University of Missouri
_______
Enhancing Mid-West region water sector management:
Application of a novel long range forecasting technique
Response to NOAA Solicitation: OAR-CRO-2009-2001430
Sector Applications Research Program (SARP)
MU PI:
Anthony R. Lupo
Department of Soil, Environmental and Atmospheric Sciences
University of Missouri
Columbia, MO 65211
MU Project Manager:
Verne Kaupp
Project lead: Earth science coordinator
ICREST/University of Missouri
Columbia, MO 65211
ABSTRACT
The goal of this work is to use weather and climate information on the regional level to support
the decision making activities of the public and private sector regarding water resources;
especially those that impact the economic health and vitality of the Midwestern region. Many
sectors (e.g., agriculture) of the regional economy are influenced strongly by weather and
climate. The ability to anticipate climatic variables such as temperature and precipitation, and
then drought or excess precipitation as much as one to two seasons in advance is a crucial issue.
The inter-seasonal and interannual variability of climate in the region are strongly influenced by
the tropical Pacific region phenomenon known as El Nino. While great advances have been
made in understanding this phenomenon, the ability to forecast its evolution is still an area that
needs attention. Additionally, the impact of El Nino is greatly influenced by longer-term climatic
variations and, of course climate change, which may be the result of anthropogenic activities.
Using the results of previously published studies, long-range forecasts can be made and these can
be made available to water resource decision-makers to use in order to help them formulate
policy or decide which activities to undertake. Thus, this work will have four basic objectives: a)
to examine the issue of interannual, inter-decadal, and climate change in the mid-west region
over the course of a century and use this information to generate seasonal forecasts, b) to use
global and regional modeling capability to supplement these forecasts. The models will be
evaluated for their own capability to make seasonal forecasts in the region, c) to create a
decision-making tool, which can be accessed by water resource policy-makers who make
economically related decisions throughout the region. This will also include integrating the use
of satellite information to supplement the forecast process, and d) to create a web-based interface
that will be accessible and useful to that local community in support of their activities.
Additionally, this system will be made adaptable for other regions as long as the background data
is provided.
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TABLE OF CONTENTS
EARTH SCIENCE RESEARCH RESULTS........................................... 3
STATEMENT OF WORK .................................................................... 4
REFERENCES………………………………………………………………………….14
BUDGET ......................................................................................... 18
BUDGET JUSTIFICATION ............................................................... 18
CURRENT/PENDING SUPPORT ...................................................... 20
VITAE .............................................................................................. 21
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EARTH SCIENCE RESEARCH RESULTS
In the middle part of North America, the sea surface temperature patterns (SST) as forced by
ENSO in the tropical Pacific region correlates quite well with seasonal temperature and
precipitation regimes (e.g., Kung and Chern, 1995; Park and Kung 1998; Lee and Kung 2000;
Berger et al. 2002; Lupo et al. 2007), especially during the cold season. For example, Lupo et al.
(2005) (Berger et al. 2003) demonstrate that winters tend to be snowier in the southern (northern)
part of Missouri during El Nino (La Nina) years. Ratley et al. (2002) and Lupo et al. (2007)
demonstrate that La Nina years tend to correlate with very dry summers and fall seasons within
this region. Using these results can produce simple seasonal forecasts that show skill beyond
climatology (see Changnon et al. 1999; Lupo et al. 2008b). Long Range Forecasts for
temperature and precipitation two seasons ahead can be evaluated two seasons ahead in terms of
percent, where 0% is a forecast that is the same as climatology and 100% is a perfect forecast
(Lupo et al. 2008b).
Using the results from above, observed data provided by NOAA and satellite data provided
by NOAA and NASA, for example, the MODIS (Moderate Resolution Imaging Spectrometer),
such as vegetation indexes and land cover indexes, would be able to be correlated with
temperature, precipitation, tropical Pacific Ocean region SSTs (ENSO phase), and Palmer
Drought Index. This kind of information could be used by the forecasting group in order to
supplement long range forecasting tools by providing a view of the ground surface conditions.
This would give the forecaster information on how current weather conditions are already
influencing the biosphere. This data would be available through MODIS
(http://modis.gsfc.nasa.gov/about/), and vegetation indexes use visible and near-infrared
channels to derive these. The MODIS instrument is aboard the Terra (a morning flyover vehicle)
and Aqua (an evening flyover vehicle) satellites.
The NASA GISS climate models are General Circulation Models (GCM) and several have
been developed for use by the research community. Examples of the GISS model in use can be
found in Schmidt et al. (2006) or Hansen et al. (1984). The GISS GCMs are cartesian which can
be run at a variety of horizontal and vertical resolutions. However, this work will use output
provided on grids with a resolution of 2°×2.5° in the horizontal (latitude × longitude) and 31layers in the vertical. The dynamics are based on generally the "Arakawa B" grid scheme.
Scheme B uses no horizontal viscosity and is particularly suitable for coarse resolution models.
The newest GISS GCM is the ModelE, which was released in 2004. Our work will use the basic
set of inputs, and utilize surface temperature, precipitation, sea surface temperatures, and
standard level heights/pressures.
The University of Missouri possesses in-house a regional scale model which can be used
either as a forecast model, or to simulate climate on a regional scale. The Mesocale Atmospheric
Simulation System (MASS) is a limited-area terrain-following sigma-coordinate model. It was
developed, maintained and improved by MESO, Inc. The latest version of MASS has interactive
multiple-nest capability, nonhydrostatic dynamics allowing simulations on the order of 1 km or
greater, a four-dimensional data-assimilation capability, four levels of microphysics and several
convective parameterization schemes. The physics of the model are similar to that of the GISS
GCM with the major difference being that the horizontal resolution can be run as low as 3 km,
and there are more than 50 layers in the vertical. The same outputs as the GISS will be used here.
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STATEMENT OF WORK
Introduction and background
In the Midwestern region of the United States, weather and climate play critical roles in the
economic vitality of the region (e.g., Changnon 1999; Changnon et al. 1999), and especially in
the management of water resources. Thus, the decisions made by those who formulate and then
implement policy or who make economic decisions must take weather and climate into account
(Changnon and Kunkel 1999). For example, in agriculture, which crops to plant or when and if a
particular field should be fertilized will depend critically on the forecast of temperature and/or
precipitation up to two seasons in advance. Also, as drought and excess precipitation impact
water supplies critically, it is important for us to understand the frequency of drought and it’s
associated climatic regimes. To complicate matters, droughts can be considered climatologically,
agricultural,
and/or
hydrological,
and,
at
times,
these
do
not
coincide
(http://www.drought.unl.edu/dm/). Additionally, two of the most important climatic issues
influencing this region of the country are a) the interannual (and interdecadal) variability of
temperatures and precipitation, and b) climate change.
The former are largely influenced by physical phenomenon, such as El Nino and Southern
Oscillation (ENSO) (e.g., Kunkel and Angell 1999, Changnon 1999, Berger et al. 2002, Lupo et
al. 2005). The degree to which ENSO influences weather and climate in a region can be modified
over the course of several decades. Recently, it has been shown that the Pacific Decadal
Oscillation (e.g., Mantua et al. 1997; Gershunov and Barnett 1998; Lupo et al. 2005, 2007) can
modify the influence of the ENSO cycle in this part of the country. In popular culture, these
issues and concepts are most readily understood by the general public in the discussion of
hurricane frequencies (Gray et al. 1997; Lupo and Johnston 2000; Lupo et al. 2008a).
Climate change is the other issue that will have a critical role in the long-term decision
making processes (Barnston et al. 2005). While there is wide-spread agreement among scientists
that climate change is constantly occurring and that over the last several decades, the climate has
become warmer globally (e.g. IPCC 2001, 2007), but there is some debate as to the degree to
which there may be human contribution (e.g., IPCC 2007). Also, while most of the IPCC
projections suggest that a monotonic increase in temperatures can be expected globally, an
important paper was recently published that demonstrated that interannual and interdecadal
variability, such as that forced by the ENSO and PDO, would still occur, although their
frequency and interaction may change (e.g., Tsonis et al. 2007). Some research has suggested
that ENSO has been occurring more frequently over the last part of the 20th century (e.g.,
Mokhov et al. 2004), and the IPCC (2007) states that one of the key questions to be answered by
research is how climate change will influence the occurrence and / or strength of ENSO. Thus,
these issues must be taken into account when trying to project future weather and climatic
conditions.
