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It is shown that simple persistence or climatology of the 200 mb winds south of a TUTT axis is superior to the Aviation model's 48 h forecast. Until this bias in the AVN is successfully removed, the tropical cyclone forecaster for the Atlantic basin should be aware of this systematic error and make subjective changes in his/her forecasts. For 200 mb west winds 10 ms-1, forecasts based on persistence are best, while for west winds < 10 ms-1, half climatology and half persistence is the preferable predictor. If the TUTT is weak such that 200 mb easterly winds occur, climatology tends to be the best predictor as it nudges the forecast back to a normal westerly wind regime.
In the science of tropical cyclone (TC) forecasting, three key components - genesis, intensification, and on occasion movement - are dependent upon an accurate assessment of current and future upper tropospheric (200 mb) winds. Therefore knowing the strength and location of the Tropical Upper Tropospheric Trough (TUTT; Sadler 1976b) are crucial pieces of information for the TC forecaster.
TUTTs often can inhibit the formation of TCs by allowing large amounts of vertical wind shear (VWS) to be positioned directly over the prestorm disturbance. VWS can be quantified in the following manner:
|
where u and v are the zonal and meridional wind components at each
grid point, respectively, for the 200 and 850 mb levels.
According to equation (1), westerly flow at 200 mb
superimposed over easterly tradewind flow at 850 mb will give high VWS
values. Therefore, VWS south of a TUTT axis is usually large.
Likewise, a tropical disturbance in a deep tropospheric
easterly flow has a better chance of development if
u850 and u200 are similar in magnitude, since this will yield
low VWS values. Values of VWS 10 ms-1 are generally considered
to be great
enough to inhibit TC genesis by advecting upper level moisture
and temperature anomalies away from the low-level disturbance center
(Zehr 1992).
In contrast, the TUTT and associated cold lows
may enhance the possibility of genesis
by importing upper-level angular momentum
(Pfeffer and Challa 1992) and/or upper-level potential vorticity
(Montgomery and Farrell 1993) over the prestorm disturbance
if the VWS remains below the 10 ms-1 threshold.
Sadler (1976a) also found that directly below the divergence
sector of the TUTT a surface disturbance may be induced in a trade wind
regime which could then develop into a TC. Sadler (1976b) proposed a
comparable genesis mechanism for the monsoon trough region.
Ramage (1959) also found that a TUTT cell could transform itself into
a TC.
Similarly, the competing effects of VWS
and angular momentum eddy fluxes by TUTTs and mid-latitude
troughs are also hypothesized
to affect TC intensification (Molinari and Vollaro 1989)
once genesis has occurred.
In a quantitative treatment of the
problem, DeMaria et al. (1993) found that VWS has a strong negative
influence on intensification, and that the momentum eddy fluxes have
a positive yet much weaker effect on TC intensity change.
Sadler (1978) notes the proper positioning of a TC's outflow channel
with respect to a TUTT may encourage intensification by efficiently
removing mass from the eyewall region, especially for a
dual outflow situation. Additionally, Chen and Gray (1986) have extensively
discussed the different upper tropospheric outflow characteristics
associated with TC intensification.
Finally, it is generally accepted that the motion of
the TC is primarily
the result of the deep layer flow in which it resides, usually taken
to be from 850 to
200 mb (Elsberry 1987). Velden and Leslie (1991) have suggested, however,
that tropical
storms and weak hurricanes (central pressure > 975 mb)
are generally guided by flow lower (850 to 500 mb)
in the atmosphere.
While TUTTs are primarily maximum in strength at 200 mb,
many times they can extend into the mid-troposphere.
Thus, they can often influence the current and future motion of a
nearby TC of any intensity.
It has also been shown
recently that the infringement of a deep baroclinic layer of
westerly winds upon a TC can be a precursor to
recurvature, since this usually precedes encroachment of deeper
westerly flow close to the poleward side of the
storm center (Hodanish and Gray 1993).
Therefore, poor forecasting of any upper-level wind characteristic can
result in degraded motion predictions.
From this discussion, it is clear that the upper
tropospheric flow is very important in many forecasting aspects of TCs.
The aim of this paper is to examine the forecasting skill of the National
Meteorological Center's Aviation (AVN)
model with respect to the tropical North Atlantic 200 mb flow and its
handling of the TUTT and embedded cold lows. The next section will discuss
the structure, climatology, and hypothesized
causes of the TUTT, and it describes
the AVN model and the systematic biases that have been identified in the
tropical predictions of this model. Section 3 details a 200 mb AVN easterly
wind bias in the Caribbean basin during the peak hurricane season
and shows
that currently persistence and climatology are better 200 mb wind
forecast tools.
