Unstable climate−growth relations for white spruce in southwest Yukon, Canada

We used dendroclimatology to quantify inter-annual to multi-decadal climatic variation effects on white spruce radial growth in southwest Yukon, Canada. Local climate is dry and cold, such that tree growth was primarily moisture- rather than temperature-limited, although the mechanisms varied temporally. During the 20th century, significant increases in precipitation countered warming temperatures, so that heat?moisture indices have not changed significantly. Directional climatic change, superimposed on variation due to the Pacific Decadal Oscillation (PDO), resulted in unstable climate?growth relations. Prior to 1977, ring widths were positively correlated with previous growing season precipitation and warm temperatures had a negative impact, exacerbating moisture limitations in dry years especially during the cool, dry negative PDO phase (1946?1976). After 1977, correlations with previous growing season precipitation became negative and correlations with previous fall and winter precipitation and current year July and August temperatures became positive, although not statistically significant. These changes suggest precipitation and temperature increases over recent decades benefitted white spruce growth. Climate projections for this region include further temperature and precipitation increases, which may promote white spruce growth depending on the seasonality and interactions between temperature and precipitation. This study demonstrated the complexity of potential responses of white spruce to climate variation and change.     

Climate Variability and Land-use Change in Danangou Watershed, China—Examples of Small-Scale Farmers' Adaptation

With global concern on climate change impacts, developing countries are given special attention due their susceptibility. In this paper, change and variability in climate, land use and farmers' perception, adaptation and response to change are examined in Danangou watershed in the Chinese Loess Plateau. The first focus is to look at how climate data recorded at meteorological stations recently have evolved, and how farmers perceived these changes. Further, we want to see how the farmers respond and adapt to climate variability and what the resulting impact on land use is. Finally, other factors causing change in land use are considered. Local precipitation and temperature instrumental data and interview data from farmers were used. The instrumental data shows that the climate is getting warmer and drier, the latter despite large interannual variability. The trend is seen on the local and regional level. Farmers' perception of climatic variability corresponds well with the data record. During the last 20 years, the farmers have become less dependent on agriculture by adopting a more diversified livelihood. This adaptation makes them less vulnerable to climate variability. It was found that government policies and reforms had a stronger influence on land use than climate variability. Small-scale farmers should therefore be considered as adaptive to changing situations, planned and non-consciously planned.     

Adaptation in Canadian Agriculture to Climatic Variability and Change

The effects of climatic variability and change on Canadian agriculture have become an important research field since the early 1980s. In this paper, we seek to synthesize this research, focusing on agricultural adaptation, a purposeful proactive or reactive response to changes associated with climate, and influenced by many factors. A distinctive feature of methods used in research on adaptation in Canadian agriculture is the focus on the important role of human agency. Many individual farmers perceive they are well adapted to climate, because of their extensive 'technological' tool-kit, giving them confidence in dealing with climatic change. In many regions, little concern is expressed over climatic change, except where there are particular types of climatic vulnerability. Farmers respond to biophysical factors, including climate, as they interact with a complex of human factors. Several of these, notably institutional and political ones, have tended to diminish the farm-level risks stemming from climatic variability and change, but may well increase the long term vulnerability of Canadian agriculture. Notwithstanding the technological and management adaptation measures available to producers, Canadian agriculture remains vulnerable to climatic variability and to climate change.     

A Ricardian analysis of US and Canadian farmland

In this analysis, we undertake a comparative Ricardian analysis of agriculture between Canada and the United States. We find that the climate responses of the two countries are similar but statistically different despite the fact that the two countries are neighbors. Comparing the marginal impacts of climate change, we find that Canadian agriculture is unaffected by warmer temperatures but would benefit from more precipitation. US farms are much more sensitive to higher temperatures and benefit relatively less from increased precipitation. These marginal results were anticipated given that Canadian farms are generally cooler and drier than American farms.     

