Transient atmospheric response to interactive SST anomalies

The transient atmospheric response to interactive SST anomalies in the midlatitudes is investigated using a three-layer QG model coupled in perpetual winter conditions to a slab oceanic mixed layer in the North Atlantic. The SST anomalies are diagnosed from a coupled run and prescribed as initial conditions, but are free to evolve. The initial evolution of the atmospheric response is similar to that obtained with a prescribed SST anomaly, starting as a quasi-linear baroclinic and then quickly evolving into a growing equivalent barotropic one. Because of the heat flux damping, the SST anomaly amplitude slowly decreases, albeit with little change in pattern. Correspondingly, the atmospheric response only increases until it reaches a maximum amplitude after about 1–3.5 months, depending on the SST anomaly considered. The response is similar to that at equilibrium in the fixed SST case, but it is 1.5–2 times smaller, and then slowly decays away.

Statistical-dynamical downscaling for wind energy potentials: evaluation and applications to decadal hindcasts and climate change projections

A statistical–dynamical downscaling (SDD) approach for the regionalization of wind energy output (Eout) over Europe with special focus on Germany is proposed. SDD uses an extended circulation weather type (CWT) analysis on global daily mean sea level pressure fields with the central point being located over Germany. Seventy-seven weather classes based on the associated CWT and the intensity of the geostrophic flow are identified. Representatives of these classes are dynamically downscaled with the regional climate model COSMO-CLM. By using weather class frequencies of different data sets, the simulated representatives are recombined to probability density functions (PDFs) of near-surface wind speed and finally to Eout of a sample wind turbine for present and future climate. This is performed for reanalysis, decadal hindcasts and long-term future projections. For evaluation purposes, results of SDD are compared to wind observations and to simulated Eout of purely dynamical downscaling (DD) methods. For the present climate, SDD is able to simulate realistic PDFs of 10-m wind speed for most stations in Germany. The resulting spatial Eout patterns are similar to DD-simulated Eout. In terms of decadal hindcasts, results of SDD are similar to DD-simulated Eout over Germany, Poland, Czech Republic, and Benelux, for which high correlations between annual Eout time series of SDD and DD are detected for selected hindcasts. Lower correlation is found for other European countries. It is demonstrated that SDD can be used to downscale the full ensemble of the Earth System Model of the Max Planck Institute (MPI-ESM) decadal prediction system. Long-term climate change projections in Special Report on Emission Scenarios of ECHAM5/MPI-OM as obtained by SDD agree well to the results of other studies using DD methods, with increasing Eout over northern Europe and a negative trend over southern Europe. Despite some biases, it is concluded that SDD is an adequate tool to assess regional wind energy changes in large model ensembles.

Adjustments in the forcing-feedback framework for understanding climate change

The traditional forcing-feedback framework has provided an indispensable basis for discussing global climate changes. However, as analysis of model behavior has become more detailed, shortcomings and ambiguities in the framework have become more evident and physical effects unaccounted for by the traditional framework have become interesting. In particular, the new concept of adjustments, which are responses to forcings that are not mediated by the global mean temperature, has emerged. This concept, related to the older ones of climate efficacy and stratospheric adjustment, is a more physical way of capturing unique responses to specific forcings. We present a pedagogical review of the adjustment concept, why it is important, and how it can be used. The concept is particularly useful for aerosols, where it helps to organize what has become a complex array of forcing mechanisms. It also helps clarify issues around cloud and hydrological response, transient vs. equilibrium climate change, and geoengineering.

