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3
Atmospheric Dynamics and Weather Forecasting Research Entering the
Twenty-First Century1
Summary
Progress in understanding and predicting weather is one of the
great success stories of twentieth century science. Advances in
basic understanding of weather dynamics and physics, the
establishment of a global observing system, and the advent of
numerical weather prediction put weather forecasting on a solid
scientific foundation, and the deployment of weather radar and
satellites together with emergency preparedness programs led to
dramatic declines in deaths from severe weather phenomena such as
hurricanes and tornadoes.
Basic research in atmospheric science has been one of the most
cost-effective investments that society has made in science.
Progress in the basic understanding of phenomena such as severe
thunderstorms has led directly to improved warnings and the
reduction of loss of life, while technical advances in numerical
weather prediction, application of statistics to model output, and
advanced satellite and radar technology have contributed to much
improved forecasts of all kinds.
1. Report of
the Ad Hoc Group on Weather Dynamics and Storm Systems: K. Emanuel
(Chair), Massachusetts Institute of Technology; K.C. Crawford,
Oklahoma Climatological Survey; R. Rotunno, National Center for
Atmospheric Research; L. Shapiro, NOAA/AOML/Hurricane Research
Division; J. Smith, Princeton University; R. Smith, Yale
University; L. Uccellini, NOAA/National Meteorological Center; M.
Wolfson, MIT/Lincoln Laboratories. The group gratefully
acknowledges contributions from A. Betts, L. Bosart, C. Bretherton,
J. Derber, K. Droegemeier, B. Farrell, R. Fleming, J.M. Fritsch, R.
Houze, M. LeMone, D. Lilly, M. Shapiro, A. Thorpe, S. Tracton, and
E. Zipser.
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Society chooses to invest in basic research not only because of
perceived tangible benefits but also because of the intrinsic value
of pushing back the frontiers of knowledge. Few would deny the
largely intangible but very real value of intellectual achievements
such as the formulation of quantum mechanics, the discovery of DNA,
or the characterization of the physics of deterministic but
nonperiodic systems. In the United States, the intellectual appeal
of progress in the atmospheric sciences rivals that of such fields
as cosmology and molecular biology.
Atmospheric science is poised to make another series of major
advances, many of which will lead directly to improved weather
warnings and predictions. Great strides in the basic understanding
of the dynamics of weather systems and the development of new
techniques such as ensemble forecasting combine with the deployment
of new measurement systems and advanced means of communicating
information to offer the promise of much improved forecasts to the
American public.
To realize these potential improvements, new means of measuring
the atmosphere, oceans, and land surface must be developed and
implemented, and existing measurement systems such as rawinsondes,
mobile radars, and research aircraft must be maintained and
upgraded. We cannot stress enough the continued need for in situ
and ground-based remote sensing capabilities and are alarmed at the
deterioration of fundamental observing systems such as the global
rawinsonde network. In surveying the state of basic research in
weather dynamics, time after time we came to the conclusion that
further progress was limited by the lack of appropriate measurement
capabilities. For this reason, many of our recommendations focus on
the need for better measurement systems. However, it must be
recognized that we have the ability to predict, with some accuracy,
how improvements in observing systems or techniques might actually
improve forecasts. This capability is largely unexploited. One of
our most important conclusions is that far more must be done to
exploit known techniques, such as observing system simulation
experiments, to make a priori estimates of optimal combinations of
observing systems and forecasting techniques for application to
specific forecast-related problems. Further, we feel that
atmospheric scientists must work much more closely with other
disciplines, particularly economists, to determine the potential
costs and benefits of new observing systems and forecasting
methods.
The major body of this Disciplinary Assessment was completed
just as the U.S. Weather Research Program (USWRP) was being
defined. Much of what is contained here is strongly consonant with
the objectives of the USWRP as outlined in Emanuel et al.
(1995).
Emerging Research Opportunities
We have identified a number of emerging basic research,
technique, and technological developments that, on the basis of
their intrinsic intellectual value
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and/or potential economic or societal payoff, should be given
high priority in the coming decades. Here, these key developments
are summarized, and specific recommendations based on them are
offered. The developmental foundations behind the identification of
these opportunities are delineated later.
1. The fundamental physics of land-air interaction: Basic
understanding of the nature of the interaction between atmospheric
and land surface processes is at the threshold of major advances
and has the potential, when coupled with greatly improved routine
measurements of land surface properties, to lead to substantial
improvements in understanding and forecasting convection, boundary
layer cloud cover, and regional climate anomalies. The link between
soil moisture and precipitation may be the key to improved
quantitative precipitation forecasts.
2. Seasonal climate variations and their dependence on the
stochastic, internal variability of the atmosphere as well as
variations linked to longer time-scale phenomena in the oceans,
atmosphere, and land surface: Research on blocking and on
land-atmosphere interactions has the potential to yield significant
improvements in seasonal forecasts. The seasonal prediction problem
is highly dependent on proper representation of sources and sinks
of heat, moisture, and momentum, whereas short-range prediction
depends more on advection of these quantities.
3. The continued development of ensemble forecasting and data
assimilation techniques: These offer great promise for improved
numerical weather forecasts and the quantification of forecast
uncertainty.
4. Adaptive observation strategies: Budding research
suggests that ensemble forecasting techniques, including the use of
model adjoints and breeding methods, may provide real-time
estimates of optimal observation location and timing, given the
availability of programmable observation platforms. Observing
system simulation experiments could be used to help determine
optimal combinations of observing systems. This may lead to large
gains in the skill of numerical weather forecasts for a relatively
small investment in additional observations.
5. Improved understanding of the hydrological cycle and much
better measurements of atmospheric water: Ongoing advances in
understanding the control of atmospheric water (in all phases) will
lead to much improved understanding of and ability to predict a
variety of dynamical systems. Critical physical processes include
the control of water vapor by convection and cloud microphysics,
and the coupling of the atmospheric boundary layer with the
underlying surface. Improved understanding of these processes,
together with the advent of much improved techniques for measuring
soil properties, atmospheric water vapor, and condensed water, is
essential for solving the difficult problem of quantitative
precipitation forecasting and will be necessary for adequate
modeling of climate as well.
6. Coupling the atmospheric boundary layer with deep
convection and merging the understanding of cell-scale dynamics and
prediction with the understand-
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ing of convective ensemble dynamics: There have been
enormous advances in understanding the cell-scale dynamics of moist
convection, and in understanding and representing the interaction
between ensembles of convective cells and larger-scale
circulations; the time appears ripe for a productive synthesis of
these developments.
