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Climate models help us simulate and predict how the Earth's climate is going to change in the future. Wind speed data is critical for developing and validating such models. However, in the real world, often owing to many factors such as station maintenance and sensor failures, a considerable amount of wind data goes missing. The Generative Adversarial Network (GAN) has been used to impute missing wind data, but the handling of unrealistic GAN output has remained largely unstudied. In this paper, we propose a novel hybrid approach that combines both the GAN and dual annealing algorithms to not only impute missing wind speed data but also counter unrealistic GAN outcomes. The hourly mean wind data has been collected from the National Centers for Environmental Information for four Indian stations, viz. Ahmedabad, Indore, Mangaluru and Mumbai. We compared the performance of the proposed approach with those of k-nn, soft imputation, and plain GAN-based approaches on mean, variance, standard deviation, kurtosis, skewness, and R-square. We found that our approach ranks number one based on the R-square value for all the considered stations. Our model consistently produces realistic results, unlike plain GAN. We observed that Mumbai has the lowest percentage of missing data (13.14%) and the highest R-square value (0.9999186451). However, Indore has the highest percentage of missing data (46.6463%) and the lowest R-square value (0.9046885604). [ABSTRACT FROM AUTHOR]

Introduction and background to the Stratosphere–troposphere Processes And their Role in Climate (SPARC) project, the QBOi, and the papers contained in this Special Section. [ABSTRACT FROM AUTHOR]

Sea ice is an important and complex component of the Earth system and is considered a sensitive indicator of climate change. The seasonal sea ice cycle regulates the exchange of heat and salinity, altering the energy balance between high and low latitudes as well as the ocean and atmospheric circulation. The accurate representation of Antarctic sea ice has been considered a hot topic in the climate modelling community and lacks conclusive answers. In this paper, we evaluated the ability of 11 climate models from Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) to simulate the sea ice seasonal cycle in Antarctica in terms of area (SIA) and concentration (SIC), as well as the improvements in the most recent models' version, submitted to CMIP6. The results indicated that all models are able to accurately capture the seasonal cycle of the Antarctic SIA, with the minimum (maximum) occurring in February (September). In the Weddell Sea, Amundsen Sea, Bellingshausen Sea, and the Ross Sea, the simulated sea ice concentration revealed a large and systematic bias in February when compared to observations. In September, a large and systematic bias was found nearby the Southern Ocean's northern limit in the Polar Front. Several CMIP6 models exhibited slight improvements on the SIA and SIC estimate over the previous version (CMIP5). All models indicated a significant sea ice loss in the coming years as a response to CO2 forcing. Despite the advancements in the sea ice representation, our findings show that the models are still unable to accurately represent the regional sea ice changes [ABSTRACT FROM AUTHOR]

Gravity waves generated by mountains are multiscale and three‐dimensional. Current orographic gravity wave drag parametrisation schemes assume that the waves are two‐dimensional, varying only in the vertical and along one horizontal direction. These schemes, therefore, do not represent the process of partial critical‐level filtering, whereby a portion of the wave spectrum is saturated where the winds parallel to the wavevectors become small. This results in an unrealistic vertical distribution of the momentum flux and forcing of the waves on the mean flow. In this paper, a method of accounting for partial critical‐level filtering in an orographic gravity wave drag parametrisation using the full spectrum of realistic topography is presented. This is achieved through binning of the expression for linear hydrostatic surface stresses, computed using Fourier transforms of the subgrid orographic heights within model grid boxes, into wavevector directions. The parametrisation is compared with idealised nonlinear simulations of flow over complex topography and is shown to perform well as the number of wavevector direction bins is increased. Implementation of the scheme into the Met Office Unified Model is tested using short‐range 5‐day forecasts. As is found from idealised simulations, the binned scheme leads to less forcing in the troposphere and increased forcing in the stratosphere within the model. The binned scheme is shown to alleviate biases in the upper stratosphere, between 45 and 65 km, as well as having significant local effects in the troposphere. [ABSTRACT FROM AUTHOR]

