John B. Kim

Selecting climate change scenarios using impact‐relevant sensitivities

Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide plausible results for future climate in the region of interest. We demonstrate an approach to select a subset of GCMs that incorporates both concepts and provides insights into the range of climate impacts. To represent how an ecosystem process responds to projected future changes, we methodically sample, using a simple sensitivity analysis, how an ecosystem variable responds locally to projected regional temperature and precipitation changes. We illustrate our approach in the Pacific Northwest, focusing on (a) changes in streamflow magnitudes in critical seasons for water management and (b) changes in annual vegetation carbon.

Global climate change impacts on forests and markets

This paper develops an economic analysis of climate change impacts in the global forest sector. It illustrates how potential future climate change impacts can be integrated into a dynamic forestry economics model using data from a global dynamic vegetation model, the MC2 model. The results suggest that climate change will cause forest outputs (such as timber) to increase by approximately 30% over the century. Aboveground forest carbon storage also is projected to increase, by approximately 26 Pg C by 2115, as a result of climate change, potentially providing an offset to emissions from other sectors. The effects of climate mitigation policies in the energy sector are then examined. When climate mitigation in the energy sector reduces warming, we project a smaller increase in forest outputs over the timeframe of the analysis, and we project a reduction in the sink capacity of forests of around 12 Pg C by 2115.

Inter-comparison of multiple statistically downscaled climate datasets for the Pacific Northwest, USA

Statistically downscaled climate data have been widely used to explore possible impacts of climate change in various fields of study. Although many studies have focused on characterizing differences in the downscaling methods, few studies have evaluated actual downscaled datasets being distributed publicly. Spatially focusing on the Pacific Northwest, we compare five statistically downscaled climate datasets distributed publicly in the US: ClimateNA, NASA NEX-DCP30, MACAv2-METDATA, MACAv2-LIVNEH and WorldClim. We compare the downscaled projections of climate change, and the associated observational data used as training data for downscaling. We map and quantify the variability among the datasets and characterize the spatio-temporal patterns of agreement and disagreement among the datasets. Pair-wise comparisons of datasets identify the coast and high-elevation areas as areas of disagreement for temperature. For precipitation, high-elevation areas, rainshadows and the dry, eastern portion of the study area have high dissimilarity among the datasets. By spatially aggregating the variability measures into watersheds, we develop guidance for selecting datasets within the Pacific Northwest climate change impact studies.

Climate Change Trends for Chaparral

Chaparral vegetation is a dominant and unique feature of California’s Mediterranean-type climate. The evergreen shrubs that characterize chaparral are well adapted to long, hot, dry summers and extreme fluctuations in inter-annual precipitation. Despite the ability of chaparral species to tolerate climatic extremes, the integrity of the chaparral ecosystem is currently being challenged by rising temperatures, increased variability in precipitation, and longer and more persistent droughts. Climate scenarios for California project continued warming through the century leading to increased physiological stress, canopy thinning, and mortality of chaparral vegetation across portions of the state. In some instances, however, chaparral vegetation may expand into forested landscapes. Climate change forecasts suggest enhanced fire activity, including an extended fire season and more frequent large fires. In this already stressed system, non-climate stressors, like increased fire frequencies, can lead to decreased shrub biomass, loss of species diversity, and conversion to other vegetation types. Chaparral in southern California is already trending toward conversion to dominance by non-native annual grasses, and climate projections suggest that this trend will continue in the future. In this chapter, we evaluate historical and projected climate trends in California and explain how they might directly and indirectly affect the integrity and persistence of chaparral on the landscape. We show that the interaction of climate and non-climate stressors can drive landscape level conversion of shrublands to non-native annual grasses leading to the loss of social and ecological benefits provided by the ecosystem. We provide a detailed review of projected changes in carbon storage for one of the (under-valued) ecosystem services provided by chaparral. We conclude by highlighting key management lessons from our review, and point to a few high priority information gaps that must be filled by future research.

Climate-Smart Approaches to Managing Forests

The climate of Pacific Northwest moist forests is characterized by abundant rainfall (1644 mm [65 in] annually) and mild temperatures throughout the year, averaging 9°C (48°F). Most precipitation falls in winter on the two major mountains ranges, the Coast and Cascade Ranges. Global warming is bringing distinct changes to the climate of these forests. Emissions of heat-trapping gases by human activities since industrialization have sharply increased global average temperatures and altered global precipitation patterns in the last 50 years. In the Northwest, the annual average temperature has risen 0.7°C (1.3°F) in the last century. The long-term trend is unclear for precipitation, but spring precipitation has increased in the last century (Abatzoglou et al. 2014), and year-to-year variability has increased since 1970 (Dalton et al. 2013). Under a business-as-usual scenario, the average annual temperature of the Northwest is projected to increase by 6°C (~11°F) by the end of this century compared with the 1950–2005 mean. For precipitation, enhanced seasonal cycles are projected, with a small change (−5% to +14%) in the annual mean precipitation by midcentury (2041–2070) (Dalton et al. 2013). The pace of climate change is projected to be rapid: the average annual temperatures of Washington and Oregon are predicted to depart from historical ranges within the next 3 to 5 decades (plate 14).