7. The dynamics of deep convective downdrafts: These play
a major role in the dynamics of at least some mesoscale convective
systems and in the overall heat balance of the tropical boundary
layer but have received comparatively little attention in
formulating representations of cumulus convection.
8. The fundamental role of the tropopause in atmospheric
dynamics and the possible benefits of better observations at and
near the tropopause: Recent advances in the dynamics of
synoptic-scale systems and better analyses of potential vorticity
(a measure of atmospheric rotational motion) have pointed to the
tropopause as a locus of important dynamical processes and the
exchange of chemical constituents. This suggests that future models
and observing systems may profit from much improved resolution near
the tropopause. One especially promising candidate observing system
for improving resolution of the tropopause is the global
positioning system (GPS), which can be used to deduce profiles of
temperature in the upper atmosphere.
9. Tropical cyclone genesis and intensity change, including
the role of the upper-ocean response and interactions with
dynamical systems in the upper troposphere and lower
stratosphere: Tropical cyclones have been implicated in costly
weather-related catastrophes in the United States, but there is
little skill in forecasting open-ocean intensity change or genesis.
Moreover, the modernization of the National Weather Service has
done little to improve our ability to observe and forecast these
storms.
10. The dynamics of landfallen tropical cyclones,
particularly as they relate to flash floods: Some of the worst
disasters in U.S. history were caused by tropical
cyclone-associated flooding, but relatively little research effort
has been expended in understanding the dynamics of landfallen
tropical cyclones.
11. The dynamics and cloud physics of mesoscale convective
systems and of other convective systems that produce heavy
rainfall: Mesoscale convective systems are responsible for much
of the summertime rainfall over the central United States, and
research aimed at understanding the underlying dynamics and cloud
physics appears to be at the threshold of major advances.
12. Orographic and other influences on sources and sinks of
atmospheric potential vorticity: The understanding and
numerical modeling of synoptic-scale dynamical processes that
center on advection is comparatively well developed, but we are
only beginning to understand the nature of diabatic and frictional
processes. Forecasts beyond a few days rely heavily on an accurate
account of such processes.
13. The interaction of quasi-balanced and unbalanced
circulation systems: This interaction is responsible for, among
other things, the generation of internal
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waves in synoptic-scale cyclones and the creation of unbalanced
flows such as gap winds or Kelvin waves by orography. These
mesoscale events are major impediments to improvements in forecasts
and warnings.
14. The development and evolution of mesoscale frontal
cyclones: These are often missed by models, and their dynamics
are not well understood.
15. The development of mesoscale models for forecasting
''fire weather'' conditions and interactive models for prediction
of actual fire development and movement: Very recent research
and modeling results suggest that such developments may aid
considerably in the prediction and control of forest and
wildfires.
16. Research on advanced statistical techniques and on
optimal blends of numerical and statistical approaches: The
best forecasts available today are based on combinations of
deterministic model output and statistical guidance that depends
mostly on model output. Further improvements should result from the
production of higher-order moments related to the probability of
events and from application of model output statistics to nonlocal
quantities such as drainage basin-integrated precipitation.
Key Recommendations
We make the following recommendations, based in part on
recognition of the value of the research opportunities summarized
above and in part on further deliberations:
1. Fundamental improvements in forecasting in the two- to
seven-day range have enormous potential economic benefits but
require far better collection and utilization of data over the
oceans and other data-sparse areas. We strongly encourage the
support of research seeking to determine optimal combinations of
satellite and ground-based remote sensing, and aircraft, balloon,
and surface observations, as well as the support of key
technological developments such as satellite-borne active sensing
techniques, near-field remote sensing of atmospheric water vapor,
and observations from commercial and pilotless aircraft. Such
research should include comprehensive, well-posed observing system
simulation experiments (OSSEs) and data denial experiments.
Cost-benefit analysis should play a key role in the definition of
"optimal" as it is used above, and the cost to the nation as a
whole, rather than the cost to individual agencies, should be the
criterion.
2. Recent research strongly suggests that adjoint techniques or
breeding methods can be used to target specific regions of the
atmosphere for observational scrutiny during the subsequent data
assimilation cycle, resulting in greatly reduced forecast error.
We advocate enhanced research on adaptive observations and their
potential for substantial reduction in forecast error.
3. The deterioration of the global rawinsonde network must be
reversed or a better substitute developed if progress is to be made
on a variety of operational
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and basic research problems. The reduction of in situ
measurements in general, in favor of remote sensing measurements,
is at best premature, and we reemphasize the desirability of
performing research that seeks to determine an optimal mix of
observation techniques and placement.
4. Much-improved understanding of land-atmosphere interaction
and far better measurements of land surface properties, especially
soil moisture, would constitute a major intellectual advance and
may hold the key to dramatic improvements in a number of
forecasting problems, including the location and timing of the
onset of deep convection over land, quantitative precipitation
forecasting in general, and seasonal climate prediction. We see
a major opportunity that may be exploited by encouraging
interactions between hydrologists and atmospheric scientists and by
developing new means of routine and comprehensive measurement of
soil properties.
5. Improvement in understanding the dynamics of atmospheric
circulations affected by phase change of water, as well as in
numerical weather prediction, especially quantitative precipitation
forecasting, is severely impeded by poorly resolved and inaccurate
measurements of atmospheric water vapor. High priority must be
given to new water vapor measurement systems and to research that
seeks to delineate the water vapor observations necessary to
address specific research and forecast problems.
6. At present, the extent to which seasonal climate variations
represent stochastic, internal variability of the atmosphere versus
variations linked to longer time-scale phenomena in the oceans,
atmosphere, and land surface is poorly understood. Research on
blocking and on land-atmosphere interactions presents an exciting
opportunity for fundamental advances in understanding and has the
potential to lead to significant improvements in seasonal
forecasts. The seasonal prediction problem is highly dependent on
the correct specification of sources and sinks of heat, moisture,
and momentum, whereas short-range prediction depends more on
advection. We encourage enhanced research efforts on blocking,
land-atmosphere interactions, and frictional and diabatic effects
on atmospheric dynamics.
7. The worst natural catastrophes in U.S. history were caused by
tropical cyclones. Although research on the dynamics of tropical
cyclone genesis, intensity and structure change, and motion is
ongoing, it has received little emphasis in recent national
programs or in the modernization of the National Weather Service.
