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Chain polymerizations are defined as chain reactions where the propagation steps occur by reaction between monomer(s) and active site(s) on the polymer chains with regeneration of the active site(s) at each step. Many forms of chain polymerization can be distinguished according to the mechanism of the propagation step (e.g., cyclopolymerization - when rings are formed, condensative chain polymerization - when propagation is a condensation reaction, group-transfer polymerization, polyinsertion, ring-opening polymerization - when rings are opened), whether they involve a termination step or not (e.g., living polymerization - when termination is absent, reversible-deactivation polymerization), whether a transfer step is involved (e.g., degenerative-transfer polymerization), and the type of chain carrier or active site (e.g., radical, ion, electrophile, nucleophile, coordination complex). The objective of this document is to provide a language for describing chain polymerizations that is both readily understandable and self-consistent, and which covers recent developments in this rapidly evolving field. IUPAC [2010-007-1-400] Published version This work was prepared under project 2010-007-1-400 of IUPAC (Funder ID: 10.13039/100006987).

The use of self-consistent terminology to describe polymerizations is important for litigation, patents, research and education. Imprecision in these areas can be both costly and confusing. To address this situation the International Union of Pure and Applied Chemistry (IUPAC) has made recommendations, which are summarized below. In the version shown as the supplementary material, references and hyperlinks lead to source documents; screen tips contain definitions published in IUPAC recommendations. More details can also be found in the IUPAC Purple Book. This guide is one of a series on terminology and nomenclature. Refer to the supplementary material for the complete and interactive version of this brief guide.

Climate data records (CDRs) of essential climate variables (ECVs) as defined by the Global Climate Observing System (GCOS) derived from satellite instruments help to characterize the main components of the Earth system, to identify the state and evolution of its processes, and to constrain the budgets of key cycles of water, carbon, and energy. The Climate Change Initiative (CCI) of the European Space Agency (ESA) coordinates the derivation of CDRs for 21 GCOS ECVs. The combined use of multiple ECVs for Earth system science applications requires consistency between and across their respective CDRs. As a comprehensive definition for multi-ECV consistency is missing so far, this study proposes defining consistency on three levels: 1) consistency in format and metadata to facilitate their synergetic use (technical level); 2) consistency in assumptions and auxiliary datasets to minimize incompatibilities among datasets (retrieval level); and 3) consistency between combined or multiple CDRs within their estimated uncertainties or physical constraints (scientific level). Analyzing consistency between CDRs of multiple quantities is a challenging task and requires coordination between different observational communities, which is facilitated by the CCI program. The interdependencies of the satellite-based CDRs derived within the CCI program are analyzed to identify where consistency considerations are most important. The study also summarizes measures taken in CCI to ensure consistency on the technical level, and develops a concept for assessing consistency on the retrieval and scientific levels in the light of underlying physical knowledge. Finally, this study presents the current status of consistency between the CCI CDRs and future efforts needed to further improve it.

As increasingly smaller molecular materials and material structures are devised or developed for technological applications, the demands on the processes of lithography now routinely include feature sizes that are of the order of 10 nm. In reaching such a fine level of resolution, the methods of lithography have increased markedly in sophistication and brought into play 2terminology that is unfamiliar, on the one hand, to scientists tasked with the development of new lithographic materials or, on the other, to the engineers who design and operate the complex equipment that is required in modern-day processing. Publications produced by scientists need to be understood by engineers and vice versa, and these commonly arise from collaborative research that draws heavily on the terminology of two or more of the traditional disciplines. It is developments in polymer science and material science that lead progress in areas that cross traditional boundaries, such as microlithography. This document provides the exact definitions of a selection of unfamiliar terms that researchers and practitioners from different disciplines might encounter.

