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.     

Socio-climatic hotspots in Brazil

Brazil suffers yearly from extreme weather and climate events, which can be exacerbated in a warmer climate. Although several studies have analyzed the projections of climate change in Brazil, little attention has been paid to defining the locations that can be most affected, and consequently have a more vulnerable population, in a spatially-explicit form. This study presents a spatial analysis of summarized climate change data and a joint investigation combining these possible climate changes and social vulnerability indicators in Brazil. The Regional Climate Change Index (RCCI), which can synthesize a large number of climate model projections, is used for the climate analysis, and the Socio-Climatic Vulnerability Index (SCVI) is proposed to aggregate local population vulnerabilities to the climate change information. The RCCI results show climatic hotspots emerging in Brazil, covering the western portion of the Northeast (NE), northwestern Minas Gerais state and center-western (CW) and northern regions (N), except northeast Pará and Amapá states. The SCVI analysis reveals major socio-climatic hotspots in the NE and several localized hotspots in some of the major Brazilian metropolitan regions, namely Manaus, Belo Horizonte, Brasília, Salvador, Rio de Janeiro and S?o Paulo. The two novelties of this study are a spatially detailed analysis of the RCCI in Brazil and the development of an index that can summarize the large amount of climate model information available today with social vulnerability indicators. Both indices may be important tools for improving the dialogue between climate and social scientists and for communicating climate change to policymakers in a more synthetic and socially relevant form.     

Engagement,involvement and empowerment: Three realms of a coproduction framework for climate services

While knowledge coproduction between climate scientists and climate information users has become a common theme in the climate services discourse, the interface between climate service providers and users is an aspect of climate services projects that still calls for more attention. This is due in part to the dominance of the physical sciences in these projects, as well as the prevalence of an instrumental and narrow interpretation of coproduction. Following up on the World Meteorological Organisation’s Guidance on Good Practices for Climate Services User Engagement, and incorporating insights from the social and human sciences, we develop a coproduction framework for climate services to help establish a smooth and effective interface between scientists and stakeholders. This framework is intended for research and innovation projects developing climate knowledge and services. The coproduction framework comprises three realms: (i) engagement using various communication channels; (ii) involvement through interviews, workshops and webinars; and (iii) empowerment of stakeholders and scientists through focused relationships. This incremental participatory process involves stakeholders in increasingly profound ways: from a broad stakeholder group identified through awareness-raising campaigns, on to potential users with whom we exchange knowledge, and then to a set of “champion users” who co-develop the service and pioneer its use in decision-making processes. This paper illustrates the application of the coproduction framework in PRIMAVERA, an EU H2020-funded project for designing, running and testing new high-resolution global climate models and evaluating their outputs. While PRIMAVERA provided ground breaking scientific findings that could potentially benefit various stakeholders and support climate risk assessment activities, these results are highly specialised and their added value has yet to be assessed. Accordingly, the user engagement component of the project faced the challenging task of both motivating stakeholders’ participation in the project and motivating future users of potential services based on PRIMAVERA data. The trial of the framework in PRIMAVERA provided key lessons for enhancing coproduction in research and innovation projects. We demonstrate how the role of scientists gradually shifted in this coproduction cycle from masters of knowledge(Roux et al., 2017) to co-learners, and how the involvement of the project’s interdisciplinary team and their interaction with stakeholders served to move the project towards transdisciplinary knowledge production.     

Towards a dedicated impact portal to bridge the gap between the impact and climate communities : Lessons from use cases

Future climate evolution is of primary importance for the societal, economical, political orientations and decision-making. It explains the increasing use of climate projections as input for quantitative impact studies, assessing vulnerability and defining adaptation strategies in different sectors. Here we analyse 17 national and representative use cases so as to identify the diversity of the demand for climate information depending on user profiles as well as the best practices, methods and tools that are needed to answer the different requests. A particular emphasis is put on the workflow that allows to translate climate data into suitable impact data, the way to deal with the different sources of uncertainty and to provide a suited product to users. We identified three complementary tools to close the gap between climate scientists and user needs: an efficient interface between users and providers; an optimized methodology to handle user requests and a portal to facilitate access to data and elaborated products. We detail in the paper how these three tools can limit the intervention of experts, educate users, and lead to the production of useful information. This work provides the basis on which the ENES (European Network for Earth System Modelling) Portal Interface for the Climate Impact Communities is built.     