Little is known about the dynamics of landfallen tropical cyclones,
and this has limited our ability to forecast related flooding.
Detection of hurricanes has been greatly facilitated by
satellite-based observations, but much of the current state of
understanding as well as the quantitative prediction of storm
motion and structure and intensity change has relied on in situ
measurements. We strongly recommend the support of research on
the physics of tropical cyclone motion and intensity change, and of
research seeking to delineate optimal combinations of measurement
systems in aid of hurricane forecasting.
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8. Tropical cyclones and some classes of extratropical marine
cyclones are sensitive to local sea surface temperature and are
known to influence ocean temperature through wind-induced stirring
and upwelling. Modeling studies show that this feedback has an
important effect on hurricane intensity, but observations of this
interaction are lacking. We strongly encourage enhanced
observations of the upper ocean during the passage of tropical and
some extratropical cyclones.
9. The resources to maintain a balanced, national, basic
research observing infrastructure must be restored, enhanced, and
maintained. Satellites do not provide the spatial resolution or
three-dimensional coverage required to diagnose many basic physical
processes such as those involving clouds and precipitation. Next
Generation Weather Radars (NEXRADs) have operational constraints
that compromise their use in basic research, even if combined with
other technologies. Mobile and transportable radars, research
aircraft, and surface observations used to make high-precision,
high-resolution observations with sufficient time continuity are
required as research tools in the study of many atmospheric
processes.
10. Many of the exciting and potentially beneficial developments
identified earlier are of a nature that cuts across traditional
disciplinary boundaries, involving much more intimate ties among
atmospheric science, oceanography, atmospheric chemistry,
hydrology, computational science, economics, communications, and
operational forecasting. Yet the breakdown of these barriers is not
well reflected in the organizational structures of the principal
government funding and oversight agencies, and this is impeding
progress on a number of fronts. We recommend that consideration
be given to streamlining federal funding and oversight channels
with a view to facilitating interdisciplinary research.
Introduction
This section summarizes what we regard as the important elements
of current basic research efforts, as well as key developments in
measurement and forecast techniques and technology.
Basic Research Foci
Extratropical Cyclones and Associated
Mesoscale Processes
Most significant weather events in the midlatitudes occur in
association with extratropical cyclones. Mesoscale features
characterized by strong upward motion and moderate to heavy
precipitation are often embedded in the synoptic-scale region of
ascending air in cyclones. These smaller-scale features include
fronts, rain bands, and squall lines. Being unable to forecast the
formation and ground-relative motion of these mesoscale features is
a significant impediment to
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having accurate precipitation forecasts. Broadly speaking, a
front forms as a natural consequence of the deformation field of a
large-scale cyclone acting on existing temperature gradients. We
need to know more about the diabatic processes (convection,
radiation, boundary layer) that modulate this frontogenesis. Mature
fronts are known to have characteristic precipitation features such
as rain bands; the origin and nature of these have to be understood
better. Finally, circulations associated with fronts can instigate
significant weather many tens of kilometers away from the front
itself (e.g., prefrontal squall lines); the precise nature of these
influences is still poorly understood.
Mesoscale processes often exert a significant influence on the
larger-scale cyclone behavior. It is still a matter of uncertainty
whether the radiosonde network (with station spacing of
approximately 400 km) contains enough of the mesoscale information
needed to forecast accurately many cases of the large-scale
cyclogenesis itself. Sensitivity studies using adjoint models
indicate that in many cases, the forecast location and intensity of
the cyclones depend on upwind flow features of mesoscale size; in
particular, finer-scale information concerning perturbations of the
tropopause is needed. Cyclone-scale waves growing on preexisting
fronts are still poorly observed and understood. Forecast models
still have difficulty with lee cyclogenesis; we need to know more
about how, precisely, mesoscale terrain features contribute to the
cyclogenesis and how to incorporate this knowledge into a forecast
model. Similar comments apply to cyclogenesis in the presence of
mesoscale physiographic features such as ice-edge boundaries or
coastlines. A major uncertainty is the cumulative effect of moist
convection on large-scale cyclone behavior.
In general, diabatic processes and their influence on
synoptic-scale dynamics must be better understood. We note that
much of the total latent heating and frictional dissipation that
occurs in the atmosphere is associated with mesoscale and
convective-scale processes. Thus, better understanding of mesoscale
and larger-scale processes is inextricably bound.
Observations of the middle-latitude atmosphere show that the
gradients of potential vorticity that are so fundamental to
large-scale dynamics are usually concentrated at the surface and
the tropopause. The mixing and other irreversible processes that
lead to nearly uniform potential vorticity distributions in the
interior of the troposphere and to the concentration of potential
vorticity gradients near the tropopause have to be better
understood. We must further explore the consequences of the
observed potential vorticity distributions for synoptic and
planetary wave propagation and instability.
Better forecasts out to three days are critical for a number of
important forecasting problems, such as snowfall, precipitation
type, and high winds; these will depend largely on better upstream
observations and improvements in understanding and capturing
mesoscale phenomena. However, current numerical weather prediction
techniques may not be uniformly applicable at the mesoscale. A
large issue that must be faced is the initialization problem. Most
current
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techniques are designed to filter out phenomena such as gravity
waves and upright and slantwise convection—the very phenomena
we wish to forecast on the mesoscale. We believe that better
weather forecasts on time scales less than one day will require
much improved understanding of mesoscale phenomena such as gravity
waves, slantwise convection, and frontal cyclones, together with
advanced numerical weather prediction techniques such as dynamic
and diabatic initialization that preserve real internal waves and
condensational heating.
Forecasting at all time scales on the U.S. West Coast and beyond
a day or two on the East Coast is seriously impaired by lack of
usable data over the Pacific, but there is a paucity of research on
the effects of these data voids. We strongly recommend that
OSSEs and data denial experiments be undertaken to estimate the
effect of oceanic data voids on medium-range numerical weather
prediction and, similarly, to estimate the influence of potential
new data sources on numerical forecasts. Another intriguing
technique that should be explored is the use of ensemble
forecasting methods and adjoint techniques to make a priori
estimates of the distribution, magnitude, and sensitivity of
forecast skill measures to upcoming analysis error, so that
programmable observation platforms, such as unmanned aerial
vehicles or programmed deployment of dropsondes from commercial
aircraft, can be directed to focus on sensitive regions. Adaptive
observational strategies may serve to help optimize observations in
aid of numerical weather prediction.
