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Scientists
engaged in mesoscale and microscale meteorology research
are poised to make major progress on improving forecasts
of precipitation, and accounting more accurately for
mesoscale and microscale processes in models of the climate
and weather. This progress is made possible by recent
advances in observing systems, computers, and theoretical
understanding.
Spectacular
advances have taken place in our ability to observe the
atmosphere on the meso- and microscales. These include
the installation of NEXRAD, wind profilers, and observations
from commercial aircraft. There are new radar techniques
that allow detection of the microphysical properties
of clouds; mobile radars on the ground and airborne radars
that allow mapping the structure of mesoscale convective
systems and even tornadoes at unprecedented resolution;
satellite observations that take advantage of the GPS
system to sample the atmosphere globally with near-mesoscale
resolution; new particle imagers that can clearly define
the drop and ice-crystal structure of clouds; and, new
airborne instrumentation measuring chemical, physical
and dynamical properties of the atmosphere.
Computing
power has advanced to the point where it is now possible
to perform idealized simulations of atmospheric flow
over large domains with high resolution; in particular,
small-scale processes, which cannot generally be resolved
in models for climate and weather forecasting, can be
explicitly computed. These idealized simulations will
allow investigations of the effects of the unresolved
processes on larger scales, and perhaps even a method
to account for them in realistic lower-resolution models. These
simulations are necessary steps on the path to the development
of modeling systems that accurately forecast weather,
and simulate climate change on long time scales.
Other
advances have occurred in the theory of cyclones and
mesoscale convective systems, in the predictability of
mesoscale weather systems, in the interactions of the
atmosphere with orography at the meso- and microscales,
in the development and structure of turbulence and boundary-layer
processes, and in ice processes at very low temperatures. New
mathematical techniques involving adjoints of prediction
models, and the 3DVAR and 4DVAR data assimilation systems
promise to make impressive strides in weather forecasting.
The
Mesoscale and Microscale Meteorology Division of NCAR
has contributed strongly to all of these areas. MMM
is unique because of the breadth of its expertise in
mesoscale and microscale meteorology and its ability
to integrate its program to focus this diverse expertise
on important problems that require an interdisciplinary
approach. The division will continue to play a major
role in mesoscale and microscale meteorology research
and, as it plans for the future, will structure its program
to address a few specific problems that have been identified
as objectives of the U.S. Weather Research Program (USWRP)
and the Global Change Research Program (GCRP). The two
main research themes of the division are Prediction
of Precipitating Weather Systems and Cloud and
Surface Processes Parameterizations.
For
prediction of precipitating weather systems, the main
goal is to advance the understanding and prediction of
significant precipitation events in order to reduce substantially
forecast errors toward the limits of predictability.
To accomplish this goal, there will need to be research
to develop the numerical forecast tools, including high-resolution
forecast models and the data assimilation systems needed
to initialize those models. In addition, there will
need to be efforts to understand the limits of mesoscale
predictability and what it is going to take to drive
the forecast systems toward those limits. Understanding
the dynamics and life cycles of the weather systems responsible
for major precipitation events will be necessary to understand
the factors that limit predictability and its dependence
on the weather systems themselves. Programs within the
division will address each of these areas. Accurate
prediction of precipitation is one of the major objectives
of the USWRP and the division's program is intentionally
aligned with this national program.
For
assessing the cloud and surface processes parameterizations,
the main goal is to quantify the large-scale effects
of mesoscale and microscale processes and to develop
physically based methods to account for these effects
in large-scale models. The emphasis is on understanding
how the moist atmosphere, land and ocean surface, and
hydrological processes interact and how these processes
can be quantified. This effort will include four key
research areas: deep convective cloud systems, boundary-layer
clouds, surface-atmosphere interactions, and the physical
chemistry of clouds. Nonhydrostatic fine-scale modeling
using large-eddy simulation and cloud-resolving models
will be an important component of our approach to these
problems since they allow high-resolution definition
of the mesoscale and microscale systems involved, and
are therefore a good means for testing methods to quantify
the effects of these processes on larger scales. Critical
for the success of our program will be the evaluation
of these models against detailed observational studies
of the underlying physical processes. The goals of this
program will contribute to the objectives of the GCRP
Global Energy and Water-cycle Experiment (GEWEX) and
the Cloud System Study (GCSS) component of GEWEX.
The
present document is the "Science Plan" of the
Mesoscale and Microscale Meteorology Division of NCAR
for the next five years and beyond. The plan describes
what the division intends to accomplish during this period
and the rationale for the choice of topics. Details on
how the Division plans to meet these goals are outlined
in the Director's Message of the FY 1999 Annual Scientific
Report (ASR) where we discuss our research plans for
a two-year period; the ASR gives a detailed account of
all the current research of the division. The Science
Plan has been developed with the existing expertise of
the division in mind and with the expectation that fulfillment
of the goals will require extensive collaboration with
other groups outside the division, such as other NCAR
divisions and the university community. It is recognized
that additional expertise may be needed to fully implement
our plans, but we are optimistic and excited about the
prospects of achieving the research goals outlined within
our Science Plan.
I.
SCOPE OF THE PROGRAM (top)
The
mission of the Mesoscale and Microscale Meteorology
Division of NCAR is to advance the understanding of
the meso- and microscale aspects of weather and climate,
and to apply this knowledge to benefit society.
The
division strives to address the most important and fundamental
scientific themes in mesoscale and microscale meteorology,
with emphases on understanding and forecasting weather
and on evaluating the influence of meso- and microscale
processes on larger-scale phenomena. These basic scientific
themes are reflected by the nature of the division's
subgroups:
-
The
Physical Meteorology Group focuses on investigation
of physical and chemical processes of clouds and
aerosols. Their observational, laboratory and modeling
studies include mechanisms of precipitation and hydrometeor
formation in different cloud types ranging from cirrus
to mid-latitude thunderstorms to tropical cumuli;
determination of derived properties inside clouds
such as ice water content and terminal velocities;
radiative properties of clouds with differing microphysical
makeup and parameterization thereof, indirect and
direct effects of aerosols in clean and polluted
environments; electrification of clouds, mapping
and characterization of total lightning (both intra-cloud
and cloud-to-ground) in thunderstorms, production
of nitrogen oxides by lightning; interactions of
clouds, chemistry and aerosols, modeling of gas and
aqueous chemistry in boundary layer and deep convective
clouds; development and evaluation of microphysical
instruments; and, development of software for processing
and analysis of measurements.