The final section relates these
findings to the context of TC forecasting and provides hypotheses
which may explain the biases found.
One of the more intriguing tropical weather features
in the summer
oceanic climatology is the TUTT. The TUTT is a semi-permanent summertime
feature of the North Atlantic, South Atlantic, North Pacific and South Pacific.
It is a shallow, cold core trough that is oriented across
the subtropical and tropical portions of these oceans (Whitfield and
Lyons 1992). The maximum intensity of the cold core of the TUTT exists
at roughly 300 mb while the vorticity maximum is located
approximately at 200 mb below strong upper tropospheric and lower
stratospheric subsidence-forced warming, as shown in
Fig. 1. TUTTs and
associated cold lows are thought to be maintained by radiational
cooling which causes this upper tropospheric subsidence,
as is required to maintain
atmospheric thermal balance in the mid-ocean regions during the
summer.
Defining Q as the contribution from sensible, latent, and
radiative heating rates and cp as the specific heat at constant pressure,
estimates of the total diabatic heating rate per unit mass
Q/cp are as strong as -6 K day-1 in the vicinity
of the TUTT (Geller and Avery 1978).
Little research has been conducted to explain the seasonal
cycle of the TUTT, but one possible scenario for the North Atlantic
is as follows.
During the summer, continental convection increases
due to higher sensible heat flux (Jaeger 1976; Peixoto and Oort
1992), transporting heat and moisture
upwards (in the form of latent heat) which more than balances radiational
cooling. Observations show that Q/cp in the mid and upper
troposphere over continents are about 1-2 K day-1 in the
summer (Schaack et al. 1990; Geller and Avery 1978).
However, precipitation decreases (on average) over the subtropical
ocean in the warmer months. For example, at the climatological
position of the TUTT maximum (30° N and 50° W), seasonal
winter rainfall is 300 mm compared to 170 mm in the summer (Dorman and
Bourke 1981).
Therefore, the upper tropical atmosphere experiences
net cooling due to radiational losses in the summer, and
subsidence occurs to maintain thermal
balance. In turn, this upper-tropospheric subsidence dries the
atmosphere, creating large long-wave radiation flux divergence
which further enhances cooling. It is through this feedback
process and the strong continental/oceanic
gradient of Q/cp that the TUTT may be initiated.
The TUTT dissipates in the fall as Q/cp decreases due to
less continental convection, increasing oceanic convection,
and baroclinic intrusions into the tropics.
More research on the summer genesis and maintenance of the TUTT
needs to be conducted to determine the specific role of these and
other processes.
In the North Atlantic, the TUTT first develops in
June, strengthens in July
and August, and dissipates in September and October. In its climatological
position, the trough axis tilts from the central North Atlantic into
the Gulf of Mexico as shown for mean August conditions in
Fig. 2.
Smaller scale (few hundred kilometers) closed circulations - cold lows or
TUTT cells - form within the TUTT and move to the south and west along the
TUTT axis throughout the summer. It
is these strong cold lows that are most important in regards to
tropical cyclone forecasting because they are associated with
maxima in VWS and horizontal eddy momentum fluxes.
The National Meteorological Center's AVN model has evolved
through a number of changes and upgrades during its existence. It is
a global spectral model run on a 12 h cycle after assimilating all
available data 2 h 45 min after the synoptic time (Peterson and Stackpole
1989). The analysis/forecast/postprocessing
then takes about 2 h to complete. Forecasts are generated
out to 72 h from the initialization time. The medium-range
forecast model (MRF) is essentially the same model as regards to its
construction as the AVN, except
that the MRF is run only once daily from 00
UTC after collecting 9 h worth of data. As of 1990,
the AVN had a horizontal resolution of T126 which corresponds
to a horizontal resolution of 105 km, mean
orography, and observed 2° resolution sea-surface temperatures
updated once a week (Kanamitsu et al. 1991). According to Kanamitsu
et al., changes were made to the marine-stratus parameterization,
mass-conservation was
improved, and horizontal diffusion was reduced in medium scales. In addition,
on 11 August 1993, the number of levels in the vertical was increased to
28 and an Arakawa-Schubert convective parameterization
scheme with moist downdrafts was implemented in the model.
This new scheme is a slight modification of that
described in Grell et al. (1991) which further enhances
boundary layer forcing and modifies downdraft levels
in accordance with the greater resolution near the surface of the AVN
(H. Pan, personal communication).