Tropical Cyclones
Landfalling hurricanes can have catastrophic societal impacts in
terms of loss of life and property near the U.S. coastline.
Hurricanes have accounted for more than $40 billion damage and
costs to the U.S. economy since 1980 and more than 200 deaths. In
1992, Hurricane Andrew alone caused about $25 billion in damage and
costs, with 58 lives lost, and was the single costliest natural
disaster in the history of the United States.
Detection of an incipient tropical cyclone is generally made by
geostationary weather satellite. Although satellites are also used
to monitor the evolution of a cyclone, errors from these remote
sensors can involve as much as tens of miles in position and tens
of knots in wind speed. Measurements from reconnaissance aircraft,
coastal radars, ships, buoys, and land stations provide additional
sources of data.
The track of a tropical cyclone is determined primarily by the
environmental flow in which it is embedded. The internal structure
of the cyclone and its interaction with the environment are also
important for track and intensity prediction. For accurate
forecasts, detailed measurements are required on scales ranging
from those of the large-scale environment to the cyclone's small
inner-core structure. As noted in a recent American Meteorological
Society policy statement (AMS, 1993), however, "The present
reconnaissance aircraft fleet and
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weather satellite information cannot provide the full
three-dimensional data required for hurricane track forecasting.
Omega dropwinsondes deployed from the aircraft can provide wind,
temperature, and moisture information from flight level to the
surface, and have been shown to have a positive impact on track
forecast models. The aircraft are relatively slow, however, and the
information derived from the sondes does not cover the important
region above flight level. The remote-sensing satellite data are
limited in accuracy and coverage, particularly at the critical
middle-tropospheric levels."
More accurate tropical cyclone forecasts and warnings require
that improved understanding of basic physical processes and
improved depictions of the hurricane and its environment be
incorporated into forecast models. Skillful forecasts of hurricane
track and intensity require simultaneous, accurate prediction of
multiple scales of motion ranging from several thousand kilometers
(which determine motion) to several kilometers (which represent
intensity).
Research with barotropic models, representing the depth-averaged
flow that steers storms, has improved understanding of the
mechanisms that influence motion, including effects due to
interactions with the environment. Skillful operational track
forecasts have been achieved using a barotropic model. The effects
of vertical shear on motion have been investigated with baroclinic
models, representing the full three-dimensional structure of the
hurricane and its environment. The application of initialization
schemes that include a synthetic representation of a hurricane has
demonstrated the potential for substantial improvements in track
prediction. It has also been demonstrated that track forecast
improvements of 20 percent or more result from the addition of
supplemental environmental observations, including Omega
dropwinsondes. Field experiments in the western Pacific have
studied the environmental factors, including interactions with
mesoscale convective complexes, that influence tropical cyclone
motion. We are now in a position to use advanced numerical models
to make a priori estimates of the potential benefits of new
observing systems for hurricane track forecasts, and the
application of objective adaptive observation strategies may be
particularly beneficial in the case of hurricane forecasting.
Here, perhaps more than anywhere, the use of hurricane forecast
models in suitably designed observing system simulation experiments
could delineate a superior mix of observations necessary for
accurate forecasts of tropical cyclone movement. There can be
little doubt, however, that improved measurements of the
synoptic environment of hurricanes offers perhaps the best
opportunity for improved forecasts that would lead to reduced loss
of life and property damage. Platforms that should be
considered in estimating an optimal mix of data sources include
satellite-borne sea surface scatterometers, Special Sensor
Micorowave/Imager (SSM/I), passive water vapor measurements,
GPS-based temperature and water vapor profiles, and active radar
and Doppler lidar systems as well as in situ and dropwinsonde
measurements from manned and unmanned aircraft.
At present, forecasters show little if any skill in hurricane
intensity predic-
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tion. Current research on intensity prediction indicates that
physical processes in the hurricane boundary layer and in the
upper-tropospheric outflow layer have a strong controlling
influence on intensity changes. High-altitude regions are,
unfortunately, the area in which observations and understanding
have been lacking. High-altitude (15-20 km) research aircraft
are essential for making measurements that will allow understanding
and forecasting of hurricane intensity and structure change by
environmental interactions. Modeling studies demonstrate that
hurricane intensity is very sensitive to the ratio of the
coefficients governing the exchanges of heat and the momentum at
the sea surface, but almost nothing is known about the nature of
these exchanges at high wind speeds. Understanding the nature of
the exchange of heat and momentum between the air and sea at high
wind speed is important for understanding and predicting hurricane
intensity.
The mesoscale and convective characteristics of a hurricane,
including eyewall and spiral rainbands, are being studied. The
importance of concentric eyewalls and their associated secondary
wind maxima in influencing the short-term evolution of some intense
hurricanes has been established, but the basic physical mechanism
of this phenomenon has not been conclusively identified. The role
of air-sea interactions, including the controlling influence of sea
surface temperature, on cyclone intensification is being
elucidated. Intensity prediction using a statistical regression
model has highlighted the importance of sea surface temperature as
a cap on hurricane intensity. Cooling of the ocean surface owing to
the passing of a hurricane has been shown to moderate the
intensification of the hurricane, but great uncertainty remains
about the physics of entrainment of cold water into the ocean mixed
layer. Research on this aspect of tropical cyclone physics would
profit from better measurements of the ocean response during and
after passage of tropical cyclones.
Although the axisymmetric dynamics of hurricane evolution are
reasonably well understood, the asymmetric interactions with the
environment that influence a storm's intensity are just beginning
to be established. Current research emphasizes the importance of
upper-tropospheric interactions in modulating storm development.
Intensity forecasts with dynamical prediction models show
considerable promise but are still at an early stage of
development. Data deficiencies, in both the hurricane's inner core
and its environment, particularly at upper levels, limit the skill
of these models. Innovative numerical techniques are being applied
to the development of more accurate prediction in the context of a
multinested model. Doppler radar measurements from aircraft are
being used to deduce inner-core structure, and satellite imagery is
being used to infer storm-associated rain rates.
Earlier stages of tropical cyclone development are also being
investigated, from both a dynamical and a statistical perspective.
The importance of upper-level influences on tropical storm genesis
is being studied from the potential vorticity perspective. The
factors that determine the evolution of an incipient
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assimilation cycle, and the use of model adjoints to generate
particularly rapidly growing perturbations. Two principal benefits
result from ensemble forecasting: the spread between members of the
ensemble gives a quantitative estimate of uncertainty in the
numerical forecast, and as it turns out, the average of all members
of the ensemble is statistically a better forecast than any single
member. Although many additional conceptual and practical questions
must be considered, ensemble prediction is applicable also to
shorter-range forecasting with regional models.