Evaluating historical simulations of CMIP5 GCMs for key climatic variables in Zhejiang Province,China

Assessing the regional impact of climate change on agriculture, hydrology, and forests is vital for sustainable management. Trustworthy projections of climate change are needed to support these assessments. In this paper, 18 global climate models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to simulate regional climate change in Zhejiang Province, Southeast China. Simple graphical approaches and three indices are used to evaluate the performance of six key climatic variables during simulations from 1971 to 2000. These variables include maximum and minimum air temperature, precipitation, wind speed, solar radiation, and relative humidity. These variables are of great importance to researchers and decision makers in climate change impact studies and developing adaptation strategies. This study found that most GCMs failed to reproduce the observed spatial patterns, due to insufficient resolution. However, the seasonal variations of the six variables are simulated well by most GCMs. Maximum and minimum air temperatures are simulated well on monthly, seasonal, and yearly scales. Solar radiation is reasonably simulated on monthly, seasonal, and yearly scales. Compared to air temperature and solar radiation, it was found that precipitation, wind speed, and relative humidity can only be simulated well at seasonal and yearly scales. Wind speed was the variable with the poorest simulation results across all GCMs.     

An essay on the impact of climate change on US agriculture: weather fluctuations, climatic shifts, and adaptation strategies

The impact of climate change on US agriculture has been debated for more than two decades, but the estimates ranged from no damage at the lower end to 80 % losses of grain yields at the higher end. This essay aims to help understand such divergent predictions by clarifying the concepts of weather and climate. First, the widely-read panel fixed effects models capture only the impacts of weather fluctuations but not of climate normals. Random weather fluctuations and climatic shifts are two different meteorological events and they have distinct implications on farming decisions. The former is perceived as random while the latter is perceived as non-random by the farmers. Using the historical corn yield data in the US, I explain the differences between the impact of random weather and that of climate change. Second, adaptation strategies to climatic changes and increased climate risks cannot be accounted for by the panel fixed effects models. Using the farm household data collected in sub-Saharan Africa and Latin America, I discuss quantitative significance of modeling adaptation strategies in the estimates of climate damage. Distinction between random weather fluctuations and climatic shifts is critical in modeling farming decisions, as they are fundamental to climate science, but is poorly understood by the impact researchers.     

Groundwater depletion limits the scope for adaptation to increased rainfall variability in India

Recent studies have found that increasing intra-seasonal precipitation variability will lead to substantial reductions in rice production in India by 2050, independently of the effect of rising temperatures. However, these projections do not account for the possibility of adaptations, of which the expansion of irrigation is the primary candidate. Using historical data on irrigation, rice yields, and precipitation, I show that irrigated locations experience much lower damages from increasing precipitation variability, suggesting that the expansion of irrigation could protect Indian agriculture from this future threat. However, accounting for physical water availability shows that under current irrigation practices, sustainable use of irrigation water can mitigate less than a tenth of the climate change impact. Moreover, if India continues to deplete its groundwater resources, the impacts of increased variability are likely to increase by half.     

Climate Change, Agriculture, and Water Quality in the Chesapeake Bay Region

Research on climate change and agriculture has largely focused on production, food prices, and producer incomes. However, societal interest in agriculture is much broader than these issues. The objective of this paper is to analyze the potential impacts of climate change on an important negative externality from agriculture, water quality. We construct a simulation model of maize production in twelve watersheds within the U.S. Chesapeake Bay Region that has economic and watershed components linking climate to productivity, production decisions by maize farmers, and nitrogen loadings delivered to the Chesapeake Bay. Maize is an important crop to study because of its importance to the region's agriculture and because it is a major source of nutrient pollution. The model is run under alternative scenarios regarding the future climate, future baseline (without any climate change), whether farmers respond to climate change, whether there are carbon dioxide (CO₂) enrichment effects on maize production, and whether agricultural prices facing the region change due to climate change impacts on global agricultural commodity markets. The simulation results differ from one scenario to another on the magnitude and direction of change in nitrogen deliveries to the Chesapeake Bay. The results are highly sensitive to the choice of future baseline scenario and to whether there are CO₂ enrichment effects. The results are also highly sensitive to assumptions about the impact of climate change on commodity prices facing farmers in the Chesapeake Bay region. The results indicate that economic responses by farmers to climate change definitely matter. Assuming that farmers do not respond to changes in temperature, precipitation, and atmosphericCO₂ levels could lead to mistaken conclusions about the magnitude and direction of environmental impacts.     