In a study on the systematic errors of the MRF
model, Rosen et
al. (1991) found that the model experienced a large bias in the tropical
upper troposphere with the easterlies becoming much too strong when the
MRF was run out to 10 days. They also found that this bias was observable
even in a two day forecast. Apparently, this type of systematic
error is a common one for operational
global spectral models as the same unrealistic overproduction of tropical
upper level easterlies
was identified in the European Centre for Medium Range Weather Forecasts
(ECMWF) model (Bengtsson 1991). According to Rosen et al.,
it is unlikely that new computational
procedures introduced in the last few years have created this bias, as
earlier versions of global forecast models have also experienced this
problem.
However, beyond this general identification of an easterly
bias in the tropical troposphere, specifics about the longitudes, times of
year, and synoptic conditions (including periods when the TUTT is present)
when this problem was most severe are, to our knowledge, lacking. The
next section details our findings for the tropical North Atlantic during
the hurricane-prone months of August and September for the year 1993.
Real-time AVN output data for the following analyses
were received locally
via the Numerical Products Service (NPS) satellite broadcast through the
Alden/Zephyr Weather Incorporated downlink system. Unidata's Local Data
Management (LDM) version 4 software decoded the incoming NPS gridded data
to General Meteorological Package (GEMPAK) version 5.1 format
(desJardins et al. 1991). The data were provided to us with a grid
spacing of 2.5° latitudinally and 5° longitudinally. Graphical
hardcopy GEMPAK images were generated automatically when the AVN output
arrived.
Starting in early August 1993,
AVN analyses and forecast fields for the 48 h forecast for 850 and 200
mb were saved when data were received. (Note that over 90% of the data
analyzed in this study was
collected after the implementation of the new convective parameterization
scheme on 11 August 1993.) The 48 h forecast fields were selected,
since this lead time provides
key information for crucial tropical cyclone forecast decision making, such as
the placement of watches and warnings (Sheets 1990).
From early August through late September 1993, a total of 63 cases that
contained the analyses, forecast fields, and their verification were available.
On the whole, data availability for the initial time analyses
were very good. Within the region of the climatological TUTT axis, there
exists several reliable rawindsonde stations, numerous jet aircraft reports,
and many cloud track wind vectors (from cirrus) at 200 mb every synoptic time.
A typical analysis contains between 15 and 25 observations in the crucial 10° to 30° N, 60 to 80° W region. No systematic difference between
00 UTC and the
12 UTC data availability was detected. Thus the ability of the Aviation
analysis was more than adequate to pick out synoptic-scale features,
such as the TUTT.
It was found that the upper tropospheric
forecast flow fields in the vicinity of the climatological position of
the TUTT were biased toward stronger easterlies than what
verified. The low-level forecast flow fields were, in general,
observed to have very little systematic bias.
Figure 3 provides an example of
the behavior of the AVN when a strong TUTT is observed in the initial analysis
time. On 00 UTC 1 September, the 200 mb flow shows a strong TUTT
extending from near 30° N and 50° W southwestward into the
Caribbean Sea, westward to Central America, and then northwestward into eastern
Texas (Fig. 3a). The TUTT also
has a cold low along its axis centered
at 22° N and 58° W.
Maximum westerly winds south of the TUTT axis in the Caribbean Sea
are on the order of 15 ms-1.
Figure 3b shows the 200 mb
forecast field valid on 00 UTC 3 September. The
AVN completely dissipates the TUTT leaving only a weak cold low near
23° N and 65° W, replacing the TUTT westerlies with
weak to moderate easterly
flow associated with the subtropical ridge to the north.
However, in the verification of the 200 mb forecast field
(Fig. 3c),
the TUTT is still strongly present on 00 UTC 3 September.
The TUTT axis is in nearly the same location with the same magnitude of
westerlies south of the axis. One new feature is the anticyclone over
northern South America. This feature also was not forecast by the AVN.
Since the 850 mb was observed to have very
little bias (not shown), errors in the vertical wind shear (VWS) -
the critical measure for TC genesis and intensity forecasting - are
dominated by the errors at 200 mb. Shear values were calculated from
the AVN for the initial time period and the 48 h prediction fields by
using equation (1).
