In mid-FY99, Principal Investigator Michael Glantz organized a 19-month study of the impacts of the 1997-98 El Niño event on 16 countries in four major areas: Asia, Southeast Asia, Subsaharan Africa, and Latin America. The study was conducted in cooperation with the UN Environment Programme, the UN University, the World Meteorological Organization, and the International Strategy for Disaster Reduction (ISDR, formerly the IDNDR). Glantz identified team leaders for each country and convened a workshop in July 1999 to identify research strategies. The "forecasting by analogy" (FBA) approach was chosen to identify strengths and weaknesses in societal responses to El Niño-spawned droughts, floods, fires, frosts, and disease outbreaks in order to provide governments with quantitative and qualitative information on the impacts of previous El Niño events. Such assessments provide a government with insights into regions, sectors, and populations that are likely to be at increased risk during El Niño. FBA can also provide disaster agencies with an opportunity to review how well their contingency plans worked in 1997-98 and make adjustments to them. In FY00, Glantz organized a "Mid-Course Evaluation Meeting," held in Macau, a Special Administrative Region in China, to assess the progress of the country studies, discuss problems encountered, and finalize dissemination procedures. An Executive Summary of the findings, prepared by Glantz and Stewart, was released on 27 October 2000 to the UN Millennium Assembly at the United Nations in New York. It was released by UNEP's Director, Klaus Toepfer, and the WMO's Secretary-General G.O.P. Obasi. The full summary will be available in mid-FY01. The UN University Press will also provide, in its entirety, each country study on CD-ROMs. Stewart acted as the Project Liaison during this project, as well as serving as Rapporteur for the various workshops and project advisory meetings.
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Climate Variability in the NCAR Parallel Climate Model (PCM)
Mearns, with Gerald Meehl and Julie Arblaster (CGD) are analyzing changes in high-frequency (daily to interannual) variability in several simulations of the NCAR PCM, e.g., current climate, and future climate. This research project began in FY00. They have applied the domain statistical package developed by Mearns and colleagues to these simulations. They have found significant decreases in temperature variability in the winter in Northern Hemisphere midlatitude land areas. Substantial changes in the frequency and intensity of precipitation have also been identified.
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Development of Interactive Vegetation Package
for Regional Climate
Elena Tsvetsinskaya, with Linda Mearns and Filippo Giorgi (CGD/Trieste Institute of Physics, Italy), has coupled the CERES-maize model into RegCM2. The growth functions of CERES-maize were incorporated into the biosphere-atmosphere transfer scheme (BATS), which is the surface scheme for the regional climate model, RegCM2. Off-line tests of coupled CERES-BATS indicated that strong responses (of plant height, growth of leaf area index, and surface radiative fluxes) to different temperature and precipitation conditions were found. Coupling of the interactive surface scheme with RegCM2 has been completed. RegCM2, with the coupled surface package, has been run for the domain of the Great Plains of the US to determine the effect of the growing vegetation on surface fluxes and local climate.
The model was run using European Centre for Medium Range Forecasting (ECMWF) boundary conditions for 1991, a normal year, and 1988, a dry year. Results indicate that for 1988 large differences occur between the non-interactive run and the interactive run. With the interactive growth and development module, the simulated climate is warmer and drier than in the default run, and closer to the observed climate [ Contour Plot Showing July Mean Difference in Air Temperature for 1988 ]. Differences in 1991 were less striking
[ Contour Plot Showing July Mean Difference in Air Temperature for 1991 ]. These results indicate that including growth and development of vegetation in a climate model can have important effects on the simulated climate. Two articles on this research are in press in the Journal of Climate. This work formed part of the ESIG contribution to CMAP.
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Effect of Changed Climate Variability
on Simulated Crops and Ecosystems
While most studies of the impacts of climate change on resource systems and ecosystems have examined the effect of mean change in climate, it is widely believed that changes in variability of climate, in addition to the mean, can have substantial effects. This issue is becoming more important as we learn more about how climate variability may change in the future. During FY99, Mearns and colleagues examined the possible additional effects of changes in variability on these systems.
A variant of the daily weather generator of Richardson (1981) was modified for these studies. By manipulating the parameters of the generator, changes in the variance (daily and interannual) of time series of temperature and/or precipitation may be produced. In FY96, 97, 98, and 99, Mearns, with colleagues at the Goddard Institute for Space Studies (GISS) and Larry McDaniel, published several papers on the effect of variance changes of temperature and precipitation on simulated crop yields. Much of this work used locations in the Great Plains and primarily considered continuous and fallowed wheat cropping. These studies established the importance of considering changes in both the mean and variability of climate on simulated crops. Additional studies were performed in FY00:
- Mearns, with Cynthia Rosenzweig and Richard Goldberg (NASA Goddard, New York) continued research on the effect of changes in variability of climate on simulated crop yields at other locations in the Great Plains and mid-West. They have applied time series of temperature and precipitation with changed variances to CERES-corn and CROPGRO-soybean models. Results so far indicate that increased variance of temperature and precipitation cause substantial decreases in yield, while decreases in variability cause only slight increases in yield [ The effect of variance changes of temperature and precipitation on simulated corn yield at three locations in the central U.S. ]. They have begun applying changes in variance from two major AOGCMs, the NCAR PCM and that of GISS, for the region of the Midwest and Great Plains to these crop models for the end of the twenty-first century.