Understanding and enhancing climate information use in water management

This paper expands our understanding of water manager's climate information (CI) use and of the effectiveness of interactive research efforts in improving use by quantitatively measuring usability both within and outside the interactive research model. Using a mixed method approach (i.e., interviews and surveys), data was collected across five states and hundreds of water managers to understand the production of CI by scientists at two Regional Integrated Sciences and Assessments (RISAs) employing an interactive approach and the use of that information by water managers in the corresponding RISA regions. This study finds that RISAs are effective in three important ways: first, in co-producing usable information and achieving a high rate of information use among RISA clients; second, in overcoming barriers to information use arising from negative perceptions about the usability and reliability of CI; and, finally, in fostering innovation. RISA information use is contingent on sustained scientist-client interaction and is enabled by users' willingness and capacity making RISAs most effective in reaching the largest, most capable users. These users and those who use CI from other sources do so as a strategy to manage risk. This research suggests areas for enhancing RISA CI uptake: structuring RISAs as consortia, cultivating relationships with knowledge brokers and capitalizing on existing knowledge networks, and increasing public education and outreach. Beyond the interactive research models, findings suggest CI uptake may be enhanced by building capabilities for long-term water planning at water systems and bolstering public science citizenship and climate literacy.     

Creating usable science: Opportunities and constraints for climate knowledge use and their implications for science policy

In the past several decades, decision makers in the United States have increasingly called upon publicly funded science to provide “usable” information for policy making, whether in the case of acid rain, famine prevention or climate change policy. As demands for usability become more prevalent for publicly accountable scientific programs, there is a need to better understand opportunities and constraints to science use in order to inform policy design and implementation. Motivated by recent critique of the decision support function of the US Global Change Research Program, this paper seeks to address this issue by specifically examining the production and use of climate science. It reviews empirical evidence from the rich scholarship focused on climate science use, particularly seasonal climate forecasts, to identify factors that constrain or foster usability. It finds, first, that climate science usability is a function both of the context of potential use and of the process of scientific knowledge production itself. Second, nearly every case of successful use of climate knowledge involved some kind of iteration between knowledge producers and users. The paper argues that, rather than an automatic outcome of the call for the production of usable science, iterativity is the result of the action of specific actors and organizations who ‘own’ the task of building the conditions and mechanisms fostering its creation. Several different types of institutional arrangements can accomplish this task, depending on the needs and resources available. While not all of the factors that enhance usability of science for decision making are within the realm of the scientific enterprise itself, many do offer opportunities for improvement. Science policy mechanisms such as the level of flexibility afforded to research projects and the metrics used to evaluate the outcomes of research investment can be critical to providing the necessary foundation for iterativity and production of usable science to occur.     

Assessing the ‘usability’ of climate change research for decision-making: A case study of the Canadian International Polar Year

The creation of ‘usable science’ is widely promoted by many environmental change focused research programs. Few studies however, have examined the relationship between research conducted as part of such programs and the decision-making outcomes that the work is supposed to advance, and is constrained by limited methodological development on how to empirically assess the ‘usability’ of science. Herein, this paper develops a conceptual model and assessment rubric to quantitatively and systematically evaluate the usability of climate change research for informing decision-making. We focus on the process through which data is collected, analyzed and reported and examine the extent to which key principles of usable science are integrated into project design, using grant proposals as our data source. The approach is applied to analyze climate change research conducted as part of the International Polar Year in Canada, with 23 projects identified as having explicit goals to inform decision-making.While the creation of usable science was promoted by funded projects in the International Polar Year, this was not generally reflected in research design: fewer than half determined objectives with input of decision makers, decision context was not widely considered, and knowledge users were not widely reported to be engaged in assessing the quality of data or in resolving conflict in evidence. The importance of science communication was widely emphasized, although only 8/23 projects discussed tailoring specific results for end user needs. Thus while International Polar Year research has made significant advances in understanding the human dimensions of Arctic climate change, key attributes necessary for determining success in linking science to decision-making (pertinence, quality, timeliness) were not captured by many projects. Integrating these attributes into research design from the outset is essential for creating usable science, and needs to be at the forefront of future research programs which aim to advance societal outcomes. The framework for assessing usability here, while developed and tested in an Arctic climate change context, has broader applicability in the general environmental change field.     