-
The Boundary
Layer and Turbulence Group seeks to increase
the basic understanding of atmospheric processes
that operate on scales of up to a few kilometers
and to determine their collective effects on larger-scale
atmospheric phenomena. Their interests include
boundary layer structure and dynamics; turbulence
dynamics of both convective and stably-stratified
flows; turbulent exchange processes (including
both conserved and chemically reactive trace species);
dynamical and radiational effects of boundary-layer
clouds; and, atmosphere-surface interactions over
land, water and ice. By themselves, these processes
are interesting and important. They are also crucial
to understanding the larger scale behavior of the
atmosphere. To achieve these goals requires a
combination of observational studies to provide
data sets and test cases, and numerical and theoretical
modeling for comparison with the observational
data. Their goal is to develop a better understanding
of microscale phenomena, and improved parameterizations
of microscale phenomena, which are essential for
larger-scale models.
-
The Cloud
Systems Group seeks to quantify the physics
of convective cloud systems, their multi-scale
organization, and how they interact with the larger
scales of motion. They approach the problem through
cloud-resolving numerical models, evaluated against
field observations and satellite data where practicable,
and compared with theoretical analysis to elucidate
basic physical principles. An application of this
work is the derivation of physically based parameterizations
of clouds, convection, and organized mesoscale
systems within atmospheric general circulation
models. Their focus is primarily on tropical cloud
systems on time scales up to intra-seasonal, and
on space scales ranging from about a kilometer
to planetary.
-
The Mesoscale
Dynamics Group seeks to understand the important
mechanisms that govern mesoscale weather systems
and promote the application of this knowledge toward
enhancing mesoscale weather forecast accuracy.
Basic research within this group is directed toward
understanding the dynamics of mesoscale processes
such as gravity waves, convective systems, fronts,
and cyclones. This research seeks to determine
how the larger mesoscale environment organizes
to initiate and control significant weather events,
and how these events in turn modify the larger-scale
environment. Research in this group combines theoretical,
modeling, and observational approaches in addressing
these issues. Theoretical studies are required
to help understand the fundamental interactions
that control the evolution of mesoscale weather,
while observational research is required to assist
us in identifying the important processes that
occur within weather systems and in determining
how best to incorporate observed data into simulation
models. These models are used to evaluate the predictability
of mesoscale weather, to test theoretical hypotheses,
and to assess the potential for improved weather
prediction.
-
The Mesoscale
Prediction Group seeks to advance the science
and technology of mesoscale weather prediction.
Toward this end, they develop advanced mesoscale
weather prediction models (i.e., MM5 and WRF) and
mesoscale data assimilation techniques (i.e., 3DVAR/4DVAR).
Using these tools, they contribute to the science
through the study of important mesoscale weather
prediction problems (i.e., mesoscale convective
systems, cyclones, hurricanes). They develop real-time
mesoscale weather prediction systems for operational
forecast applications and provide community support
for the use of advanced weather models and data
assimilation systems.
To
maintain this scientific program and respond quickly
to new research opportunities, the scientific staff must
have diverse expertise. Therefore, a central aspect
of our science plan is to attract and retain leading
scientists in the field and to develop the careers of
young scientists toward leadership roles. To achieve
this goal, the division will respect scientific uniqueness
and will promote collaboration and teamwork through maintenance
of a congenial, supportive, and professional working
environment.
The
division also devotes resources to community service
activities. This service is not only regarded as an
important part of our role as a national center, but
it enhances our scientific program. Current service
functions include the maintenance and support of a community
mesoscale numerical prediction model (MM5), including
training on its use and making it generally available
to the community; the maintenance of access to a suite
of data analysis software packages; and the support of
a strong and viable visitor program.
Our
research in mesoscale and microscale meteorology spans
a broad spectrum, as reflected by the diverse research
interests within the Division subgroups mentioned above.
For example, MMM scientists have research projects ranging
from the mechanics of the freezing process, wildfire
modeling, advanced numerical methods in computational
fluid mechanics, to theoretical models of synoptic-scale
cyclones and anticyclones. However, as is appropriate
at a national center, our scientific program has a few
major themes that require extensive collaboration among
collections of scientists within MMM, NCAR, and the university
community. MMM has chosen the following two major themes:
- Improve
the ability to forecast precipitation events on time
scales ranging from a few hours to a few days.
- Assess
the influence of mesoscale and microscale systems
on larger-scale systems and account for their effect
in weather and climate models.
These
themes will be supported through an optimal application
of MMM's existing expertise in observing, modeling, and
describing the fine-scale structure of the atmosphere
and through given national and international initiatives
in advancing the ability to predict the weather and climate
change. As such, close collaboration, coordination, and
shared leadership will be required with researchers within
universities and NCAR and with mission agencies, both
nationally and internationally. The following
two sections give a more- detailed account of how we
plan to contribute to the achievement of these goals.
II.
Prediction of Precipitating Weather Systems (top)
1. Mesoscale
Predictability (top)
Goal:
To estimate upper bounds on the time over which forecasts
of precipitation within mesoscale weather systems retain
useful skill, and to identify the key physical processes
that limit forecast skill.
Mesoscale
weather systems are typically embedded within synoptic-scale
flows, while at the same time contain a variety of smaller-scale
motions such as moist convection, symmetric instabilities,
gravity waves, and frontal and boundary-layer circulations. Since
these motions are unique to the mesoscale, studies of
mesoscale predictability with models in which these mesoscale
motions are parameterized are of limited utility. Moreover,
the fact that these motions are highly intermittent and
localized casts doubt on predictability results based
on turbulence closures, which assume the turbulence to
be homogeneous and isotropic. These facts suggest that
further progress in understanding mesoscale predictability
hinges on knowing how uncertainty in mesoscale forecasts
is influenced by uncertainty in both smaller and larger
scales.
These
issues are being addressed by examining the growth of
small differences (or "errors") in the initial
conditions for forecasts of interest, such as the snow
storm of 24--25 January 2000 that brought Washington,
D.C. to a standstill. These experiments, which focus
on the evolution of the scale and amplitude of the initial
error, employ local horizontal resolution of a few kilometers
in order to minimize spurious effects of parameterized
physics and limited resolution. It appears to date that
moist processes exert a controlling influence on the
error growth.