Quantifying the role of biosphere-atmosphere feedbacks in climate change: coupled model simulation for 6000 years B.P. and comparison with palaeodata for northern Eurasia and northern Africa

The LMD AGCM was iteratively coupled to the global BIOME1 model in order to explore the role of vegetation-climate interactions in response to mid-Holocene (6000 y BP) orbital forcing. The sea-surface temperature and sea-ice distribution used were present-day and CO2 concentration was pre-industrial. The land surface was initially prescribed with present-day vegetation. Initial climate “anomalies” (differences between AGCM results for 6000 y BP and control) were used to drive BIOME1; the simulated vegetation was provided to a further AGCM run, and so on. Results after five iterations were compared to the initial results in order to identify vegetation feedbacks. These were centred on regions showing strong initial responses. The orbitally induced high-latitude summer warming, and the intensification and extension of Northern Hemisphere tropical monsoons, were both amplified by vegetation feedbacks. Vegetation feedbacks were smaller than the initial orbital effects for most regions and seasons, but in West Africa the summer precipitation increase more than doubled in response to changes in vegetation. In the last iteration, global tundra area was reduced by 25% and the southern limit of the Sahara desert was shifted 2.5 °N north (to 18 °N) relative to today. These results were compared with 6000 y BP observational data recording forest-tundra boundary changes in northern Eurasia and savana-desert boundary changes in northern Africa. Although the inclusion of vegetation feedbacks improved the qualitative agreement between the model results and the data, the simulated changes were still insufficient, perhaps due to the lack of ocean-surface feedbacks.

Evidence of resilience to past climate change in Southwest Asia: early farming communities and the 9.2 and 8.2 ka events

Climate change is often cited as a major factor in social change. The so-called 8.2 ka event was one of the most pronounced and abrupt Holocene cold and arid events. The 9.2 ka event was similar, albeit of a smaller magnitude. Both events affected the Northern Hemisphere climate and caused cooling and aridification in Southwest Asia. Yet, the impacts of the 8.2 and 9.2 ka events on early farming communities in this region are not well understood. Current hypotheses for an effect of the 8.2 ka event vary from large-scale site abandonment and migration (including the Neolithisation of Europe) to continuation of occupation and local adaptation, while impacts of the 9.2 ka have not previously been systematically studied. In this paper, we present a thorough assessment of available, quality-checked radiocarbon (14C) dates for sites from Southwest Asia covering the time interval between 9500 and 7500 cal BP, which we interpret in combination with archaeological evidence. In this way, the synchronicity between changes observed in the archaeological record and the rapid climate events is tested. It is shown that there is no evidence for a simultaneous and widespread collapse, large-scale site abandonment, or migration at the time of the events. However, there are indications for local adaptation. We conclude that early farming communities were resilient to the abrupt, severe climate changes at 9250 and 8200 cal BP.

Selecting algorithms for Earth observation of climate within the European Space Agency Climate Change initiative: introduction to a special issue

This special issue is focused on the assessment of algorithms for the observation of Earth’s climate from environ- mental satellites. Climate data records derived by remote sensing are increasingly a key source of insight into the workings of and changes in Earth’s climate system. Producers of data sets must devote considerable effort and expertise to maximise the true climate signals in their products and minimise effects of data processing choices and changing sensors. A key choice is the selection of algorithm(s) for classification and/or retrieval of the climate variable. Within the European Space Agency Climate Change Initiative, science teams undertook systematic assessment of algorithms for a range of essential climate variables. The papers in the special issue report some of these exercises (for ocean colour, aerosol, ozone, greenhouse gases, clouds, soil moisture, sea surface temper- ature and glaciers). The contributions show that assessment exercises must be designed with care, considering issues such as the relative importance of different aspects of data quality (accuracy, precision, stability, sensitivity, coverage, etc.), the availability and degree of independence of validation data and the limitations of validation in characterising some important aspects of data (such as long-term stability or spatial coherence). As well as re- quiring a significant investment of expertise and effort, systematic comparisons are found to be highly valuable. They reveal the relative strengths and weaknesses of different algorithmic approaches under different observa- tional contexts, and help ensure that scientific conclusions drawn from climate data records are not influenced by observational artifacts, but are robust.