Made available in DSpace on 2022-05-01T11:07:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-01-01 These recommendations are specifically for polymers and polymer systems showing a significant response to an electromagnetic field or one of its components (electric field or magnetic field), i.e., for electromagnetic-field-responsive polymer materials. The structures, processes, phenomena and quantities relating to this interdisciplinary field of materials science and technology are herein defined. Definitions are unambiguously explained and harmonized for wide acceptance by the chemistry, physics, polymer and materials science communities. A survey of typical electromagnetic-field-responsive polymers is included. Department of Physical and Macromolecular Chemistry Faculty of Sciences Charles University, Albertov 2030 DF-FC UNESP - Universidade Estadual Paulista, Av. Eng. Luiz Edmundo Carrijo Coube 14-01 Institut des Science Analytiques et Physico-Chimie Pour l'Environnement et les Materiaux CNRS Univ Pau and Pays Adour University of Kent Pi-Conjugated Polymer Unit Okinawa Institute of Science and Technology, Onna-son Organisation Moléculaire Evolution et Matériaux Fluores UMR CNRS 5073 Laboratoire de Chimie Macromoléculaire Université Montpellier II Science et Techniques du Languedoc, Place Eugène Bataillon, Cedex 5 Department of Materials Centre of Plastic Electronics (CPE) Imperial College, Exhibition Road Department of Chemistry University of North Carolina at Charlotte DF-FC UNESP - Universidade Estadual Paulista, Av. Eng. Luiz Edmundo Carrijo Coube 14-01

Low-level jets (LLJs) drive frequent emission of mineral dust in the central and western Sahara in boreal summer. A major hotspot for this process is central Algeria, northern Mali and Mauritania, through which blow the dry near-surface northeasterly Harmattan winds, with a peak in dust emission around the low-lying Tidihelt region. North African orography is thought to contribute to the strength of the LLJ over the Bodele dust source in Chad, but its influence on erosivity over summertime source regions remains unquantified. In this paper, the contribution of central Saharan orography to the strength of Harmattan LLJs and associated dust emission frequency is tested. An idealized simulation with flattened Hoggar mountains is compared with a control using the Met Office Unified Model at 12 km horizontal resolution. In the absence of the Hoggar mountains, dust emission frequency estimated using an empirical relationship with surface wind speeds is found to decline across the entire northeasterly “LLJ alley,” including by 31% in the Tidihelt where composited jet surface winds drop from 9.0 to 7.3 m s−1 under a more easterly regime. The mountains are linked to a low-level leeward geopotential height perturbation, with a northern limb reinforcing northeasterlies through the Tidihelt. Dome-shaped elevated heating situated over the Hoggar mountains explains the difference between the simulated wind fields in the two experiments. These findings suggest that central Saharan orography plays an important role in sustaining erosive dusty conditions during boreal summer.

This paper provides a list of the most important terms from all areas of polymer science including polymer chemistry, polymer physics, polymer technology and polymer properties. These have been assembled into a representative list of terms that serves as an IUPAC recommended list of keywords for polymer science.

Pan-Africa convection-permitting regional climate model simulations have been performed to study the impact of high resolution and the explicit representation of atmospheric moist convection on the present and future climate of Africa. These unique simulations have allowed European and African climate scientists to understand the critical role that the representation of convection plays in the ability of a contemporary climate model to capture climate and climate change, including many impact-relevant aspects such as rainfall variability and extremes. There are significant improvements in not only the small-scale characteristics of rainfall such as its intensity and diurnal cycle, but also in the large-scale circulation. Similarly, effects of explicit convection affect not only projected changes in rainfall extremes, dry spells, and high winds, but also continental-scale circulation and regional rainfall accumulations. The physics underlying such differences are in many cases expected to be relevant to all models that use parameterized convection. In some cases physical understanding of small-scale change means that we can provide regional decision-makers with new scales of information across a range of sectors. We demonstrate the potential value of these simulations both as scientific tools to increase climate process understanding and, when used with other models, for direct user applications. We describe how these ground-breaking simulations have been achieved under the U.K. Government’s Future Climate for Africa Programme. We anticipate a growing number of such simulations, which we advocate should become a routine component of climate projection, and encourage international coordination of such computationally and human-resource expensive simulations as effectively as possible.