Figure 4 demonstrates the large
magnitude of error (observed
minus forecasted VWS) that was found for the 48 h AVN forecast verifying
on 00 UTC 3 September. A wide region near the Caribbean Sea
experienced 8 ms-1 or greater error in the forecast VWS
field. Note that the locations of large positive errors correspond extremely
well with the regions of observed westerly winds south of the TUTT
axis. It is also possible that the unanticipated development of
the South American anticyclone contributed to the shear errors in this
particular case - but in general such errors were observed to be
associated with the AVN's unproper handling of the TUTT.
While Figs. 3 and 4 have presented the errors found in
conjunction with one of the stronger TUTTs that were present in the two
month time period, 48 h forecast
errors in the vicinity and south of the TUTT axis
typically were on the order of 10 ms-1. However, when the TUTT was
either very weak or not present in the analysis, it was found that the
errors were substantially reduced.
To contrast results shown in Figs. 3
and 4, a weak TUTT case was
examined. Figure 5 provides an example
of the forecast behavior of the
AVN when only a very weak TUTT is observed in the initial analysis.
On 12 UTC 27 August 1993, the 200 mb flow shows a weak
closed cold low at roughly 17° N and 63° W which is
attached to a mid-latitude trough over the Azores and adjacent to a
weak trough extending from the Northeastern Pacific Ocean region
(Fig.
5a). The normal climatological position of the TUTT
(see Fig. 2) is occupied by
two closed upper-level anticyclones - one located over eastern Honduras
and the other situated about 7° north of Puerto Rico. The
eastern half of the United States is under the influence of a strong
subtropical ridge. Figure 5b shows
the 48 h AVN forecast of 200 mb
winds valid 12 UTC 29 August. When compared with
the analysis at the verification time
(Fig. 5c), the AVN forecast
does well, specifically, with respect
to both positioning and strength of the cold low near Hispanola and of
the upper-level anticyclones in the Caribbean and over the U. S.
mainland. It does, however, dissipate the 200 mb trough that extends from the
eastern Pacific basin and washes out the closed anticyclone over Honduras.
Figure 6 shows the observed minus forecast
VWS valid 12 UTC 29
August. The magnitude of errors is strikingly small ( < 4 ms-1)
when compared to Fig. 4 throughout the
entire Caribbean
basin. The errors are smallest where easterly winds persisted
throughout the analysis period, and are small where westerly winds
became northeasterly in the eastern Caribbean.
There is only one region that has errors in excess
of 12 ms-1 which is located in a region of westerly winds just
south of a weak east-west trough in the Gulf of Mexico. This feature is
curiously eliminated in the forecast field (see Fig. 5b). Note that
with the exception of two small regions to the south of Honduras and the
other over South Carolina all positive forecast errors shown are associated
with observed upper-level westerly winds at verification time.
Table 1 documents the 48 h AVN
model errors found
at specific locations throughout the entire two month time period
under analysis. The locations of these four points are shown in
Fig. 2.
All four locations show an underestimation of the VWS
during the two month period for all cases with the largest errors occurring
at the two westernmost points. When stratified by 200 mb
westerly and easterly wind cases
at the verification time (48 h), it becomes apparent that the easterly
bias is strongest
when westerly winds were observed.
Typically, these westerlies only occurred when the TUTT axis was to the
north of the location in question.
When moderate ( < 10 ms-1) westerlies were observed at 48 h, this bias
is on the order of 5 ms-1.
Furthermore, when strong ( ° 10 ms-1) westerlies
were observed at 48 h, the
underestimation in the VWS is on the order of 10 ms-1. This
implies that there is a consistent tendency for the AVN to unrealistically
diminish all westerly momentum, even for westerly winds with substantial
strength, in the tropics.
However, when 200 mb easterly winds occurred at 48 h,
the errors are small.
This contrast is even more
evident when the four locations on Fig.
2 are averaged together - the
error associated with the strong westerlies is 7.8 ms-1, while
for the easterly case it is 1.1 ms-1.
For an additional perspective, the 48 h forecast
VWS errors are plotted
in terms of 5 ms-1 classes for
easterly, westerly, and strong westerly wind regimes at the 48 h verification
time (Fig. 7). As expected, when
easterly winds were observed, the AVN errors are semi-Gaussian.
However, west winds experience a positive error bias and, in fact, very
few errors are negative. For strong westerlies the bias is
strongly skewed to toward positive, and the errors are almost never negative.