An ocean observation system for monitoring the affects of climate change on the ecology and sustainability of pelagic fisheries in the Pacific Ocean

Climate change presents an emerging challenge to the sustainable management of tuna fisheries, and robust information is essential to ensure future sustainability. Climate and harvest affect tuna stocks, populations of non-target, dependent species and the ecosystem. To provide relevant advice we need an improved understanding of oceanic ecosystems and better data to parameterise the models that forecast the impacts of climate change. Currently ocean-wide data collection in the Pacific Ocean is primarily restricted to oceanographic data. However, the fisheries observer programs that operate in the region offer an opportunity to collect the additional information on the mid and upper trophic levels of the ecosystem that is necessary to complement this physical data, including time-series of distribution, abundance, size, composition and biological information on target and non-target species and mid trophic level organisms. These observer programs are in their infancy, with limited temporal and spatial distribution but recent international and national policy decisions have been made to expand their coverage. We identify a number of actions to initiate this monitoring including: consolidating collaborations to ensure the use of best quality data; developing consistency between sub-regional observer programmes to ensure that they meet the objectives of ecosystem monitoring; interrogating of existing time series to determine the most appropriate spatial template for monitoring; and exploring existing ecosystem models to identify suitable indicators of ecosystem status and change. The information obtained should improve capacity to develop fisheries management policies that are resilient and can be adapted to climate change.     

Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River,Cambodia

Cambodia is one of the most vulnerable countries to climate change impacts such as floods and droughts. Study of future climate change and drought conditions in the upper Siem Reap River catchment is vital because this river plays a crucial role in maintaining the Angkor Temple Complex and livelihood of the local population since 12th century. The resolution of climate data from Global Circulation Models (GCM) is too coarse to employ effectively at the watershed scale, and therefore downscaling of the dataset is required. Artificial neural network (ANN) and Statistical Downscaling Model (SDSM) models were applied in this study to downscale precipitation and temperatures from three Representative Concentration Pathways (RCP 2.6, RCP 4.5 and RCP 8.5 scenarios) from Global Climate Model data of the Canadian Earth System Model (CanESM2) on a daily and monthly basis. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were adopted to develop criteria for dry and wet conditions in the catchment. Trend detection of climate parameters and drought indices were assessed using the Mann-Kendall test. It was observed that the ANN and SDSM models performed well in downscaling monthly precipitation and temperature, as well as daily temperature, but not daily precipitation. Every scenario indicated that there would be significant warming and decreasing precipitation which contribute to mild drought. The results of this study provide valuable information for decision makers since climate change may potentially impact future water supply of the Angkor Temple Complex (a World Heritage Site).     

A weather-resolving index for assessing the impact of climate change on tourism related climate resources

This study develops and tests a Modified Climate Index for Tourism (MCIT) utilizing more than 50 years of hourly temperature, wind and significant weather data from contrasting climatic regions, Florida and Alaska. The index measures climate as a tourism resource by combining several tourism-related climate elements. It improves previous methods by incorporating variables that are more relevant to tourism activities, by addressing the overriding nature of some conditions, and by incorporating hourly observations rather than simple daily averages. The MCIT was tested using hourly weather observations from King Salmon, Alaska and Orlando, Florida. The results show that average temperature alone is not sufficient to represent tourism climate resources. For example, at both the Florida and Alaskan sites, showers and thunderstorms are more limiting factors than temperature during much of the year. When applied to past climate data, the proposed MCIT generates meaningful results that capture tourism-related climate variations and trends, including (a) the increasingly favorable tourism conditions in Alaska due to a lengthening of the warm season and (b) a decrease of ideal climatic conditions in central Florida due to the increased summer temperatures. Thus, the index has the potential to become a useful quantitative tool to be used in conjunction with climate models to predict the nature and magnitude of the impact of anticipated climate changes on tourism.     

A methodological framework for rapidly assessing the impacts of climate risk on national-level food security through a vulnerability index

This article describes an experimental Hunger and Climate Vulnerability Index showing the relative vulnerability of food insecure populations to climate risks at country level, as a tool for better understanding risks to food security presented by climate change. Data from socioeconomic and environmental indicators were analysed, and the most relevant indicators were aggregated using a composite index to compare differential vulnerabilities. The paper shows the high correlation between hunger and climate risk, especially for the regions of the world most affected by food insecurity. The analysis goes beyond the impact of climate on crop yields and provides a multidimensional analysis of vulnerability, while demonstrating the critical role that adaptive capacity has in determining vulnerability. The paper also presents a method for analysing food security vulnerability to climate risks that is replicable at different scales to provide a robust planning tool for policy makers. This approach can also be used to monitor vulnerability, evaluate potential effectiveness of programmes, and/or examine plausible impacts of climate change by introducing scenarios into the vulnerability model.     