Similarities in butterfly emergence dates among populations suggest local adaptation to climate

Phenology shifts are the most widely cited examples of the biological impact of climate change, yet there are few assessments of potential effects on the fitness of individual organisms or the persistence of populations. Despite extensive evidence of climate-driven advances in phenological events over recent decades, comparable patterns across species' geographic ranges have seldom been described. Even fewer studies have quantified concurrent spatial gradients and temporal trends between phenology and climate. Here we analyse a large data set (~129 000 phenology measures) over 37 years across the UK to provide the first phylogenetic comparative analysis of the relative roles of plasticity and local adaptation in generating spatial and temporal patterns in butterfly mean flight dates. Although populations of all species exhibit a plastic response to temperature, with adult emergence dates earlier in warmer years by an average of 6.4 days per °C, among-population differences are significantly lower on average, at 4.3 days per °C. Emergence dates of most species are more synchronised over their geographic range than is predicted by their relationship between mean flight date and temperature over time, suggesting local adaptation. Biological traits of species only weakly explained the variation in differences between space-temperature and time-temperature phenological responses, suggesting that multiple mechanisms may operate to maintain local adaptation. As niche models assume constant relationships between occurrence and environmental conditions across a species' entire range, an important implication of the temperature-mediated local adaptation detected here is that populations of insects are much more sensitive to future climate changes than current projections suggest.

Be the Change You Wish to See: National Attiudes and Climate Change Policy

A multitude of views characterize what should or should not be done about climate change, and in the past decades, nations have acted very differently in the face of climate change. This study explores factors that affect individuals' attitudes and concerns towards the environment and how those attitudes ultimately affect climate change policy. One model investigates the link between individual attitudes and countries' actions on climate change, and the results show that attitudes indeed matter in the implementation of policy. Different measures of democracy such as freedom of the press also prove to be important as channels for these attitudes. A second model identifies a number of political, socioeconomic and demographic characteristics that matter for people's attitudes towards climate change.

A Spatial-Temporal Downscaling Approach To Construction Of Rainfall Intensity-Duration-Frequency Relations In The Context Of Climate Change

This paper proposes a spatial-temporal downscaling approach to construction of the intensity-duration-frequency (IDF) relations at a local site in the context of climate change and variability. More specifically, the proposed approach is based on a combination of a spatial downscaling method to link large-scale climate variables given by General Circulation Model (GCM) simulations with daily extreme precipitations at a site and a temporal downscaling procedure to describe the relationships between daily and sub-daily extreme precipitations based on the scaling General Extreme Value (GEV) distribution. The feasibility and accuracy of the suggested method were assessed using rainfall data available at eight stations in Quebec (Canada) for the 1961-2000 period and climate simulations under four different climate change scenarios provided by the Canadian (CGCM3) and UK (HadCM3) GCM models. Results of this application have indicated that it is feasible to link sub-daily extreme rainfalls at a local site with large-scale GCM-based daily climate predictors for the construction of the IDF relations for present (1961-1990) and future (2020s, 2050s, and 2080s) periods at a given site under different climate change scenarios. In addition, it was found that annual maximum rainfalls downscaled from the HadCM3 displayed a smaller change in the future, while those values estimated from the CGCM3 indicated a large increasing trend for future periods. This result has demonstrated the presence of high uncertainty in climate simulations provided by different GCMs. In summary, the proposed spatial-temporal downscaling method provided an essential tool for the estimation of extreme rainfalls that are required for various climate-related impact assessment studies for a given region.

Belize: effects of climate change on agriculture

Incluye Bibliografía

An economic assessment of the impact of climate change on the health sector in Montserrat