Present-day and future precipitation in the Baltic Sea region as simulated in a suite of regional climate models

Here we investigate simulated changes in the precipitation climate over the Baltic Sea and surrounding land areas for the period 2071–2100 as compared to 1961–1990. We analyze precipitation in 10 regional climate models taking part in the European PRUDENCE project. Forced by the same global driving climate model, the mean of the regional climate model simulations captures the observed climatological precipitation over the Baltic Sea runoff land area to within 15% in each month, while single regional models have errors up to 25%. In the future climate, the precipitation is projected to increase in the Baltic Sea area, especially during winter. During summer increased precipitation in the north is contrasted with a decrease in the south of this region. Over the Baltic Sea itself the future change in the seasonal cycle of precipitation is markedly different in the regional climate model simulations. We show that the sea surface temperatures have a profound impact on the simulated hydrological cycle over the Baltic Sea. The driving global climate model used in the common experiment projects a very strong regional increase in summertime sea surface temperature, leading to a significant increase in precipitation. In addition to the common experiment some regional models have been forced by either a different set of Baltic Sea surface temperatures, lateral boundary conditions from another global climate model, a different emission scenario, or different initial conditions. We make use of the large number of experiments in the PRUDENCE project, providing an ensemble consisting of more than 25 realizations of climate change, to illustrate sources of uncertainties in climate change projections.     

Indicators of Climate Change for the Russian Federation

Observed climate changes over the Russian Federation (RF) territory are considered. Several indicators based on monthly mean temperature and precipitation station data are used to quantify regional climate changes. Some of these are the components of two aggregated indices of climate change, suggested by Karl et al. (1996): the Climate Extremes Index (CEI) and the Greenhouse Climate Response Index (GCRI). For the RF territory as a whole, and for its western part, the "Russian Permafrost Free (RPF) territory" in particular, changes in surface air temperature are investigated, together with changes in precipitation and drought indices, and also the fraction of the Russian territory experiencing climatic anomalies below and/or above certain specified percentiles. Composite indices CEI-3 and GCRI-3 based on three parameters (air temperature, precipitation and drought indices) are examined, as well as the Climate Anomaly Index (CAI), known in Russia as Bagrov's coefficient of "anomality".It is shown, that over the area of the RPF as a whole, air temperature and the occurrence of drought has increased somewhat during the 20th century, while precipitation has decreased; these changes were non-uniform in space. The linear trend accounts for only a small fraction of the total variability, but the role of climate variations on decadal scales seems more substantial. The CEI, determined as the percentage of the area experiencing extreme anomalies (with a 10% or less frequency of occurrence) of either sign, increased for mean annual temperature, decreased for total precipitation and increased slightly for the occurrence of drought conditions; the aggregated index based on all three of these quantities increased slightly. There was also an increase in the GCRI-3 index, which is indicative of an agreement between the observed climate changes and the changes owing to the greenhouse effect as predicted by climatic models.The observed climate changes are too small to enable us confidently to reject a hypothesis that they are a reflection of the natural variability of climatic parameters within the context of a stationary climate. However, there is no doubt about the reality and importance of the observed changes.     

Faster growth in warmer winters for large trees in a Mediterranean-climate ecosystem

Large trees (>76 cm breast-height diameter) are vital components of Sierra Nevada/Cascades mixed-conifer ecosystems because of their fire resistance, ability to sequester large amounts of carbon, and role as preferred habitat for sensitive species such as the California spotted owl. To investigate the likely performance of large trees in a rapidly changing climate, we analyzed growth rings of five conifer species against 20th century climate trends from local weather stations. Over the local station period of record, there were no temporal trends in precipitation, but maximum temperatures increased by 0.10 to 0.13 °C/decade (summer and autumn), and minimum temperatures increased by 0.11 to 0.19 °C/decade in all seasons. All species responded positively to precipitation, but more variation was explained by a significant positive response to minimum winter temperatures. High maximum summer temperature adversely affected growth of two species, and maximum spring temperatures in the year prior to ring formation were negatively associated with growth of one species. The strong coherent response to increasing minimum temperatures bodes well for growth of large trees in Sierra/Cascades region mixed conifer forest under continued climatic warming, but these trees will still be under threat by the increased fire intensity that is a indirect effect of warming.     

