Usage of Atmospheric Reanalysis Data for Dynamical Diagnoses of
the Atmospheric Circulation and Climate Variability
Hisashi Nakamura1,2, Y. Kosaka1, D. Hotta3, K. Nishii1, T. Miyasaka1 and K. Takaya2
1

Department of Earth and Planetary Science, University of Tokyo, Japan
2
Frontier Research Center for Global Change, JAMSTEC, Japan
3
Forecast Department, Japan Meteorological Agency, Japan
Correspondence: hisashi@eps.s.u-tokyo.ac.jp

INTRODUCTION
The release of the first global atmospheric reanalysis project by the U.S. National Centers for Environmental
Prediction (NCEP) and U.S. National Center for Atmospheric Research (NCAR) (Kalnay et al. 1996) has exerted
an epoch-making impact on our data analysis study of the large-scale atmospheric circulation and its variability.
Since then, several global atmospheric reanalysis datasets have been released, including the NCEP-Department ofEnergy (DOE) reanalysis (Kanamitsu et al. 2002), European Centre 40-year Reanalysis (ERA40; Uppala et al.
2005) and Japanese 25-year Reanalysis (JRA-25; Onogi et al. 2005, 2007). Compared to conventional operational
analyses of the atmosphere, those reanalysis datasets have several advantages with which our understanding of thelarge-scale atmospheric circulation and its variability has been deepened. The advantages include (i) availabilityof 6-hourly global analysis of the global atmospheric state over decades with relatively high, uniform quality, (ii)availability of variables at more vertical levels than in conventional analysis, and (iii) inclusion of various
model-diagnosed variables that were not available widely to the community in conventional analysis. In this paper,
examples are presented where our diagnoses were benefited from those advantages of the reanalysis datasets inapplication of modern diagnostic methods.
EXAMPLE 1: SUMMERTIME TELECONNECTION ASSOCIATED WITH ANOMAOUS
CONVECTIVE ACTIVITY OVER THE NORTHWESTERN PACIFIC (P-J PATTERN)
A fixed configuration of a forecast model used for a reanalysis and assimilation of satellite-measured wind andthermal fields throughout the period since the 1980s provide the global atmospheric circulation fields over aquarter of the century. It is particularly beneficial in study of climatic phenomena and monthly or seasonal
anomalies in the Tropics and Southern Hemisphere. The following is an example where analysis of reanalysis data
has revealed essential dynamics of an atmospheric teleconnection pattern associated with tropical convective
anomalies. Analyzing six years of monthly operational analysis data with resolution of 10° both in latitude and inlongitude and only four pressure levels, Nitta (1987) found a Pacific-Japan (PJ) teleconnection patterncharacterized by a pressure seesaw between the tropical northwestern Pacific and Japan and accompanied byanomalous convection near the Philippines. His claim that the pattern exhibits an equivalent barotropic structurearound Japan and the first baroclinic structure in the Tropics has been believed in the community until Kosaka andNakamura (2006) analyzed its three-dimensional structure based on monthly reanalysis data for a 25-year period.
They showed that, unlike what Nitta (1987) claimed, its structure is characterized by vorticity anomalies with theiraxes tilting poleward tilting with height, which could not have been revealed without the usage of long-term
reanalysis data with sufficiently high spatial resolution. Kosaka and Nakamura (2008) have confirmed that thecharacteristic vertical structure of the PJ pattern can be recognized in each of the four reanalysis datasets(NCEP-NCAR, NCEP-DOE, ERA-40, JRA-25) and that dry energetics, i.e., conversions of kinetic energy (KE)and available potential energy (APE) from the three-dimensional climatological mean state into the PJ-associatedanomalies, is quite consistent among the four datasets. At the same time, they have shown substantial
discrepancies in APE generation due to anomalous convection among three out of the four datasets available forthem, which arose not only from uncertainties in convective diabatic heating evaluated in forecast models but also
from discrepancies in spatial correlation between anomalies in diabatic heating and temperature within the deep
tropics. This is a typical example that shows strong model dependency of diabatic heating fields. Using the
NCEP-DOE reanalysis, Kosaka and Nakamura (2006) showed the primary importance of dry energy conversion
for the maintenance of the PJ pattern, to reveal its characteristics as a dry dynamical mode. Results of Kosaka andNakamura (2008) suggest that the APE generation by anomalous convection and the energy conversion from themean state can be equally important in the maintenance of the monthly PJ pattern, which is thus likely to possesscharacteristics of both dry and moist dynamical modes. Nevertheless, a quantitative assessment of the relative
importance between the dry and moist processes requires further improvement in evaluation of diabatic heating inreanalysis. Refer to Kosaka’s paper (2008) in this abstract volume for more specifics.
EXAMPLE 2: DIAGNOSES OF THERMAL FORCINGS ON SUMMERTIME SUBTROPICALANTICYCLONES AND LOW-LEVEL BAROCLINICITY ALONG STORM TRACKS
Another advantage of the reanalysis datasets lies in the inclusion of separate contributions to diabatic heatingfrom various physical processes due to cumulus convection, large-scale condensation, radiation, surface fluxes
among others. Of course, their model dependency and uncertainties have to be realized, and the usage of thosevariables therefore requires a certain level of caution. Nevertheless, the reanalysis data provide us with a unique
opportunity to make a qualitative assessment on which diabatic heating contribution is the primary thermal
forcing on a given atmospheric phenomenon. An evaluation of the total diabatic heating distribution has beenpossible based on conventional operational analysis through thermodynamic equation. Though may be moreaccurate than its counterpart provided in (re)analysis, the diabatic heating thus evaluated indirectly cannot be
decomposed into the individual contributions.
As an example of such an assessment as above, Wu and Liu (2003) examined longitudinal dependency ofvertical profiles of various diabatic-heating contributions within the summertime subtropics for each of thehemispheres based on the NCEP/NCAR reanalysis. They found that subtropical anticyclones are associatedlocally with shallow low-level radiative cooling over the ocean and with upward sensible heat flux from theheated continents to their east. Miyasaka and Nakamura (2005) incorporated the zonally symmetric component of
diabatic heating and the zonal-mean flow, both based on the July climatology of the NCEP-DOE reanalysis, into a
nonlinear atmospheric planetary wave model (Rodwell and Hoskins, 2001). They have shown that each of thesurface subtropical anticyclones, whose center is situated in the eastern portion of a particular ocean basin, isforced primarily with a local low-level heating/cooling couplet that consists of near-surface heating over thewestern portion of the continent and low-level maritime cooling off the coast. Inspection of diabatic heating
contributions has revealed that this couplet, which reflects a pronounced zonal land-sea thermal contrast across thewest coast of a subtropical continent, is a manifestation of heating due mainly to sensible heat flux over the dry,heated continent and cloud radiative cooling off the coast. This result is consistent with Wu and Liu (2003), but
inconsistent with Rodwell and Hoskins (2001), who emphasized the primary role of monsoonal deep heating to
the east of an anticyclone. Miyasaka (2008; in this abstract volume) has confirmed the conclusion of Miyasaka nd
Nakamura (2005), by incorporating the corresponding diabatic heating fields based on the JRA-25 data to thesame planetary wave model. At the same time, the surface anticyclonic response to the JRA-25 heating/coolingtends to be slightly weaker than that to the NCEP-DOE heating/cooling, which appears to be due to stronger
vertical diffusion counteracting on radiative cooling with low-level maritime clouds in the JRA-25 data.
Another example can be found in our latest assessment of the maintenance mechanism of near-surface
baroclinicity observed along mid-latitude storm tracks. Though indicated theoretically as the necessary condition