Climate change has the potential to impact on global, regional, and national disease burdens both directly and indirectly. Projecting and valuing these health impacts is important not only in terms of assessing the overall impact of climate change on various parts of the world, but also in terms of ensuring that national and regional decision-making institutions have access to the data necessary to guide investment decisions and future policy design. This report contributes to the research focusing on projecting and valuing the impacts of climate change in the Caribbean by projecting the climate change-induced excess disease burden for two climate change scenarios in Montserrat for the period 2010 - 2050, and by estimating the monetary value associated with this excess disease burden. The diseases initially considered in this report are variety of vector and water-borne impacts and other miscellaneous conditions; specifically, malaria, dengue fever, gastroenteritis/diarrheal disease, schistosomiasis, leptospirosis, ciguatera poisoning, meningococcal meningitis, and cardio-respiratory diseases. Disease projections were based on derived baseline incidence and mortality rates, available dose-response relationships found in the published literature, climate change scenario population projections for the A2 and B2 IPCC SRES scenario families, and annual temperature and precipitation anomalies as projected by the downscaled ECHAM4 global climate model. Monetary valuation was based on a transfer value of statistical life approach with a modification for morbidity. Using discount rates of 1%, 2% and 4%, results show mean annual costs (morbidity and mortality) ranges of $0.61 million (in the B2 scenario, discounted at 4% annually) – $1 million (in the A2 scenario, discounted at 1% annually) for Montserrat. These costs are compared to adaptation cost scenarios involving increased direct spending on per capita health care. This comparison reveals a high benefit-cost ratio suggesting that moderate costs will deliver significant benefit in terms of avoided health burdens in the period 2010-2050. The methodology and results suggest that a focus on coordinated data collection and improved monitoring represents a potentially important no regrets adaptation strategy for Montserrat. Also the report highlights the need for this to be part of a coordinated regional response that avoids duplication in spending.

An assessment of the economic impact Of climate change on the health sector in Saint Lucia

Climate change has the potential to impact on global, regional, and national disease burdens both directly and indirectly. Projecting and valuing these health impacts is important not only in terms of assessing the overall impact of climate change on various parts of the world, but also of ensuring that national and regional decision-making institutions have access to the data necessary to guide investment decisions and future policy design. This report contributes to the research focusing on projecting and valuing the impacts of climate change in the Caribbean by projecting the climate change-induced excess disease burden for two climate change scenarios in Saint Lucia for the period 2010 - 2050, and by estimating the non-market, statistical life-based costs associated with this excess disease burden. The diseases initially considered in this report are a variety of vector and water-borne impacts and other miscellaneous conditions; specifically, malaria, dengue fever, gastroenteritis/diarrhoeal disease, schistosomiasis, leptospirosis, ciguatera poisoning, meningococcal meningitis, and cardio-respiratory diseases. Disease projections were based on derived baseline incidence and mortality rates, available dose-response relationships found in the published literature, climate change scenario population projections for the A2 and B2 IPCC SRES scenario families, and annual temperature and precipitation anomalies as projected by the downscaled ECHAM4 global climate model. Monetary valuation was based on a transfer value of statistical life approach with a modification for morbidity. Using discount rates of 1, 2, and 4%, results show mean annual costs (morbidity and mortality) ranges of $80.2 million (in the B2 scenario, discounted at 4% annually) -$182.4 million (in the A2 scenario, discounted at 1% annually) for St. Lucia.1 These costs are compared to adaptation cost scenarios involving direct and indirect interventions in health care. This comparison reveals a high benefit-cost ratio suggesting that moderate costs will deliver significant benefit in terms of avoided health costs from 2010-2050. In this context indirect interventions target sectors other than healthcare (e.g. water supply). It is also important to highlight that interventions can target both the supply of health infrastructure (including health status and disease monitoring), and households. It is suggested that a focus on coordinated data collection and improved monitoring represents a potentially important no regrets adaptation strategy for St Lucia. Also, the need for this to be part of a coordinated regional response that avoids duplication in spending is highlighted.

Regional implementation meeting on access rights and sustainable development in the Caribbean. Workshop on enhancing access to information on climate change, natural disasters and coastal vulnerability: leaving no one behind

This document summarizes the regional implementation meeting on access rights and sustainable development in the Caribbean and the workshop on enhancing access to information on climate change, natural disasters and coastal vulnerability: leaving no one behind held in Rodney’s Bay, Saint Lucia, from 24 to 26 August 2015.