General Background on the Weather and Climate Impacts
Assessment Initiative
Climate and weather create
hazards and opportunities for society at multiple scales. However, most of society does not have
scientific expertise, and most scientists are unfamiliar with how societal
decision-making processes work. In the
climate context, this process of bridging between scientific knowledge and
societal need is known as “assessment,”
while the weather community might more familiarly call it “developing usable
forecast information.” Assessment can be broadly defined as “the entire social
process by which expert knowledge related to a policy problem is organized,
evaluated, integrated and presented in documents to inform policy or
decision-making” (GEA 1997). Assessments
such as the U.S. National Assessment of the Potential Consequences of Climate
Variability and Change (USNA) and the international Intergovernmental Panel on
Climate Change (IPCC) assessment reports focus on synthesizing, evaluating and
reporting on what is known about climate variability and change and its impacts
Not all processes and products that fall under the rubric of assessment are the same however. The NCAR Assessment Initiative focuses on impact assessments, a more narrow focus that aims to assess the severity, likelihood, and effects of a given phenomenon, such as climate change and extreme weather events, on a system of concern to society, such as agriculture, health or energy supply. Within this area of research lie a number of critical scientific gaps that currently limit our ability to effectively assess future impacts and provide quality information to decision-makers. These difficulties include differing perceptions of uncertainty and extremes between climate scientists, social scientists, and decision-makers; lack of tools for quantifying current and future frequency of extremes; and so on (e.g., Moss and Schneider 2000, Webster et al. 2003, Parson et al. 2003). This initiative concerns both filling these critical gaps and integrating the different scientific disciplinary research necessary for informing decision makers regarding current and future weather and climate hazards.
The Weather and Climate Impacts Assessment Initiative is organized around three themes: characterizing uncertainty in all phases of impacts assessment, extreme weather and climate events, and climate and health. It is mapped onto the following specific scientific objectives.
· To quantify uncertainties related to multiple forcings (i.e., greenhouse gases plus land cover change, and natural forcings--solar variability, aerosols from volcanic eruptions) in climate models;
· To characterize uncertainty on regional scales in climate projections that support decision-making;
· To determine new robust measures of changes in weather and climate extreme events and their uncertainties (using extreme value theory), for extremes relevant to societal impacts;
· To nurture an interdisciplinary research community to address the interactions between climate and human health; and
· To work towards end-to-end integrated projects in extreme events and uncertainty that encompass physical science, impacts, and decision-making.
These objectives are fulfilled by a number of individual tasks (described below) that have been selected because they address identified weaknesses of existing national and international assessment processes such as lack of uncertainty estimates for climate projections, missing elements of scenarios, or differences in the perceptions of the most appropriate way to consider extremes (e.g., Moss and Schneider 2000, Webster et al. 2003, Parson et al. 2003).
NCAR is uniquely poised to study these topics, as it has a mission firmly grounded in the atmospheric sciences, including climate and weather, as well as the responsibility as a national center to provide science in service to society. NCAR also is staffed by renowned scientists in these areas and has a multidisciplinary structure--the capability to mobilize scientists from different disciplines around a central topic. This initiative is also of critical relevance for NCAR because it provides timely, needed input to ongoing processes of national and international importance—for example the IPCC, and future national and regional assessments.
Renewal Proposal for the
NCAR Weather and Climate
Impact Assessment
Science Initiative
Linda O. Mearns and Warren Washington
Introduction
The WCIAS
Initiative is built on three major themes:
·
Characterizing
Uncertainty in Impact Assessment Science
·
Extreme
Weather and Climate Events
·
Climate/Health
Interactions
We organize
this document around these three themes, which are described in full in the
Assessment
Initiative Foundation Document (Mearns and
I.
Characterizing Uncertainty in Impact Assessment Science
The projects
described in this Initiative element are highly diverse and cover many
different aspects of uncertainty analysis: uncertainty in climate model
simulations with different emissions forcings, uncertainty in future climate
due to changes in land cover, exploration of the uncertainty of past climates
in climate models, incorporating uncertainty measures into climate scenarios
for impacts use, and uncertainty and decision making. Five projects covering
these topics are described below.