- With Marta Vinocur (National University of Redo, Cordoba, Argentina) Mearns has investigated simulated peanut crop responses to climate variability in Cordoba, Argentina. Using PeanutGRO, they explored the effects of different combinations of mean and variance changes of temperature. They found that the crop model was sensitive to both mean and variance changes, but that increases in temperature variance substantially exacerbated decreases in yield and greatly increased the likelihood of crop failures. They are currently exploring the causes for these crop model responses. Several conference preprints were produced during FY00 on this work (Vinocur and Mearns, 2000; Vinocur et al., 2000).
- A project studying the impact of variability changes on forest/ecosystems in the Northwestern United States funded by NSF and in collaboration with scientists at U Washington and Oregon State U, has been completed. Changes in variance of precipitation were applied to the MAPPS biome model for locations in Oregon. Preliminary results indicate that variance increases lead to decreased leaf area index, while decreases in variability result in slight increases. The effect is much more striking when the version of the model using daily climate input is used in contrast to the version using monthly climate input. A paper describing these results is in preparation.
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El Niño and Statistics
The general goal of this research is to examine historical connections between statistics and atmospheric science and draw lessons for future multidisciplinary collaborations. During the past fiscal year, Katz wrote a paper on a little-appreciated connection between El Niño and statistics. In this paper, the research of Sir Gilbert Walker, noteworthy for contributions to both statistics and atmospheric science, is reviewed.
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Extreme Value Theory
The general goals of this research are to develop improved statistical methodology for climate variability, climate change, and impacts involving extreme events. Specific topics include: extreme events and climate change, stochastic models for damage from extreme weather, and statistical downscaling of extremes.
Extreme Events and Climate Change: In collaboration with Philippe Naveau (NCAR/GSP), Richard Katz continued work on a review of the use of the statistical theory of extremes as applied to climate change and its impacts. Evidence is increasing that climate variables (e.g., precipitation), related variables (e.g., streamflow), and impact variables (e.g., economic damages) all have distributions with heavy upper tails. Yet, this characteristic is not taken into account in statistical analysis of extremes (e.g., trend detection).
Stochastic Models for Damage from Extreme Weather: In collaboration with Roger Pielke, Katz continued work on a stochastic model for economic damage associated with extreme weather events, such as hurricanes. Research during the past year focused on more firmly establishing that the damage from individual hurricanes has a heavy-tailed distribution.
Statistical Downscaling of Extremes: This topic is a new thrust with the FY00 fiscal year. Although there has been much work on statistical downscaling as well as on statistical modeling of extremes, this effort is the first to make use of the statistical theory of extreme values in downscaling. It involves collaboration with Marc Parlange (Johns Hopkins U).
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Flood Loss Data Reanalysis
Roger Pielke Jr., Mary Downton, Zoe Miller and Roberta Klein continued work on a NOAA/OGP project (begun in FY98) on "Understanding Damaging Floods in the United States: Data Reanalysis and Correlation with Precipitation Trends," to create an improved historical flood loss data set. They have begun an assessment of climate indicators and damage trends. The completed flood base will include at least (1) national flood damages 1902-present; (2) flood damages by state, 1955-present; (3) flood damages by watershed, 1933-1974 or later; (4) flood damages by National Weather Service district, 1933-1974 or later. Preston Heard (SOARS student) completed a pilot study in summer 2000 to assess whether an ENSO signal can be detected in California flood damage data. This study was the first step in the precipitation correlation phase of the project. The project will continue through FY01 with a report available in late 2001.
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Methods for Assessing Economic Value
of Weather and Climate Forecasts
The goal of this research is to evaluate methodology for quantifying the economic value of imperfect weather and climate forecasts. During the past year, Richard Katz continued work on a review of Bayesian decision-theoretic studies of the economic value of imperfect weather and climate forecasts (i.e., prescriptive approach). A Web site that categorizes recent case studies of the value of weather and climate forecasts continues to be maintained and updated as well.
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Other Changed Climate and Crop/Ecosystem Projects
Linda Mearns, Justin Wettstein (U Washington), and Larry McDaniel, in collaboration with Allan Auclair (Rand Corporation, Washington, DC) continued their NOAA study of the effects of climate variability on forest dieback in the northeastern United States. In FY00, they have focused on analyzing the relationships between the North Atlantic Oscillation (NAO)/Arctic Oscillation (AO) and local temperature conditions. They found an intensification of spatial patterns of contrasts in winter maximum and minimum temperature in extreme phases of the AO. For example, an extreme positive AO index winter had minimum temperatures 2.5 degrees C warmer in the southwest portion of the Northeast, and .5 degrees C cooler in the Northeast, compared to the extreme negative AO index. Important variations in the daily variance of temperature were also found. A paper describing results is in preparation for submission to the Bulletin of the American Meteorological Society.