for baroclinic instability in a realistic circumstance, the critical importance of the near-surface baroclinicity for the
successive development of baroclinic disturbances along the storm tracks has not been pointed out observationally
until the availability of thermal data at the 925-hPa level in the reanalysis data (Nakamura and Shimpo, 2004).
Hoskins and Valdes (1990) was the first to make this kind of assessment, by incorporating the zonallyasymmetric component of diabatic heating into a planetary wave model. In their assessment the heating had beenobtained as the residual of thermodynamic equation. They showed that latent heat release associated withindividual cyclones is organized along a storm rack over a particular ocean basin to act as a thermal forcing ofplanetary waves. They showed that the resultant planetary wave response act to maintain near-surface
baroclinicity, suggestive of a self-maintaining nature of a storm track with a moisture supply into cyclones from awarm ocean current south of the baroclinic zone. To verify the conclusion of Hoskins and Valdes (1990), we haverecently performed a similar diagnosis with a planetary wave model in which contributions to the zonallyasymmetric diabatic heating from individual processes are assigned separately as a thermal forcing. Ourassessment indicates that the near-surface baroclinicity, which is strongest across a midlatitude oceanic frontal
zone, can be maintained much more effectively by surface sensible heat flux than by latent heat release associatedwith storms. This result is inconsistent with the assessment by Hoskins and Valdes (1990) but consistent with ahypothesis by Nakamura et al. (2004), who emphasized the primary importance of differential heat supply fromthe ocean across an oceanic frontal zone for the maintenance of the near-surface baroclinicity along a storm track.
EXAMPLE 3: PROPAGATION OF ROSSBY WAVE PACKETS THROUGH LOCALIZED VERTICALWAVEGUIDES: A NEW ASPECT OF TROPOSPHERE-STRATOSPHERE DYNAMICAL LINKAGE
Increased vertical resolution of the reanalysis data relative to conventional operational analyses is beneficial
also in study of troposphere-stratosphere dynamical linkage through quasi-stationary Rossby wave packets.
Confined zonally, their propagation should be sensitive to both latitudinal and longitudinal structure of westerly
jets and associated static stability around the tropopause level. Through their analysis of the NCEP/NCAR
reanalysis, Nishii and Nakamura (2004) have found that intra-seasonal height fluctuations along thelower-stratospheric polar night jet (PNJ) in the southern hemisphere during late winter and early spring of 1997
were mainly associated with Rossby wave packets that had propagated from localized tropospheric anomalies.
Their upward propagation was through localized waveguides ("chimneys"). Using the same data, Nishii andNakamura (2005) have presented pieces of observational evidence that part of wave activity associated with awave packet along the PNJ can propagate downward through a "chimney" to force a tropospheric circulation
anomaly locally, yielding zonal teleconnection from a tropospheric anomaly in a given region to another
tropospheric anomaly in a distant region via the stratospheric PNJ. Nishii (2008; in this abstract volume) has
conformed the downward propagation of Rossby wave packets. However, he has also found some subtle
differences in the three dimensional structure of "chimneys" as revealed among the reanalysis data sets. The
differences may result from those in stratospheric temperature fields that arise from model biases used in thereanalyses. The model biases become apparent in the analyses when satellite measurements for the stratosphere
are missing.
EXAMPLE 4: FORMATION OF COLD SURFACE ANTICYCLONES ASSOCIATED WITH
EXTERNAL ROSSBY WAVE TRAINS
Increased vertical resolution in the troposphere in the reanalysis datasets (and forecast models used) is also
beneficial in application of such a modern dynamical diagnosis as potential vorticity inversion (Hoskins et al.
1985) or a wave-activity flux for stationary Rossby waves (Takaya and Nakamura, 2001) that requires second
vertical derivative of streamfunction anomalies. Combining those two diagnostic tools, Nakamura and Fukamachi(2004) examined how a cool surface anticyclone develops in summer over the Sea of Okhotsk in the presence of a