Extreme and impactful weather events of the recent past provide a vital but under-utilised data source for understanding present and future climate risks. Extreme event attribution (EEA) enables us to quantify the influence of anthropogenic climate change (ACC) on a given event in a way that can be tailored to stakeholder needs, thereby enhancing the potential utility of studying past events. Here we set out a framework for systematically recording key details of high-impact events on a national scale (using the UK and Puerto Rico as examples), combining recent advances in event attribution with the risk framework. These ‘inventories’ inherently provide useful information depending on a user’s interest. For example, as a compilation of the impacts of ACC, we find that in the UK since 2000, at least 1500 excess deaths are directly attributable to human-induced climate change, while in Puerto Rico the increased intensity of Hurricane Maria alone led to the deaths of up to 3670 people. We also explore how inventories form a foundation for further analysis, learning from past events. This involves identifying the most damaging hazards and crucially also vulnerabilities and exposure characteristics over time. To build a risk assessment for heat-related mortality in the UK we focus on a vulnerable group, elderly urban populations, and project changes in the hazard and exposure within the same framework. Without improved preparedness, the risk to this group is likely to increase by ~50% by 2028 and ~150% by 2043. In addition, the framework allows the exploration of the likelihood of otherwise unprecedented events, or 'Black Swans’. Finally, not only does it aid disaster preparedness and adaptation at local and national scales, such inventories also provide a new source of evidence for global stocktakes on adaptation and loss and damage such as mandated by the Paris Climate Agreement.

The use of regional climate model‐based projections for providing regional climate information in a research and climate service contexts is currently expanding very fast. This has been possible thanks to a considerable effort in developing comprehensive ensembles of regional climate model (RCM) projections, especially for Europe, in the EURO‐CORDEX community (Jacob et al., 2014; Jacob et al., 2020). Currently, EURO‐CORDEX has developed a set of 55 historical and scenario projections (RCP8.5) using 8 driving global climate models (GCMs) and 11 RCMs. This article presents the ensemble including its design. We target the analysis to better characterize the quality of the regional climate models by providing an evaluation of these RCM simulations over a number of classical climate variables and extreme and impact‐oriented indices for the period 1981‐2010. For the main variables, the model simulations generally agree with observations and reanalyses. However, several systematic biases are found as well, with shared responsibilities among RCMs and GCMs: simulations are overall too cold, too wet and too windy compared to available observations or reanalyses. Some simulations show strong systematic biases on temperature, others on precipitation or dynamical variables but none of the models/simulations can be defined as the best or the worst on all criteria. The article aims at supporting a proper use of these simulations within a climate services context.

Constructing climate information to inform climate change risk-related decision-making is challenging and requires a rigorous interrogation and understanding of multiple lines of evidence and an assessment of the values, limits and uncertainties involved. Critically, there is no definitive approach agreed on by all climate scientists. Rather, a range of approaches and assumptions are used, with implications for robustness, reliability and uncertainty. Often these choices and assumptions are informed by the values and objectives of climate science rather than the decision context. We propose an approach, information distillation, that makes explicit and open for deliberation many of the implicit decisions and value judgements that occur throughout the process of constructing information. We argue that this approach must engage substantively with the decision context and open up choices and assumptions in a transparent manner to deliberation across climate scientists and context experts. This should ensure relevance and usability, and build understanding and trust to form an important basis for effective uptake of information. Two case studies are described demonstrating the effectiveness of these approaches and illustrating several important principles for transparent information distillation.