To
gain further understanding of how mesoscale forecast
errors evolve in the presence of moisture, idealized
numerical simulations are planned of the up-scale organization
of moist convection in simple environments, and of synoptic-scale
flows with embedded precipitation systems. The simulations
of convection initiation and organization, which are
intimately related to efforts to understand the life
cycle of precipitation systems discussed below, will
assess the sensitivity of initiation, cell evolution
and up-scale organization to perturbations of initial
conditions. The simulations of synoptic-scale flows
will begin with simulations of idealized baroclinic waves
and fronts to assess the degree to which uncertainties
in the forcing at synoptic scales can alter the predictability
of meso- and convective-scale flow and, conversely, the
way in which variability at sub-100 km scales can influence
larger scales.
Through
these and other sensitivity studies, guidance will be
provided for the development of the model forecast systems
by identifying those
physical processes most crucial for mesoscale forecast
accuracy.
2. Life
Cycle of Precipitating Weather Systems (top)
Goal:
To understand the life cycles of precipitation events
and the implications of their behavior on predictability,
data-assimilation requirements, and the treatment of
forecast-model physics.
a. Convection
initiation
An
important element of this effort is to improve the treatment
of convection initiation in forecast models, particularly
during the spring and summer when large-scale forcing
may be weak. Achievement of this goal is impeded by the
lack of understanding of the mechanisms responsible for
convective triggering. This lack is in large part due
to the absence of fine-scale observations which might
indicate the ways that convection is initiated (or "triggered''),
such as convergence lines, boundary-layer rolls, gravity
waves, differential heating, and orographically modified
flow. To better document the local initiation processes
and linkages with larger-scale forcing, MMM expects to
participate with NOAA/NSSL, ATD, RAP, and the University
of Oklahoma in the planning and execution of field experiments,
such as the International H2O Project (IHOP) which will
use new observational tools to probe the fine scale structure
of water vapor within the planetary boundary layer.
b. Long-time-scale
dynamics of mesoscale convective systems
Until
quite recently, much of the effort devoted toward understanding
three-dimensional organized convection stemmed from the
Pre-Storm Experiment in the Midwest U. S. in 1985. Over
the past few years, the rich spectrum of organized convection
in midlatitudes and the tropics was realized through
the examination of new, large-domain radar and satellite
data sets made possible because of the NWS modernization.
In addition, newer cloud-resolving models are able to
capture the growth stage of a variety of MCSs. Despite
these advances, there is relatively little understanding
of MCS behavior in the mature and decaying stages. Cloud-resolving
simulations are unable to capture the mature-to-decaying
phase of systems while observational field studies tend
to be too confined geographically to document both the
mesoscale environment and convective scale circulations.
A
collaborative effort with ATD, RAP, NOAA/NSSL, and university
scientists to analyze radar and satellite information
over domains of approximately 1000-2000 km is being conducted
to document the mature convective system and its interaction
with the environment. This effort complements field-project
studies and, combined with modeling efforts incorporating
ever-more complicated environmental structure, will allow
us to address the relative importance of synoptic-scale
forcing versus internal dynamics in MCS evolution, the
mechanism(s) by which convective systems regenerate,
the interaction of mesoscale convective vortices (MCVs)
with convection, and the feedback of microphysical processes
and radiation onto system-scale dynamics. The Bow Echo
and MCV Experiment (BAMEX), planned for 2002 or 2003,
will address many of these issues in the context of convective
systems developing in both strongly sheared and weakly
sheared environments.
c.
Tropical cyclones
The
single most damaging weather phenomenon is the landfalling
tropical cyclone. The need for continued research on
formation, intensification, and track of tropical cyclones,
the promise for major advances in prediction in the near
future, and the large potential societal impacts made
landfalling tropical cyclones one of the main foci of
the USWRP. Research in MMM on tropical cyclones will
emphasize integration of observations (i.e., airborne
dual Doppler winds, cloud-track and water vapor winds
from GOES, TRMM data, and additional data from field
experiments such as CAMEX and EPIC) with mesoscale and
cloud-scale numerical simulations to study hurricane
formation and the predictability of landfall intensity,
location and timing. We will emphasize the interaction
of tropical cyclones with extratropical systems and the
upscale organization of convection within the tropical
cyclone circulation. We expect strong collaboration with
researchers at CSU and Albany in these efforts.
d. Orographic
effects
Orography
significantly modulates the initiation and evolution
of precipitation systems, and can promote substantially
higher precipitation amounts and greater spatial variability. The
quantitative prediction of the amount as well as the
type of precipitation, together with accurate treatment
of land surface characteristics (vegetation, snow cover,
topography, and soil type), are extremely important for
an accurate prediction of run-off and stream flow. In
spite of its importance, the accurate prediction of precipitation
in mountainous terrain has remained an elusive goal.
However, recent studies suggest that prediction of the
spatial and temporal distribution of orographic precipitation
can be significantly improved with high-resolution mesoscale
atmospheric models that adequately capture the orographic
influence on the flow. In particular, simulations based
on cases observed during the Mesoscale Alpine Experiment
(MAP) have shown that the horizontal variation of relative
humidity along mountain barriers can produce localized
blocking of an impinging air stream and, when juxtaposed
with an area of saturated, unblocked flow, can lead to
mesoscale convergence and heavy rainfall. Further analysis
of MAP datasets will be undertaken. Modeling techniques,
including microphysical parameterizations, to predict
accurately both the phase and quantity of orographic
precipitation, will be developed and evaluated, possibly
in collaboration with RAP.
e. Cloud
microphysics and precipitation
It
is well known that the structure and evolution of precipitating
weather systems depend strongly on the microphysics and,
in particular, on the conversion of water to ice. Microphysical
processes affect the dynamics of systems through their
influence on the strength of updrafts, downdrafts, and
cold outflows, as well as important forecast parameters
such as precipitation type and amount. As new understanding
is gained of the factors that regulate the amount and
type of precipitation in cold clouds from ice microphysics
research, this knowledge will be applied to improve the
prediction of ice properties in cloud-resolving models.
As part of this effort, the specific sources of error
must be identified in current microphysical parameterizations,
and physically based improvements to the model physics
must be developed, particularly for ice formation, which
are responsible for these deficiencies. A comprehensive
assessment of microphysical processes within precipitation
systems will be conducted, using multi-parameter radar
observations and where possible, detailed in-situ microphysical
observations. Observations obtained in the Stratosphere-Troposphere
Experiments: Radiation, Aerosols, and Ozone (STERAO)
and from the Severe Thunderstorm Electrification and
Precipitation Study (STEPS) will be utilized together
with model simulations to provide the basis for evaluation
and improvement of the cloud microphysics in precipitation
forecast models. Cooperation with ATD and RAP to develop
new capabilities to estimate hydrometeor type and shape
from multi-parameter radar will facilitate these efforts.