The major goals of this project are to develop new techniques for quantifying uncertainty in climate model projections and to apply theses techniques to recent transient runs of atmosphere-ocean general circulation models (AOGCMs). Particular emphasis will be given to quantifying regional uncertainty.
In the first year of this project, transient Business as Usual (BAU) runs from the Parallel Climate Model (PCM) were used to investigate aspects of the control run and climate change run in reproducing some extreme events. Also, using a mixed model approach, progress was made in elaborating on the uncertainty approach of Giorgi and Mearns (2002) in combining criteria of validation and convergence in evaluating future climate changes using regionalized output from 9 different atmosphere-ocean general circulation models (AOGCMs) run with two different emissions scenarios.
The research on uncertainty in climate model simulations will continue to be developed in three main tasks.
The first one is aimed at the analysis of single model ensemble runs, using model output already available to us (PCM all forcings runs for present day climate; BAU runs for end of the 21st century climate; and Special Report on Emissions Scenarios [SRES] scenarios). Within this context, the analysis of uncertainty will focus on issues of downscaling model output to the observations' domain - and conversely “upscaling” station records to the model gridbox domain - in order to correctly compare present-day climate simulations to available records and to sensibly infer local impacts of simulated future changes. Aspects of climate change analyzed will be indices of extreme events' intensity and frequency, influence of ENSO-like signals on them, their trends and spatial patterns, and, for all of these quantities, a characterization of uncertainty under precise statistical assumptions will be the central part of the analysis.
The second task will be the continuation of the analysis of multi-model ensembles following Giorgi and Mearns (2002), with particular focus on determining regional measures of climate change and their confidence levels. In this context, statistical models will be aimed at separating within from between model variability through mixed effects models; assessing different factors' relative importance (region/season/scenario/model and their interactions, for example) through ANOVA-type analysis; accounting for outliers through robust statistics; investigating the sensitivity of the summary measures of climate change to the scales of regional aggregation, by use of spatial statistical models; and modeling the temporal evolution of processes through multivariate time series analysis.
The third task concerns designing of experiments (model runs). A proof-of-concept will take place using the idea of “daughters ensemble members.” These will be short runs generated by randomly selecting as initial conditions states at the end of ensemble members' long runs in order to explore the “weather patterns” space under the same climate scenario. Underlying this experiment is the more general issue of studying the relation between ensemble size and variance of the estimates. A more complete approach will then be pursued, in which the theory of experimental design will be applied, in particular ideas of latin hypercube-type design, in which factors are varied optimally and efficiently in order to analyze their relative importance. We will consider factors including changes to the emission scenarios.
(Note: Under level
funding, only the second task could be accomplished).
YEAR 1
Results from tasks 1 and 2 will be available for specific study regions, together with a toolbox of R software programs able to be easily adapted for similar analyses of different regions.
YEAR 2
Results of global analyses and full development of R software plug-in modules will be complete, ready to be made available for the larger research community.
YEAR 3
Inter-model and inter-scenario comparisons will be performed. The results of task three will have been analyzed with particular attention to the issue of modeling the propagation of uncertainty stemming from emission scenario uncertainty.
D. Nychka, C. Tebaldi, J. Meehl, L. Mearns, T. Wigley
2.
Land Cover Forcing From the SRES Scenarios in Climate Models
To extend future climate change scenarios by including human impacts on land cover and soils. This work has been initiated with LSM/PCM and will be expanded to use CLM/CCSM. Simulated changes are land cover, human impacts on soil, and urbanization. These experiments will address how human land use and land cover change are altering climate, water and carbon cycles, and biogeochemistry. In particular it will address: (1) How have changes in land use and land cover altered present-day climate, and how are they likely to alter future climates? (2) How important is the land use and land cover change forcing relative to other IPCC SRES forcings (e.g., greenhouse gases)? Parts of this work will be accomplished in collaboration with the Biogeosciences Initiative.
To assess the first-order impacts of land cover change, we propose a series of simulations using PCM with the LSM land surface model. These simulations will complement existing climate simulations of PCM using pre-industrial atmospheric forcings for 1870, transient historical forcings from 1870 to present-day, and transient simulations to 2100 using the SRES A2 atmospheric forcing.
