Integrated Assessment of Climate Variability

## Integrated Assessment of Climate Variability, Impacts and Policy Response in the Pacific Northwest

### by Edward L. Miles

This article describes a project concerned with the human and ecological implications/responses to two sources of global and regional climate variability. At the global scale, the focus is on anthropogenically-induced climate change as a result of the increasing concentration of greenhouse gases in the atmosphere (IPCC 1990, 1992, 1994). The principal forcing function is represented by increasing emissions of CO2 and other greenhouse gases and the timescale of change is on the order of decades to centuries and perhaps millennia (Broecker, 1987).

At the regional scale, the focus is first on the projected regional climate response to anthropogenic greenhouse forcing and the impacts of such forcing on natural ecosystems, natural resources, and human activities. The timescale of change is on the order of decades to centuries. Secondly, however, we consider naturally-occurring climate variations on the regional scale in which the principal forcing functions are fluctuations in the coupled atmosphere/ocean/land system. The timescale of change here is seasons to decades.

In the Pacific Northwest (PNW), the dominant regional climate signal is linked to the large-scale, interannual climate phenomenon called El Niño-Southern Oscillation (ENSO) (Battisti and Sarachik, 1995). ENSO has been shown to have strong Pacific-wide effects with direct connections to regional climate anomalies over Australia, the Indian Ocean, and South America on seasonal/interannual timescales and with mid-latitude Northern hemispheric teleconnections on seasonal to decadal timescales (Graham 1994; and Trenberth 1994).

Since the ENSO phenomenon occurs on a much shorter timescale than the anthropogenic contribution to greenhouse forcing, we, like U.S. GLOBEC (U.S. GLOBEC 1994), choose to treat ENSO and its impacts as a model experiment of how global climate variability might affect natural ecosystems, natural resources, and human activities on a regional scale. In this connection, we are ultimately most concerned with the sensitivities and vulnerabilities of ecosystems, resources, and human activities to climate variability/change of all types and with what kinds of response strategies may make the most sense on different timescales.

### Defining Integrated Assessment

Global climate variability generates pervasive, multi-dimensional effects. The prospect of human-induced global climate change necessitates the development of response strategies at a variety of time and space scales. Details of the effects expected as a result of human-induced global climate change are still poorly understood and there is still substantial uncertainty embedded in the predictions generated by general circulation models (GCMs). Since the resolution of the GCMs is poor, our understanding of the regional-scale effects of global climate change (GCC) is as yet rudimentary. It would not be advisable simply to parameterize the GCMs downwards to regional scales because such an approach could yield spectacular errors. Therefore, we will take a bottom-up approach, matching data on regional characteristics to those processes and dynamics of global climate variability, e.g., the ESNO cycle, which are fairly well understood.

Working through the causal chain from climate dynamics to climate impacts to policy response strategies is what we mean by providing integrated assessment. This means that in the PNW, we shall try to link the dominant climate signal, i.e., ENSO, to regional climate variability impacts; and secondly to link the regional climate impacts to response strategies. Care must be taken to estimate the level of uncertainty attached to predictions of specific impacts. Presently, we focus on climate dynamics in relation to water resources, forest resources, marine ecosystems, and coastal activities. In the future, we propose to add energy, urban centers, agriculture, and human health.

There is no one way of doing integrated assessment. Since we are concerned principally with natural climate variability on the regional scale, we begin with the phenomenon itself and the capability to predict its occurrence. In this context, vertical or end-to-end prediction and assessment consists of the following elements (Sarachik, unpub. MS 1995):

- A model to make the predictions.
- Data: Must be quality controlled, ingested and assimilated into a form the model can accept.
- Initialization: The data and the model must be combined to provide an optimal estimate of the state of the coupled system.
- Large Scale Prediction: One, and perhaps an ensemble of predictions must be run.
- Evaluation: The data must be used to see how good the forecast was and to provide an objective measure of skill.
- Assessment: Look at the impacts of seasonal-to-interannual variability and decide on the appropriate regional site and scale.
- Regionalization: Regional data and models must be combined to provide regional data products.
- Regional Forecasts: The regional data products are combined with the large scale forecast to provide a regional forecast.
- Applications: The regional forecasts are applied to different sectors of usability.
- Effectiveness of Applications: Understanding and implementing appropriate ways of distributing and communicating information (including uncertainties) about seasonal-to-interannual variability, prediction, and applications to a broad user community.
- Evaluation of Applications: The impact of the applications and the effectiveness of whatever actions are taken are evaluated.

We note also the following point made by Dowlatabadi and Morgan (1993):

> Whereas the arguments for integrated assessment are intellectually compelling, current understanding of the natural and social sciences of the climate problem is so incomplete that today it is not possible to build traditional analytical models that incorporate all the elements, processes, and feedbacks that are likely to be important....The result has often been that the policy discussion has focused on what we know, rather than what is important....it will be necessary to evolve a new class of policy models that allows an integration of subjective expert judgment about poorly understood parts of the problem with formal analytical treatments of the well-understood parts of the problem.