State-of-the-science general circulation models (GCMs) are the primary tools for making policy-relevant climate calculations. Yet, these models face challenges in monsoon regions where live more than 70 % of the world's population, due to the complex interplay of local and remote influences on a spectrum of space and time scales. This work examines the fidelity to reproduce regional and global monsoons climatological features using the Met Office Unified Model (MetUM) third and fourth generations Global Atmosphere (GA3.0) and (GA4.0), two configurations of the HadGEM3 system developed for seamless use across climate and weather time scales. Results are compared both against multiple observational gridded datasets and outputs from 20 atmospheric-only GCMs simulations from the CMIP5 campaign. Furthermore, we investigate the influence of remote versus local atmospheric circulation errors by constraining realistically HadGEM3 circulations over a prescribed monsoon domain and examining the consequences outside and inside this domain using the grid-point nudging method. The GA3.0 largely captures global monsoon features, including the monsoon precipitation patterns and extent of regional monsoon domains, when integrated using a low (~ 135-km in mid-latitudes), medium (~ 60 km in mid-latitudes) and high (~ 25 km in mid-latitudes) horizontal resolutions. GA4.0 and GA3.0 results display a close similarity, and compares reasonably well against the best available CMIP5 models. The common failure of HadGEM3 configurations is the simulated weak magnitude and extent of the Asian Summer Monsoon (ASM) precipitation pattern, and associated low-level Somali jet. This situation is also apparent within HadGEM2-A, ACCESS1-0, and CSIRO-Mk3-6-0 – three GCMs sharing dynamical and physical components. HadGEM3 performance improves significantly over ASM with atmospheric circulations constrained realistically over the tropics, West African and Asian Summer monsoon domains. Conversely, constraining atmospheric circulations over other remote monsoon domains show little influence on the ASM precipitation. We argue that GA4.0 and GA3.0 poor simulations over the ASM domain are attributable, partly to local atmospheric circulations errors and excessive precipitation over the southwest equatorial Indian Ocean, rather than to remote tropical atmospheric responses of varying forcing fields, such as SST over the Arabian Sea, aerosols, and growing greenhouse gas emissions. The improved understanding of GCM performance in monsoon regions is an important step for credible projections of global monsoon changes.

Multi-thousand member climate model simulations are highly valuable for showing how extreme weather events will change as the climate changes, using a physically-based approach. However, until now, studies using such an approach have been limited to using models with a resolution much coarser than the most modern systems. We have developed a global atmospheric model with 5/6°x5/9° resolution (~60km in middle latitudes) that can be run in the climateprediction.net distributed computing system to produce such large datasets. This resolution is finer than that of many current global climate models and sufficient for good simulation of extratropical synoptic features such as storms. It will also allow many extratropical extreme weather events to be simulated without requiring regional downscaling. We will show that this model's simulation of extratropical weather is competitive with that in other current models. We will also present results from the first multi-thousand member ensembles produced at this resolution, showing the impact of 1.5°C and 2°C global warming on extreme winter rainfall and extratropical cyclones in Europe.

Climate impacts and adaptation studies often use output from impact models that require data representing future climates at a resolution greater than can be provided by Global Climate Models (GCMs). This paper describes the use of Regional Climate Model (RCM) simulations to generate high-resolution future climate information for assessing climate impacts in the Ganges-Brahmaputra-Meghna (GBM) and Mahanadi deltas as part of the DECCMA project. In this study, three different GCMs (HadGEM2-ES, CNRM-CM5 and GFDL-CM3), all using a single scenario for future greenhouse forcing of the atmosphere (RCP 8.5), were downscaled to a horizontal resolution of 25 km over south Asia using the HadRM3P RCM. These three GCMs were selected based on ability to represent key climate processes over south Asia and ability to sample a range of regional climate change responses to greenhouse gas forcing. RCM simulations of temperature, precipitation, and lower level (850 hPa) atmospheric circulation in the monsoon season (June, July, August, September - JJAS) were compared with observational datasets and their respective driving GCMs to ensure large-scale consistency. Although there are some biases in the RCM simulations, these comparisons indicate that the RCMs are able to simulate realistically aspects of the observed climate of South Asia, such as the monsoon circulation and associated precipitation that are key for informing downstream impacts and adaptation studies. Simulated future temperature and precipitation changes on seasonal and daily timescales suggest increases in both temperature and precipitation across all three models during the monsoon season, with an increase in the amount of extremely heavy precipitation over the GBM and Mahanadi basins. Despite different driving conditions, these results are consistent across all three RCM simulations, providing a level of confidence in the magnitudes and spatial characteristics of temperature and precipitation projections for South Asia.

This brief Technical Report summarizes the key points on the nomenclature of macromolecules and polymers.