The Uncertain Value of Perfect ENSO Phase Forecasts: Stochastic Agricultural Prices and Intra-Phase Climatic Variations

Climate and crop yield variability associated with El Niño—Southern Oscillation (ENSO) are now predictable within limits. This predictability suggests a potential to tailor agricultural management to mitigate impacts of adverse conditions and to take advantage of favorable conditions. However, improved climate predictions may benefit society only with parallel advances in our ability to use this knowledge. We show that the value that will accrue to any given actor from an ENSO phase forecast should be viewed not as a known number but instead as a random draw from a distribution, even when the forecast is always correct. Forecast value depends on the highly variable contexts in which forecasts are used. Randomness in forecast value has significant implications for choices made by forecasters, forecast users and policy makers. To show randomness, we estimate potential economic values of ENSO forecasts for agricultural producers based on two realistic assumptions: the crop prices farmers receive are uncertain; and within an ENSO phase, the actual climate is variable in ways that affect profits. The use of synthetic weather and crop price series, with crop simulation models, helps show the range and likelihood of climate forecast value.     

Rainfall thresholds for the initiation of landslides in central and southern Europe

Summary We review rainfall thresholds for the initiation of landslides world wide and propose new empirical rainfall thresholds for the Central European Adriatic Danubian South-Eastern Space (CADSES) area, located in central and southern Europe. One-hundred-twenty-four empirical thresholds linking measurements of the event and the antecedent rainfall conditions to the occurrence of landslides are considered. We then describe a database of 853 rainfall events that resulted or did not result in landslides in the CADSES area. Rainfall and landslide information in the database was obtained from the literature; climate information was obtained from the global climate dataset compiled by the Climate Research Unit of the East Anglia University. We plot the intensity-duration values in logarithmic coordinates, and we establish that with increased rainfall duration the minimum intensity likely to trigger slope failures decreases linearly, in the range of durations from 20 minutes to ∼12 days. Based on this observation, we determine minimum intensity-duration (ID) and normalized-ID thresholds for the initiation of landslides in the CADSES area. Normalization is performed using two climatic indexes, the mean annual precipitation (MAP) and the rainy-day-normal (RDN). Threshold curves are inferred from the available data using a Bayesian statistical technique. Analysing the obtained thresholds we establish that lower average rainfall intensity is required to initiate landslides in an area with a mountain climate, than in an area characterized by a Mediterranean climate. We further suggest that for rainfall periods exceeding ∼12 days landslides are triggered by factors not considered by the ID model. The obtained thresholds can be used in operation landslide warning systems, where more accurate local or regional thresholds are not available.     

The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation

We present a set of indicators of vulnerability and capacity to adapt to climate variability, and by extension climate change, derived using a novel empirical analysis of data aggregated at the national level on a decadal timescale. The analysis is based on a conceptual framework in which risk is viewed in terms of outcome, and is a function of physically defined climate hazards and socially constructed vulnerability. Climate outcomes are represented by mortality from climate-related disasters, using the emergency events database data set, statistical relationships between mortality and a shortlist of potential proxies for vulnerability are used to identify key vulnerability indicators. We find that 11 key indicators exhibit a strong relationship with decadally aggregated mortality associated with climate-related disasters. Validation of indicators, relationships between vulnerability and adaptive capacity, and the sensitivity of subsequent vulnerability assessments to different sets of weightings are explored using expert judgement data, collected through a focus group exercise. The data are used to provide a robust assessment of vulnerability to climate-related mortality at the national level, and represent an entry point to more detailed explorations of vulnerability and adaptive capacity. They indicate that the most vulnerable nations are those situated in sub-Saharan Africa and those that have recently experienced conflict. Adaptive capacity—one element of vulnerability—is associated predominantly with governance, civil and political rights, and literacy.     

Translational Science for Climate Services: Mapping and Understanding Users' Climate Service Needs in CSSP China

The Climate Science for Service Partnership China(CSSP China) is a joint program between China and the United Kingdom to build the basis for climate services to support the weather and climate resilient economic development and welfare in China. Work Package 5(WP5) provides the translational science on identification of: different users and providers, and their mandates; factors contributing to communication gaps and capacities between various users and providers; and mechanisms to work through such issues to develop and/or evolve a range of climate services.Key findings to emerge include that users from different sectors have varying capacities, requirements, and needs for information in their decision contexts, with a current strong preference for weather information. Separating climate and weather services when engaging users is often not constructive. Furthermore, there is a need to move to a service delivery model that is more user-driven and science informed; having sound climate science is not enough to develop services that are credible, salient, reliable, or timely for diverse user groups. Greater investment in building the capacity of the research community supporting and providing climate services to conduct translational sciences and develop regular user engagement processes is much needed. Such a move would help support the China Meteorological Administration's(CMA) ongoing efforts to improve climate services. It would also assist in potentially linking a broader group of "super" users who currently act as providers and purveyors of climate services because they find the existing offerings are not relevant to their needs or cannot access CMA's services.     