Mearns continued the study of the effect of climate change on wheat yields in Italy with Carlo Pona (Agency for New Technologies, Energies, and Environment, Italy [ENEA]). In this case, the effect of both a high spatial resolution climate change scenario (required for a land mass as small as Italy) and changed variance of climate in the future are being investigated. Climate change scenarios for Italy have been generated from output of the RegCM2 European runs. Numerous sensitivity analyses with CERES-wheat have been performed for locations in Italy; crop model runs with mean climate change scenarios throughout Italy have been made; and the effects of changes in daily and interannual climate variability are being examined at selected stations.
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Prediction in the Earth Sciences
In modern society, prediction serves two important goals: (1) as a test of scientific understanding, and (2) as a potential guide for decision making. Calls for prediction as a basis for environmental policy making suggest confusion about these two motives for why we predict. Prediction: Science, Decision-Making and the Future of Nature is the culmination of two workshops and papers from ten case studies, ranging from asteroid paths to climate change to nuclear waste disposal. The volume was edited by Dan Sarewitz (CSPO, Columbia U), Roger Pielke Jr., and Radford Byerly (US House Science Committee, retired) to help refine the case histories and view the prediction problem in a more coherent way. This book provides insight into the promise and limitations of prediction as a tool for decision-makers, explores alternatives to prediction, presents fresh perspectives about the interface between science and environmental decision making, and makes recommendations to increase the likelihood of effective decision making.
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Regional Climate and Crops in the Great Plains
Linda Mearns, along with Larry McDaniel, Elena Tsvetsinskaya (U Nebraska-Lincoln), Theo Mavromatis (U Florida-Gainesville), William Easterling (Pennsylvania State U) and Cynthia Hays (U Nebraska-Lincoln), completed work on a four-year NIGEC (National Institute for Global Environmental Change) project, "Development of a Nested Regional Climate Change Scenario with an Application to Crop Models." The project involved regional climate modeling with RegCM2 by Filippo Giorgi (International Centre for Theoretical Physics, Italy) and Christine Shields (CGD), detailed climate model evaluation, and application to crop models. Each stage of the work focused on some kind of uncertainty analysis of: (1) spatial scale of climate change; (2) effect of scale differences on agricultural impacts; and (3) choice of impact model. Numerous publications have resulted from this work.
- A high-resolution climate change scenario (control and doubled carbon dioxide) was formed using the RegCM2 at 50-km grid point spacing of the western two-thirds of the United States. A coarse resolution scenario was formed from the output of the CSIRO general circulation model, which provided the boundary conditions for the regional model runs.
- They applied the two different scales of climate change scenarios to the EPIC corn, wheat, and soybean crop models for the GCM grid boxes in the central Great Plains. We found that the different scale scenarios produced substantial differences in the impacts of climate change on these agricultural crops [ Change in Simulated Crop Yields ]. They also analyzed the spatial patterns of the simulated yields, and found some important differences in spatial variances among the treatments. Tempero-spatial statistical models were developed with the assistance of D. Marx (U Nebraska) and T. Haas (U Wisconsin, Milwaukee), who is a visitor with the Geophysical Statistics Project at NCAR. Two articles on this work have been accepted by Climatic Change.
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Robert Harriss and colleagues aim to form a Biocomplexity Design Team for a dialogue to investigate dynamic and complex interactions fundamental to the co-evolution of cities and the atmosphere. The core hypothesis is that the continuing, rapid urbanization of the human population will have a profound influence on the evolving nature of our global chemical and physical climate systems. The Team will conduct a series of workshops and a collaborative dialogue that will bring leading scholars from relevant disciplines together to structure a search for sustainable urban growth strategies. Our design objective is to accomplish significant reduction in urban respiration products (e.g., criteria air pollutants and greenhouse gases) in the coming era of urban growth. The Team also intends to bring new insights to unresolved issues of local and regional near-surface air quality management that have plagued most major cities in the United States for decades. The integrated study design and modeling tools developed in this incubator project will provide the basis for understanding the role of urbanization as a driving force in global atmospheric change.
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Use and Value of Weather Bibliography
This bibliography on the Use and Value of Weather by Pielke, Klein, Jennifer Oxelson, and Aaron Nutter begins the task of providing a single resource for published, peer-reviewed articles on the use and value of weather and climate forecasts. This area is a subset of the broader area of forecasting in the earth sciences. The bibliographies were put together based on searches of meteorological and geophysical abstracts, UnCover, and Dialog@CARL, including several journals: Applied Social Science, Chemical Safety, Electric Power Data, Federal News Service, and Thompson Risk Management. The overall list of more than 500 entries is organized into a set of "sub"-bibliographies in order to facilitate finding useful information.
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