In April 2017, over 70 scientists, policymakers and practitioners from 32 countries convened at the International Conference on Climate Risk Management in Nairobi, Kenya. This conference utilized innovative approaches to facilitate a process of constructive, critical reflection of the existing climate risk management knowledge base, as well as its relevance to decision-maker needs and views of the most vulnerable people. The conference articulated recommendations to the Intergovernmental Panel on Climate Change (IPCC) in the development of their Sixth Assessment Report (AR6)–in support of the Chair’s vision for AR6 to have a strong focus on solutions. This report highlights key recommendations distilled from these discussions in areas such as risk-framing approaches and risk metrics. The meeting also suggested that the next IPCC assessment could be strengthened by stronger interaction with practitioners and policymakers working at the forefront of implementing global climate and development agreements, especially in the most vulnerable contexts, and identified associated research priorities.

To meet the growing demand for climate change information to guide national and local adaptation decision-making in the Philippines, the climate science and services community is producing an increasing volume of future climate data using a range of modelling approaches. However, there is a significant methodological challenge in how to best compare and combine information produced using different models and methods. In this paper, we present the landscape of climate model data available in the Philippines and show how multi-model, multi-method climate projections are being used and communicated to inform climate change policy and planning, focusing on the agriculture sector. We highlight the importance of examining and communicating methodological strengths and weaknesses as well as understanding the needs and capabilities of different user communities. We discuss the assessment of projections from different methods, including global and regional downscaled simulations, and discuss ways to summarise and communicate this information to stakeholders using co-production approaches. The paper concludes with perspectives on how to best use an “ensemble of opportunity” to construct defensible, plausible and usable climate projections.

We have implemented dynamical downscaling of the Met Office GloSea5 global seasonal forecasting system and analysed its ability to generate skilful forecasts of characteristics of the June-September rainy season in Ethiopia that are of societal relevance. The downscaling used a regional model with a resolution of 25 km, and the same atmosphere and land configuration as the global model, to produce a 3-member ensemble of seasonal hindcasts for the period 1991–2011 and a larger 15-member ensemble for four of these years comprising two anomalously dry and two anomalously wet years. The regional model was also driven by the quasi-observed ERA-Interim dataset. To provide context for the assessment of the downscaled seasonal forecasts and to show the limit for the skill of a global seasonal forecast downscaling system for the region.A mainly qualitative assessment of GloSea5 and downscaled GloSea5 forecasts demonstrated that the downscaled forecasts could be considered a faithful disaggregation of the coarse resolution GloSea5 forecasts. Forecasts of average seasonal rainfall anomalies in the three regions of Ethiopia studied were captured in three of the four years with the wet season of 2006 incorrectly forecast in all three regions, and the 21 year 3-member hindcast had a correlation of 0.65 with observations. Whilst exploring the potential for the downscaled GloSea5 to generate skillful forecasts of rainy season onset and dry spells we note that both the global and regional model have skill with onset correctly predicted as being early or late in more than 75% of cases for some regions. Keywords: Seasonal forecast, Ethiopia, Downscaling, Rainy season onset, Dry spells

Loss and Damage (L&D;) has been the subject of contentious debate in international climate policy for several decades. Recently, formal mechanisms on L&D; have been established, but arguably through unclear language. This ambiguity is politically important, but researchers and practitioners require clearer understandings of L&D.; Here we report on the first in-depth empirical study of actor perspectives, including interviews with 38 key stakeholders in research, practice, and policy. We find points of agreement and also important distinctions in terms of: the relationship between L&D; and adaptation, the emphasis on avoiding versus addressing L&D;, the relevance of anthropogenic climate change, and the role of justice. A typology of four perspectives is identified, with different implications for research priorities and actions to address L&D.; This typology enables improved understanding of existing perspectives and so has potential to facilitate more transparent discussion of the options available to address L&D;.