Indigenous climate knowledge in southern Uganda: the multiple components of a dynamic regional system

Farmers in southern Uganda seek information to anticipate the interannual variability in the timing and amount of precipitation, a matter of great importance to them since they rely on rain-fed agriculture for food supplies and income. The four major components of their knowledge system are: (1) longstanding familiarity with the seasonal patterns of precipitation and temperature, (2) a set of local traditional climate indicators, (3) observation of meteorological events, (4) information about the progress of the seasons elsewhere in the region. We examine these components and show the connections among them. We discuss the social contexts in which this information is perceived, evaluated, discussed and applied, and we consider the cultural frameworks that support the use of this information. This system of indigenous knowledge leads farmers to participate as agents as well as consumers in programs that use modern climate science to plan for and adapt to climate variability and climate change.     

丽水市生态气候休闲养生适宜性分析

人们的休闲养生活动与气候条件和生态环境密切关联。选取反映气候综合状况的4项气候指数和表征生态环境质量的5项生态指标,对丽水市生态气候的休闲养生适宜性进行了分析。分析结果表明:丽水气候全年有8个月的人体舒适度气象指数BCMI等级达到"舒适"和"较舒适"级别,其中"舒适"级别有4个月;有11个月的气候适宜旅游度假(度假气候指数HCI60),其中"很适宜"级别月份有5个,"特别适宜"级别月份有1个;丽水冬季气候风寒指数WCI值在550 kcal/m~2·h以下,极少出现严寒天气,气候仅会对人体产生弱度冷胁迫;夏季丽水气候温湿度相对较高,尤其是7月温湿指数THI值可达80以上,城市区域的温湿胁迫较为强烈。丽水市生态环境优质,森林覆盖率为80.8%、物种丰度指数达0.96、断面水质达标率为98.9%、优良空气天数达360天,并拥有14个国家4A级旅游景区。国内21座城市生态气候数据的对比分析显示,丽水市气候指标占优、生态指标领先,其休闲养生适宜性在国内城市中具有突出优势。     

Identifying the exposure of two subsistence villages in Alaska to climate change using traditional ecological knowledge

Dramatic climatic change in the Arctic elevates the importance of determining the risk of exposure for people living in vulnerable areas and developing effective adaptation programs. Climate change assessment reports are valuable, and often definitive, sources of information for decision makers when constructing adaptation plans, yet the scope of these reports is too coarse to identify site-specific exposure to the impacts of climate change and adaptation needs. Subsistence hunters and gatherers in the Arctic are valuable knowledge holders of climate-related change in their area. Incorporating both their traditional ecological knowledge and information found in climate science assessment reports can offer adaption planners a deeper understanding of exposure to climate change and local adaptation needs. In this study, we compare information found in assessment reports of climate change in the Arctic with what we have learned from the Alaskans Sharing Indigenous Knowledge project from 2009 to 2012, a research project documenting traditional ecological knowledge in two Native villages in Alaska, Savoonga and Shaktoolik. Content analysis of the interviews with hunters and gatherers reveal the site-specific impacts of climate change affecting these two villages. We find that their traditional ecological knowledge is complimentary and largely corroborates the climate science found in assessment reports. Traditional ecological knowledge, however, is more current to the social and local conditions of the villages, and presents a more unified social and biophysical portrayal of the impacts of climate change. If taken together, these two forms of knowledge can focus adaptation planning on the pertinent needs of the communities in question.     

Future climate resources for tourism in Europe based on the daily Tourism Climatic Index

Climate is an important resource for many types of tourism. One of several metrics for the suitability of climate for sightseeing is Mieczkowski’s “Tourism Climatic Index” (TCI), which summarizes and combines seven climate variables. By means of the TCI, we analyse the present climate resources for tourism in Europe and projected changes under future climate change. We use daily data from five regional climate models and compare the reference period 1961–1990 to the A2 scenario in 2071–2100. A comparison of the TCI based on reanalysis data and model simulations for the reference period shows that current regional climate models capture the important climatic patterns. Currently, climate resources are best in Southern Europe and deteriorate with increasing latitude and altitude. With climate change the latitudinal band of favourable climate is projected to shift northward improving climate resources in Northern and Central Europe in most seasons. Southern Europe’s suitability for sightseeing tourism drops strikingly in the summer holiday months but is partially compensated by considerable improvements between October and April.