Proposed runs include: a pre-industrial atmospheric forcing equilibrium run to evaluate the impact of present-day land use (existing control) against a natural vegetation land surface representation; and transient simulations using the A2 SRES atmospheric forcings from 1980 to 2100 to evaluate the impacts of SRES-derived changes in land cover. By comparing runs using natural vegetation, present land cover, and the A2 2100 land cover scenario (for the period 2065 to 2100 only), we can evaluate the impacts of land cover change and the need for accurate land cover information in assessing SRES scenarios.
While the LSM/PCM model
provides a good first order estimate of land cover influence on climate, there
are a number of shortcomings to these simulations, especially the
representation of sub-grid scale land heterogeneity. We propose several new databases and model
improvements for the Community Land Model (CLM) used with CCSM to simulate
different aspects of human land cover change in more detail. These include:
Goal: Create transient CLM land surface datasets to match those used in the IPCC SRES scenarios.
Needs: Develop translation algorithms to convert SRES scenario land cover classes (biome classification) to CLM-compatible plant functional types (PFTs), which allow for sub-grid land cover.
Expected outcome: We expect significant impacts to both the hydrologic cycle and energy balance on regional scales. We propose to develop a temperature fingerprint associated with historic land cover change to compare to the observed surface temperature record.
Goal: Include multiple crop types and implement aspects of the CERES crop models and the CENTURY soil biogeochemistry and crop management to improve agriculture productivity estimates and their impacts on climate. This will be in collaboration with the Biogeosciences Initiative.
Needs: This work will proceed in several phases. (a) Develop additional agricultural classes matching those used in the IPCC assessments. (b) Implement existing models of crop growth and development (i.e., CERES crop models). (c) Develop and implement an irrigation parameterization and a global irrigation dataset. (d) Develop and implement a full carbon cycle for agroecosystems.
Expected outcome: Simulations of natural vegetation, and historical, present-day, and future land-cover change will assess, in a consistent manner, the impact of agroecosystems on climate, water resources, and the carbon cycle.
Goal: Assess the effect of human-induced erosion and soil compaction on regional climates.
Needs: Use the GLASOD database and historical population trends to simulate past and future soil degradation. CLM soil properties will be modified on the basis of these simulations.
Expected outcome: We propose to evaluate this impact on a global scale, and to identify a temperature fingerprint.
Goal: Evaluate the effects of urban heat islands on regional and global climate and hydrology.
Needs: Develop an urban canyon model as part of CLM. Develop an urban land cover database linked to population density. Collaborative work in the Biogeosciences initiative will develop anthropogenic biogeochemical emissions datasets in relation to population.
Expected outcome: Simulations will help understand the scale and nature of urban impacts on regional and global climate. We will evaluate potential mitigation measures such as urban planning policies that limit urban sprawl.
Goal: Much of land use and land cover change occurs at a fine spatial scale not explicitly resolved by global models. This landscape heterogeneity is better resolved by regional climate models, which are an important scientific tool for downscaling and impacts research.
Needs: Develop a common modeling framework and databases for global and regional climate models.
Expected outcome: Reduction in redundancy and a common modeling framework for global and regional models.
In addition to the
previously described LSM/PCM simulations, the following CLM/CCSM simulations
will address the climatic impacts of the new land cover specifications (bold script
indicates the difference from control):
|
Run |
Type of Run |
Objective |
Sensitivity test |
Status |
|
CEC |
22 years Equilibrium |
Present day atmosphere Present CLM land cover |
Control Run
|
Exists
|
|
CE1 |
22 years Equilibrium |
Present day atmosphere Urbanization
|
a) Optimal number of urban classes b) Sprawl vs no sprawl scenarios |
Year 1 |
|
CE2 |
22 years Equilibrium |
Present day atmosphere Irrigation |
a) Impact of irrigation |
Year 1 |
|
CE3 |
22 years Equilibrium |
Present day atmosphere Land Cover |
a) IPCC scenario comparison (e.g. A2 vs B2 etc.) b) Within scenario land cover uncertainty |
Year 2 |
|
CE4 |
22 years Equilibrium |
Present day atmosphere Agriculture |
a) Optimal number of crop types b) Prescribed vs interactive crop simulations |
Year 2 |
|
CE5 |
22 years Equilibrium |
Present day atmosphere Soil Degradation |
a) Impact of degradation |
Year 2 |
|
CT1 |
1870-2100 Transient |
IPCC Scenario Integrated land cover
|
Evaluate multiple IPCC scenarios (e.g. A2 vs B2 etc.) |
Year 3 |
With agriculture and urbanization as climate feedbacks, our model becomes more of an earth systems model and overlaps greatly with the climate change impacts community, who are greatly interested in the impacts of climate change on vegetation, agriculture, and urban climate. We propose a workshop in the second year to address the convergence of impacts and earth system models in the context of interactive vegetation (both natural ecosystems and agroecosystems) and also possibly hydrology. We expect a workshop of 40 people, of whom about 10 would be international.