Enhanced spring convective barrier for monsoons in a warmer world?

Twenty-first century climate model projections show an amplification of the annual cycle in tropical precipitation with increased strength in both wet and dry seasons, but uncertainty is large and few studies have examined transition seasons. Here we analyze coupled climate model projections of global land monsoons and show a redistribution of precipitation from spring to summer in northern (North America, West Africa and Southeast Asia) and southern (South America, Southern Africa) regions. The annual cycle changes are global in scale. Two mechanisms, remote (based on tropospheric stability) and local (based on low level and surface moisture), are evaluated through the annual cycle. Increases in tropospheric stability persist from winter into spring and are reinforced by a reduction in surface moisture conditions, suggesting that in spring both remote and local mechanisms act to inhibit convection. This enhanced spring convective barrier leads to reduced early season rainfall; however, once sufficient increases in moisture (by transport) are achieved, decreases in tropospheric stability result in increased precipitation during the late rainy season. Further examination of this mechanism is needed in observations and models, as the projected changes would have substantial implications for agriculture, water management, and disaster preparedness.     

Indian agriculture and climate sensitivity

This study estimates the relationship between farm level net-revenue and climate variables in India using cross-sectional evidence. Using the observed reactions of farmers, the study seeks to understand how they have adapted to different climatic conditions across India. District level data is used for the analysis. The study also explores the influence of annual weather and crop prices on the climate response function. The estimated climate response function is used to assess the possible impacts of a ‘best-guess’ climate change scenario on Indian agriculture.     

Identifying climatic analogs for Wisconsin under 21st-century climate-change scenarios

There is a deep disconnect between scientific and public concern about climate change. One reason is that global climate change is a fairly abstract concept with little perceived relevance, so a key challenge is to translate climate-change projections into locally concrete examples of potential impacts. Here we use climate analog analyses as an alternative method for identifying and communicating climate-change impacts. Our analysis uses multiple downscaled general circulation models for the state of Wisconsin, at 0.1 decimal degree resolution, and identifies contemporary locations in North America that are the most similar to the projected future climates for Wisconsin. We assess the uncertainties inherent in climate-change projections among greenhouse gas emission scenarios, time windows (mid-21st century vs. late 21st-century) and different combinations of climate variables. For all future scenarios and simulations, contemporary climatic analogs within North America were found for Wisconsin’s future climate. Closest analogs are primarily 200–500 km to the south-southwest of their Wisconsin reference location. Temperature has the largest effect on choice of climatic analog, but precipitation is the greatest source of uncertainty. Under the higher-end emission scenarios, the contemporary climatic analogs for Wisconsin’s end-21st-century climates are almost entirely outside the state. Climate-analog analyses offer a place-based means of assessing climate impacts that is complementary to the species-based approaches of species distributional models, and carries no assumptions about the characterization and conservatism of species niches. The analog method is simple and flexible, and can be readily extended to other regions and other environmental variables.     

Assessing the robustness of projected precipitation changes over central Africa on the basis of a multitude of global and regional climate projections

It is well accepted within the scientific community that a large ensemble of different projections is required to achieve robust climate change information for a specific region. For this purpose we have compiled a state-of-the-art multi-model multi-scenario ensemble of global and regional precipitation projections. This ensemble combines several global projections from the CMIP3 and CMIP5 databases, along with some recently downscaled regional CORDEX-Africa projections. Altogether daily precipitation data from 77 different climate change projections is analysed; separated into 31 projections for a high and 46 for a low emission scenario. We find a robust indication that, independent of the underlying emission scenario, annual total precipitation amounts over the central African region are not likely to change severely in the future. However some robust changes in precipitation characteristics, like the intensification of heavy rainfall events as well as an increase in the number of dry spells during the rainy season are projected for the future. Further analysis shows that over some regions the results of the climate change assessment clearly depend on the size of the analyzed ensemble. This indicates the need of a “large-enough” ensemble of independent climate projections to allow for a reliable climate change assessment.     