For some economic decision-making, such as in agriculture or energy usage, the use of longrange weather forecasts is already occurring, and has been for some time (e.g. Changnon and
Kunkel 1999). While the reliability of these forecasts is still low, great advances have occurred
over the last two decades (Barnston et al. 1994; Anderson et al. 1999). These forecasts generally
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attempt to predict whether or not temperatures and precipitation will be above, near, or below
normal (e.g. http://www.cpc.ncep.noaa.gov/products/predictions/) for one month to two seasons
in advance. In some cases, energy usage can be forecast one year in advance (e.g., Changnon et
al. 1999). Thus, these forecasts are generally probabilistic, but should be better than that of
climatology if they are to have any value. Long range forecasting generally uses a statistical
approach (e.g., Barnston et al. 1994; Anderson et al. 1999), and includes such procedures as
contingency tables and analogues. Contingency tables use climate classifications, and analogue
techniques look to seek out similar conditions from the past, and both are a crude form of what
are called neural networks (e.g., Roebber et al. 2003).
In the middle part of North America, the sea surface temperature patterns (SST) as forced by
ENSO in the tropical Pacific region correlates quite well with seasonal temperature and
precipitation regimes (e.g., Kung and Chern, 1995; Park and Kung 1998; Lee and Kung 2000;
Berger et al. 2002; Lupo et al. 2007), especially during the cold season. For example, Lupo et al.
(2005) (Berger et al. 2003) demonstrate that winters tend to be snowier in the southern (northern)
part of Missouri during El Nino (La Nina) years. Ratley et al. (2002) and Lupo et al. (2007)
demonstrate that La Nina years tend to correlate with very dry summers and fall seasons within
this region. Using these results can produce simple seasonal forecasts that show skill beyond
climatology (see Changnon et al. 1999; Lupo et al. 2008b, and Table 1 here). Table 1 shows the
skill of long range forecasts issued by the global change research group at MU
(http://weather.missouri.edu/gcc) for temperature and precipitation two seasons ahead in terms of
percent, where 0% is a forecast that is the same as climatology and 100% is a perfect forecast.
However, caution must be taken when looking at these results as they may have applicability
only within their regions of study (e.g., Palecki and Leathers 2000). Additionally, the skill for
long range forecasts here will not be as high as those for short range (0 – 3 days) forecasts over
climatology, but will be higher than those where a model replaces climatology for the baseline
(Market and Lupo 2002).
Climate change must also be taken into account and it is recognized that, even if the globe
warms monotonically by a large amount, the impacts of climate change on temperature and
precipitation regimes will be unevenly distributed (e.g., IPCC, 2001, 2007; Semenov and
Bengtssen, 2002) across the globe. Thus, it is important to be able to not only monitor the
climate and but to model it regionally. This is a key question that also needs resolution, as it is
not necessarily true that accounting for climate change in a forecast is as simple as adding the
trend. Climate change also impacts interannual and interdecadal variability as well (e.g., IPCC,
2001, 2007; Semenov and Bengtssen, 2002). Additionally, while progress has been made in the
last two decades in climate prediction (Reichler and Kim 2008) and the forecasting of ENSO
related interannual variability (Wittenberg et al. 2006; IPCC 2007), more progress needs to be
made in order to more faithfully replicate ENSO, and it is still not possible to forecast
interdecadal variability.
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Table 1. Skill Scores for the long range forecast generated here versus climatology (taken from
Lupo et al. 2008b).
Forecast period
Skill Score (%)
Total (Temperature + Precipitation)
20%
Temperature
34%
Precipitation
0%
Total Summer Season
38%
Temperature
40%
Precipitation
33%
Total Winter Season
0%
Temperature
19%
Precipitation
-14%
Objectives
The overall objective of this work is to examine the near term societal and public policy
impacts of climate change and interannual and inter-decadal variability in the middle of North
America on water supplies and issues, and then develop decision support materials which will be
used by decision and policy makers in order to supplement their economic decision making.
Additionally, the system we are proposing here would be easily transferrable to any region in
North America or globally.
Within this framework, there are four issues, which will require detailed investigation:
To quantify the interannual variability of climate in the middle of North America over a
longer period of time.
Lupo et al. (2005) and Lupo et al. (2007) and others have examined the interannual
variability of temperature and precipitation in relation to ENSO for the middle of North
America from 1955. They examined data acquired from the Missouri Climate Center and
from the National Center for Atmospheric Research (NCAR) / National Centers for
Environmental Prediction (NCEP) archives. We are proposing here to extend their
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investigations back further, to about 1900. This will provide for a longer data base which
will contribute to the decision making tools used to generate long range weather
forecasts. This would be accomplished during phase 1 and 2 of the work.
Additionally, this group needs to generate a longer record of scored, real-time long range
forecasts than currently available (five years – see Lupo et al. 2008b). Evaluation of these
will determine how much real progress can be made by including model data, satellite
data, or a longer observational record. In Table 1, it is clear that there is more room for
improvement in the winter season, while the summer season forecasts have been good.
This portion of the work would be implemented during the first three phases of the work,
and be operational by phase 4. Additionally, even longer term or true climate projections
(several years out) would be developed and implemented during phase 4 based on what
was learned in the first three phases.
To model climate change and climate variability.
Using the results of Lupo et al. 2007, 2008b as a guide, we will examine the ability of the
NASA GISS model (see methodology section) to capture regional interannual variability
and climate. This is a key research problem as identified by the recent IPCC report. We
will use hindcasting (back-forecast) in order to determine whether or not the model can
produce results that are similar to the published results found in Lupo et al. (2008b), who
evaluate the model performance using a modified Brier Skill score taken from Lupo and
Market (2002). The ability of models to replicate the current state of the climate as well
as internnual variability has improved, but capturing interdecadal variability is still
difficult. This work would be carried out during phase 1 and 2.
Also, we will use the regional modeling capability available in-house at the University of
Missouri. The regional model would be used to “fine tune” the GISS model results and
would be part of the work plan during phase 2 and 3 of the work, and be operational for
phase 4.
To create a decision making tool that includes information such as satellite imagery and
model forecasts.
Using the results from above, satellite data provided by NASA the MODIS (Moderate
Resolution Imaging Spectrometer), such as vegetation indexes and land cover indexes,
would be able to be correlated with temperature, precipitation, tropical Pacific Ocean
region SSTs (ENSO phase), and Palmer Drought Index. This kind of information could
be used by the forecasting group in order to supplement long range forecasting tools by
providing a view of the ground surface conditions. This would give the forecaster
information on how current weather conditions are already influencing the biosphere.
Additionally, correlations of the Midwest land cover to tropical SSTs has not been
performed before, and this would be a new and unique aspect of this work. This data
would be available through MODIS (http://modis.gsfc.nasa.gov/about/), and vegetation
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indexes use visible and near-infrared channels to derive these. The MODIS instrument is
aboard the Terra (a morning flyover vehicle) and Aqua (an evening flyover vehicle)
satellites.
Climatological impacts on the water economic sector (public water supplies) are well
known. Both drought and excessive precipitation cause changes in both water quality and
water quantity. These changes vary with climatological conditions and geographical
location. As the federal regulations limiting chemical and microbial substances in
drinking water increase, both of these changes make providing the necessary quantity of
adequately treated water for public consumption more difficult for water supplies. As
variation in weather and regulatory conditions increase, it is becoming apparent that
better forecasting of water availability and treatment requirements is needed by the
nation’s public water supplies.