Data Assimilation and Adaptive
Observations
Data assimilation combines the information in observations with
an atmospheric prediction model to provide the best possible
estimate of atmospheric state. In the past few years, there have
been substantial advances in the theory and practice of data
assimilation. These advances can be attributed to improvements in
four basic components: the forecast model, the data base, quality
control techniques, and analysis or assimilation techniques. The
improvement in the forecast models and data base is outside the
area of this Disciplinary Assessment, but it should be noted that
any improvement in these components immediately results in
improvement of the data assimilation system.
Since instruments do not work perfectly and data are collected
through a number of different paths (some still using manual means
of transmission), data can contain errors. Bad data can cause
problems with data assimilation systems. For this reason, it is
necessary to perform some type of quality control to eliminate or
correct large errors in the data. In most assimilation systems, the
observational differences from the model prediction are compared to
nearby observational differences interpolated to the observation
location. Quality control decisions are based on these differences.
At the National Centers for Environmental Prediction (NCEP), for
example, a complex quality control system has been developed that,
in addition to accepting or rejecting data, corrects some of the
observations for common types of errors.
Most operational data assimilation schemes use an intermittent
data assimilation technique in which the model is integrated
forward for some period of time and then, based on available data,
is adjusted using a three-dimensional objective analysis technique.
The technique of three-dimensional objective analysis is most
commonly some form of optimal (or statistical) interpolation. With
the development of variational techniques to solve the analysis
problem, many of the approximations contained in optimal
interpolation can be eliminated. The advantages of these schemes
include the elimination of data selection, the inclusion of more
physically realistic constraints, and the easy inclusion of
additional data types. As a result of these changes, the
independent initialization step can be eliminated and observations
such as radiances, refractivities, and scatterometer measurements
can be directly incorporated in the analysis system. An even
more
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promising approach is four-dimensional variational assimilation,
in which optimization is performed in the temporal as well as
spatial domains. With the increased understanding of the
theoretical aspects of data assimilation over the past few years,
many aspects of the future of data assimilation have become
clear.
Quality control will become even more important with the
introduction of many new observation platforms and the observation
and assimilation of new quantities. Complex quality control, which
uses several independent quality checks in order to make a more
robust decision, will continue to be improved, and an attempt will
be made to salvage information from miscommunicated or improperly
coded data.
The observing network will provide many new platforms to
assimilate data from such devices as Doppler radar and new
satellite sensors. To obtain the maximum amount of information from
these data, it is desirable to use them in their most original raw
form. Thus, the retrieval step that is currently performed with
many data sets (e.g., temperatures and moisture retrieved from
satellite measured radiances) can be eliminated, and the observed
radiances used directly. To do this, it is necessary to have a
high-quality forward model that transforms the model fields into
the same form as the observations. This step of incorporating
observed quantities directly in the analysis is vital for fully
utilizing the data. However, significant effort is required to use
properly each new type of data.
Assimilation systems of the future will also be required to
include many new quantities (e.g., clouds, soil moisture, skin
temperature, precipitation, ozone, other trace gases). To properly
assimilate such quantities, it is necessary to incorporate them in
the prediction model, develop the proper statistics, and include
observations influenced by these quantities. All three of these
steps will require substantial effort. In future systems, it is
likely that diabatic processes will play a larger role. As the
coupling between dynamics and physics becomes more important, the
inclusion of more exact constraints will become necessary.
The final configuration of data assimilation systems of the
future is not completely decided. It may be based on the extension
of a three-dimensional variational system to a four-dimensional
system or some approximation of a Kalman filter.
One exciting potential by-product of ensemble forecasting and
data assimilation schemes is the concept of adaptive
observations. Here ensemble techniques are used to identify, in
a 12- or 24-hour forecast, regions of the atmosphere that are
particularly sensitive to observational error, and/or adjoint
techniques are used to estimate the sensitivity of a given forecast
error measure to perturbations in these regions. Then programmable
platforms (such as high-flying, dropsonde-equipped aircraft) are
deployed to the regions. Experiments with low-order models show
large potential increases in forecast skill from application of
this technique. It may represent an optimal way of deploying
limited observational resources and will provide a means of
optimizing forecasts with respect to a chosen error measure, which
may be local in some cases. Thus, we may be able
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to choose, in a given meteorological circumstance, to make those
observations that minimize errors in, for example, the 72-hour
forecast of a violent storm over a populous region.
Applications of Advanced Computer
Architectures
Research and operational numerical models are just beginning to
be run on massively parallel processors (MPPs; see below). Several
problems have to be solved before the application of MPPs becomes
routine, however. A major problem is that of software for
translating standard code into code that makes efficient use of MPP
capability. Experience to date shows that codes written expressly
for MPPs are very difficult to understand and to update, making
them impractical for many applications.
It will be absolutely necessary to have a stable vendor
environment for MPPs before full-scale development can proceed. The
recent demise of several MPP vendors underscores the risks involved
for operational NWP centers in these early stages of MPP
development.
Parameterization of Physical
Processes
Accurate prediction of the moisture field, including horizontal
and vertical cloud distributions, is one of the most important
items for both numerical weather prediction and climate
forecasting. Recent studies have shown the importance of predicting
the horizontal distribution of shallow clouds for the coupled
ocean-atmosphere system. The distribution of upper-tropospheric
moisture is an important component in the radiative heat budget,
but one that is neither well observed nor well predicted by current
models. It is clear that the prediction of moisture requires an
accurate formulation of its sources and sinks, as well as extreme
care in its advection by the model wind fields. A full treatment of
model-parameterized processes is beyond the scope of this
Disciplinary Assessment, but the current status of some of the most
important components can be outlined briefly: cumulus
parameterization, explicit prediction of atmospheric suspended
liquid or ice concentration, and surface physics.