A severe drought hit the Greater Horn of Africa (GHA) in 2014, but it remains unclear whether this extreme event was attributable to anthropogenic climate change or part of longer‐term natural cycles. Precipitation patterns are known to be changing across the GHA, but trajectories in land surface variables are much less well known. We simulated the GHA land surface environment to assess the balance between natural cycles and human‐induced climate change. Using a new form of event attribution study where we focused on both climate variables and also directly simulated land surface variables, we combined publicly volunteered distributed computing with land surface simulations to quantify land surface responses. Uncertainty was quantified both for climate model and land surface model outputs. We identified two distinct “drought trajectories” in the GHA bimodal seasonality area during the March–May (Long Rains season) of 2014. Human‐induced climate change may have resulted in regions from Lake Nalubaale (Lake Victoria) to Northern Kenya receiving less precipitation in this season and having up to 20% higher probability of drought‐level evapotranspiration rates (increasing drought). In contrast, the simulated anthropogenic climate change signal for this season induced somewhat wetter conditions and up to 20% lower probability of drought‐level evapotranspiration in Eastern Ethiopia, Southern Somalia, and coastal Kenya (decreasing drought). Uncertainties in our modeling system varied by region and variable of focus, but broadly we found that land surface simulation uncertainty neither added significantly to climate model uncertainty nor significantly reduced it., Journal of Geophysical Research: Atmospheres, 124 (8), ISSN:0148-0227, ISSN:2169-897X

We compare ensemble mean daily precipitation and near-surface temperatures from regional climate model simulations over seven Coordinated Regional Climate Downscaling Experiment domains for the winter and summer seasons. We use Taylor diagrams to show the domain-wide pattern similarity between the model ensemble and the observational data sets. We use the Climatic Research Unit (CRU) and the University of Delaware gridded observations and ERA-Interim reanalysis data as an additional observationally based estimate of historical climatology. Taylor diagrams determine the relative skill of the seven sets of simulations and quantify these results in terms of center pattern root-mean square error and correlation coefficient. Results suggest that there is good agreement between the models and the CRU, in terms of their respective seasonal cycles, as shown in Taylor diagrams and bias plots. There is also good agreement between both gridded observation sets. In addition, downscaled ERA-Interim precipitation is closer to observations than raw ERA-Interim precipitation. Domains located in the low latitudes and those having high topography appear to have larger biases, especially precipitation. Fil: Glisan, Justin M.. IOWA STATE UNIVERSITY (ISU); Fil: Jones, Richard. No especifíca; Fil: Lennard, Chris. University of Cape Town; Sudáfrica Fil: Castillo Pérez, Nadia Itzel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Lucas Picher, Philippe. Université du Québec a Montreal; Canadá Fil: Rinke, Annette. Helmholtz Centre for Polar and Marine Research; Alemania Fil: Solman, Silvina Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Gutowski, William J.. IOWA STATE UNIVERSITY (ISU)

Anthropogenic climate change is already impacting ecological systems. Understanding how organisms respond to weather (short-term) and climate (long-term) variability, and the population and ecosystem-wide consequences of climate change, is a research priority. The appropriate use of information on past and potential future weather and climate conditions is crucial for such research, but uncertainties and biases in this information are seldom given full consideration, with important consequences for assessing the potential impacts of climate change on the conservation of biodiversity. Here, we highlight three important neglected issues pertaining to the major applications of weather and climate information in ecological and biogeographical studies. These are as follows: (1) the uncertainty associated with historical weather and climate information; (2) the selection of ensembles of simulated future climate conditions derived from general circulation models (GCM); and (3) the uncertainty and assumptions associated with downscaling GCM simulations to ecologically relevant spatial scales. Broadly, in order to improve the use of weather and climate information in ecological studies, we propose that ecologists must: (1) use weather and climate products that are appropriate for their intended purpose; (2) explore the consequences of uncertainty in these products for ecological conclusions; and (3) seek greater integration of ecological and climate research to create products that reflect both the requirements of ecologists and the limits of climatology. This will enable more effective research into the likely responses of ecological systems to future climate change.