Water resources for agriculture in a changing climate: international case studies

This integrated study examines the implications of changes in crop water demand and water availability for the reliability of irrigation, taking into account changes in competing municipal and industrial demands, and explores the effectiveness of adaptation options in maintaining reliability. It reports on methods of linking climate change scenarios with hydrologic, agricultural, and planning models to study water availability for agriculture under changing climate conditions, to estimate changes in ecosystem services, and to evaluate adaptation strategies for the water resources and agriculture sectors. The models are applied to major agricultural regions in Argentina, Brazil, China, Hungary, Romania, and the US, using projections of climate change, agricultural production, population, technology, and GDP growth.For most of the relatively water-rich areas studied, there appears to be sufficient water for agriculture given the climate change scenarios tested. Northeastern China suffers from the greatest lack of water availability for agriculture and ecosystem services both in the present and in the climate change projections. Projected runoff in the Danube Basin does not change substantially, although climate change causes shifts in environmental stresses within the region. Northern Argentina's occasional problems in water supply for agriculture under the current climate may be exacerbated and may require investments to relieve future tributary stress. In Southeastern Brazil, future water supply for agriculture appears to be plentiful. Water supply in most of the US Cornbelt is projected to increase in most climate change scenarios, but there is concern for tractability in the spring and water-logging in the summer.Adaptation tests imply that only the Brazil case study area can readily accommodate an expansion of irrigated land under climate change, while the other three areas would suffer decreases in system reliability if irrigation areas were to be expanded. Cultivars are available for agricultural adaptation to the projected changes, but their demand for water may be higher than currently adapted varieties. Thus, even in these relatively water-rich areas, changes in water demand due to climate change effects on agriculture and increased demand from urban growth will require timely improvements in crop cultivars, irrigation and drainage technology, and water management.     

Framings and coverage of climate change in Swedish specialized farming magazines

Climate change is a fundamental challenge for which agriculture is sensitive and vulnerable. The Intergovernmental Panel on Climate Change has identified relevant information as key to enabling appropriate climate adaptation and mitigation action. Information specifically directed to farmers can be found, for example, in specialized farming magazines. While recent studies examine how national news media frame climate change, less—if any—studies have addressed climate framings and coverage in specialized media. Media framings are storylines that provide meaning by communicating how and why an issue should be seen as a problem, how it should be handled, and who is responsible for it. This paper analyses the framings and coverage of climate change in two Swedish specialized farming magazines from 2000 to 2009. It examines the extent of the climate change coverage, the content of the media items, and the dominant framings underlying their climate change coverage. The study identifies: increased coverage of climate change starting in 2007; frequent coverage of agriculture’s contribution to climate change, climate change impacts on agriculture, and consequences of climate politics for agriculture; and four prominent frames: conflict, scientific certainty, economic burden, and action. The paper concludes that climate change communicators addressing farmers and agricultural extension officers should pay attention to how these frames may be interpreted by different target audiences. Research is needed on how specialized media reports on climate-related issues and how science-based climate information is understood by different groups of farmers and which other factors influence farmers’ engagement in climate mitigation and adaptation.     

Agricultural adaptation to climatic variation

Assumptions underlying impact assessments of climatic change for agriculture are explored conceptually and empirically. Variability in climatic conditions, the relevance of human decision-making, and the role of non-climatic forces are reviewed and captured in a model of agricultural adaptation to climate. An empirical analysis of farmers' decisions in light of variations in climate and other forces is based on a survey of 120 farm operators in southwestern Ontario. Many farmers were affected by variable climatic conditions over a six-year-period, and some undertook strategic adaptations in their farm operations. Frequency of dry years was the key climatic stimulus to farming adaptations. However, only 20 percent of farmers were sufficiently influenced by climatic conditions to respond with conscious changes in their farm operations.