An example of the impact of climate change on water quality (water chemistry) is the
increase in regulated disinfection byproduct formation potential in surface water sources
during the first several seasons of normal precipitation following a drought period. The
formation of these carcinogenic chemicals increases because of natural organic materials
in the storm water runoff into surface water bodies.
One example of the impact of climate change on water quantity is the need to modify the
water intake drawoff levels because of the depth of flow in rivers or water level in
reservoirs. Another is the need to raise wellheads in alluvial well fields when forecasting
indicates wells will be subject to increased flood elevations.
Changes in water flow and chemistry require changes in water treatment chemical feed
dosages, or the treatment chemicals, used throughout water treatment processes. The
necessary changes must be determined by laboratory analyses, associated cost changes
must be budgeted, and then they must be implemented. So the longer the lead time from
identification of potential change to implementation, the better the results. This is why
the proposed improvements in climate forecasting are becoming critical for the water
economic sector.
The major water treatment plants that provide water to the major urban areas are
required, and have the experience and databases necessary, to relate climate forecasts to
the various
management actions necessary to provide adequate supplies of properly
treated water during all climate conditions. To optimize their ability to meet these
requirements, they need high quality, short and near-term climate forecasts so they have
time to test, budget for and implement the management efforts that are required to
address the impacts of changing climatological conditions. Climatological forecasting is
not currently being used
in water supply resource planning and management
because the current forecasting does not incorporate current weather pattern trends
coupled with climate change modeling. This project is designed to mitigate that major
deficiency.
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Success in the application of improved climate forecasting to the water supply economic
sector will be impacted by a variety of factors. These include the forecast results (i.e.,
climate forecast model simulations) being in the correct units for convenient use by
water supply managers, timeliness of the forecast periods and data presentation,
knowledge of the water economic sector and its terminology by the researchers and
staff of the delivery organization, and training of the water economic sector
organizations’ staffs in the use of the forecast data. The proposed project team includes
members whose collective experience adequately addresses these issues.
The University of Missouri Water Resources Research Center (MU WRRC) has been
involved in theoretical and applications research in water supply for many years. It is
part of several national networks of sister agencies, and is well acquainted with the public
water supplies in Missouri. It is a well-respected member of the water supply industry’s
national and state organizations. It has been involved in research and related
projects with the federal and state agencies involved in water resources work; these
include the Missouri Department of Natural Resources (MDNR), US Environmental
Protection Agency (USEPA) and US Geological Survey (USGS) for many years.
Because of these relationships, it is the preferred delivery mechanism for the
products of this project at both the state and national levels.
The decision support tools to be developed are the improved climate forecasts provided
in a timely manner to facilitate management decision-making, and training modules on
the use of the forecast data. Pilot projects will involve presentation of the forecast data to
major municipal water economic sector members in Missouri, tracking their use of the
data in management decision-making, and the water quality and quantity results of the
management decisions. The results of these projects will be published in water economic
sector journals, incorporated in university training courses, and shared with the major
federal and state water resource agencies. The delivery mechanism will be the MU
WRRC. The water resource agencies are expected to identify other uses of the results of
this proposed project; those uses will be specific to the agencies’ various missions
With adequate public and private-sector policy-level decision-making with respect to
water supplies, not only will negative impacts of climate change be minimized, but
positive results from the changing conditions can be optimized. Input for decisionmaking on water use and policy issues will result from Climate Modeling that includes
the impacts of global climate change. Model simulation results are of potential value to a
variety of individual, local, regional and national decision-makers. Following are brief
explanations of some of the potential user groups.
Flood mitigation and response will be improved by providing better input for targeting
locations and regions that will require assistance. Indigenous aquatic species maintenance
can be improved by identification of areas in which water bodies will be impacted by
higher or lower stream flows. Public water supplies at the local and regional levels can
be better managed if more accurate forecasts of excessive precipitation and drought are
available. Air, land, and water transportation system management will benefit from more
accurate forecasting of storms, road flooding, and river levels. Wastewater treatment is
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impacted by ambient air temperatures, and precipitation that impacts infiltration and
inflow to sewer systems and retention time in treatment basins; climate forecasts will
assist treatment plant planners, designers, and managers. Wetland management for
surface water quality maintenance can be improved with better forecasting of seasonal
temperatures and precipitation.
Water resource decision-makers are potential users of the results of climate modeling
simulation results, and should be identified and targeted as a client. This is the target
population that the project team will identify. Information will be transmitted and the
target population will be defined by presentations at regional and national seminars, and
organizational and industry conferences and meetings. During Phases 3 and 4, this
population will be contacted to make them aware of the availability of and methods to use
the model simulation results, and included in the dissemination of the website use
instructions. Specifics on the use of the Climate Forecast Website and the results posted
thereon will be provided by on-line training on the University of Missouri Distance
Learning Website.
To create a web-based interface to support the regional public and private entities, which
can access information to support decision making with regard to water resources.
The purpose of this element of the proposed work is to provide broader access to static
and dynamic geospatial climate and weather modeling results and information between
federal, state, and local agencies by promoting a service-oriented architecture (SOA)
(Booth et al. 2004) that promotes the use of Web services for access to these results and
data. The specific goals are to:
o Provide users with the ability to view regionalized climate and weather data and
information products via a browser-based user interface.
o Provide geospatial community users (agriculture, weather, water resources, etc) with
the ability to view/consume regional climate and weather data and information
products via a viewer.
o Make regional climate and weather models and data easily available for humans and
applications alike;
o Provide seamless access to modeled climate and weather results as well as data
repositories;
o Provide a common and standard data format for each information area;
o Support search capabilities on the catalogs for certain properties, filtering the search
results, and retrieving the results in various formats; and
o Integrate web services data within both scientific applications and business processes.
SOAs are implemented around two basic components: service definition languages (which
describe how to invoke the remote service) and message formats for over-the-wire
transmissions (Aktas et al. 2005). We propose using the Web Service approach to building
an SOA. Currently we propose using WSDL (http://www.w3c.org/TR/wsdl) for service
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description and SOAP (http://www.w3.org/TR/soap/) for the message formats. Web
Service systems have an important design feature: services are decoupled from the user
interface components. This provides latitude to build any number of services that are
capable of interacting with the same data or image service. Typical of this user interface
are browser-based computing portals. These have been researched and developed over a
number of years (Fox and Hey 2002). This field is rapidly expanding as a proliferation of
component-based portal systems are being adopted and standardized component
programming interfaces are being released. This approach promotes reuse of developed
interfaces, applications, tools, and service components. The Open Geospatial Consortium
(OGC) (http://www.opengis.org) defines a number of standards for modeling earth data
and services for interacting with this data. The data models are expressed in the XMLbased Geography Markup Language (GML), and the OGC service framework is
continuing its evolution within the Web Service model.
Meeting climate and weather model service requirements represent an excellent
opportunity to further leverage these open standards for services that will bridge and
promote these data to the broader Geographical Information Systems (GIS) community.
This will allow us to permeate many additional third party decision systems, applications,
and tools. As part of this GIS development work, we would implement the OGC standard
Web Map Service. The broader GIS community has other data model and service
standards defined the commercial vendor ESRI such as their Image Server protocols.
Aligning with this format as well permits the leveraging of ESRI’s extensive client base as
well as their tools. The adoption of OGC as well as this industry standard is intended to
take advantage of the significant amount of freely available GIS data that already exists in
these formats. More importantly, these standards define an open architecture that may be
integrated with Grid/Web service standards to permit distributed scientific computing.
ESRI and OGC each have created interoperability tools so use of one or the other does not
preclude any integration of the proposed data services. Promoting both just provides an
ease of integration for the client.
Methodologies
The methodologies for the objectives above borrow from previous work (Lupo et al. 2007,
2008b), which were modified from the earlier studies of Kung and Chern (1995), Lee and Kung
(2000), and Mokhov et al. (2004). These can be briefly described below.