3. Mesoscale
Data Assimilation (top)
Goal:
To develop and support state-of-the-art data assimilation
systems for application in mesoscale models.
These
data assimilation systems can be used for a variety of
purposes including the assimilation of data from new
observing systems, analysis of the optimal use of observations,
and understanding the observational requirements for
accurate precipitation forecasts and optimal strategies
for obtaining targeted observations.
a. Advanced
data assimilation systems for community use
While
mesoscale data assimilation is a critical component of
USWRP research, relatively few researchers have access
to sophisticated data assimilation systems. To facilitate
broader research on this important topic, a community
mesoscale data assimilation system based on a state-of-the
art mesoscale forecast model and its full physics adjoint
will be established. A suite of supporting components,
including observational operators, minimization software,
and necessary background and observational error covariances
will be developed, and user support for the data assimilation
system will be provided. This system will initially be
based on the MM5 Model; as the next generation WRF model
is developed, the data assimilation will be migrated
to the new modeling system. Through continued interactions
with scientists at Florida State University, NOAA/FSL,
and CGD, improved techniques for assimilating data on
the mesoscale that benefit this assimilation system will
be developed and evaluated.
b. Optimal
use of existing observations and the potential benefits
of new observing systems
Over
the past decade, many new observing tools have been developed,
including Doppler radars, wind profilers, GOES (water
vapor winds), GPS/MET systems (radio occultation technique),
GPS (ground-based precipitable water observations), ACARS,
and many other in-situ and remote sensing systems. These
new observing platforms provide mesoscale observations
with greatly enhanced spatial and temporal resolution.
A major challenge is to develop techniques that provide
optimal benefit in using these observations to improve
mesoscale weather prediction, and to assess quantitatively
the potential value of new observing systems. Data assimilation
experiments using the MM5 4DVAR systems will be conducted
to assess the impact of GPS/MET data, GOES water vapor
winds, and other observing systems. MMM will also participate
actively in the NAOS (North American Observing System)
program and will conduct necessary experiments to help
determine the observational requirements for future forecast
models.
The
assimilation of Doppler radar data is a particularly
important aspect of this research. Ground-based and
airborne Doppler radars provide important wind and precipitation
observations of weather systems, including mesoscale
convective systems, wintertime banded precipitation,
and tropical cyclones. In complementary research with
RAP and the University of Oklahoma, MMM will continue
its efforts to determine how to best use the observations
from Doppler radars for cloud-scale and mesoscale model
initialization and prediction. Interactions with scientists
at ATD and NOAA Hurricane Research Division on the assimilation
of Doppler radar data for tropical cyclones, both in
the open ocean and near landfall, are also planned.
c
. Data assimilation and ensemble forecasting
Approximations
of the statistics of forecast error, typically in the
form of a forecast-error covariance matrix, are central
to data assimilation. These statistics determine the
relative weighting of observations and the first-guess
(or background) forecast, as well as how a given observation
influences other locations and other variables in the
analysis. Although in the past it has been applied primarily
at the medium range, the goal of ensemble forecasting
is to predict just such statistics of the forecast. It
is therefore natural to combine data assimilation with
ensemble forecasts at the short range, say 3--6 h.
The
ensemble Kalman filter is a promising avenue to a combined
ensemble forecast and data-assimilation system. In essence,
one begins with an ensemble of analyses and makes an
ensemble of short-range forecasts (using the full nonlinear
forecast model) to the time of the next available observations.
This ensemble of forecasts is used to estimate the forecast
covariances required to assimilate the new observations
via the standard Gaussian formalism of the Kalman filter. Each
ensemble member is then updated given the new observations
by assimilating a set of perturbed observations (that
is, the actual observations plus noise consistent with
the observational uncertainty). This approach shares
with four-dimensional variational techniques (4DVAR)
the benefit of flow-dependent forecast covariances, but,
unlike 4DVAR, it does not require the linearized or adjoint
versions of the forecast model. The ensemble Kalman
filter also has the attractive feature of providing a
short-range ensemble forecast and of ``initializing''
the ensemble members for longer-range ensemble forecasts.
This
approach has been tested within the simplified context
of a quasigeostrophic model using simulated data and
performed well with 100 ensemble members. Further testing
is planned in a nonhydrostatic model at convective scales
using simulated Doppler radar data, where comparison
against the 4DVAR scheme mentioned above will also be
made.
d.
Research in adaptive observations
A
benefit of a combined ensemble forecasting and data assimilation
system is that an estimate of the uncertainty in the
short-range forecast is then available. This estimate
is crucial to rigorous algorithms for adding observations
to the network (that is, adaptive observations), as it
allows one to calculate the expected impact of an additional
observation given the location and the observation error. Techniques
based only on adjoint sensitivities or singular vectors,
such as those employed in previous field experiments
(FASTEX, NORPEX, Winter Storms), do not utilize such
estimates and thus are likely suboptimal. In practice,
the calculation of the expected impact of an observation
must be approximated if a number of observation locations
are to be considered. Various
approximations will be tested in the context of the quasigeostrophic
model.
4. High-resolution
Weather Research and Forecast Model Development (top)
Goal:
To provide a new mesoscale forecast and assimilation
system that will advance both the understanding and
prediction of important mesoscale weather, and promote
closer ties between the research and operational forecasting
communities.
The
recent effort to develop a new model, called the Weather
Research and Forecast (WRF) Model, will be continued
as a collaborative effort among NCAR, NCEP, FSL, CAPS,
AFWA, and a number of university scientists. With this
model, these researchers seek to improve the forecast
accuracy of significant weather features across scales
ranging from cloud to synoptic, with priority emphasis
on horizontal grids of 1-10 kilometers. The model will
incorporate advanced numerics and data assimilation techniques,
multiple relocatable nesting capability, improved physics
and treatment of complex terrain. These advances will
help enhance the ability to simulate convection and mesoscale
precipitation systems, including precipitation systems
in mountainous regions. The model should be well suited
for a range of applications, from idealized research
to operational forecasting, and will have flexibility
to accommodate future enhancements.