Current cumulus parameterization schemes can be classified into
three basic types:
1. Adjustment schemes (e.g., Manabe-type moist convective
adjustment and the Betts and Miller scheme)
2. Mass flux schemes (e.g., that of Arakawa and Schubert)
3. Schemes based on statistical equilibrium of water (Kuo
schemes)
Recently, many operational centers have decided to use one of
the mass flux schemes. Overall experience in testing cumulus
parameterization schemes in
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forecast models has indicated the importance of including (1)
saturated downdraft effects, (2) the interaction of penetrative
convection with boundary- and subcloud-layer mixing processes, and
(3) cloud-radiative interactions. There is some indication from
coupled atmosphere-ocean experiments that, perhaps owing to
inadequacies in cumulus/boundary layer interactions,
model-generated convective precipitation is less sensitive to
changes in sea surface temperature than in nature. Evaluation of
cumulus parameterization schemes is, however, difficult since
cumulus convection interacts with many other physical processes
that themselves may not necessarily be represented adequately in
the model. Although tuning may ameliorate the most obvious
problems, questions still remain about the theoretical foundation
of cumulus parameterization.
The prediction of cloud liquid and ice water content is now
being attempted in mesoscale and global forecast models. The
interaction between cloud water and radiation is also being
explicitly calculated. Preliminary results indicate improvements in
many aspects of the forecasts, including the amount and location of
precipitation, and cloud amounts. These improvements are being
documented quantitatively using comparisons with satellite
data.
More attention should be paid to accounting for cloud
microphysical processes both in explicit clouds and in
parameterized convective clouds. The water vapor content of the
atmosphere is very sensitive to assumed cloud physical processes,
and better prediction of water vapor content will be necessary for
improvement in quantitative precipitation forecasts, longer-range
numerical weather prediction, and climate simulation.
Considerable effort has been made to improve the
parameterization of surface physics, particularly ground hydrology.
These improvements include two-layer soil thermodynamics and
hydrology with explicit evaporation, transpiration, and canopy
intercept for latent flux estimates; improved surface exchange
coefficients; and parameterizations for drainage, runoff, and snow
cover. Results indicate improved forecasts of screen temperature
and precipitation over land and, in general, improvements in the
diurnal cycle over land.
A comprehensive program covering both numerical upgrades and a
review and development of physical parameterizations will be
necessary to take advantage of recent research developments and
greater computer resources. Upgrades to physical parameterizations
should be based on more refined theory, much better evaluation
techniques, better model resolution, and affordability. In the near
term, one may expect advances to occur in the above-mentioned areas
of surface physics, cloud and cloud-radiation parameterizations,
and the increasingly realistic simulation of phenomena associated
with severe weather such as squall lines, outflow boundaries, and
mesocyclones.
Numerical Techniques
The nature of the typical weather forecast problem motivates the
continued
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search for accurate and cost-effective ways of making discrete
approximations to the continuous equations. Much effort is
currently being spent on developing two-time-level,
semi-Lagrangian techniques, although the outcome of these
efforts may be the development of a two-time-level Eulerian method
that avoids its originally encountered unattractive features (e.g.,
instability, damping) while keeping its natural advantages (e.g.,
simplicity, conservation easily enforced). Another technique is to
increase resolution over only those parts of the computational
domain which it is required. The technique of automatically
adjusting selective grid enhancement presents a promising
avenue of exploration since many significant weather phenomena are
related to sharp horizontal variations of the meteorological fields
(e.g., fronts and airmass contrast across coasts) that form, move,
and dissipate. A related recent development, which will continue,
is the implementation of a single general model for almost all
meteorologically relevant scales (i.e., from the planetary to the
cloud scale). These unified models, run with selective grid
enhancement, may allow simultaneous computation of nonhydrostatic
clouds and/or breaking gravity waves on nested domains with
enhanced resolution and of large-scale flow on a planetary-scale
domain. Other important numerical issues include the following:
Model Vertical Coordinate
One of the very recent advances in numerical techniques is the
utilization of isentropic coordinates as the vertical coordinate in
both global and regional models. Because isentropic coordinates are
quasi-Lagrangian, they do not suffer from the problems usually
associated with vertical differencing. On the other hand, they
cannot be used readily in nonhydrostatic models, in which phenomena
such as breaking internal waves may cause isentropic surfaces to
overturn. This weighs against the use of isentropic coordinates in
a unified model. A hybrid-coordinate approach has been proposed to
overcome the lack of resolution near the ground and the problem of
isentropic surfaces intersecting the ground. More investigation is
needed into the feasibility of using such hybrid coordinates and
determining whether there is an advantage to their use in numerical
weather prediction and climate modeling. Some operational mesoscale
forecast models use the eta coordinate, which is a variation of the
sigma coordinate that remains relatively horizontal and uses step
mountain topography. This permits a more accurate description of
orography with rapidly changing slopes than some spectrally based
topographic representations. With recent increases in computer
power, mesoscale models can have a horizontal resolution of the
order of 20 km with 50 layers in the vertical, which represents a
major improvement over present models.
Numerical Techniques for
Advection
Although many forecast models still employ classical numerical
schemes, the semi-Lagrangian approach of treating the dynamics has
received much attention in recent years. This approach, when
coupled with semi-implicit time integration, allows much longer
time steps com-
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pared to those allowed by the traditional
Courant-Friedrichs-Lewy stability criterion, minimizes phase errors
and computational dispersion, and easily allows shape preservation.
These considerations have led to the use of semi-Lagrangian
formulations in many research and operational models. One major
drawback of semi-Lagrangian methods is their lack of an a priori
conservation guarantee, which is viewed by some as essential for
climate modeling. Although further work is needed on this subject,
a novel semi-Lagrangian approach has recently been proposed, in
which exact conservation of mass and any other scalar variables can
be achieved. The semi-Lagrangian technique is also being applied to
nonhydrostatic systems in both regional and global models. One
unresolved problem with semi-Lagrangian schemes that will require
future attention is the treatment of flow around steep orography
when large time steps are being used.
Technological Developments
Ground- and Aircraft-Based Measurement
Systems
In situ measurements from surface stations, ships, aircraft, and
balloons remain the backbone of the global observing system in aid
of weather forecasting. Improvements of this in situ measurement
capability and of ground- and aircraft-based remote sensors offer
the promise of much improved knowledge of the overall state of the
atmosphere, which should lead to improved understanding of weather
dynamics and physics and to improved forecasts.
In situ measurements have also proved valuable to the very
short-range prediction problem. The State of Oklahoma recently
funded a high-density mesonetwork of surface observing stations.
Data from these stations have led demonstrably to improvements in
short-term local and regional forecasts and to associated economic
benefits, as well as improved public awareness and science
education. Efforts are now under way to enhance the mesonet by
adding profiler measurements and measurements of soil moisture, and
to network the data through primary and secondary schools. The
panel believes that such mesonets are a cost-effective route to
much improved short-range regional and local forecasts, as well as
better science education. Such mesonets may be funded ideally
through public-private partnerships.
