth and Fasullo (2008) delve into the ocean heat budget in considerable detail and provide acomprehensive assessment of uncertainty. As shown here, decadal and longer term variability in both atmosphereand ocean for the energy quantities is poorly replicated and mostly demonstrably wrong. This highlights thechallenges for future reanalyses to improve the way the changing observing system affects the results.
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