### The UW Project on Integrated Assessment for the Pacific Northwest (PNW)

Based on the reasoning outlined above, this project incorporates two foci: a) applying predictions of PNW climate; and b) an integrated assessment of climate variability impacts in the PNW, both as a model for potential climate change and as an economically practical use of current scientific knowledge of seasonal to interannual climate variability.

The state of the art in air/sea interaction studies offers substantial promise for improving long-range climate forecasts, particularly on the seasonal/interannual time scale. These forecasts can encompass precipitation, run-off patterns, sea-surface layer conditions, the frequency and/or probability of storm surges, and changes in the ocean environment of relevance to fisheries.

The ability to offer seasonal/interannual climate forecasts of increasing accuracy implies that the scientific community and the user community of the forecast products must be linked dynamically. Such linking will facilitate reciprocal understanding of the needs, resources, and limitations of both communities; influence design of forecast products which are clearly tailored to the needs of the user community; and expand the research community's capabilities to conduct integrated assessment of the probable impacts of global climate change on the Pacific Northwest.

### A Workshop

NOAA/OGP organized a one-day workshop held at NOAA/Pacific Marine Environmental Laboratory (PMEL) on February 1, 1995 to discuss what we know about regional-scale climate change, its impacts on the PNW, and new types of forecasts. The workshop brought together climate diagnosticians from NOAA and JISAO and representatives of the user community in Washington and Oregon.

From the perspective of climate diagnostics, the point was made that while it would not be possible to predict what would happen in a particular month or variability over several years, it was possible to predict seasonal and interannual climate fluctuations. We defined the region of the PNW as the entire Columbia Watershed and focused on the relationships between ENSO variability, precipitation, temperature, and snowpack. Temperature is strongly correlated with ENSO in the PNW and temperature predicts to snowpack. New technology is yielding better understanding of the ENSO phenomenon and gives promise of better resolution (smaller scale) in prediction and more lead time in the forecasts.

Anticipated forecast products, based on the new technology, include: a) monthly seasonal forecasts out to one year lead time; b) monthly coupled dynamical model forecasts for Tropical Pacific SSTs out to one year; and c) monthly 9-member ensemble/2-season atmospheric GCM forecasts using either observed or tropical model forecast SSTs.

Who are the users of climate prediction data and what are their needs? Potentially, they are the 1) Washington Dept. of Fish and Wildlife (salmon stock management), 2) Washington Department of Ecology (monitoring and management of eutrophication; habitat management; flooding and coastal erosion hazards), 3) Seattle City Light, Bonneville Power Authority, and Tacoma Power and Light (hydroelectric power generation; monitoring and regulating watersheds; runoff), and 4) the National Marine Fisheries Service (ocean conditions, circulation, fisheries management in face of uncertain climate change). There are many others. Forecasts of the spatial and temporal patterns of temperature, precipitation, stream flow and runoff are needed to enable these agencies (users) to more efficiently and economically manage resources (e.g., water, fisheries). For example, the U.S. Bureau of Reclamation/Yakima has a focus on managing water for multiple uses. They need specific predictions rather than loose statements like "above or below normal." At minimum, they would like a forecast for a range of expected climate conditions. The runoff forecast is their critical management tool, therefore temperature and precipitation are the most important variables. 60% of their summer water comes from snowpack. Most agencies operate on the basis of historical data, i.e., ca. 30 years. They need to understand what is normal in the PNW and how to predict and understand regime shifts.

Based on these views, expressed at the workshop, the project will focus on:

- Climate variability and the ENSO phenomenon on seasonal/interannual and intra-decadal/decadal time-scales and their impacts on the PNW, in particular on the relationships between precipitation, temperature, and snowpack.

- Describing and evaluating the policy framework on the basis of which management decisions are made with respect to multiple uses of freshwater resources, salmon production/survival, agriculture, energy, coastal zone utilization and development. Part of the evaluation will assess the prospects for a more holistic approach.

- Changes in and upgrades of climate information systems in the context of understanding which players are sensitive and vulnerable to climate variability.

- Improved communication and public education as a result of the above; the Internet provides a means of information exchange; and encouraging and providing a mechanism for feedback between climate diagnosticians and the user community.

- Implications for the PNW's ability to adapt to human-induced climate change that may result from anthropogenic greenhouse gas emissions.

### Human Dimensions of Climate Variability

The last four foci (above) relate to the human dimensions of climate variability in the PNW. Human activities in fact provide part of the context into which climate variability is introduced. The other part of the context consists of the natural ecosystems and natural resources which constitute the objects of use. In the first instance, therefore, we are concerned to describe the social organization of the various user communities, their relative capabilities, and how they interact with each other.

Perhaps the central components of the social context relate to institutional arrangements for managing patterns of use. Institutional arrangements include the legal frameworks underlying the resource use, defining ownership and use rights, defining authority relationships, and the right to manage. In addition, the degree of centralization/fragmentation of authority is critical to effective performance and relates to patterns of inter-organizational relations and the potential for coordinated responses across multiple uses. Such patterns include both conflict and cooperation and the capacity to mobilize organizational constituencies and resources.