Other Funding Opportunities
We will seek outside funding to partially support activities in
the second and third years through the NASA Land Cover Land Use Change Program.
First-order sensitivity of IPCC simulations to land cover. Transient human population datasets.
Urban land cover parameterization and transient datasets. Irrigation sub-model and datasets.
Soil degradation parameterization and transient datasets. Transient SRES land cover change. Interactive crop parameterization using CERES crop models. Workshop on Impacts and Earth System Model Convergence.
Simulated climate with cities, soil degradation, and land cover change. Transient SRES simulations. Merging crop model with Biogeosciences initiative.
G. Bonan, L. Mearns, J. Meehl, K. Oleson
J. Feddema,
3. Climate Scenario Development and
Distribution
Goal
To continue
and expand upon NCAR's role as developer and provider of climate scenarios for
impacts research in the
Progress
to Date
The U.S.
Workshop on Climate Projections, Uncertainty, and Climate Scenario Development
for Impacts Assessments was held in July 2002 at NCAR. An action plan on
developing a Unified U.S. Program on Scenario Development is being developed as
the main output of the Workshop.
Research
Plans
We will
develop a data system to collect the most recent outputs from AOGCMS, minimally
all the climate model simulations from the SRES scenarios, develop appropriate
baseline data sets needed for combining with the climate model output, and
incorporate measures of uncertainty into the scenarios (perhaps even regional
probabilities of the different scenarios). We will also create a web-based tool
that will allow for easy data acquisition of the scenarios, provide guidance
material on the use of scenarios, and provide links to other data distribution
centers. Particular attention will be given to providing scenarios based on
projections from the three U.S. Climate modeling Centers, NCAR, GFDL, and GISS.
Also, collaboration with the
(Note: under
level funding, little could be accomplished on this project, beyond continued
development of the action plan and some minor work on gathering outputs.)
Timeline of Accomplishments
YEAR 1
Work will begin in mid-FY03.
Collect outputs of existing AOGCM simulations using SRES scenarios A2
and B2, from North American Climate Centers.
Start Development of Web-tool. Coordinate with NOAA NCDC the development
of gridded climate database.
YEAR 2
Incorporate newer climate simulations from the other SRES
scenarios, including North American regional model runs, into the data
distribution. Start developing guidance material for scenario use. Complete development of Web-tool.
YEAR 3
Develop measures of uncertainty and incorporate into the
scenarios. Provide guidance on the measures of uncertainty and how they can be
used in impacts assessment.
NCAR
Team
L. Mearns,
J. Meehl, D. Middleton, W. Washington, D. Nychka, T. Wigley
External
Collaborators
R. Stouffer,
GFDL. J. Hansen, GISS, T. Karl, NOAA NCDC, G. Boer, F. Zwiers, CCCma, R.
Street, E. Barrow, Environment Canada, L. Gates, B. Santer, LLNL
Goal
This component of the strategic initiative is an extension
to the CSENT project of the CGD-Paleogroup, which focuses on natural climate
variability during pre-industrial times. Previously, Climate System Model (CSM)
and Parallel Climate Model (PCM) simulations have been very successful in
reproducing climate variability and trends verified by the instrumental record,
a period strongly affected by the anthropogenic forcing. Extending the time
frame several hundred years prior to the appearance of this trend is crucial to
verifying overall climate sensitivity. CSENT performs experiments employing the
fully coupled Community Climate System Model (CCSM vers. 2.0) by sequentially
adding important forcings including volcanic aerosol, solar irradiance changes,
land use and greenhouse gases. Because the period after A.D. 1600 is now well
covered by high-resolution proxy data of exceptional quality, comparing the
best currently available proxy records with coupled climate model results acts as an important test of the model’s ability to represent both past and future
climatic changes. This is the first-order goal of this project. Three general
focus areas are pursued.