Observational and Model Data
The analyses used in Lupo et al. (2007, 2008b) were the global monthly mean and
reconstructed SSTs and SST anomalies compiled by the NCEP and available through the
National Oceanic and Atmospheric Administration (NOAA) online archive available online at
(http://www.cdc.noaa.gov/cdc/reanalysis/). Monthly SSTs and anomalies are also available and
these can be found in the monthly Climate Diagnostics Bulletin online at
(http://www.cpc.ncep.noaa.gov). The mean SST anomalies in the ENSO region are available
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from 1864 to the present through the Center for Ocean and Atmospheric Prediction Studies
(COAPS –http://www.coaps.fsu.edu), and the phase of the ENSO is found also at the COAPS
site. These data would be used to meet objectives #1 and 2 and extend the observational record
back to 1948 in phase 1 and phase 2 of the work.
The ENSO definition is used in many studies (e.g., Lupo et al. 2005; 2007 and references
therein). In summary, the index classifies years as El Niño (EN), La Niña LN, and neutral (NEU)
based on 6-month running-mean Pacific Ocean basin sea surface temperatures (SST) anomaly
thresholds bounded by the region 5o N, 5o S, 150o W, and 90o W. The defined region
encompasses both the Nino 3 and 3.4 regions in the tropical Pacific. The anomaly thresholds
used to define EN years are those greater than +0.5o C, less than -0.5o C for LN years and NEU
otherwise. The ENSO year is defined as beginning on 1 October for the year and ending in
September the next year (following the references above and COAPS). The 500 hPa heights and
height anomalies from the NCEP re-analysis project (Kalnay et al. 1996) were also examined
and are available via the many of the same sources referenced above. Finally, the mean monthly
temperature and precipitation records for the Midwest will be taken from the Missouri Climate
Center and the Midwestern Regional Climate Center. These are available back to the late 1800s
for many places in the region (e.g., Columbia, MO back to 1890). The ENSO data and the
observed mid-western surface records will be used in each objective and project phases 1 - 3, and
we will use these to extend the work of Lupo et al. (2007) back to 1900.
Making and evaluating Long Range Forecasts
In order to construct long range forecasts, seasonal forecasts can be made and then evaluated
against climatology. Climatology is simply the 30-year mean of temperature or precipitation for
a particular period (a day or a month), and represents the minimal standard that any forecasting
technique needs to exceed to be useful. We will use these techniques in meeting each objective.
The long range forecasts of temperature and precipitation will be made for the winter
(December – February) and summer seasons (June – August), which are the time periods of
interest for the local and regional media and agricultural communities. The forecasts will be
made four to five months in advance of each season. The forecasts will be made based on the
prevalent SST patterns of the previous few months (see Lupo et al. 2008b), and a first guess as to
how these may evolve over the next few months (using past history and/or model forecasts). The
potential for atmospheric blocking (Wiedenmann et al. 2002) and the evolution of large-scale
flow regime will also be factors that contribute to the long-range forecast. Thus, the forecasters
are using contingency and analogue techniques to make forecasts. GISS model and regional
model information will be used as guidance.
Long range forecasts are a mix of probability based techniques and qualitative analysis. To
evaluate them we will use the point scoring scheme shown in Table 7 of Lupo et al. (2008b). The
scheme, which is modeled after Lupo and Market (2002), is based on defining normal as within
+/- 0.5 standard deviations of the mean, and above and below normal as outside that range. Two
points are awarded for a good forecast of seasonal temperature and precipitation (observed
category matched the forecast category), while none are awarded for a poor forecast. For
example, if a forecaster predicted the summer temperatures would be close to normal (-0.5 – 0.5
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standard deviations from the seasonal mean) and the observed was within this range, this
constitutes a good forecast. Using the example above, a poor forecast would constitute a situation
where the observed seasonal temperatures were greater than one standard deviation above
normal. We will then examine the skill scores (Table 1) to evaluate the utility of these forecasts,
and these were calculated using the formula taken from Lupo and Market (2002):
(our forecast – climatology) / (perfect forecast – climatology) * 100% (1)
The long range forecasts issued by Lupo et al. (2008) were better than climatology overall,
but showed no improvement over climatology in the winter season. In Table 1 the numbers are
large, since the number of forecasts issued (and therefore the sample size) is, as of yet, small.
During the summer season, our forecasts were better than climatology by 38%, which compares
to 0% during the winter season. When examining precipitation, our forecasts were significantly
worse than climatology in the winter season (14%), but did not show any difference overall when
considering temperature as well. Thus, the information derived here has the potential for use as a
tool or guidance for long range forecasts in our region (especially during the summer season),
and this information could be constructed for other areas of the United States and applied to long
range forecasts as well.
The GISS Model
The NASA GISS climate models are General Circulation Models (GCM) and several have
been developed for use by the research community. These models use numerical techniques to
solve the fundamental equations of geophysical fluid dynamics, which describe such physical
principles as the conservation of mass, momentum, and energy. Mass can be separated into dry
and moist processes. Physical processes that do not have an analytical expression can be
parameterized, and examples of this include incoming and outgoing solar radiation, cloudiness,
albedo, etc. Examples of the GISS model in use can be found in Schmidt et al. (2006) or Hansen
et al. (1984).
The GISS GCMs are Cartesian, which can be run at a variety of horizontal and vertical
resolutions. However, this work will use output provided on grids with a resolution of 2°×2.5° in
the horizontal (latitude × longitude) and 31-layers in the vertical. The dynamics are based on
generally the "Arakawa B" grid scheme. Scheme B uses no horizontal viscosity and is
particularly suitable for coarse resolution models. The newest GISS GCM is the ModelE, which
was released in 2004.
The MASS Regional Model
The University of Missouri possesses in-house a regional scale model which can be used
either as a forecast model, or to simulate climate on a regional scale. This model is available
through the Atmospheric Science Wav Laboratory, and resides on a UNIX based platform using
a SUN Blade-2000 workstation.
- 13 -
The Mesocale Atmospheric Simulation System (MASS) is a limited-area terrain-following
sigma-coordinate model. It can be run in either hydrostatic or non-hydrostatic mode. It was
developed, maintained and improved by MESO, Inc. The latest version of MASS has interactive
multiple-nest capability, non-hydrostatic dynamics allowing simulations on the order of 1 km or
greater, a four-dimensional data-assimilation capability, four levels of microphysics and several
convective parameterization schemes. There are three available map projections, and we can
globally re-locate the model easily. The physics of the model are similar to that of the GISS
GCM with the major difference being that the horizontal resolution can be run as low as 3 km,
and there are more than 50 layers in the vertical.
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Climatology of Northwest Missouri Snowfall Events: Long Term Trends and Interannual
Variability. Physical Geography, 14, 427 - 448.
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- 14 -
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Takahashi, Eds. American Geophysical Union, pp. 130-163.
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Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Edited by: S.
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Chen. Cambridge University Press, Cambridge, UK. 996 pp.
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Third Assessment Report of the Intergovernmental Panel on Climate Change. Edited by:
J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, M.
Maskell, C.A. Johnson. Cambridge University Press, Cambridge, UK. 881 pp.
Kalnay, E., and Co-authors, 1996. The NCEP/NCAR 40-year re-analysis project. Bull. Amer.
- 15 -
Meteor. Soc. 77, 437-471.
Kirsgeb, P., McCluskey, M., Vogel, R., Strzepek, K., 2005: Global Analysis of Changes in
Water Supply Yields and Costs under Climate Change: A Case Study in China. Department of
Civil and Environmental Engineering and WaterSHED Center, Tufts University, Medford, MA,
USA. Climatic Change (2005), 68(3), 303-330.
Kung, E.C., and J.-G. Chern, 1995. Prevailing anomaly patterns of the Global Sea Surface
temperatures and tropospheric responses. Atmósfera 8, 99-114.
Kunkel, K.E. and J.R. Angel, 1999: Relationship of ENSO to snowfall and related cyclone
activity in the contiguous United States. J. Geophys. Res., Vol. 104, 19425 – 19434.
Lee, J.-W., and E.C. Kung, 2000. Seasonal-range forecasting of the Ozark climate by a principal
component regression scheme with antecedent seas surface temperatures and upper air
conditions. Atmósfera 13, 223-244.