To examine these errors in more detail, the AVN
shear values were stratified by winds observed at model initialization
and by winds observed at the 48 h verification time (Table 2). From
this tabulation, it is clear that the AVN suffers a tendency to weaken
or eliminate 200 mb westerly winds and/or to introduce 200 mb easterly
winds in the Caribbean Sea. For example, the VWS errors are highest when:
1) west winds were observed to increase with time, 2) east
winds became westerly with time, or 3) west winds were observed to
be steady-state. This indicates the AVN model's inability to generate,
maintain, or build westerlies associated with a steady-state or
growing TUTT. It is also possible the AVN is misplacing the location
of the TUTT, but it was observed that the easterly bias was much more
common. In contrast, for the cases when: 1) easterlies were observed
throughout the forecast period, 2) west winds weakened with time,
or 3) west winds became easterly with time, the VWS forecast errors
are small. This probably also reflects the model's bias toward
generating 200 mb easterlies in most cases.
While
identifying such a bias provides useful information, the forecaster is
left with a dilemma - how does one predict the 200 mb flow in the
future for a tropical westerly wind regime? One approach is to assume
that the TUTT is approximately
a steady-state system, and use persistence.
Another approach is to utilize climatology to
predict the future 200 and 850 mb wind flow.
Both procedures are further investigated. The persistence scheme
simply extrapolates the observed VWS into the future. The
climatology scheme uses average 15 day
climatological values for the verification time.
Climatological data were
provided by the Climate Analysis Center's Global
Tropical Climate Diagnostics for the years 1979 to 1988 (prepared by
Muthuvel Chelliah at the National Center for Atmospheric Research).
This ten-year VWS climatology is interpolated from 2.5° deg grid
spacing to the four individual locations
for the following time periods:
1) 10 August - 20 August, 2) 21 August - 9 September, 3) 10 September
- 20 September, and 4) 21 September - 30 September. For this
ten-year climatology, westerlies exist in all four time frames at 200
mb (not shown).
The climatological VWS values are shown in
Table 3. VWS tends to
decrease south of the TUTT in early September because the
trade winds are weakest at this time while (for this ten-year
climatology) the 200 mb westerlies remained fairly constant in
magnitude during August and September.
The effectiveness of these
schemes are examined in Table 4,
in which the average errors now are
stratified by winds observed at the initialization time.
For this two-month period, both climatology and persistence
experience smaller VWS errors than the AVN for all stratifications.
Furthermore, all the AVN forecast errors are positive, again showing
the model's tendency to diminish westerly momentum and therefore
underforecast VWS.
When all cases are considered, average persistence errors are
approximately zero,
implying that this procedure introduces no forecast bias. When
sub-divided by different wind stratifications, the errors are smallest
in magnitude compared to the other two predictive procedures (though
it is the same as climatology for weak westerlies) except for
observed easterlies at initialization. This implies that 200 mb easterlies
often did not persist for two consecutive days during August and September
1993.
Climatology
VWS forecast errors are weakly positive for all cases
indicating that the shear was
greater than the 1979-1988 climatology during 1993.
This is indicative of the westerly wind anomalies associated
with that year's El Niño which partially explains the fairly
inactive 1993 hurricane season (Gray 1993).
It is somewhat interesting that using climatology yields almost no
forecast error for an initial easterly wind, since 200 mb westerlies
exist in the climatology. Apparently, this procedure nudges the
forecast back to a normal 200 mb westerly wind regime. This tendency is also
apparent for the weak westerly stratification, since climatological
winds are < 10 ms-1.
However, some caution
is needed in interpreting the findings utilizing a ten-year climatology.
A longer term
climatology would possibly yield different results, since
August/September wind flow patterns possibly were different in the 1950s and
1960s. Landsea and Gray (1992) note a reduction in major
hurricanes (Saffir-Simpson Categories 3, 4, and 5) in the last twenty
years associated with a multidecadal drought in Africa's western
Sahel. Teleconnection patterns related to this drought may have, in
turn, altered the Atlantic's general circulation. According to
Landsea and Gray, during these drought years anomalous westerly winds were
observed in the Caribbean.
Unfortunately, synoptic-scale
quantitative data over the whole basin for the long-term climatology is
lacking.
It has now been
established that using persistence and/or climatology introduces less
VWS forecast bias, especially when compared
to the rather large bias in the AVN model.
But does using these alternate schemes actually reduce the
overall forecast error? To answer this question, average absolute errors
were calculated for the AVN model, persistence, and climatology
and stratified by observed winds at model initialization
(Table 5). Overall, persistence
and climatology surpass the AVN in
performance, but the 200 mb wind stratifications offer more insight. For an
initial easterly wind regime, climatology has the smallest absolute
error. For an initial weak west wind, climatology and persistence are
equal in forecast performance. For an initially strong west wind,
persistence contains the smallest absolute error.