Patterns of information flow and communication capabilities are important. To what extent, for instance, do patterns of social organization permit the user community to respond to and make use of climate forecasts. In part, the response will be determined by the value to the user of the information embedded in the forecast, but responses can also be facilitated or hindered by legal frameworks defining ownership/use rights and by highly fragmented managerial authority. Who has the authority to make resource decisions is therefore a question of particular importance.

We shall therefore seek to understand which players are most sensitive and vulnerable to climate variability in the PNW and assess how the new information should be conveyed to maximize its value. The Internet will be important in linking the climate diagnostic community dynamically with the user community.

Finally, response strategies will include a focus on adaptation to climate variability to reduce vulnerabilities. Consequently, we are concerned with thresholds of effects and rates of change as constraints to adaptation. The intent is to determine how to best use more accurate climate forecasts to reduce socioeconomic vulnerability and enhance economic planning.

### An Approach

Our analytical approach to the overall integrated assessment is based on the concept outlined in Table 1. We conceive of a four-dimensional space/time matrix in which we attempt to link climate dynamics with its impacts on biogeochemical systems and socioeconomic political systems. The relationship is reciprocal rather than a one-way flow.

Since we wish to determine the sensitivities and vulnerabilities of biogeochemical systems and socioeconomic/political systems in the Pacific Northwest to climate variability/change, we are concerned with threshold effects and rates of change, which could lead to catastrophic changes, e.g., fishery collapses. The final step in the causal chain will be to link our understanding of climate dynamics/impacts/threshold effects to socioeconomic and political response strategies. Up to this point, quantitative modeling will play a large part in our analysis. When we focus on response strategies, however, the analysis must be largely qualitative since the case study material available suggests the crucial importance of institutional arrangements as constraints on or facilitators of response strategies.

The questions which our analytical approach lead us to ask are:

- What is the natural climate variability in the PNW?

- How are the effects of natural climate variability related across dimensions in time and space (hydrology, forests, marine ecosystems, and coastal activities)?

- What are the sensitivities and vulnerabilities of the various social and ecological dimensions to global climate change at rates of 0.2-0.35 deg C per decade (i.e., 1-2 deg C by 2050) (IPCC/95)?

- What are the impacts of climate variability/change on biogeochemical systems and on social systems? Are there feedback loops which connect BGS and SS?

- Are there thresholds? If so, what?

- What makes the human systems associated with the Columbia Watershed vulnerable to climate variability? How can improved climate forecasting capabilities be used to reduce vulnerability and enhance economic planning by users?

- What are probable mitigation/adaptation response strategies and what changes/innovations in institutional design are required to facilitate implementation?

- Do scientists know enough about the climate system to provide accurate predictions of climate variability for the PNW at seasonal to interannual leadtimes?

(Dr. Miles is Virginia and Prentice Bloedel Professor of Marine Studies and Public Affairs and Senior Fellow at the Joint Institute for the Study of Atmosphere and Oceans (JISAO) of the University of Washington.)

### References

Battisti, D. S. and E. S. Sarachik. 1995. Understanding and Predicting ENSO, Reviews of Geophysics, Supplement, July, pp. 1367-1376. (U.S. National Report to International Union of Geodesy and Geophysics, 1991-1994).

Broecker, W. S. 1987. Unpleasant Surprises in the Greenhouse?, Nature, Vol. 328 (9 July), pp. 123-126.

Dowlatabadi, H., and M. G. Morgan. 1993. Integrated Assessment of Climate Change, Science, Vol. 259 (26 March), pp. 1813 & 1932.

Graham, N. E. 1994. Decadal-scale Climate Variability in the Tropical and North Pacific during the 1970s and 1980s: Observations and Model Results, Climate Dynamics, Vol. 10, pp. 135-162.

Intergovernmental Panel on Climate Change (IPCC). 1990. Climate Change: The Scientific Assessment, Report of Working Group I (J. T. Houghton, G. J. Jenkins, and J. J. Ephraunis, eds.), (Cambridge: Cambridge University Press).

IPCC. 1992. IPCC Supplement: Scientific Assessment of Climate Change, (Geneva: WMO/UNEP).

IPCC. 1994. Radioactive Forcing of Climate Change: The 1994 Report of the Scientific Assessment Working Group of IPCC, Summary for Policy Makers, (Geneva: WMO/UNEP).

Sarachik, E. S. 1995. Seasonal-to-Interannual Variability and the USGCRP, unpub. MS.

Trenberth, K.E., and J.W. Hussell. 1994. Decadal Atmosphere-Ocean Variations in the Pacific, Climate Diagnostics, Vol. 9, pp. 303-319.

U.S. GLOBEC. 1994. Eastern Boundary Current Program: A Science Plan for the California Current, Report Number 11, August.