Evolution of hurricane Alberto (2000) in the field of - SEOM

Evolution of hurricane Alberto
(2000) in the field of water vapor
over North Atlantic retrieved
from satellite data
D. Ermakov1, E. Sharkov2
(1)
Institute of Radioengineering and Electronics of RAS, Fryazino department, 141195
Vvedenskogo sq. 1, Fryazino, Moscow region, Russia, Email: dima@ire.rssi.ru
(2) Space Research Institute, 117997, 84/32 Profsoyuznaya str., Moscow, Russia,
Email: e.sharkov@mail.ru
Abstract
The hurricanes or tropical cyclones (TC) of the Northern Atlantic often
demonstrate extremely complicated and unpredictable behaviour which
to a certain extent can be explained by the features of the Atlantic
basin: its relative narrowness, active interaction with Polar Region, and
the resulting picture of winds and currents. TC Alberto (2000) with its
three stages of intensification and dissipation is a bright example of
such a complicated behavior. The animated analysis of total precipitable
water (TPW) field reveals a particular interdependence between the
Alberto evolution (in terms of standard meteorological parameters) and
the large-scale features of the TPW field (which can be formally
characterised with convergent/divergent flows of the latent heat
estimated by the authors’ original approach).
Schematic flowchart of data processing
Input remote data (SSM/I F13, F14, F15 27 July – 26 August 2000)
Stage 1: TPW fields calculation
Reference fields (2 daily TWP fields on 0.2° grid)
Stage 2: spatiotemporal interpolation
Animated fields (16 TWP fields on 0.2° grid and 8 vector-ofmotion fields on 0.8° grid per day)
Stage 3: calibration/integration
Derivative characteristics (Latent heat flow)
Issue of precision of TWP estimates
Global TPW distribution on 5 August,
2000 as by (Ruprecht, 1996) (top) and
(Alishouse et al, 1990) (bottom)
A simple formula by (Ruprecht,
1996) was used to recover TPW
values from the SSM/I data.
Though known to somewhat
overestimate higher values of
TPW, it was initially used by us in
testing purposes. As it was later
checked by us in comparison
with other widely used methods
like (Alishouse et al, 1990) it
gave
qualitatively
correct
patterns of TPW distributions, so
that the results of the further
animated
analysis
can
be
considered quite robust though
possibly
requiring
some
recalibration to be more precise.
A thorough analysis of the
influence of the TPW algorithm
onto the results of the overall
data processing is a subject to
further research.
TC Alberto evolution
5
1
7
9
3
TC Alberto evolution: maximum 2
wind speed in the wall, W (red),
and minimum pressure in
8
4
6
10
the eye, P (black); arrows labelled ‘a’…‘k’ indicate stages of the TC illustrated
and analyzed
below; dates by horizontal axis are in MM/DD format. (Pokrovskaya, Sharkov, 2001)
TC Alberto trajectory: colours indicate the
TC stages. (Pokrovskaya, Sharkov, 2001)
Generally, evolution of TC Alberto can be
subdivided into the three stages of
intensification (indicated in as a, d, h), of
maximum intensity (b, e, i), of
weakening (c, f, g) and final dissipation
(j,
k).
Animated
approach
allows
performing a detailed analysis of the TC
evolution in the TPW field over the North
Atlantic and makes it possible to point
out some characteristic features of this
field
correlating
with
the
TC
intensification/dissipation.
a) Generation and fast intensification
P = 994 mbar
W = 28 m/s
11:00
b) First maximum
P = 979 mbar
W = 41 m/s
17:00
c) First dissipation
P = 990 mbar
W = 31 m/s
14:00
d) Second intensification
P = 981 mbar
W = 38 m/s
11:00
e) Second maximum
P = 950 mbar
W = 65 m/s
21:00
f) Second dissipation
P = 990 mbar
W = 31 m/s
17:00
g) Second minimum
P = 1000 mbar
W = 21 m/s
06:30
h) Third intensification
P = 974 mbar
W = 44 m/s
08:00
i) Third maximum
P = 966 mbar
W = 49 m/s
21:30
j) Third dissipation
P = 985 mbar
W = 33 m/s
17:00
k) Collapse
P = 986 mbar
W = 31 m/s
03:00
Latent heat flow estimation
Contours of integration (black
circles) in the TPW field
TC Alberto evolution: maximum
wind speed in the wall, W (red),
and latent heat flow, Q (black);
dates in MM/DD format
The values of latent heat flow Q were calculated as
described in (Ermakov et al, 2013). The contours
of integration were round, centred at the TC eye.
The positive flow corresponds to the direction
towards centre. To check the calculations stability
a pair of contours with similar radii (about 8° of
latitude) was used to obtain two values of Q per
every calculation. The resulting time series of
latent heat flow values were plotted with the time
series of the maximum wind speed value W in the
TC wall (independent data source).
The plot shows that series of Q for both contours
of integration are very close to each other and are
in a remarkable correlation with the series of W.
Generally, positive values of Q (convergence)
correspond to growth of W, while negative values
of Q (divergence) correspond to decrease of W.
Possibly there is some lag between Q (earlier
change) and W series. Yet the plots of Q
demonstrate some “oscillations”. They can reflect
some features of the calculation approach itself
(effects of sampling) or/and a complicated
spatiotemporal structure of the latent heat flow in
the area of investigation and are subject to further
analysis.
Conclusion
The considered case of the TC Alberto evolution reveals a
remarkable interdependence between the phases of its
intensification/dissipation and the convergent/divergent flows in
the TPW field around the TC. Namely, the TC intensification
matches the cases of positive latent heat flow to the region
around the TC, realized by the advective streams of the
atmospheric air saturated with water vapour (typical TPW values
of about 40 mm and higher), while the TC dissipation matches
the cases of destruction of these vapour-saturated streams and
the negative sign of the latent heat flow.
This primary conclusion requires further thorough examination
by collecting representative statistics for multiple cases of TC
intensification/dissipation which is one of the aims of the further
authors’ research.
Important research efforts will focus on a more precise
calibration of the results (including the analysis of initial TPW
estimates), and extending the approach to investigate other
important geophysical characteristics of the atmosphere-ocean
system to integrate them into complex analysis of TC evolution.
Acknowledgements
The authors are grateful to Dr. A.P. Chernushich, I.V. Pokrovskaya and Dr.
M.D. Raev for their useful advices and cooperation in the research.
Microwave measurements of the SSM/I instrument (hereafter the SSM/I
data) were obtained from the Global Hydrology Resource Center (GHRC) at
the Global Hydrology and Climate Center, Huntsville, Alabama, US
(http://ghrc.nsstc.nasa.gov/)
References
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