The
WRF Model has the potential benefits of providing a more
direct path for research advancements to feed into operational
forecast models, and an easier transition for personnel
moving between university research and the operational
modeling and forecast centers. A functional version of
the WRF Model is imminent, and will be maintained, supported,
and freely distributed by MMM as a community model. When
the WRF model becomes sufficiently mature to be used
operationally, NCEP will consider implementing it initially
as a very high-resolution nest within the Eta model (by
2002). At that point, the WRF model would also be a
candidate for replacing the regional operational models.
To
receive acceptance in the research and NWP communities,
specific model features are being designed based on convincing
theoretical analyses and evaluation of controlled model
testing. With this in mind, the model is being developed
in stepwise fashion, beginning with the solver for the
basic dynamical equations and progressing to include
more complex physical processes and data-assimilation
techniques. Comparisons with known analytic solutions
and converged idealized simulations are being used to
the extent possible in evaluating alternative approaches
for specific components of the model system. As model
complexity increases, the system will be evaluated for
real-data NWP applications.
The
focus on high-resolution regional prediction will require
new efforts in model verification. Because of the highly
intermittent and localized nature of mesoscale weather
systems, traditional measures of forecast accuracy developed
for synoptic-scale forecasts may be inadequate to provide
useful statistics on model performance. In addition,
datasets representing details of mesoscale systems over
appropriately large domains are generally lacking. Our
efforts in improving the quality of model verification
will thus proceed along two paths. First, in collaboration
with ATD, RAP, and NOAA/NSSL, we will create regional
data sets from WSR-88D radar, rain-gauge networks, and
other local observations to document adequately the structure
of precipitating weather systems. Second, as needed,
new verification techniques will be developed that consider
the physical character of
mesoscale systems as well as whether prediction is inherently
deterministic or stochastic.
III.
Cloud and Surface Processes Parameterizations (top)
1.
Deep Convective Cloud Systems (top)
Goal:
To understand the physics of convective cloud systems
on time scales up to intraseasonal, how they influence
large scales, and how they can be parameterized.
Deep
convective cloud systems can now be numerically simulated
for long periods over large domains with high resolution. These
simulations provide a way of understanding large-scale
circulations of which deep convection is an integral
part, and they provide a consistent basis for the development
of parameterizations of the effects of deep convection
cloud systems in larger-scale motions. However, microphysical
processes, cloud-radiation interaction, and sub-grid
turbulent processes have inherent uncertainties that
feed back to produce uncertainties in predicted large-scale
motions. The work described in this section is part
of the NCAR Clouds in Climate Program (CCP) which is
a concerted effort to bring together process studies
and parameterization of deep convection relevant to climate
modeling and numerical weather prediction.
a. Cloud
systems on long time scales
Emphasis
will continue to be on cloud systems in the tropics,
on time scales from a week or so up to the intraseasonal,
and on space scales from about a kilometer to planetary.
The focus on the tropics is motivated by the fact that
the tropics play a key role in the climate system in
terms of the energy and water cycle. In spite of its
importance, the coupling between moist convection and
large-scale dynamics in the tropics lacks a fundamental
basis. The difficulty has been that large-scale processes
in the tropics depend directly on the continued and systematic
action of small-scale processes. For example, the concerted
effect of deep cumulus clouds may influence a slow, large-scale
tropical oscillation, but the tropical oscillation equally
affects the cumulus convection. Hence the small and large
scale motions must be solved for together. The need
for long-time-and-space-scale integrations means that
processes that can usually be neglected for short-time-scale
weather prediction (e.g., cloud-radiation and air-sea
interaction) must be accounted for in models of climate.
In
simulating convection on a time scale of a few hours,
the primary issue is how to approximate the rates of
change between the three phases of water. On time scales
longer than a day or so, the evaporation rate and fall
velocity of the hydrometeors, and the interaction of
water in any of its three phases with solar and long-wave
radiation becomes progressively more important. When
cloud-resolving models are integrated for long times
a key issue is the nonlinear coupling between the parameterized
microphysics and radiation through explicitly resolved
dynamics. We will continue to use the single-column-type
approach in which the model (i.e., the cloud-resolving
model (CRM), or the single-column model) is driven by
large-scale conditions derived from the data gathered
in major observational campaigns (e.g., GATE and TOGA
COARE). This approach is a valuable testbed to evaluate
various parameterizations (cloud microphysics in particular)
used in the CRM and to assess the impact of cloud systems
on surface processes and on the radiative transfer.
Building
on our experience with GATE and TOGA COARE cloud systems,
we aim to couple the cloud-resolving model with an ocean
model. Multiscale modeling of a coupled system of clouds
and the ocean has only very recently become computationally
feasible. This kind of multiscale modeling is necessary
to achieve realistic Hadley and Walker circulations in
domains of order 10,000 km, and will build on ongoing
idealized prototype simulations. A new approach, whereby
convection is explicitly simulated is also in a prototype
stage and will soon be brought to maturity.
Idealized
modeling will also be used to study cloud systems and
their impact on the large-scale tropical dynamics. We
will continue to study convection organization in long-term
simulations of convective-radiative equilibrium, applying
two- and three-dimensional domains within the equatorial
waveguide using both cloud-resolving and parameterized
convection. A nonhydrostatic global model will be used
in a series of studies of convection organization on
a rotating planet, starting with a constant sea surface
temperature (SST) aquaplanet, and proceeding to a planet
with idealized distribution of the SST and land masses,
including topography. Using such an idealized setup
we aim to study the role of convection in monsoons.
Finally
we plan to study the influence of organized convection
(e.g., mesoscale convective systems) on the large-scale
momentum budget in the tropics. Convection organization,
how it is modulated by the large-scale dynamics, and
how it feeds back into the large-scale flow are key issues. MMM
has a strong heritage in the dynamics of the organized
convection that will be essential in theoretical and
observational studies of the large-scale impacts of organized
convection.
b. Convectively
generated tropical ice clouds
Tropical
cirrus covers a significant part of the tropics and has
a key effect on the Earth's radiation budget and dynamics. Because
anvils occupy an area much greater than the deep convection
producing them, studies are needed to understand better
the interactions among radiation, dynamics, and microphysics.
Modeling studies and satellite data will be used to determine
the complete life cycle of tropical anvils and factors
responsible for their persistence.