In summary, it is
recommended that the forecaster use persistence
and/or climatology near the Caribbean Sea during the hurricane season to
forecast 48 h VWS and 200 mb winds. For 200 mb east winds, climatology is the
suggested predictor.
For westerly winds < 10 ms-1, half climatology and half
persistence is advised.
For westerly winds , persistence is suggested.
What has been detailed here are systematic biases in the
forecasted tropical upper tropospheric flow patterns in the AVN that can
seriously degrade the performance of models like NHC90 and the QLM,
as well as to
misinform the forecaster as to the future evolution of the tropical
circulation. We observed a strong tendency in the AVN's 48 h forecast of
200 mb flow to possess an easterly bias of 5 ms-1 for all cases and up
to 10 ms-1 in cases where westerly winds were observed. This
bias is most apparent near and south of
the climatological position of the TUTT axis
during August and September - the height of the Atlantic hurricane season.
There are a number of possible causes of such a systematic
error.
The bias might result from poor model resolution of the upper
troposphere and lower stratosphere
(Petersen and Stackpole 1989).
In addition to the coarse resolution problem,
previous studies that identified the general tropical upper
tropospheric bias suggest that four other
factors may be responsible. Bengtsson
(1991) in his discussion of ECMWF model errors suggests that both convective
parameterization and the treatment of momentum fluxes may be the cause
of the excessive easterlies.
Rosen et al. (1991) discuss the possibility that the parameterization of
radiation may be the culprit in the AVN/MRF. In turn, a properly
formulated radiation scheme will still suffer errors if the vertical moisture
field is inaccurately portrayed in the model (Slingo and Webb 1992).
However, the primary purpose
of this paper is to simply document a systematic bias in the AVN
model, not to specifically identify its cause.
Until this bias in the AVN is successfully reduced, it is
desirable that the Atlantic basin TC forecaster be aware of this
systematic error and make subjective changes in his/her forecasts.
In fact, it is
recommended that the forecaster utilize persistence in cases where strong
westerly winds are observed at 200 mb in the Caribbean Sea.
For weak westerlies at
200 mb, half climatology and half persistence
is the preferable predictor. If the TUTT is weak such that 200 mb
easterly winds occur, climatology tends to be the best predictor as it
nudges the forecast back to a normal westerly wind regime. However,
should a forecaster surmise this to be improbable (as in the case of a
far-displaced TUTT or a non-existent TUTT), the AVN or persistence is
probably best.
We would hope that these suggestions
would be only a temporary
fix and that the performance of the AVN itself can be improved. Accordingly,
we would encourage research into the causes of this bias by
members of the modeling research community.
2 Background
2.1 The tropical upper tropospheric trough
2.2 Aviation model description and known systematic tropical
wind biases
3 Methodology and results
4 Discussion
Because TC genesis, intensity,
and track models largely depend
on the forecast fields of the AVN, a more complete understanding of
the AVN model's systematic biases is necessary. For example, the latest
statistical-dynamical model for TC track forecasting in the Atlantic
basin, NHC90, as well as the latest baroclinic track forecasting model, the
Quasi-Lagrangian Model (QLM), utilize AVN forecast
fields of the geopotential heights, including 200 mb heights
(Neumann and McAdie 1991; Mathur and Ruess 1993). Note that
once a bias (such as the one shown here) is identified, it is possible in
a statistical model like NHC90 to account for it. Additionally, future plans
for the only statistical-synoptic model available for TC intensity
forecasting - the Statistical Hurricane Prediction Scheme (SHIPS) -
call for it to include AVN
forecast fields of both VWS and 200 mb eddy angular momentum fluxes
(DeMaria and Kaplan 1994).
Acknowledgments
We wish to thank Profs. William Gray, Roger Pielke,
and Wayne Schubert
for providing us with enlightening discussions regarding this problem.
James Stricherz and Florida State University provided some of the data
used in the persistence calculations.
The streamline figures were drafted by Judy Sorbie-Dunn.
A special thanks is extended to George Forristall and Mike Vogal
for the impetus to look closely at the AVN
forecast fields.
Lance Leslie and two anonymous reviewers made helpful comments on an
earlier version of this paper.
Partial support was given by NASA who provide funding
for J. Knaff and C. Landsea through the Global Change Fellowship
Program under contract NGT 30147 and 30064.
P. Fitzpatrick received partial funding through the Air Force
Office of Scientific Research under Grant DEO102.
This analysis was partially supported
by a grant from the Office of Naval Research under Grant DEO306.