Lubick, N., 2008: Preparing water supplies for climate change. Environmental Science &
Technology, 42(10)3487.
Lupo, A.R., E. P. Kelsey, D.K. Weitlich, N.A. Davis, and P.S. Market, 2008b: Using the
Monthly classification of global SSTs and 500 hPa height anomalies to predict temperature and
precipitation regimes one to two seasons in advance for the mid-Mississippi region. National
Weather Digest, in press.
Lupo, A.R., T.K. Latham, T. Magill, J.V. Clark, C.J. Melick, and P.S. Market, 2008a: The
Interannual Variability of Hurricane Activity in the Atlantic and East Pacific Regions. National
Weather Digest, in press.
Lupo, A.R., Kelsey, E.P., D.K. Weitlich, I.I. Mokhov, F.A. Akyuz, Guinan, P.E., J.E. Woolard,
2007: Interannual and interdecadal variability in the predominant Pacific Region SST anomaly
patterns and their impact on a local climate. Atmosfera, 20, 171- 196.
Lupo, A.R., D. Albert, R. Hearst, P.S. Market, F. Adnan Akyuz, and C.L. Allmeyer, 2005:
Interannual Variability of Snowfall Events and Snowfall-to-Liquid Water Equivalents in
Southwest Missouri. National Weather Digest, 29, 13 – 24.
Lupo, A.R., and P.S. Market, 2002: The Verification of Weather Forecasts in Central Missouri
And Seasonal Variations in Forecast Accuracy. Weather and Forecasting, 8, 891 - 897.
Lupo, A.R., and G. Johnston, 2000: The Interannual Variability of Atlantic Ocean Basin
Hurricane Occurrence and Intensity. National Weather Digest, 24:1, 1-11.
Mantua, N.J., S.R. Hare, Y. Zhang, J.M. Wallace, and R.C. Francis, 1997: A Pacific Interdecadal
Climate Oscillation with Impacts on Salmon Production. Bull. Amer. Meteor. Soc. 78, 10691079.
- 16 -
Marshall, E., Randhir, T., 2008: Effect of climate change on watershed system: a regional
analysis Climate Change, 89, 263-280
Mokhov, I.I., D.V. Khvorostyanov, and A.V. Eliseev, 2004. Decadal and Longer-term Changes
in ENSO Characteristics. I. J. Climatol. 24, 401-414.
Palecki, M.A., and D.J. Leathers, 2000. Spatial modes of drought in the central United States.
Preprints of the 12th Conference on Applied Climatology, 8 - 11 May, 2000, Asheville, NC.
Pelley, Janet, 2004: Climate change threatens Canadian Water supply. Environmental Science
and technology, 38(11), 200A.
Park, C.-K., and E.C. Kung, 1988. Principal components of the North American summer
temperature field and the antecedent oceanic and atmospheric condition. J. Meteor. Soc. Japan
66, 677-690
Ratley, C.W., A.R. Lupo and M.A. Baxter, 2002: Determining the Spring to Summer Transition
in the Missouri Ozarks Using Synoptic Scale Atmospheric Data. Transactions of the
Missouri Academy of Sciences, 36, 69 - 76.
Reichler, T., and J. Kim, 2008: How well do coupled models simulate today’s climate? Bull.
Amer. Meteor. Soc., 89, 303 – 311.
Roebber, P. J., S. L. Bruening, D. M. Schultz, and J. V. Cortinas, 2003: Improving snowfall
forecasting by diagnosing snow density. Wea. Forecasting, 18, 264 - 287.
Schmidt, G.A., and co-authors, 2006: Present day atmospheric simulations using GISS ModelE:
Comparison to in-situ, satellite and reanalysis data. J. Climate, 19, 153-192,
doi:10.1175/JCLI3612.1.
Semenov V.A. and Bengtsson L. (2002) Secular trends in daily precipitation characteristics:
greenhouse gas simulation with a coupled AOGCM. Climate Dynamics, 19, 123–140.
Tsonis, A.A., K. Swanson, and S. Kravtsov, 2007: A new dynamical mechanism for major
climate shifts. Geophys. Res. Let, 35, 303 – 307.
Wiedenmann, J.M., A.R. Lupo, I.I. Mokhov, and E. Tikhonova, 2002: The Climatology of
Blocking Anticyclones for the Northern and Southern Hemisphere: Block Intensity as a
Diagnostic. Journal of Climate, 15, 3459-3473.
Wittenberg, A.T., A. Rosati, N.C. Lau, and J.J. Ploshay, 2006: GFDL’s CM2 global coupled
climate models, Part 3: Tropical Pacific climate and ENSO. J. Clim., 19, 698 – 722.
- 17 -
BUDGET
- 18 -
BUDGET JUSTIFICATION
- 19 -
CURRENT/PENDING SUPPORT
PI: Anthony R. Lupo
Current –
Title:
Collaborators:
Agency:
Period Covering
Amount:
Multi millennia climate and growth variability from ancient oak wood in
the Midwest agricultural ecosystem.
R. Guyette (PI), M. Stambaugh (Forestry) (Co-PI) (my contribution 10%)
NSF
1 January 2006 – 31 December 2008
$297,000
Title:
Collaborators:
Agency:
Period Covering:
Amount:
Center for Agricultural / Environmental Experiential Learning.
Dr. Frieda Eivazi (Lincoln U.), A.R. Lupo and P. P. Motavalli
USDA / CREES 1890 Institution Grant
9/1/06 – 8/31/09
$299,639 total (sub-award: $53,622.00 – Lupo, Motavalli)
Title:
Increasing use of the Integrated Data Viewer (IDV) in the Atmospheric
Science Curriculum at the University of Missouri – Columbia.
P.S. Market and N.I. Fox
9/1/2007 - 12/31/2008
NSF/ UCAR/UNDIDATA
$ 11,661.00
Collaborators:
Period:
Agency:
Amount Req:
Pending – none
Project Manager: Verne H. Kaupp
Current –
Benchmarking Enhancements of National Applications Decision Support Systems with Focus on
the Potential of Non-Traditional NASA Results for Operational Value and Societal Benefit
PI: Verne H. Kaupp
Goddard Space Flight Center, Performance Period: 03/15/2006-03/14/2009
Total funding, $499,680
Person months: 8 months per year
From INFOMART to SOLUTIONS NETWORKS: A Plan for Identifying, Documenting, Peer
Review and Publishing Candidate Solutions
PI: Verne H. Kaupp
Langley Research Center, Performance Period: 01/01/2007-12/31/2007
Total funding, $149,996
Person months: 2.0 months
Pending – none
- 20 -
Biographical Sketch
Anthony R. Lupo
Address:
Department of Atmospheric Science Office Phone: (573)-884-1638
302E ABNR Building
Fax: (573)-884-5070
University of Missouri – Columbia
Cell: (573)-489-8457
Columbia, MO 65211
E-mail: LupoA@missouri.edu
A.
Vitae
1.
Education
Cayuga County Community College
State University of New York at Oswego
Purdue University
Purdue University
2.
1984 – 1986
1986 – 1988
1989 – 1991
1991 – 1995
A.S.
B.S.
M.S.
Ph.D.
Mathematics
Meteorology
Atmospheric Science
Atmospheric Science
Professional Experience
2003 – present
Associate Professor, University of Missouri – Columbia,
Department of Atmospheric Science
1997 – 2003
Assistant Professor, University of Missouri – Columbia,
Department of Soil and Atmospheric Sciences.
1995 – 1997
Postdoctoral Research Associate, State University of New
York at Albany, Department of Earth and Atmospheric Sciences.
B.





Professional Organizations
American Meteorology Society, Nominated for Fellow April 2008
Fellow, Royal Meteorological Society
Missouri Academy of the Sciences
American Geophysical Union
National Weather Association
C.


Honors and Awards
Sigma Xi Honor Society
Gamma Sigma Delta


D.
