Large scale climate and rainfall seasonality in a Mediterranean Area: Insights from a non‐homogeneous Markov model applied to the Agro‐Pontino plain

In the context of climate change and variability, there is considerable interest in how large scale climate indicators influence regional precipitation occurrence and its seasonality. Seasonal and longer climate projections from coupled ocean–atmosphere models need to be downscaled to regional levels for hydrologic applications, and the identification of appropriate state variables from such models that can best inform this process is also of direct interest. Here, a Non‐Homogeneous Hidden Markov Model (NHMM) for downscaling daily rainfall is developed for the Agro‐Pontino Plain, a coastal reclamation region very vulnerable to changes of hydrological cycle. The NHMM, through a set of atmospheric predictors, provides the link between large scale meteorological features and local rainfall patterns. Atmospheric data from the NCEP/NCAR archive and 56‐years record (1951–2004) of daily rainfall measurements from 7 stations in Agro‐Pontino Plain are analyzed. A number of validation tests are carried out, in order to: 1) identify the best set of atmospheric predictors to model local rainfall; 2) evaluate the model performance to capture realistically relevant rainfall attributes as the inter‐annual and seasonal variability, as well as average and extreme rainfall patterns. Validation tests show that the best set of atmospheric predictors are the following: mean sea level pressure, temperature at 1000 hPa, meridional and zonal wind at 850 hPa and precipitable water, from 20°N to 80°N of latitude and from 80°W to 60°E of longitude. Furthermore, the validation tests show that the rainfall attributes are simulated realistically and accurately. The capability of the NHMM to be used as a forecasting tool to quantify changes of rainfall patterns forced by alteration of atmospheric circulation under climate change and variability scenarios is discussed.     

The role of hydrological processes in ecosystem conservation: Comprehensive water management for a wetland in an arid climate

Water agreements between Mexico and the United States have been crucial to preserving and restoring the Colorado River Delta's wetlands. Nowadays, increased water demand and climate change in the Colorado River Basin could threaten the conservation of the Ciénega de Santa Clara, a 4709 ha coastal wetland at the Sonoran Desert's edge. The international Ramsar convention recognizes the Ciénega de Santa Clara ecosystem for providing vital ecological services, including habitat for endemic, endangered, and migratory species. The hydrology of this wetland has not been completely understood since the 2010–2011 trial run of the Yuma Desalting Plant. Therefore, this study was conducted to identify and quantify the hydrological elements essential for the conservation of this wetland, under three scenarios: (a) normal inflow conditions of the water source – the Wellton-Mohawk canal; (b) inflow reductions, and; (c) an increase of temperature due to global warming. Water and mass balances estimates were conducted every month during 2014–2015; in situ measurements of inflows were carried out on Southern International Boundary in Wellton-Mohawk canal, the Riíto Drain, groundwater, and precipitation: evapotranspiration outputs were estimated using local weather stations and Penman-Monteith formulations. Temperature increases were based on the Intergovernmental Panel on Climate Change projections for the next 100 years. Results showed disconnection in the surface flow of water from the wetland to the adjacent Gulf of California. This behaviour was observed mainly in the summer months in the three scenarios. The disconnections reduced the wetland area and water storage. The hydrological functionality of the Ciénega de Santa Clara wetland depends on the water supply from the Wellton-Mohawk canal, with a minimum continuous discharge of 5.10 m³ s⁻¹ during the summer months.     

Effectiveness of flood damage mitigation measures: Empirical evidence from French flood disasters

Recent destructive flood events and projected increases in flood risks as a result of climate change in many regions around the world demonstrate the importance of improving flood risk management. Flood-proofing of buildings is often advocated as an effective strategy for limiting damage caused by floods. However, few empirical studies have estimated the damage that can be avoided by implementing such flood damage mitigation measures. This study estimates potential damage savings and the cost-effectiveness of specific flood damage mitigation measures that were implemented by households during major flood events in France. For this purpose, data about flood damage experienced and household flood preparedness were collected using a survey of 885 French households in three flood-prone regions that face different flood hazards. Four main conclusions can be drawn from this study. First, using regression analysis results in improved estimates of the effectiveness of mitigation measures than methods used by earlier studies that compare mean damage suffered between households who have, and who have not, taken these measures. Second, this study has provided empirical insights showing that some mitigation measures can substantially reduce damage during floods. Third, the effectiveness of the mitigation measures is very regional dependent, which can be explained by the different characteristics of the flood hazard in our sample areas that experience either slow onset river flooding or more rapid flash and coastal flooding. Fourth, the cost-efficiency of the flood damage mitigation measures depends strongly on the flood probability faced by households.     

Geographical imbalances and divides in the scientific production of climate change knowledge

Studies on scientific production of climate change knowledge show a geographical bias against the developing and more vulnerable regions of the world. If there is limited knowledge exchange between regions, this may deepen global knowledge divides and, thus, potentially hamper adaptive capacities. Consequently, there is a need to further understand this bias, and, particularly, link it with the exchange of knowledge across borders. We use a world-wide geographical distribution of author affiliations in >15,000 scientific climate change publications to show that (1) research production mainly takes place in richer, institutionally well-developed countries with cooler climates and high climate footprints, and (2) the network of author affiliations is structured into distinct modules of countries with strong common research interests, but with little knowledge exchange between modules. These modules are determined mainly by geographical proximity, common climates, and similar political and economic characteristics. This indicates that political-economic, social and educational-scientific initiatives targeted to enhance local research production and collaborations across geographical-climate module borders may help diminish global knowledge divides. We argue that this could strengthen adaptive capacity in the most vulnerable regions of the world.     