a) Fingerprinting of Forcings
Results from the CSENT simulations will be compared to recent climate
reconstructions on a number of spatial and temporal scales. This work will be
done as a data-model intercomparison with Prof. M.E. Mann (
b) Regional and Climate Mode Responses
American Southwest (SW): Environmental conditions in the US-SW have always been strongly controlled by climate, in particular, the availability of water. The richness of good high-resolution proxy data (derived from tree rings) allows reconstruction of important environmental parameters such as precipitation, summer temperature, drought, and fire occurrence. As a regional application, we will compare the climate variability represented in the global coupled experiments with the range observed in the historical and proxy climate record over the US-SW. We particularly focus on drought conditions, which can directly be related to regional wild fire danger. We will investigate controlling mechanisms for low-frequency changes responsible for wet and severe drought conditions. To complement these investigations, a regional modeling effort using the MM5/OSU nested into CCSM covering the conterminous U.S. and Northern Mexico will be led by E. Small (U. of Colorado), building on his previous work to investigate climatic patterns in higher spatial resolution. Forced with CSENT runs as boundary conditions for a selected multi-decadal window, the regional model can better resolve local contributions from, for example, topography and soil moisture, to the regional climate variability. Of particular interest will be the influence from land use and external forcing effects on the North American Monsoon system.
c) Uncertainty Propagation
The overarching problem of uncertainty propagation in paleo applications
(from the forcings to the impacts) has not been seriously addressed in the
literature. We will evaluate the robustness of
climate signals in both modeling and proxy data. On the one hand, we revisit fundamental assumptions often applied
in proxy reconstructions through comparison with globally available, physically
consistent climate model output. On the other hand, a number of “unusual”
events of past climates well captured by climate proxy information are
simulated, using varying forcing combinations and internal mode states with the
GCM to evaluate uncertainty forcings and model.
d) Education and Outreach Component
We are collaborating and cost-sharing with the NCAR Education and Outreach
Office (EO) to develop K-12 educational activities on natural climate changes
of the LIA that directly integrate into the new Climate and Global Change
exhibit (in preparation for FY03) for the Mesa Laboratories. Inquiry-based
exhibit components and worksheets for classroom use (K-12 levels), as well as
instructional support materials for teachers following National Science
Education Standards are developed, tested, and disseminated by EO and the PIs
together with an education consultant.
Requested Computer
Time:
To produce the special runs required for this project (dedicated runs of the AOGCM for regional model resting, regional model runs, etc.), a total of approximately 10,000 GAUs would be required. While some of these GAUs can be accommodated through the CGD allocations, approximately 5,000 GAUs will be needed from other sources. We are requesting approximately 5,000 GAUs from the Director’s Reserve to cover primarily the regional modeling runs over the three-year period. Most of the GAUs will be needed in the second year (see timeline below).
Additional funding opportunities:
We have identified a number of programs and special calls that we will pursue for complementary funding of this project. These include: NOAA OGP, NSF-GEO-MATH for aspects of the uncertainty analysis, and NASA RAs for the Earth System Enterprise Program.
Timeline of Accomplishments
YEAR 1
Completion of CCSM forcing
runs and general analysis; temporal fingerprinting of
Forcings, estimate uncertainty; assemble database of North Atlantic
reconstructions, characterize patterns and their evolution; study of temporal ENSO/drought teleconnections in US-SW;
drought-fire link in SW from proxy data and control runs; Setup of MM5/OSU
nested in CCSM.
YEAR 2
Spatial fingerprinting of external forcing and internal modes (NAO); sensitivity experiments using varying forcings; specified SST runs with North Atlantic basin cooling; 30-year runs of MM5/OSU using control conditions; analysis of drought and fire in US-SW.
Focus on uncertainty: test of robustness of global reconstruction techniques; investigate mechanism for low frequency variability in North Atlantic (thermohaline circulation); 30-year nested runs of MM5/OSU forced with landuse and external forcing; comparison of model and proxy climate reconstructions for SW; depending on previous results, extension of analyses using projection runs to AD 2100 with statistically prescribed external forcing; Winter: workshop on integrated Little Ice Age research at intersection of models and proxy data.