March 2002: Introductory Meteorology course was co-winner of the Distance Learning Community of
Practice Meritorious College Course Award.
Fulbright Research Scholar (April 2003) AY 2003 – 2004 to Russian Academy of
Sciences (Member: Fulbright Scholars Alumni Association)
Publications (2002 – 2008)
Tilly, D.E., A.R. Lupo, and C.J. Melick, P.S. Market 2008: Calculated height tendencies in a Southern Hemisphere blocking and
cyclone event: The contribution of diabatic heating to block intensification. Monthly Weather Review, in press
- 21 -
Zuki, Md. Z., and A.R. Lupo, 2008: The interannual variability of tropical cyclone activity in the southern South China Sea. J.
Geophys. Res., 113, D06106, doi:10.1029/2007JD009218 – 14 pp.
Luo, D., and A.R. Lupo, 2007: Dynamics of eddy-driven low-frequency dipole modes. Part II: Free mode characteristics of NAO
and diagnostic study. Journal of the Atmospheric Sciences, 64, 3 - 28.
Luo, D., A.R. Lupo, and H. Wan 2007: Dynamics of eddy-driven low-frequency dipole modes. Part I: A simple model of North
Atlantic Oscillations. Journal of the Atmospheric Sciences, 64, 29 - 55.
Market, P.S., A. M. Oravetz, D. Gaede, E. Bookbinder, A.R. Lupo, C. J. Melick, L. L. Smith, R. Thomas, R. Fay, B. P.
Pettegrew, and A. E. Becker, 2006: Proximity Soundings of Thundersnow in the Central United States. Journal Geophysical
Research – Atmospheres, 111, D19208 – 19217.
Barriopedro, D., R. Garcia-Herrera, A.R. Lupo, and E. Hernandez, 2006: A climatology of Northern Hemipshere Blocking.
Journal of Climate, 19, 1042 - 1063.
Lupo, A.R., D. Albert, R. Hearst, P.S. Market, F. Adnan Akyuz, and C.L. Allmeyer, 2005: Interannual Variability of Snowfall
Events and Snowfall-to-Liquid Water Equivalents in Southwest Missouri. National Weather Digest, 28, in press.
Barriopedro, D., R. Garcia-Herrera, and A.R. Lupo, 2004: Metodo de Deteccion y Climatologia de Bloqueos en el Hemisferio
Norte. I Escuela de Estudios Climaticos Avanzados, 1 – 12.
Akyuz, F.A., Chambers, M.D., and A.R. Lupo, 2004: The Short and Long-Term Variability of F2 or Stronger (Significant)
Tornadoes in the Central Plains. Transactions of the Missouri Academy of Science, 38, 26-45.
Burkhardt, J.P., and A.R. Lupo, 2005: The planetary and synoptic-scale interactions in a Southeast Pacific blocking episode using
PV diagnostics. Journal of Atmospheric Sciences, 62, 1901 - 1916.
Akyuz, F.A., P.S. Market, P.E. Guinan, F.A. Akyuz, J.E. Lam, A. M. Oehl, and W.C. Maune, 2004: The Columbia, Missouri,
Heat Island Experiment (COHIX) and the Influence of a Small City on the Local Climatology. Transactions of the Missouri
Academy of Science, 38, 56 - 71.
Lupo, A.R., P.S. Market, F.A. Akyuz, P.E. Guinan, J.E. Lam, A. M. Oehl, and W.C. Maune, 2003: The Columbia, Missouri, Heat
Island Experiment (COHIX): The Influence of a Small City on Local Surface Temperatures and the Implications for Local
Forecasts. Electronic Journal of Operational Meteorology (www.nwas.org)
Lupo, A.R., E.P. Kelsey, E.A. McCoy, C.E. Halcomb, E. Aldrich, S.N. Allen, A. Akyuz, S. Skellenger, D.G. Bieger, E. Wise, D.
Schmidt, and M. Edwards, 2003: The Presentation of Temperature Information in Television Broadcasts: What is Normal?
National Weather Digest, 27:4, 53 -58.
Lupo, A.R. (Contributing author only), 2003: Report on Wind Chill Temperature and Extreme Heat Indicies: Evaluation and
Improvement Projects. An NOAA OFCM Tech. Report FCM-R-19-2003 Edited by: Mary Cairns, Cynthia Nelson. 50 pp.
Berger, C.L., A.R. Lupo, P. Browning, M. Bodner, C.C. Rayburn, M.D. Chambers, 2003: A Climatology of Northwest Missouri
Snowfall Events: Long Term Trends and Interannual Variability. Physical Geography, 14, 427 - 448.
Lupo, A.R., and P.S. Market, 2003: First Conference on Weather Analysis and Forecasting Issues in the Central United States.
Bulletin of the American Meteorological Society, 84, 1245-1247.
Ratley, C.W., A.R. Lupo and M.A. Baxter, 2002: Determining the Spring to Summer Transition in the Missouri Ozarks Using
Synoptic Scale Atmospheric Data. Trans. of the MissouriAcademy of Sciences, 36, 69-76.
Wiedenmann, J.M., A.R. Lupo, I.I. Mokhov, and E. Tikhonova, 2002: The Climatology of Blocking Anticyclones for the
Northern and Southern Hemisphere: Block Intensity as a Diagnostic. J. Climate, 15, 3459-3473.
Lupo, A.R., and P.S. Market, 2002: The Verification of Weather Forecasts in Central Missouri And Seasonal Variations in
Forecast Accuracy. Weather and Forecasting, 8, 891 - 897.
Lupo, A.R., 2002: The Role of Ageostrophic Forcing in a Height Tendency Equation. Mon. Wea. Rev., 130, 115-126.
- 22 -
CURRICULUM VITAE
Verne H. Kaupp
Research Professor & Director of ICREST
University of Missouri-Columbia
FAX: (573) 882-0397
KauppV@missouri.edu
Phone: (573) 882-0793
Email Address:
Present Position:
(2001 – Present) Director and Research Professor, ICREST (Interdisciplinary Center for Research in Earth Science Technology),
University of Missouri-Columbia.
Previous Experience:
(1997 – 2001) Director and Chief Scientist, Alaska SAR (Synthetic Aperture Radar) Facility, Geophysical Institute, University of
Alaska Fairbanks
(1979 – 1997) Professor of Electrical Engineering, Department of Electrical Engineering, University of Arkansas
Education:
Doctor of Engineering (D.E.); Electrical Engineering (honors), University of Kansas, Lawrence.
Bachelor of Science (B.S.); Physics (high honors), University of Maryland, College Park.
Professional Societies:
IEEE
Institute of electrical and Electronic Engineers
GRSS
Geoscience and Remote Sensing Society of the IEEE
Member of the Administrative Committee
General Chairman – IGARSS04 (Anchorage)
 Phi Kappa Phi – Honor Society
PE
Registered Professional Engineer, State of Arkansas, Certificate No. 6312
Experience:
Dr. Kaupp has been active since 2001 in both research and proof-of-concept studies for Decision Support Systems; designing the recommended process,
preparing the Guidebook (see Selected Reports), and applying the concepts; and developing a Federal Enterprise Architecture model for several of the
National Applications elements of the Applied Sciences Program at NASA HQ. He has been active in microwave remote sensing since 1971 in both academic
and commercial enterprises, both domestic and international. His role was typically one of leadership, the customer liaison and point of focus, and the
lead or project manager. He has a long history of interdisciplinary research and functions well with scientists and engineers of all disciplines. He has
taught at both the undergraduate and the graduate level and was named “Outstanding Teacher, Department of Electrical Engineering,” by the EE honor
societies. He was also named “Outstanding Researcher, Department of Electrical Engineering” by the Alumni Association. Dr. Kaupp has been President,
Vice President, Chief Executive Officer, and Treasurer of three companies.
Professional Activities (earlier activities available on request):
1998 — 2005
2001 — Present
2003
2004
2004
2005
2006
2006
2006
2007
Organizing and General Chairman: International Geoscience and Remote Sensing Symposium 2004
Member of the Administrative Committee, Geoscience and remote Sensing Society
Various presentations, workshops, etc at NASA functions..