The South Asian summer monsoon (SASM) is a continental scale weather phenomenon, which fluctuates at a range of temporal and spatial scales. Although majority of global climate models are broadly able to simulate the large scale characteristics of the SASM, they generally have major deficiencies such as constraints in reproducing observed mean precipitation. It is generally anticipated that higher resolution regional climate models (RCMs) would be able to simulate an improved mean state owing to their capacity to better simulate fine temporal and spatial scale features and variability. Here, we analyse SASM simulations using a contemporary Hadley Centre RCM, forced by ERA-Interim reanalysis and observed sea surface temperature, at medium (0.44°) and high (0.11°) horizontal resolutions. Evaluation of the results show that, compared to the medium resolution RCM, the high resolution RCM is able to better resolve the interaction of the low level monsoon flow with the Himalayan orography leading to added value in simulating many aspects of SASM precipitation such as the seasonal mean, relative frequency distribution of daily precipitation, and various metrics of precipitation extremes. In contrast to many previous studies, maximum added value is note along the Indo-Gangetic plain rather than over the complex Himalayas, and the added values of up to 5 mm day−1 and 50 days are noted for mean precipitation and number of wet days, respectively over the region. Similarly, added values of up to 15 and 3 mm day−1 are noted for 95th percentile of daily precipitation and simple daily intensity index, respectively over central India and the Himalayan range. These results suggest that higher resolution RCMs have the potential to add more value when downscaling global climate model climate change projections.

IUPAC recommendations on source-based nomenclature for single-strand polymers have so far addressed its application mainly to copolymers, non-linear polymers and polymer assemblies, and within generic source-based nomenclature of polymers. In this document, rules are formulated for devising a satisfactory source-based name for a polymer, whether homopolymer or copolymer, which are as clear and rigorous as possible. Thus, the source-based system for naming polymers is presented in a totality that serves as a user-friendly alternative to the structure-based system of polymer nomenclature. In addition, because of their widespread and established use, recommendations for the use of traditional names of polymers are also elaborated.

The Nile Basin is one of the most important shared basins in Africa. Managing and developing the water resources within the basin must not only address different water uses but also the trade-off between developments upstream and water use downstream, often between different countries. Furthermore, decision-makers in the region need to evaluate and implement climate adaptation measures. Previous work has shown that the Nile flows can be highly sensitive to climate change and that there is considerable uncertainty in climate projections in the region with no clear consensus as to the direction of change. Modelling current and future changes in river runoff must address a number of challenges; including the large size of the basin, the relative scarcity of data, and the corresponding dramatic variety of climatic conditions and diversity in hydrological characteristics. In this paper, we present a methodology, to support climate adaptation on a regional scale, for assessing climate change impacts and adaptation potential for floods, droughts and water scarcity within the basin.

A temperature-based snow module has been coupled with a grid-based distributed hydrological model, to improve simulations of river flows in upland areas of Britain subject to snowfall and snowmelt. The coupled model has been driven with data from an 11-member perturbed-parameter climate model ensemble, for two time-slices (1960-1990 and 2069-2099), to investigate the potential impacts of climate change. The analysis indicates large reductions in the ensemble mean of the number of lying snow days across the country. This in turn affects the seasonality of peak river flows in some parts of the country; for northerly regions, annual maxima tend to occur earlier in the water year in future. For more southerly regions the changes are less straightforward, and likely driven by changes in rainfall patterns rather than snow. The modelled percentage changes in peak flows illustrate high spatial variability in hydrological response to projected climate change, and large differences between ensemble members. When changes in projected future peak flows are compared to an estimate of current natural variability, more changes fall outside the range of natural variability in southern Britain than in the north.

The results of a large ensemble of regional climate models lead to two contrasting but plausible scenarios for the precipitation characteristics over West Africa; one where mean precipitation is projected to decrease significantly over the Gulf of Guinea in spring and the Sahel in summer, and the other one where summer precipitation over both regions is projected to increase. Dry and wet models show similar patterns of the dynamic and thermodynamic terms of the moisture budget, although their magnitudes are larger in the dry models. Largest discrepancies are found in the strength of the land-atmosphere coupling, with dry models showing a marked decrease in soil moisture and evapotranspiration. Some changes in precipitation characteristics are consistent for both sets of models. In particular, precipitation frequency is projected to decrease in spring over the Gulf of Guinea and in summer over the Sahel, but precipitation is projected to become more intense.