In-situ
and remote-sensing measurements of cloud microphysical
and radiative properties help derive distributions of
cloud microphysical properties as a function of altitude
as well as their relationship to cloud radiative properties. Convectively
generated cirrus have sufficiently high optical depths
near cloud top to produce localized areas of bright or
optically thick cirrus, reflecting more than 40 of the
incoming solar radiation. However, the upper parts of
cirrus cannot alone account for the high albedos. The
lower parts sometimes extend down to the melting layers
in the so-called stratiform cloud regions that are usually
necessary to produce high albedos. These aspects need
to be further quantified and we will carry out studies
to do so using microphysical, radiometer and conventional,
polarimetric, and Doppler-radar data from TRMM.
Using
observational data from earlier tropical cirrus measurements
and ongoing TRMM field programs, parameterizations will
be developed of the tropical cirrus microphysical properties
in terms of diagnostic or prognostic variables for GCMs
and CRMs. For example, expressions for the ice-particle
effective radius, extinction coefficient, absorption
coefficient, and mean terminal velocity in terms of cloud
ice water content and temperature will be developed.
Additionally, a characterization of ice particle shapes
will be provided.
Aside
from the difficulty of parameterizing convection per
se, the calculation of convective cloud-system areal
extent, or cloud fraction, is very important for radiative
transfer in GCMs. A primary area of research is based
upon satellite data and analyses, and progress will be
accelerated by using cloud-resolving models. In turn,
observational data will aim to develop new microphysical
schemes to be used in CRMs and provide important validation
for CRM simulations.
c.
Impact of tropical cloud systems on radiative transfer
Clouds
impact radiative processes in a complicated way. Large-scale
weather and climate models apply a plane-parallel approach
to deal with the transfer of shortwave (solar) and longwave
(thermal) radiation. Such an approach can be argued
appropriate for models with grids featuring large aspect
ratio (i.e., the ratio between the horizontal and vertical
grid spacings). Cloud-resolving models, featuring grids
with aspect ratios close to one, usually apply a similar
approach because of the lack of affordable alternatives.
However, the validity of the plane-parallel approach
can be questioned when vertical columns with a few-kilometer
horizontal extent are treated independently, and only
vertical radiative fluxes are considered. We will evaluate
the effects of detailed three-dimensional radiative transfer
on the energy budget and evolution of the resolved convection
models. The traditional "independent pixel" radiative
parameterizations adapted from GCMs will be replaced
by multidirectional quasi-exact calculations. The objectives
are to (1) determine the changes in the surface and top-of-atmosphere
radiative fluxes when radiation is allowed to interact
with the 3D structure of the cloud field; (2) determine
the relative importance of changes to cloud microphysics
and changes to radiative parameterizations for the energy
budget; and (3) quantify the effects of three-dimensional
radiative transfer on the structure of radiative equilibrium
solutions for tropical convection. The principal objective
is to determine what aspects of radiative interactions
with cloud geometry and inhomogeneity are important for
large-scale model parameterizations.
Radiative
processes have long been postulated to strongly influence
tropical deep convection (e.g., the early morning maximum
of convective intensity over tropical oceans). Such an
influence was reproduced using cloud-resolving models.
It is not clear, however, what influence radiative transfer
has on the large-scale tropical dynamics and on the SST
through the interaction of radiation with water vapor
and clouds. For instance, idealized studies suggest that
convective-radiative equilibrium is unstable in the sense
that self-maintaining circulations have to develop to
balance the differential radiative cooling between dry/cloud-free
and moist/cloudy large-scale regions. It remains to be
seen if this "moisture-radiation instability" is
relevant for the intraseasonal variability in the tropics.
A need for a cloud-resolving approach to address the
large-scale impacts of radiative transfer is apparent.
Microphysical
parameterizations used in cloud-resolving models have
been developed to represent phase changes of water substance
and precipitation fallout. They are not designed to predict
parameters relevant for the radiative transfer (such
as effective radius or single scattering albedo of cloud
particles). Moreover, impact of some hydrometers (e.g.,
graupel or rain) is often neglected in radiative transfer
models. One can argue, however, that parameterizations
of cloud microphysics and of radiation transfer should
be closely coupled in order to address the cloud-radiation
interaction in a meaningful way. We will attempt to develop
such microphysical parameterizations.
d. Parameterization
of deep convection
Current
parameterizations do not account for the effects of convective
organization, which influences the life cycle and spatial
coherence of large-scale circulations in the tropics. We
have a hierarchy of models to tackle such problems ranging
from idealized process models, to cloud-resolving models,
to an intermediate model in which convection is parameterized
but dynamical interactions are resolved, and finally
to a large-scale "cloud-resolving parameterization" model
which applies a cloud-resolving model instead of a parameterization
scheme. This unique suite of models will allow comprehensive
study of not only the parameterization problem, but also
the underlying fundamental problem of understanding the
interaction between convection and
the mean flow.
2. Boundary
Layer Clouds (top)
Goal:
To understand the physical processes of PBL (shallow)
clouds and represent their effects in climate models.
In
the following we describe our observational and modeling
studies of the different types of boundary-layer clouds. These
cloud studies will continue to be coordinated with the
GCSS (GEWEX Cloud System Study) program, which seeks
to develop physically based parameterizations of cloud-related
processes for climate and global numerical weather prediction
models. We will also work as the NCAR CSM Atmospheric
Modeling Working Group (AMWG) to improve PBL clouds in
climate models.
In
the future, when computer resources permit, we intend
to combine all of our cloud modeling efforts in the areas
of marine stratocumulus, trade cumulus and deep tropical
convection to simulate whole cloud systems within the
Hadley Circulation over the oceans and to study their
role in the hydrological cycle.
a. Marine
stratocumulus regime
One
of the most climatologically important PBL cloud types
is marine stratocumulus. Small changes in its fractional
cloud cover or microphysical properties can drastically
alter the amount of solar radiation input to the ocean
surface. Hence, an accurate representation of this cloud
regime in a coupled climate model is required to simulate
accurately the energy budget of the Earth's surface. Current
climate models treat clouds, turbulence and radiation
separately using independently developed parameterization
schemes, but these physical processes can interact strongly
on a temporal (or spatial) scale that is smaller than
the time step (or grid resolution) commonly used in current
climate models. Our goal is to develop parameterizations
that represent the net effect of all these processes.