IGARSS04, Anchorage – Organizing and General Chair, IGARSS04 Symposium
Various presentations, workshops, etc at NASA functions..
Various presentations, workshops, etc at NASA functions..
Various presentations, workshops, etc at NASA functions
IGARSS06, Denver – Organized and conducted two workshops for NASA Applied Sciences Program
1. Integrated Solutions for Sustainable Resources
2. Integrated Systems for Agriculture
IGARSS06, Denver – Organized and chaired two oral paper sessions:
1. Integrated Earth Observations Systems for GEOSS Societal Benefit
2. GEOSS Architecture and Data Management
Various presentations, workshops etc., at NASA functions
- 23 -
2007
IGARSS07, Barcelona – Organized and conducted a workshop for NASA Applied Sciences Program
2007
IGARSS07, Barcelona – Organized and chaired an oral paper session.
From Integrated Systems Solutions to Rapid Prototyping, a Solutions Network Approach
Rapid Prototyping: A Concept for Moving earth Science to Operations for Societal Benefit.
Selected Publications (Others available on request):
Kaupp, Verne, Joe Engeln, Jeff Bennett, Leanne Tippett Mosby, Tim Haithcoat, Robert Reed, Nichole Hilstrom, Connor Henley, Jacob Mueth, and Jordan Paashal, Missouri
Satellite Air Quality Project, (Invited for presentation), Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Smposium (IGARSS 2007) 23 – 27
July, 2007, Barcelona, Spain
Kaupp, Verne, Charles Hutchinson, Sam Drake, Wim Van Leeuwen, Tim Haithcoat, and Vlad Likholetov, Benchmarking: The End of the Process,, (Invited for presentation),
Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007) 23 – 27 July, 2007, Barcelona, Spain
Frederick, M.E., E.L. Cox Jr., L.A. Friedl, and V.H. Kaupp, Evaluating the Potential of NASA’s Earth Science Research Results for Improving Future Operational Systems, (Oral
Presentation) AGU 2006 Fall Meeting, 11 – 15 December, 2006, San Francisco.
Kaupp, Verne, Charles Hutchinson, Martin Frederick, and Ron Birk, Integrated Earth Observations Systems for GEOSS Societal Benefit, Proceedings of the 2006 IEEE
International Geoscience and Remote Sensing Symposium (IGARSS 2006), 31 July – 4 August, 2006, Denver
Haithcoat, Tim, Vladislav Likholeto, Verne Kaupp, Brad Doorn, Dave Trallic, Wim van Leeuwen, Sam Drake, Chuck Hutchinson, Benchmarking the performance of a decision
support system. Proceedings of the 31st International Symposium on Remote Sensing of Environment, Global Monitoring for Sustainability and Security, June 20 - 24,
2005. Saint Petersburg, Russian Federation.
van Leeuwen, W., S. Drake, C. Hutchinson, B. Doorn, D. Tralli, V. Kaupp, T. Haithcoat, V. TLikholetov., Assimilating NASA Data into a Crop Production Estimation System: Risk
Management. Proceedings of the 31st International Symposium on Remote Sensing of Environment, Global Monitoring for Sustainability and Security, June 20 - 24,
2005. Saint Petersburg, Russian Federation. pp 1-4.
Mironov, V.L., M.C. Dobson, V.H. Kaupp, S.A. Komarov, and V.N. Kleschenko, “Generalized Refractive Mixing Dielectric Model for Moist Soils”, IEEE Transactions on Geoscience
and Remote Sensing, Vol 42, No. 4, pp., 773 – 785, April 2004.
Kaupp, V, C Hutchinson, W van Leeuwen, S Drake, and A Tuyahov, Assimilation of NASA Earth Science Results and Data in National Decision Support Systems, Proceedings of
the 2003 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2003), Volume 2, pp., 1065-1070, 21-25 July, 2003, Toulouse, France
Mironov, V L, V H Kaupp, S A Komarov, and V N Kleschenko, Frozen Soil Dielectric Model Using Unfrozen Water Spectroscopic Parameters, Proceedings of the 2003 IEEE
International Geoscience and Remote Sensing Symposium (IGARSS 2003), Volume 2, pps 4172 – 4174, 21-25 July, 2003, Toulouse, France
Kaupp, V.H. and B. Holt, The Alaska SAR Facility, Digest of the 1999 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 1999), Hamburg, Germany, June.
Noltimier, K.F.; Jezek, K.C.; Sohn, H.G.; Li, B.; Liu, H.; Baumgartner, F.; Kaupp, V.; Curlander, J.C.; Wilson, B.; Onstott, R., RADARSAT Antarctic Mapping Project-mosaic
construction, Digest of the 1999 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 1999), Hamburg, Germany, June. ,Page(s): 2349-2351 vol.5
Kaupp, V.H. and B. Holt, The Alaska SAR Facility: Overview and Key Geophysical Applications, Digest of the 1998 IEEE International Geoscience and Remote Sensing
Symposium (IGARSS 1998), Seattle, Washington, July.
Jezek, K.C., F. Carsey, J. Crawford, J. Curlander, B. Holt, V. Kaupp, K. Lord, N. Labelle-Hamer, A. Mahmood, P. Ondrus, and C. Wales,. Snapshots of Antarctica from Radarsat1, Digest of the 1999 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 1999), Seattle, Washington, July.
Kaupp, V.; Holt, B.; The Alaska SAR Facility: overview and key geophysical applications, 1998 International Geoscience and Remote Sensing Symposium Proceedings (IGARSS
'98)., Volume 3, 6-10 July 1998 Page(s):1424 - 1427 vol.3
R. Guritz, O. Lawlor, T. Logan, S. Li, and V. Kaupp, Repeat-Pass Satellite Interferometric Tools Available at the Alaska SAR Facility, EOS, Transactions, AGU, 1998 Fall Meeting,
Vol. 79, No. 45, U11A-42, F21-22, 1998.
Selected Technical Reports (Available on request):
Kaupp, V., C. Hutchinson, S. Drake, T. Haithcoat, W. van Leeuwen, V. Likholetov, D. Tralli, R. McKellip, B. Doorn, Benchmarking the USDA Production Estimates and Crop
Assessment Division DSS Assimilation, September 2005.
Kaupp, V. and C. Hutchinson, DSS Assimilation Guidebook Summarized, March 2004.
Hutchinson, C., Van Leeuwen, W., Sam Drake, Verne Kaupp, Tim Haithcoat, Characterization of PECAD’s DSS: a zeroth-order assessment and benchmarking preparation, August
2003.
Kaupp, V.H., C. Hutchinson, S. Drake, W. Van Leeuwen, and D. Tralli, Assimilation of NASA Earth Science Results and Data in National Decision Support Systems: A
Guidebook, October 15, 2003.
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ROBERT E. REED, P.E., Ph.D.