C. Ammann, H. Cullen, E. Wahl, D. Nychka, R. Johnson, S. Foster, L. Carbone
E. Small (regional modeling):
U. of Colorado; G. Bond, E. Cook and R. D’Arrigo (Lamont-Doherty Earth
Observatory, Columbia U.), H. Wanner (Swiss National Competence Center of
Research in Climate, Director), J. Luterbacher and C. Casty (Dept. of
Geography, U. of Bern), T.W. Swetnam (U. of Arizona, Laboratory of Tree-Ring
Research), M.E. Mann (U. of Virginia), and R.S. Bradley (U. of Massachusetts),
P. Naveau (U. of Colorado), H.-S. Oh (U. of
5.
Decision Making and Uncertainty: Managing Wildland Fire Risks: Climate and
Weather Information and Uncertainty
This program element will contribute to the development of a methodology for examining the effects of uncertainty and the value of weather and climate information for the effective management of wildland fire risks. The focus of the research will be on analyzing the roles of uncertainty and information in situations where autonomous, but mutually interdependent, decisions are being made by a number of individuals whose interests and objectives may conflict. The goal of the proposed research is to contribute to the development of policy alternatives, decision support tools and risk communication methods that could improve societal management of these risks. This project entails major collaboration with the Wildland Fire Initiative and some with the Water Cycle Initiative.
Progress to Date
Alison Cullen
has spent time at NCAR assisting in the development of the Uncertainty and
Decision– Making part of this initiative.
Kathleen Miller attended a conference on decision-making and uncertainty
to gather information on the state of research in this area world-wide. Through these activities, Miller and Cullen
developed the idea of starting the task on wildland fires and decision-making.
Research Plan
The incidence and
significance of wildland fire risks as well as the costs and damages arising
during and after individual fire events are the result of decisions made by a
large number of public agencies and private individuals on many different time
scales. Long-term decisions regarding road construction, timber harvesting,
vegetation management and investment in homes and other built infrastructure
affect the likelihood, intensity, and costliness of fire events. Near-term fire-suppression decisions
determine the net social costs and environmental impacts, as well as the
distribution of costs and benefits arising from current fire events. Post-fire
land treatment has further ecological and hydrological impacts, for example on
aquatic ecosystems. Fire suppression also affects future fire risks. (We will be working in
collaboration with the Wildland Fire and Water Cycle Initiatives regarding
post-fire hydrologic impacts and land management decisions.)
A systematic analysis of the interconnections among decision problems faced by all of these many players would help to illuminate the nature of current controversies surrounding implementation of the National Fire Plan, and could be useful in tailoring policies to best fit local circumstances. Such an analysis also could help to identify the types of climate/weather and other scientific information likely to be most valuable at various points in the decision process and the most effective modes for transmitting that information to the appropriate decision-makers.
Our proposed analytical approach will be to characterize decision environments as composed of a set of interconnected decision trees. This will allow us to map out important nodes of interaction among otherwise independent decision problems. This mapping technique can be extended over any appropriate time-scale. Our working hypothesis is that conflicts, as well as opportunities for productive negotiations and policy interventions, will tend to be clustered around those points of intersection.
(Note, under level funding, this project will essentially
not exist-- some continued project idea development could be pursued through
visits from A. Cullen).
YEAR 1
1) Survey existing work in this area. Identify linkages to other research efforts. Convene small workshop to help map out research strategy and to develop a template or framework of elements to be considered in looking at the role of climate/weather or other atmospheric science information in the various decisions relevant to wildfire risks and impacts.
2) Create a mock-up model of the interconnected decision framework. Identify relevant software for displaying and quantifying the decision problems, and examine the flexibility of the modeling framework and the potential sensitivity of the overall social optimum to model specification (e.g., number of independent actors, number and magnitude of spillover effects among their decisions).
YEAR 2
3) Conduct case studies focused on two regions with contrasting characteristics (e.g., with respect to: climatic fire regime/seasonality; level of development; susceptibility to post-fire erosion damage; land ownership characteristics). This element will entail conducting on-site interviews with relevant decision-makers in each area to identify variables affecting their individual decisions, and their perceptions regarding the impacts of decisions made by others on the costs and risks pertaining to their own decision problems.