Some effort has been made to improve the technology of the
rawinsonde. The next generation of balloon sounding will be more
automated, perhaps requiring human attendance only weekly or
monthly, and state variable sensors should be much improved.
Tracking by the GPS is just being developed for rawinsonde and
dropsonde wind finding. Despite its obvious sampling limitations,
balloon sounding remains a cost-effective means of sampling the
atmosphere, and the deterioration of the global rawinsonde network
is alarming.
Commercial air carriers offer another means of sampling the
atmosphere, both at cruising level and during ascent and descent.
These measurements offer
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many advantages over balloon soundings, including much better
spatial and temporal coverage and potentially low operating costs.
One disadvantage compared to balloons is that sounding data are
restricted to cruising altitudes and below. We strongly encourage
observing system simulation experiments and data denial experiments
aimed at determining the importance, or lack thereof, of routine
measurements above standard aviation cruising altitudes.
Another means of obtaining atmospheric measurements is by
remotely piloted aircraft. Unmanned aircraft have been used by the
military for about 50 years; they played a vital role in
reconnaissance and as decoys in the Yom Kippur war and in Desert
Storm. Technological advances in low-Reynolds-number aerodynamics,
propeller design, carbon fiber epoxy construction, and power plants
now make it possible to build unmanned aircraft that can cruise at
18 km altitude for two or three days, carrying many hundreds of
kilograms in payload, including GPS-based dropwindsondes. These
aircraft may soon enable plentiful direct measurements up to the
lower stratosphere, at relatively low cost. They are particularly
well suited to obtaining soundings over the ocean and over sparsely
populated land. They would be instrumental in observation or
numerical forecast systems that made use of adaptive observations.
A major hurdle to be cleared is the problem of coordinating
unmanned aircraft operations with the air traffic control
system.
A number of technological developments promise much-improved
measurements of atmospheric water vapor. Differential absorption
lidar (DIAL) operates by transmitting laser pulses in and slightly
off a water vapor absorption band, and comparing the intensities of
the received return. A major limitation of the technique is eye
safety; this requires transmitting low-power and/or broad-beam
pulses, necessitating integration of the return over relatively
long periods to achieve a reasonably high signal-to-noise ratio.
Current estimates place the minimum error of water vapor estimates
by this technique at about 1 g/kg, with vertical resolutions of the
order of 100 m and a maximum altitude of about 3 km. The technique
cannot be used to retrieve water vapor profiles above cloud base.
Even so, DIAL offers much improved sampling of lower-tropospheric
water vapor.
Some information about atmospheric water vapor content can be
obtained from the GPS. A single GPS receiver is capable of
measuring the time delay between reception and transmission of the
signal from one or more satellite-borne transmitters. This delay is
due to electromagnetic effects in the ionosphere, the total
atmospheric mass, and water vapor. The ionospheric delay can be
corrected by using two different frequencies and comparing the two
time delays, whereas the atmospheric mass component can be
accounted for if surface pressure is known to an accuracy of
greater than about 0.3 millibar (mbar). The remaining delay is
proportional to the vertically integrated water content. At any one
time, about six GPS satellites are visible from a single location,
so that the different elevation angles of the satellites can be
used to make some inferences about the
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vertical distribution of water vapor. The maximum vertical
resolution from this technique is limited to about 1 km. Finally, a
satellite-borne GPS receiver can be used to estimate vertical
profiles of water vapor by observing the occultation of
satellite-borne GPS transmitters, provided an independent
evaluation of the vertical temperature profile is available. The
water vapor content determined by this technique is effectively
averaged over about 200 km horizontal distance, and vertical
resolution is limited to about 1 km.
Vertical profiles of virtual temperature can be estimated using
the radio-acoustic sounding system (RASS). In this technique, a
vertically propagating sound pulse is tracked by radar; since the
speed of sound is a function of virtual temperature, the latter can
be deduced from the measured velocity of the sound pulse. Vertical
resolution and maximum altitude are limited principally by the
characteristics of the transmitter, and the data tend to be
noisy.
Satellite-Based Measurement
Systems
Satellite data fill the space-time gaps within in situ systems
more uniformly than data from any other observing system, although
information is mostly limited to radiance integrals and cloud-top
properties.
Satellite remote sensing will improve in several technical areas
during the next decade. Passive microwave observations are
promising for detecting precipitation, but the remoteness of
geostationary positions presents a major obstacle that must be
overcome. Active cooling and better infrared detectors can improve
precision from one part in 100 to a few parts in 10,000. Pointing
accuracy to the nearest pixel will be possible. Arrays of detectors
could deliver "snapshots" of regions within a few seconds, and
low-light sensors could deliver high-resolution cloud cover
observations on a moonlit night. On-demand "skycam" operations
could be directed by local forecast officers with immediate digital
data delivery through commercial paths.
During the next decade, satellites will carry infrared
spectrometers that can resolve the infrared spectrum and double the
vertical resolution to the theoretical limit for passive sensing of
temperature and moisture.
Knowledge of the global wind field is widely recognized as
fundamental to advancing the understanding and prediction of
weather and climate. Several active sensing techniques can be used
to detect atmospheric winds. One such technique is Doppler lidar,
which operates much like Doppler radar in that signals returned to
the receiver from distant targets are analyzed spectrally to
recover the Doppler shifts imposed by the motion of the target. The
short wavelengths (e.g., 9 µm) involved in lidar, however,
mean that the targets can be much smaller than for radar and that
comparable Doppler shifts and signal bandwidths are much greater.
For wind sensors, the targets are cloud particles or naturally
occurring aerosols suspended in the atmosphere, which move at
approximately the speed of the wind.
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Representative terms from entire chapter:
numerical weather
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Studies have concluded that tropospheric winds can be measured
from space with current lidar technology. Successful experimental
demonstrations of a 5-joule class, carbon dioxide (CO2) laser were conducted in the laboratory
as part of design studies for the Laser Atmospheric Wind Sounder
(LAWS) instrument.
Sea surface scatterometers can be used to reconstruct surface
wind fields over the oceans. Scatterometers are absolutely
calibrated radars that measure reflected signal strength from
distributed targets. For given operational parameters (wavelength,
incidence angle, and polarization), backscatter from the sea
surface is primarily a function of the capillary wave spectrum,
which is a direct measure of surface wind stress. This can be
related to the surface wind vector. Thus, backscatter measured from
several perspectives (as provided by an instrument in polar orbit
and employing multiple fixed antennae) can be used to infer several
possible averaged wind vectors over a portion of the ocean surface.