Water Resources Research Center
E2509 Laferre Hall
Columbia, MO. 65211
Education
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(573) 884-6162
email: reedre@missouri.edu
University of Missouri-Rolla: PhD in Environmental Engineering - 2002
University of Missouri: Master of Public Administration -1984
University of Missouri: Master of. Science in Sanitary Engineering - 1969
University of Missouri: Bachelor of Science in Civil Engineering - 1968
Professional History
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Water Resources Research Center, College of Engineering, University of Missouri, Columbia, MO., Research
Associate Professor, 2006 - Present
MECO Engineering Company, Inc., Branch Office Manager & Environmental Engineer, 1993 – 2006
Howard Moore Group, Springfield. MO., Principal Engineer/ General Manager, 1989-1993
Water Pollution Control Program, Missouri Department of Natural Resources (MDNR), Jefferson City, MO,
Deputy Program Director, 1979-1989
Clow Corporation Waste Treatment Division, Florence, KY, Supervisor of Application Engineering, 1974-1979
U.S. Air Force, 90th Civil Engineering Squadron, Warren AFB, WY, Base Engineering Planning, 1969-1973
Water and Wastewater Treatment Plant Operations, state-licensed, 1976 - 2000
Teaching & Research
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Industrial Pollution Prevention and Energy Conservation, 2008
Developing on-line educational courses, 2008
Honors Problems and Directed Readings Courses in Satellite Remote Sensing, Environmental Modeling, and
Environmental Research Subjects, 2006 – 2007
Mentoring NASA DEVELOP Program Air Quality Project, 2007
Water Quality – Water and Wastewater Treatment Design, University of Missouri – Columbia, 2006
Introduction to Environmental Engineering, University of Missouri – Columbia, 2006 - 2007
Introduction to Environmental Engineering, University of Missouri - Rolla, 1998-1999
In-plant water treatment research, 2007 - 2008
Modeling Disinfection Byproduct Formation in Surface Water Treatment, 2006 – 2007
Chemical Reaction Modeling in Surface Water Treatment, 2007
Ozone Reaction Modeling in Recycle Water Treatment, 1999 - 2002
Experience
Dr. Reed has been active in local and state agency policy development, environmental planning, management,
permitting, and financing since 1974. He has served on national, state, regional, and local committees involved in
environmental policy-setting and practice issues since 1980. During his employment at MDNR, he served in a
program management function including an inter-program coordination role to expedite policy and permitting
management. While working as a consultant, he provided environment-related technical, managerial, and financial
policy and implementation recommendations to local and regional governmental agencies. His research specialty is
environmental chemical modeling. His primary function at the University is environmental applications research
utilizing undergraduate and graduate students.
Professional Activities and Registrations
President of Board of Directors of Midwest Assistance Program, a Rural Community Assistance Partner
Registered Professional Engineer in Colorado, Kentucky, Missouri, Arkansas, Kansas.
Member of National Register’s Who’s Who
Member of Chi Epsilon Honorary Fraternity and Pi Alpha Alpha Honor Society
Member of Linn State (Missouri) Technical College Advisory Committee
Articles and Presentations
Dr. Reed ‘s publications have focused on environmental policy and practice including modeling subjects. He has
made numerous presentations on environmental policy, practice and financing to national, regional, state and local
conferences, boards and commissions.
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Timothy L. Haithcoat
Twenty years experience developing and managing geospatial technologies in both research and applied
environments in support of the missions and mandates of the State of Missouri and Nation
QUALIFICATIONS SUMMARY
Recent Professional Experience University of Missouri-Columbia
 Director – Missouri Spatial Data Information Service,
1995 – present
 Director – Geographic Resources Center, Department of
Geography, 1985 – present
 Co-Chair National Geospatial Programs Office –
Geospatial Enterprise Architecture Workgroup
 Chair – Information Domain – Missouri Adaptive
Enterprise Architecture Initiative, 2002 – present
 Chair – Geospatial Enterprise Architecture Working
Group – National States Geographic Information Council,
2005 – present
Security Clearance: TS/SCI
Education
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M.S., 1987, Wildlife Biology, University of
Missouri-Columbia
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B.S., 1982, Wildlife Biology, West Virginia
University
Awards
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ESRI - Special Achievement in GIS 2005 –
Missouri Spatial Data Information Service
National States Geographic Information
Council – Outstanding Service Award 2005
National Endowment for the Humanities We the People Award – 2004
MidAmerica GIS Consortium – Individual
Achievement Award 2000
ESRI - Special Achievement in GIS 2000 –
Geographic Resources Center
BIOGRAPHY
Timothy L. Haithcoat was born in Pittsburgh, PA on March 21, 1960. He received the B.S.
degree in Wildlife Biology from West Virginia University, Morgantown, WV in 1982 and received a
M.S. degree in Wildlife Biology from the University of Missouri, Columbia, MO in 1987.
Since 1985 Mr. Haithcoat has been the Director and Senior Research Specialist for the
Geographic Resources Center (GRC) a multidisciplinary, applied research and teaching group involved in
a broad range of activities relating to the collection, storage, management, and analysis of spatial data.
His responsibilities include project design and implementation, project cost estimation, and project/staff
coordination. While with the GRC he has worked on more than 300 projects with public and private
sector clients including academic units, University Extension, state agencies, federal agencies, local
government, and private organizations and companies. In carrying out and administering these projects
he has developed broad expertise in digital image analysis, GIS analysis, data base construction, spatial
analysis, geospatial architectural issues, and scholarly research, writing and evaluation.
Since 1995 Mr. Haithcoat has been the Director of the Missouri Spatial Data Information Service
(MSDIS) the State of Missouri’s spatial data retrieval and archival system. It is responsible for data
storage and access, standardization of both digital and tabular data, creation of the data dictionary,
compilation of metadata, and statewide GIS user information networks. The MSDIS does the following
functions: receives, catalogs and archives databases; checks and verifies accuracy and integrity of data;
maintains metadata; provides download via FTP; and provides conversion and integration services.
Mr. Haithcoat’s research involves the integration of remote sensing and geographic information
systems for solving application issues and their subsequent accuracy assessment and validation. In
applied research he makes use of satellite and airborne remote sensing systems for application to
vegetation mapping and change detection, urban mapping, and geospatial information extraction and
correction.
Mr. Haithcoat is widely called upon for his expertise in integrating remote sensing and
geographic information technologies.
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Dr. Vlad Likholetov
W2028 Lafferre Hall
University of Missouri-Columbia
Columbia MO 65211
Tel.: (573) 882-1520
LikholetovV@missouri.edu
EDUCATION
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MBA, William Woods University, Fulton MO, 1999
PhD, Linguistics, St.Petersburg State University, Russia, 1992
B.A., with honors, Foreign Languages, Barnaul State Pedagogical Institute, Russia, 1985
WORK EXPERIENCE
1999 - present
1999
1992-1997
1992
University of Missouri-Columbia. Research Associate. Interdisciplinary Center for Research in
Earth Science Technology (ICREST).
Participated as a co-investigator in a number of technology applications development projects
funded by NASA, Raytheon, Department of State, ISTC, USDA in the areas of decision support
systems, performance evaluation and benchmarking, technology commercialization and transfer,
user requirements assessment and analysis.
Designed and conducted user surveys, on-site interviews, focus group meetings.
Introduced QFD methodology for the analysis of GIS/remote sensing user requirements and
technology assessments and evaluations.
Missouri Department of Economic Development. Intern. Office of International Marketing. Duties
included updating customer database, trade leads processing, market research
San Ltd.Co., Barnaul, Russia. Assistant Manager.
Preparation of contractual documentation, communication with international customers, customs
clearance of imported materials
Barnaul State Pedagogical Institute, Russia. Assistant Professor. Department of English Philology.
MEMBERSIPS
Regular member, Association of University Technology Managers (AUTM)
SELECTED CONFERENCE PAPERS AND PRESENTATIONS
Likholetov V. Defining User Needs and Requirements in Precision Agriculture (QFD study for the IFAFS
project). In: Proceedings of the International Scientific Practical Conference: University science and agricultural
industry. Altai State Agricultural University, AGAU Publishing, 2005, p.p.225-230.
Leeuwen W., Drake S., Hutchinson C., Kaupp V., Likholetov V. et al. Assimilating NASA Data into a Crop
Production Estimation System: Risk Management. Paper submitted to the 31st International Symposium on Remote
Sensing of Environment. GLOBAL MONITORING FOR SUSTAINABILITY AND SECURITY, June 20 - 24,
2005, Saint Petersburg, Russian Federation.
Kaupp V., Haithcoat T., Likholetov V. et al. Benchmarking the performance of a decision support system.
Paper submitted to the 31st International Symposium on Remote Sensing of Environment. GLOBAL MONITORING
FOR SUSTAINABILITY AND SECURITY, June 20 - 24, 2005, Saint Petersburg, Russian Federation.
Krentsel E., Likholetov V. Russian R&D for Industry Needs: Market Pull vs. Technology Push. The Chemical
Journal, No.1-2, Jan-Feb 2005, p.p.45-47.
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