blocking anticyclone aloft. They showed that the accumulation of the surface cold anomaly results from cold-air
advection by anomalous easterlies induced by the tropopause-level anticyclonic PV anomaly associated with theblocking ridge that has developed to the north of the Sea. The advection occurs across the strong zonal thermal
gradient between the warm Asian Continent and the cool sea surface of the Okhotsk. Essentially the samemechanism is found operative in the extreme intra-seasonal amplification of the Siberian High (Takaya andNakamura, 2005). An upper-level pressure ridge and a trough to the east develop as components of aquasi-stationary Rossby wavetrain, inducing anomalous northeasterlies at the surface. Acting on tight thermal
gradient to the north of the Tibetan Plateau, they advect extremely cold air from Northeastern Siberia to amplify
the cold surface anticyclone. The development of both the Siberian and Okhotsk Highs can thus be interpreted asinteraction of an external Rossby wavetrain with surface baroclinicity, through the incipient equivalent barotropic
anomalies turn into more baroclinic structure and thus they can extract available potential energy from thebaroclinic background state. One of the major differences between the developments of those highs can be foundin the strength of their upward influence. The surface cold anomaly associated with the Siberian High issubstantially stronger than its counterpart associate with the Okhotsk High, reflecting the corresponding difference
in background baroclinicity that is much stronger in winter. Acting as an anticyclonic anomaly, the stronger cold
surface anomaly in winter can induce stronger circulation aloft. Acting on tight vorticity gradient associated with
the intensified westerly jetstream, the induced northerlies over the Far East yield anomalous cyclonic vorticity
advection, reinforcing the cyclonic anomaly associated with the wavetrain (Takaya and Nakamura, 2005). In
contrast, under much weaker upper-level vorticity gradient, the cool surface anomaly associated with the Okhotsk
High cannot exert significant influence in the upper troposphere.
SUMMARY
In this paper we have presented several examples where the usage of reanalysis datasets has contributed to our
deeper understanding of the atmospheric circulation and its anomalies with combination of modern dynamical
diagnostic tools. At the same time, those examples have revealed uncertainties in quality of the reanalysis data,
especially in diabatic heating fields that are strongly dependent of model representation/parameterization of
cumulus convection, cloud formation and radiation. A more quantitative assessment of the uncertainties indiabatic heating requires a carefully designed diagnosis, including evaluation of vertical motion based, forexample, on nonlinear balance equation before performing heat budget analysis, although another uncertainty may
arise from that evaluation. We also found that stratospheric thermal fields that are sensitive to model bias in theabsence of satellite-derived thermal fields can cause subtle differences in localized vertical waveguide structures
diagnosed in the reanalysis data. Therefore, we have to exercise our caution when interpreting our diagnosis if
based on any of those model-dependent variables.
Despite those shortcomings, our community has been benefited from the reanalysis datasets. Hopefully, thenext generation reanalysis data will become available near future, where we expect more than just providing
longer series of data fields. Our expectation includes (i) higher quality in the model-dependent variables throughimprovement in forecast models and data assimilation procedures, (ii) reanalysis based on coupled
ocean-atmosphere models for more consistent representation of ocean-atmosphere interaction, and (iii) the
inclusion of ensemble forecast fields for better assessment of predictability of extreme events and thereby deeper
understanding of the dynamics behind.

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