Climatic Change

Comparing statistical estimates for the long-run temperature effect of doubled CO2 with those generated by climate models begs the question, is the long-run temperature effect of doubled CO2 that is estimated from the instrumental temperature record using statistical techniques consistent with the transient climate response, the equilibrium climate sensitivity, or the effective climate sensitivity. Here, we attempt to answer the question, what do statistical analyses of the observational record measure, by using these same statistical techniques to estimate the temperature effect of a doubling in the atmospheric concentration of carbon dioxide from seventeen simulations run for the Coupled Model Intercomparison Project 2 (CMIP2). The results indicate that the temperature effect estimated by the statistical methodology is consistent with the transient climate response and that this consistency is relatively unaffected by sample size or the increase in radiative forcing in the sample.

Vulnerability to climate change was evaluated for three different time periods: 1990, 2000, and 2010. Our objective was to discuss the scope of a multi-temporal assessment of vulnerability. The method used 55 indicators—with emphasis on the agricultural sector in Mexico—of which 27 were updated for the year 2010 and 33 were retrospectively estimated for the year 1990. The results show that in the 20-year study period, the exposure of the municipalities (and inhabitants) has increased, and sensitivity and adaptive capacity have decreased. The number of municipalities vulnerable to climate change declined over the 20-year period. We found that calculating vulnerability by adding exposure and sensitivity and subtracting adaptive capacity (E + S − AC) can lead to unintentional underestimation of total vulnerability. When rating vulnerability, care must be taken in what is reported: the results differ for the number of inhabitants versus the number of municipalities. Our previous published vulnerability evaluation was for the year 2000, so we wanted to evaluate the sensitivity of some variables and the vulnerability formula itself we used in that moment. It is possible to evaluate the vulnerability multi-temporally, which allows to evaluate the sensibility and calibration of the variables and indicators used and the reconsideration of their application.

Wyoming provides more fossil fuels to the remainder of the United States than any other state or country, and its citizens remain skeptical of anthropogenic influences on their climate. However, much of the state including Yellowstone National Park and the headwaters of several major river systems, may have already been affected by rising temperatures. This paper examines the historic climate record from Wyoming in the context of ∼14,000-year temperature reconstructions based on fossil pollen data. The analysis shows that 24 of 30 U.S. Historical Climatology Network records from the state show an increase in the frequency of unusually warm years since 1978. Statewide temperatures have included 15 years (50%) from 1978 to 2007 that were greater than 1σ above the mean annual temperature for 1895–1978. The frequent warm years coincide with a reduction in the frequency of extremely low (<−20°C) January temperatures, and are not well explained by factors such as solar irradiance and the Pacific Decadal Oscillation. Linear regressions require inclusion of atmospheric greenhouse gas concentrations to explain the multi-decadal temperature trends. The observed warming is large in Yellowstone National Park where 21 years (70%) from 1978 to 2007 were greater than 1σ above the 1895–1978 mean; the deviation from the mean (>1°C) is greater than any time in the past 6,000 years. Recent temperatures have become as high as those experienced from 11,000 to 6,000 years ago when summer insolation was >6% higher than today and when regional ecosystems experienced frequent severe disturbances.

The Kyoto Protocol allows Annex I countries to use afforestation (theconversion of non-forest landto forest) to meet emissions reduction targets. We present a new method forestimating the cost of CO2mitigation through afforestation based on econometric models of land use. Landuse models are developed from dataon observed land allocation decisions and quantify the relationship betweenthe share of land in forest and the netreturns to forestry, among other land use determinants. The econometricapproach measures the actual responsesby landowners to observed changes in net returns, in contrast to earlierstudies in which landowner responses aredictated by the researcher. Models are estimated for Maine, South Carolina,and Wisconsin. The estimated modelsare used to simulate subsidies for afforestation, which imply increases inforest area and net reductions inatmospheric CO2 concentrations. Average cost measures – totalsubsidies divided by total carbon sequestered –are derived for afforestation programs with and without timber harvesting. Theuse of econometric land use modelsin integrated assessments of climate change is explored. We model the effectson land use patterns and the costsof CO2 mitigation of changes in the net returns to agricultureinduced by climate change.

Since Allen (Nature 421(6926):891–892, 2003)’s seminal article, the community of extreme event attribution (EEA) has grown to maturity. Several approaches have been developed: the main ones are the “risk-based approach” — estimating how the probability of event occurrence correlates with climate change — and the “storyline approach” — evaluating the influence of climate change on thermodynamic processes leading to the event. In this article, we map the ways to frame attribution used in a collection of 105 case studies from five BAMS (Bulletin of American Meteorological Society) special issues on extreme events. In order to do so, we propose to define EEA, based on two corpora of interviews conducted with researchers working in the field, as follows: EEA is the ensemble of scientific ways to interpret the question “was this event influenced by climate change?” and answer it. In order to break down the subtleties of EEA, we decompose this initial question into three main problems a researcher has to deal with when framing an EEA case study. First, one needs to define the event of interest. Then, one has to propose a way to link the extreme event with climate change, and the subsequent level of conditioning to parameters of interest. Finally, one has to determine how to represent climate change. We provide a complete classification of BAMS case studies according to those three problems.

Glaciers in the Cordillera Blanca, Peru, are undergoing rapid retreat, in large part due to climate change. These changes are significantly altering water availability in the region and pose critical risks to local populations that are highly dependent on these resources for livelihoods. We examine these issues through an interdisciplinary and linked evaluation of hydrological change and livelihood vulnerability in the Yanamarey watershed. Physical observations of the Yanamarey glacier show acceleration in frontal retreat at a rate of 8 m decade − 1 since 1970, accompanied by total volume loss on the order of 0.022 km3. Hydrological and hydrochemical analyses document a possible transformation of stream flow over the past decade as the seasonal storage capacity of the glacier has degraded. Recent stream discharge measurements from the proglacial lake below the glacier are more coincident with the highly variable seasonal precipitation than they were during the 1998–1999 hydrological year. Local household perceptions of glacier recession and seasonal hydrological variability agree with this trend, which is increasing human vulnerability in the watershed. Household case-study survey results demonstrate that shifting water resources, increasing weather extremes and climate-related threats to tourism are all new vectors of vulnerability for household livelihoods.

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