Amplification or suppression: Social networks and the climate change—migration association in rural Mexico

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks—the ties connecting an origin and destination—may operate as “migration corridors” with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying, social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place.     

“It won't be any good to have democracy if we don’t have a country”: Climate change and the politics of synecdoche in the Maldives

Critical attention has recently turned to the climate change “synecdoche”: a place uniquely exposed to the environmental consequences of climate crisis, such as sea-level rise, that becomes a stand-in for the global crisis as a whole and a harbinger of more widespread disaster. The Maldives, which scientists, politicians, and activists predict could be completely submerged by 2100, filled that role between the 2008 inauguration of Mohamed Nasheed, the country's first democratically elected president after years of authoritarian rule, and his 2012 ouster. This ethnography of the Maldivian challenge to climate change asks how claiming a geopolitical identity as the world’s “canary in the coalmine” fostered an emerging internal political culture.I argue that arming climate change solutions became a state-making device in the Maldives, whose fragile coral atoll ecosystem itself became the synecdoche of a young democracy. Between 2008 and 2012, how was environmental knowledge creation understood as a democratic activity? To answer this question, I draw on ethnographic interview testimony and participant-observation in Malé, the Maldivian capital, with politicians, activists, and city residents, as well as an analysis of the Nasheed administration’s public rhetoric. The article centers on the case of Bluepeace, the country’s oldest environmental NGO, which has seen significant international publicity. Following Bluepeace’s efforts to help the Maldives achieve carbon neutrality by 2020—part of Nasheed’s plan to end global climate change through exemplary national sacrifice—this article finds that climate problem solving and democracy were put to work for one another through small-scale mitigation and adaptation experiments.     

Studying local climate adaptation: A heuristic research framework for comparative policy analysis

Climate change poses a significant risk for communities, and local governments around the world have begun responding by developing climate adaptation policies. Scholarship on local adaptation policy has proliferated in recent years, but insufficient attention has been paid to operationalization of the unit of analysis, and methods employed are typically inadequate to draw inferences about variation across cases. This article seeks to contribute to the conceptual and methodological foundations of a research agenda for comparative analysis of local adaptation policies and policy-making. Synthesizing insights from policy studies literature and existing adaptation research, the article identifies and operationalizes two aspects of public policy—policy content and policy process—which are salient objects of comparative analysis that typically vary from one community to another. The article also addresses research design, outlining a comparative case study methodology that incorporates various qualitative analytical techniques as the vehicle to examine these policy elements in empirical settings.     

Rapid ecosystem change challenges the adaptive capacity of Local Environmental Knowledge

The use of Local Environmental Knowledge has been considered as an important strategy for adaptive management in the face of Global Environmental Change. However, the unprecedented rates at which global change occurs may pose a challenge to the adaptive capacity of local knowledge systems. In this paper, we use the concept of the shifting baseline syndrome to examine the limits in the adaptive capacity of the local knowledge of an indigenous society facing rapid ecosystem change. We conducted semi-structured interviews regarding perceptions of change in wildlife populations and in intergenerational transmission of knowledge amongst the Tsimane’, a group of hunter-gatherers of Bolivian Amazonia (n = 300 adults in 13 villages). We found that the natural baseline against which the Tsimane’ measure ecosystem changes might be shifting with every generation as a result of (a) age-related differences in the perception of change and (b) a decrease in the intergenerational sharing of environmental knowledge. Such findings suggest that local knowledge systems might not change at a rate quick enough to adapt to conditions of rapid ecosystem change, hence potentially compromising the adaptive success of the entire social-ecological system. With the current pace of Global Environmental Change, widening the gap between the temporal rates of on-going ecosystem change and the timescale needed for local knowledge systems to adjust to change, efforts to tackle the shifting baseline syndrome are urgent and critical for those who aim to use Local Environmental Knowledge as a tool for adaptive management.     

Addressing climate change under preferential trade agreements: Towards alignment of carbon standards under the Transatlantic Trade and Investment Partnership

With its wide coverage of economic spheres and the variety of trade and investment measures currently under negotiation, the Transatlantic Trade and Investment Partnership opens windows of opportunity for advancing action on climate change. We examine possible avenues and international trade law implications for an alignment of carbon-related standards between the EU and the US. We compare EU and US carbon emissions standards for cars and argue that negotiators should strive for a mutual recognition of their equivalence for a transitional period, while pursuing the goal of full harmonization at the level of the highest standards of two parties at some date in the future. This could be a way to balance between economic and environmental interests and harness economic incentives for the benefit of climate.     

Improving the performance of precipitation outputs from Global Climate Models to predict monthly and seasonal rainfall over the Indian subcontinent

Skilful prediction of the monthly and seasonal summer monsoon rainfall over India at a smaller spatial scale is a major challenge for the scientific community. The present study is aimed at achieving this objective by hybridising two mathematical techniques, namely synthetic superensemble (SSE) and supervised principal component regression (SPCR) on six state-of-the art Global Climate Models (GCMs). The performance of the mathematical model is evaluated using correlation analysis, the root mean square error, and the Nash–Sutcliffe efficiency index. Results feature reasonable improvement over central India, which is a zone of maximum rainfall activity in the summer monsoon season. The study also highlights improvement in the monthly prediction of rainfall over raw GCMs (15–20% improvement) with exceptional improvement in July. The developed model is also examined for anomalous years of monsoon and it is found that the model is able to capture the signs of anomalies over different gridpoints of the Indian domain.