Complementary data and continuity constraints may be used to select
the most geophysically likely solution.
Space qualification of the technique dates from the 1978 SEASAT
(U.S. sea satellite) mission, although no successor was deployed
until the launch of ERS-1 (the European Remote Sensing Satellite)
in 1991. The ERS-1 scatterometer samples a swath from 200 to 700 km
on one side of the satellite ground track with 50 km resolution for
three antennae. A large number of studies comparing SEASAT and
ERS-1 scatterometer wind data to those from National Oceanic and
Atmospheric Administration (NOAA) buoys and objectively analyzed
winds now exists. In the range of 2-3 m/s, scatterometer winds
agree to within 2 m/s and 20° of other estimates, barring
contamination from sea ice or precipitation. Moreover, assimilation
of ERS-1 scatterometer wind data can improve operational weather
forecasts, particularly of tropical cyclone formation and location.
This improvement is strongest in the data-sparse Southern
Hemisphere.
The algorithms for deriving winds and for flagging rain- or
ice-contaminated data are empirical. Many groups continue to work
to optimize these algorithms in order to provide the best possible
wind data. In addition, new algorithms should be developed to
extract secondary data products, for example, tracking sea ice to
complement images expected from synthetic aperture radar.
In addition to the important scientific advances that would be
achieved, there is substantial evidence that significant economic
benefit to the nation would occur with the use of better wind data
in operational weather forecasting. Two notable examples would be a
reduction in fuel consumption by airlines achieved through more
accurate wind forecasts in the upper troposphere, and improved
hurricane track forecasts that would reduce the area of
uncertainty. Satellite-based GPS systems can also be used to
measure atmospheric water vapor, as described in the preceding
section.
It is vitally important to undertake an analysis of the
potential costs and benefits of various systems that have been
proposed for enhancing atmospheric wind information. Here, more
than anywhere else, we must be able to compare
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the costs and benefits of existing and proposed systems that
span many federal agencies without regard for the needs and goals
of individual agencies. Once again, we stress the desirability of
using models to make a priori estimates of the impact of new
observing systems on forecasts, as one step toward devising an
optimal combination of observing systems, where ''optimal''
includes the associated costs.
Computers
Massively Parallel Machines
To circumvent the inherent limitations (the speed of light and
the minimum size of a unit) of single central processor computers,
the concept of multiple processors performing tasks in parallel has
been introduced, and several such machines are now on the market.
Thus far, their performance has not lived up to expectations, at
least as far as meteorological applications have been concerned.
The problems are twofold: (1) Learning how to program these
machines is an investment of time and effort that most scientists
tend to avoid. (2) Current experience with atmospheric general
circulation models shows performance that is basically comparable
to a Cray YMP system (1.2 gigaflops), although better performance
(10 gigaflops) can be achieved on more specialized problems. If
numerical weather prediction is to be done with kilometer-scale
resolution over synoptic-scale (1,000 km) domains, massively
parallel machines are presently the only ones that could in theory
deliver the 1,000-gigaflop speed required. Solutions to fundamental
problems with this technology remain to be worked out by the
computer industry, and better software has to be developed by users
to reach the needed speed.
Workstations
In recent years, the appearance of high-performance workstations
(approaching the speed of a single-processor Cray YMP) have made
possible truly local numerical weather prediction.
High-resolution [grid spacing O (5 km)] forecast models, run
over domains large enough (500 km) to avoid contamination by
artificial signals from the domain edge, can provide significant
enhancement of short-term forecasts (3-12 hours). Possible
applications that are being investigated by researchers include
enhancement of emergency response systems, more detailed local
forecasts for military operations, thunderstorm forecasting, and
daily weather forecasts where terrain, coastlines, and/or other
physiographic features exert a significant influence on the
weather. Given the trend in costs and the ease of access to
forecast models, local weather forecast offices could each have
such a system by the turn of the century.
Conclusion
Basic and applied research in atmospheric science has yielded
dramatic im-
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provements in weather forecasts and warnings over the past
several decades and is now poised to make even more spectacular
advances. The main stumbling block to realizing significant
progress in basic research and operational meteorology is the need
for better measurements of the atmosphere, oceans, and land
surface, and the need to better understand and delineate optimal
combinations of measurement systems for specific forecast problems.
Our nation has invested heavily in environmental satellites, and
this investment has been paid back many times in improved
understanding of the atmosphere and better warnings of hazards
ranging from hurricanes to severe thunderstorms and tornadoes.
However, observing systems of great importance, some of low cost,
have been allowed to deteriorate. Examples include research Doppler
radar facilities, global rawinsonde coverage, small research
aircraft for boundary layer studies, and research surface mesonets.
Meanwhile, the measurement of atmospheric water vapor continues to
be vastly inadequate for a number of purposes, ranging from
quantitative precipitation forecasting to climate prediction. In
some cases, we have just begun to realize the potential benefits of
certain types of measurements, such as soil moisture and the
detailed structure of the tropopause. We must stand back and take a
hard look at the costs and benefits of all existing and
proposed measurement systems, from the perspective of basic
scientific progress and societal need, with a blind eye toward the
objectives and budgets of individual federal agencies.
If we elect to take a rational and well-thought-out approach
toward observations in support of basic research and operational
objectives, there is every reason to believe that the potential
exists for great advances in understanding and prediction. A proper
accounting of land surface physics and irreversible processes in
the atmosphere may lead to large increases in the skill of seasonal
forecasts. Better measurements of atmospheric water vapor and of
cloud microphysical processes, particularly those involving ice,
may allow us to solve a number of outstanding problems such as
predicting the development and movement of mesoscale convective
systems and the response of atmospheric water vapor and cloud cover
to climate change. Advanced applications of ensemble and adjoint
techniques to numerical weather prediction may reveal, in near real
time, those parts of the atmosphere that are particularly
susceptible to initial error, allowing us to target such regions
for observational scrutiny and thereby greatly reduce numerical
forecast errors. Better in situ observations in the atmospheric and
oceanic environment of hurricanes may lead to dramatically improved
forecasts of the motion and intensity of these great hazards. These
are but examples of what we can expect to achieve in the coming
decades if we take the right approach now.