One
of the key issues in incorporating marine stratocumulus
into climate models is the rate of entrainment of warm
dry air from above the PBL into the stratocumulus-topped
boundary layer (STBL). This rate determines the thermodynamic
structure of the STBL, and hence the cloud amount. Our
numerical and observational studies of marine stratocumlus
have been focused on this particular issue. Based on
large eddy simulations, we have recently developed an
entrainment-rate formula which differs from those developed
elsewhere and requires testing with field observations. Planning
is underway for a field experiment (DYCOMS-II) to focus
explicitly on entrainment processes and test different
entrainment-rate formulae currently used for STBL parameterizations.
This proposed study is planned to use new observational
techniques on the NCAR C-130 aircraft. In addition,
we will continue to analyze data obtained from several
previous airborne observational studies in this regime:
DYCOMS-I, FIRE-I, ASTEX, and ACE.
Another
key issue in incorporating marine stratocumulus into
climate models is the effect of mesoscale variations. Mesoscale
variations, such as mesoscale cellular convection or
cloud streets, are often observed in the marine stratocumulus
region. These variations are likely to modify the grid-averaged
cloud amount within a GCM mesh, but their effect has
never been included in any GCM. Within the next few
years, increasing computer power will allow us to simulate
explicitly the mesoscale variations, along with the dominant
turbulent motions (i.e., large turbulent eddies). Such
simulated flow fields can be used to examine the effect
of mesoscale variations on the cloud properties of marine
stratocumulus.
b.
Transition from marine stratocumulus to trade cumulus
regime
As
air moves downstream towards the equator over the eastern
part of large oceanic basins, marine stratocumulus breaks
up and gives way to cumulus. During this transition,
along the air trajectory the cloud cover is drastically
reduced and hence solar radiation input to the ocean
is drastically increased. This transition between the
two cloud regimes is another focus of our PBL cloud research
within MMM.
In
the incipient stages of this transition, the stratocumulus
layer typically becomes "decoupled" from the
well-mixed layer near the surface; here stratocumulus
becomes only weakly linked to the surface process, and
cumulus often develops under the stratocumulus deck. Important
processes for this decoupling and development of cumulus
under stratocumulus include evaporation of drizzle, short
wave radiative warming of the stratocumulus, and surface
heat flux. We will continue to investigate the roles
of these processes.
Another
mechanism that may also play a role in the transition
is cloud-top entrainment instability. When evaporation
of cloud due to entrained dry inversion air is significant,
the mixture may become colder than its cloudy environment
(that is, negatively buoyant), a process known as buoyancy
reversal. Whether this buoyancy reversal process can
lead to the transition from stratocumulus to cumulus
regime is still debatable. Our recent large eddy simulations
showed that buoyancy reversal did not lead to a total
breakup of stratocumulus cloud deck but that it plays
a dominant role in determining the simulated cloud fraction
and liquid water path. We will continue looking for
other important factors that determine the cloud amount
and eventually develop a cloud scheme of the marine stratocumulus
regime and its transition to the cumulus regime.
c.
Fair weather cumulus
Fair
weather cumulus over subtropical oceans is known to play
a major role in the hydrological cycle of the Hadley
Circulation. Trade cumulus transports moisture from the
PBL to the low- to mid-troposphere, pre-conditioning
the atmosphere for deep convection further downstream. MMM
scientists have a long history of observational and modeling
studies of this cloud regime, which will serve as a basis
for further study. Examples of field studies in this
regime that will continue to be used for comparisons
with modeling studies include: BOMEX, GATE, and ATEX. Key
issues include how to represent the cloud amount, which
affects the global radiation budget, and moisture transport
by cumulus, which affects the global moisture distribution.
Fair
weather cumulus over land is also important because it
modifies the land surface through its effect on incoming
radiation. We intend to include fair-weather cumulus
in our coupled PBL-land process model, which is described
in the following section. We plan to also use observational
data from ARM for comparison with modeling results.
The
role of fair weather cumulus (over both land and ocean)
on transport of biogenic hydrocarbons and other trace
gas species, and their chemical reactions is also being
investigated. Work is now underway to incorporate these
processes in this cloud regime into our large eddy simulation
code that is coupled with a chemistry transport model
(see below).
d.
Observing the boundary layer
Improvements
in remote sensing capabilities being conducted jointly
with ATD, as well as with NOAA and NASA, will provide
new ways to observe the three-dimensional structure of
both the clear and cloudy PBL. Water vapor differential
absorption lidar (DIAL) aircraft data from SGP and other
programs will be used to study the fine-scale structure
of scalars in the PBL, as well as mesoscale variability
of humidity and PBL structure. Fine-scale measurements
of both radial velocity and scalars, for example from
the lidars in flat terrain (LIFT) experiment, will be
used to document PBL structure in the entrainment layer
and provide data for comparison with numerical simulations
of entrainment to develop improved parameterizations.
A
fundamental limitation in LES modeling is the fidelity
of the parameterizations used to represent sub-grid scale
motions. This problem is especially acute near fluid
interfaces--i.e., near the surface and near the PBL top. To
address this problem, we are planning to conduct a series
of observational studies that will measure the sub-grid
scale motions and allow comparison with parameterizations
of these motions used in large-eddy numerical models. The
objective is to develop parameterizations that more accurately
incorporate the sub-grid scale field of motion into the
resolved field. The first of these sub-grid scale experiments,
SGS-2000, has been carried out in the Central Valley
of California in September 2000 using a two-dimensional
array containing 14 three-dimensional sonic anemometers. We
are starting to develop plans for a similar experiment
to investigate sub-grid scale
parameterizations in the entrainment region at the top
of the PBL.
3. Surface-Atmosphere
Interactions (top)
Goal:
To understand the interactions between the atmospheric
boundarylayer and the underlying surface, and improve
the parameterization of air-surface interactions in
synoptic-, meso- and large-eddy-simulation models.
a. Land-atmosphere
interaction
Land
surfaces are typically heterogeneous. This leads to significant
horizontal variations in the contributors to the surface
energy budget, and thus PBL structure. This, in turn,
can result in errors in numerical climate and weather
forecast models that do not incorporate these effects. In
order to deal with this problem, variables that describe
the surface and variations in surface properties need
to be properly formulated to satisfactorily represent
the effects of the surface on the atmosphere. High quality
comprehensive datasets are critically needed for comparison
with models and development of parameterization schemes.