4) Identify the critical policy issues facing each of these regions.
5) To the extent possible, quantify the range of uncertainty surrounding the important variables in a set of policy-relevant decision problems for each of the two geographical areas.
YEAR 3:
5) Model the interconnected decision processes, using linked decision trees, in sufficient detail to identify options for (a) improving coordination among decision makers and (b) optimizing the flow of forecasts and other information to them.
K. Miller, R. Katz, R. Wagoner (Fire Initiative)
II.
Weather and Climate Extremes
Research in climate and weather extremes is fundamentally motivated by their impacts on society, which are considerable. The IPCC reports highlighted extreme events from both the physical science and impacts point of view and strongly recommended more research in all aspects of extremes. The initiative element on extremes consists of five projects, several of which are continuing. The projects concern research in weather and climate modeling of extreme events, downscaling of extreme weather phenomena, spatial scaling of extremes, application of extreme value theory to atmospheric problems, and research on reducing societal vulnerability to extremes. A particular effort is made through these different projects to integrate across both atmospheric science aspects of extremes and societal concerns. Collaboration with both the Wildfire and Water Cycle Initiatives is involved in several of the projects.
Goal
The goal is to develop software and a
web-based tutorial for the fitting of meteorological extremes in a form
accessible to the broader atmospheric community.
Accomplishments to Date
In FY02, work was begun on the toolkit in
RAP. Preliminary programming of appropriate algorithms and preliminary
development of a graphical user interface was completed.
Research Plan
A website will be developed that will
make the software available and provide a tutorial on its use, along with ample
weather, climate, and impacts examples.
The essential software in S-plus or R will be developed, as well as the
basics of the tutorial.
(Note:
under level funding, this project would still be completed as
described).
Expected Accomplishments
YEAR 1
Toolkit and guidance material and web
interface will be completed (1-year project).
NCAR
Team
R.
Katz, D. Nychka
External Collaborators
R. Smith,
Extreme events, though of great societal importance, often are difficult to forecast using standard objective forecasting approaches. Extreme value theory seems to provide a potentially useful alternative approach for these prediction problems, which will be investigated in this study. In particular, we propose to apply extreme value theory to four forecasting problems that are currently under investigation in the Research Applications Program (RAP). Although research and development in three of the four forecasting areas is supported through the Federal Aviation Administration’s Aviation Weather Research Program, this funding is for directed research, and not intended for exploratory research such as that proposed here.
During the first year, the main focus of the extremes work was on initial development of the extremes toolkit. In addition, in-flight icing was identified as the first area of focus for applications of extreme value theory. Specifically, the problem of predicting or diagnosing icing severity was selected as an area that could benefit greatly from this work. Initial datasets to be used in this application were identified, and a general approach was developed.
The four research areas to be considered are (1) In-flight
icing, (2) Turbulence, (3) Convection, and (4) Public Weather forecasts. Each
of the first three phenomena occurs quite infrequently (e.g., over less than 5%
of the continental
The four forecasting areas will be considered in the order presented above, through three stages: (1) isolate the problem; (2) apply analysis techniques to appropriate data sets; and (3) incorporate results into an improved forecasting algorithm. Stage one for each product will begin as the previous topic enters the second stage. All stages will involve collaboration with a RAP scientist. The extremes toolkit that is being developed as another aspect of this initiative will be applied to the analysis of the data for these topics.
(Note, under level funding, only two of the four research areas would be considered, and the project start would be delayed until FY04, after the completion of the extremes toolkit).
Extreme value method for icing severity in an experimental version of the Integrated Icing. Diagnosis/Forecast Algorithm. Methodology and data sets for analysis of turbulence data and severity algorithm development.
Extreme value method for turbulence severity in an experimental version of the Integrated Turbulence Forecast Algorithm. Methodology and data sets determined for analysis of convection data and forecast algorithm development. Analysis of convection data completed.
Extreme value method for convection forecasting completed, insertion either into Autonowcaster or other system. Methodology and data sets determined for analysis of public weather forecast techniques. Analysis of forecasting data completed. Extreme value method for public weather forecasts of extreme events in an experimental version of the Intelligent Forecast System.
B. Brown, M. Politovich
P. Naveau, U. of Colorado
3.
Downscaling of Extreme Weather/Climate Phenomena
Goal