P2.9
Analyses and Comparisons of Two Reanalyses for Tropical Monthly v -component wind field
Yujing Qin, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China; and P. Wang
Analyses and Comparisons of Two Reanalyses for Tropical Monthly v-component wind field
Qin Yujing ,Wang Panxing
(Nanjing University of Information Science and Technology, Nanjing 210044, China)
Wind field is the most key element in tropic weather and climate
analysis. Monthly mean v-component wind field is of importance for it represents the climatological and anomalous features of tropic meridional cell. Hadley Cell (hereafter
and extensive meridional circulation whose common
upwelling branch's location and intensity are synchronously changed with those
of the intertropical convergence zone (hereafter ITCZ). In this paper, we use
monthly mean OLR minimum band representing ITCZ in order to compare
respectively by v component Wind field of ECMWF and NCEP/NCAR
reanalysis (E data and N data ). Three datasets are chosen in tropic area (30ºS°ª30ºN)
from 1979 to 2001:1) NOAA Interpolated Outgoing Longwave Radiation (OLR)
dimensional)series; 2) ERA-40 monthly mean v component wind field (3 spatial
dimensional) series; 3)NECP1 monthly mean v component wind field (3 spatial
dimensional) series.
On
the basis of Lorenz decomposition principle, OLR of the given and 500hPa vertical speed determined by mass stream function as shown in table 1); among which the Climatological zonal unsymmetrical component month
,
(computed according to E data and N data separately)
are decomposed into 4 independent part (
)is called stationary wave and
the anomalous zonal unsymmetrical component () is called stationary wave anomaly.
Table
1 components of OLR, ,
in
derived from Lorenz
decomposition
classes
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Climatological zonal symmetrical
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Climatological zonal unsymmetrical
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Anomalous zonal symmetrical
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Anomalous zonal unsymmetrical
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Analyses are done from two perspectives
(climatological and anomalous) and we put emphasis on the relationship between ITCZ given by OLR and 500hPa H.C. upwelling branch given by ,
(locations and intensities). Main
results are as followings:
1)The
status of peak location of H.C. upwelling branch given by ,
can be divided into two types: single-peak
pattern and double-peak pattern as well as that of ITCZ given by (fig.1). Also, the months
when they appear respectively are totally consistent with those of ITCZ.
Statistical analyses show that the average latitude departure that E data maximum point departs from
minimum point is 1.25º, less
than the value 1.875º computed from N data analysis portion indicates that related to ITCZ, implying that the tropical v wind field of E data is subtlely superior to that of N data. and
. Thus, the climatological
component wind field are intimately
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Fig.1 The relationship between induced by
(thick solid line) and the
ascending branch of H.C..
a, and
; b,
and
.
2)Using
singular vector decomposition(SVD) method, the correlation between and
(
) in January and July are investigated. In the first spatial modes of
and
, the latitude location of
valley (peak) corresponding
to the maximum (minimum) value of , demonstrating consistence anomalous location
between ITCZ and ascending branch of H.C.. Meanwhile the time coefficients series
of the first spatial modes vary synchronously, with peaks (valleys) according
to simultaneous El Nino (La Nina) events, explaining that tropical SSTA is a
key factor for anomalous ITCZ and H.C., and the correlationship in January is
better than that in July.
3)Using
SVD the relationships between and
°¢
over
the tropic Indian Ocean, western and middle Pacific Ocean(30ºS°ª30ºN,60ºE°ª120ºW)in January and July are analyzed. The first SVD
spatial pattern indicate that Negative s (dark shaded) basically
overlap with positive s,
which mainly assemble in mid-Pacific in January and mitigate to tropical
western Pacific, ocean to the east of the Philippines, coastal regions in
south-east China and the Bengal Bay. The peaks (valleys) of the first SVD modes
time coefficient series are also consistent with El Nino (La Nina) events (except for La Nina in January 1985). The first SVD spatial pattern and time series of and
are similar with those of
and
. These imply that the relationships between
OLR and 500hPa from
two analyses which caused by regional difference of also have obvious physical background.
Poster Session 2, General Climate Studies: Poster Session
Monday, 21 January 2008, 2:30 PM-4:00 PM, Exhibit Hall B
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