Techniques need to be developed for comparing observations
of fluxes and other statistical properties of the boundary
layer over horizontally heterogeneous land surfaces with
model results. We address two complementary questions. First,
how can the heterogeneity be accounted for in models
with large-scale resolution, such as regional and global
models? And second, how do we incorporate the effects
of surface heterogeneity on the diurnal variation of
PBL structure in regional and global models?
Surface
heterogeneity includes spatial variations of soil types,
soil moisture, vegetation, and topography. The regional
variability of soil moisture is important in storm initiation
and evolution, and flash floods, making surface-atmosphere
interaction important to both the weather (USWRP) and
climate (GCIP, ROCEW) communities. Observational data
analysis will focus on surface, aircraft, and remotely
sensed data collected from various field campaigns, such
as the Boreal Ecosystem-Atmosphere Study (BOREAS), the
Cooperative Atmosphere-Surface Exchange Study (CASES-97),
and the Southern Great Plains (SGP-97) Experiment. Using
remotely sensed soil moisture, the effect of spatial
variations in soil moisture on the development of the
atmospheric boundary layer will be investigated. In addition,
the effect of the surface heterogeneity on stable boundary
layers will be examined using the observational data
collected during CASES-99. High spatial resolution models
with land parameterization schemes will be used to examine
model sensitivities and compare their performance with
observations. Surface land parameterization schemes
will be applied to LESs to study the influence of the
subgrid surface heterogeneity on the development of the
PBL.
In
order to evaluate the performance of numerical models,
area-averaged turbulent fluxes over heterogeneous surfaces
will be estimated using observations from surface-based
sites, aircraft, and satellites. Remotely sensed variables
include soil moisture from airborne and satellite microwave
sensors, long- and short-wave radiation (including radiative
surface temperature), and biomass and land-surface types
retrieved from satellite and aircraft imagery. In addition,
sensitivity of this scale-up process will be investigated
using the BOREAS and SGP-97 data sets. Improved formulations
of the bulk formulae for estimate of subgrid turbulent
fluxes will also be developed.
Surface
heterogeneity also plays an important role in the exchange
of carbon dioxide between the atmosphere and terrestrial
biosphere. This is very important from a global climate
perspective. We will investigate the spatial variation
of horizontal and vertical transport of carbon dioxide
and the role that they play in carbon dioxide budgets,
especially in nocturnal stably stratified boundary layers,
which are a particular problem for carbon dioxide budget
estimates.
Both
climate and weather forecast models have particular difficulty
predicting the air temperature close to the surface,
and surface energy fluxes during the morning and evening
transitions, and at night. As a result, the statistically
steady-state and homogeneous turbulence assumptions for
Monin-Obukhov (M-O) similarity are violated during these
periods. Since M-O similarity theory is the current
basis for parameterizing land-atmosphere interactions
in numerical models, we will be working on new schemes
that parameterize temperature and fluxes during the transition
and nocturnal periods emphasizing the effects of vegetation,
soil moisture, land use, and topography on the evolution
of the PBL. One approach will be to examine the temporal
and spatial variability of air temperature, wind, and
water vapor, and their vertical transport during the
diurnal cycle using data from two field programs conducted
during the spring (CASES-97) and summer (SGP-97) over
the Great Plains. We will use these data to test surface-process
parameterization schemes, linked surface-PBL schemes,
and mesoscale models. We will also focus on understanding
the nocturnal stable PBL, which is especially difficult
to parameterize because of intermittent turbulence, by
analyzing the field data collected from CASES-99. We
are exploring participation in IHOP to further studies
of PBL water-vapor evolution.
b.
Ocean-atmosphere interaction
In
order to treat the ocean and the atmosphere as one system,
we need to understand the turbulent processes on both
sides of the interface. Since the surface fluxes are
the link between these two media, accurate representation
of the surface fluxes is our primary goal in ocean-atmosphere
interaction studies. Recent field measurements suggest
that ocean waves can dynamically alter the turbulent
kinetic energy budget in the atmospheric surface layer. Depending
on the relative magnitude of the wave phase speed and
the local wind, surface waves can either be a source
or sink of momentum. As a result, the traditional relationship
between surface fluxes and mean atmospheric profiles
is altered. The effects of surface gravity waves on turbulence
in the atmospheric and oceanic PBLs, and in particular
on M-O scaling, will be investigated using LES with a
nested-grid, high-resolution surface layer and a moving
surface fitted grid. Our goal is to gain understanding
of wave effects and then develop a parameterization that
links the ocean and atmospheric PBLs as a system that
includes the wavy (interface) effects.
Over
the coastal zone, variations in oceanic bottom topography
lead to shoaling waves. Existing numerical models for
surface stress in the shoaling zone fail because of their
inability to properly account for wave age, shoaling,
and internal boundary layer development. The fetch-dependent
wave field in the shoaling zone cannot be adequately
studied without information on the spatial variation
of the wind and stress fields. Two goals to be pursued
are: to study the relationship between the spatial varying
mean wind, stress, turbulence structure, and surface
wave fields by analyzing the field data collected from
the Shoaling Wave Experiment (SHOWEX); and, to model
effects of wave age, shoaling, and internal boundary
layer development on the drag coefficient and momentum
transfer between the waves and the atmosphere.
c. Chemical
transports and transformations
The
Earth's surface is the source and sink of many trace
atmospheric constituents. The PBL acts as a conduit
between the surface and the overlying free atmosphere,
and as reactor for many of these constituents, which
have both natural and anthropogenic sources. These transport
and transformation processes occur in both clear and
cloudy PBLs, and the budgets of many of these constituents
are determined by physical processes in the PBL such
as turbulent diffusion, entrainment, PBL growth rate,
and cloud cover and transport. These processes will
be studied using data from several field programs such
as the Aerosol Characterization Experiment (ACE-1) and
the Pacific Exploratory Mission (PEM-Tropics).
The
effect of boundary-layer processes on the mixing and
chemistry of biogenic hydrocarbons and their reaction
by-products, particularly over forest canopies, is also
being investigated. Hydrocarbons emitted from vegetation
are relevant for climate because of their role as sources
of ozone and aerosols in the troposphere. By coupling
a PBL LES with biogenic hydrocarbon chemistry, an understanding
of the influence of boundary-layer mixing in chemical
constituents can be attained. By combining a forest canopy
LES with simple decay chemistry, the role of the forest
canopy and homogeneous and heterogeneous sources of hydrocarbons
may be assessed. The role of small cumulus upon the
fate of ozone and its precursors via boundary layer venting,
aqueous chemistry, or |
