Weather and Climate Context

Introduction

The United States experiences a wide variety of climate conditions. Moving across from west to east, the climates range from the semi-arid and arid climates of the Southwest to the continental climates of the Great Plains and the moister conditions of the eastern United States. North to south, the climates range from the Arctic climate of northern Alaska to the extensive forests of the Pacific Northwest to the tropical climates in Hawaii, the Pacific Islands, and the Caribbean. Although U.S. society and industry have largely adapted to the mean and variable climate conditions of their region, this has not been without some effort and cost. In addition, various extreme events each year still cause significant impacts across the nation. Weather events causing the most death, injury, and damage include hurricanes (or more generally tropical cyclones) and associated storm surges, lightning, tornadoes and other windstorms, hailstorms, severe winter storms, deep snow and avalanches, and extreme summer temperatures. Heat waves, floods, landslides, droughts, fires, land subsidence, coastal inundation and erosion, and even dam failures also can result when extremes persist over time.

To provide an objective and quantitative basis for an assessment of the potential consequences of climate change, the U.S. National Assessment was organized around the use of climate model scenarios that specified changes in the climate that might be experienced across the United States (NAST 2001). Rather than simply considering the potential influences of arbitrary changes in temperature, precipitation, and other variables, the use of climate model scenarios ensured that the set of climate conditions considered was internally consistent and physically plausible. For the National Assessment, the climate scenarios were primarily drawn from results available from the climate models developed and used by the United Kingdom's Hadley Centre and the Canadian Centre for Climate Modeling and Analysis. In addition, some analyses also drew on results from model simulations carried out at U.S. centers, including the National Center for Atmospheric Research, the National Oceanic and Atmospheric Administration's (NOAA's) Geophysical Fluid Dynamics Laboratory, and the National Aeronautics and Space Administration's (NASA's) Goddard Institute for Space Studies.

Use of these model results is not meant to imply that they provide accurate predictions of the specific changes in climate that will occur over the next 100 years. Rather, the models are considered to provide plausible projections of potential changes for the 21st century (see note). For some aspects of climate, all models, as well as other lines of evidence, are in agreement on the types of changes to be expected. For example, compared to changes during the 20th century, all climate model results suggest that warming during the 21st century across the country is very likely to be greater, that sea level and the heat index are going to rise more, and that precipitation is more likely to come in the heavier categories experienced in each region. Also, although there is not yet close agreement about how regional changes in climate can be expected to differ from larger-scale changes, the model simulations indicate some agreement in projections of the general seasonal and subcontinental patterns of the changes (IPCC 2001d).

This consistency has lent some confidence to these results. For some aspects of climate, however, the model results differ. For example, some models, including the Canadian model, project more extensive and frequent drought in the United States, while others, including the Hadley model, do not. As a result, the Canadian model suggests a hotter and drier Southeast during the 21st century, while the Hadley model suggests warmer and wetter conditions. Where such differences arise, the primary model scenarios provide two plausible, but different alternatives. Such differences proved helpful in exploring the particular sensitivities of various activities to uncertainties in the model results.