Extreme sub-daily rainfall affects flooding in the UK and urban pollution management. Water utilities in the UK need to understand the characteristics of this rainfall, and how it may change in the future in order to plan for and manage these impacts. There is also significant interest from infrastructure owners and urban authorities exposed to flood risk from short-period, intense rainfall events. This paper describes how UK flood risk guidance incorporates allowances for climate change and how recent research using convection-permitting climate models is helping to inform this guidance. The guidance documents are used by engineers and scientists in the modelling of sewer networks, smaller river catchments and urban drainage areas and provide values to 'uplift' rainfall event data used as model inputs to reflect climate change model projections. With an increasing focus on continuous simulation modelling using time series rainfall, research into adjusting time series data to reflect future rainfall characteristics in convection-permitting climate models is discussed. Other knowledge gaps for practitioners discussed are the potential changing shape (profile) of future rainfall events and future changes in antecedent wetness conditions. The author explains the challenge of developing simple and effective guidance for practitioners from the complex scientific output. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'. [ABSTRACT FROM AUTHOR]

The Mediterranean Sea is a climate change hotspot since it provides a magnified warming signal. Heavily populated areas (e.g., Spanish Mediterranean coasts) are vulnerable to negative socio-economic impacts. This is particularly important for climate-related economic sectors such as coastal tourism, the focus of this paper. To promote a sustainable development of these activities and provide key information to stakeholders, it is necessary to anticipate changes in climate. Thus, it is fundamental to use climate modelling tools which account for air-sea interactions, which largely determine the climate signal of the Mediterranean coasts. In this paper, a set of regional air-sea coupled climate model simulations from Med-CORDEX are used to (i) study the climatic conditions on the Spanish Mediterranean coasts in the next decade(s) and (ii) to assess the possibility of extending the coastal tourist season towards spring-fall. We show that climate conditions are getting warmer and drier in the area, especially in summer. Heat waves and heavy precipitation will become more frequent. Thermal discomfort will increase in summer and summer conditions are extending towards spring and fall. Our work remarks the urgent need of adaptation measures of the sector, including the extension of the high tourist season to spring-fall, especially in the long term. We make a special effort to compile a set of adaptation measures for stakeholders. This study is part of the project ECOAZUL-MED, which aims to create a climate service tool to optimize the management of relevant sectors of the blue economy in the Spanish Mediterranean coasts.

Convergence of model projections is often considered by climate scientists to be an important objective in so far as it may indicate the robustness of the models' core hypotheses. Consequently, the range of climate projections from a multi-model ensemble, called "model spread", is often expected to reduce as climate research moves forward. However, the successive Assessment Reports of the Intergovernmental Panel on Climate Change indicate no reduction in model spread, whereas it is indisputable that climate science has made improvements in its modelling. In this paper, after providing a detailed explanation of the situation, we describe an epistemological setting in which a steady (and even slightly increased) model spread is not doomed to be seen as negative, and is indeed compatible with a desirable evolution of climate models taken individually. We further argue that, from the perspective of collective progress, as far as the improvement of the products of a multi-model ensemble (e.g. means) is concerned, reduction of model spread is of lower priority than model independence. [ABSTRACT FROM AUTHOR]

This paper reviews how dynamically adaptive wavelet methods can be designed to simulate atmosphere and ocean dynamics in both flat and spherical geometries. We highlight the special features that these models must have in order to be valid for climate modelling applications. These include exact mass conservation and various mimetic properties that ensure the solutions remain physically realistic, even in the under-resolved conditions typical of climate models. Particular attention is paid to the implementation of complex topography in adaptive models. Using WAVETRISK as an example, we explain in detail how to build a semi-realistic global atmosphere or ocean model of interest to the geophysical community. We end with a discussion of the challenges that remain to developing a realistic dynamically adaptive atmosphere or ocean climate models. These include scale-aware subgrid scale parameterizations of physical processes, such as clouds. Although we focus on adaptive wavelet methods, many of the topics we discuss are relevant for adaptive mesh refinement (AMR). [ABSTRACT FROM AUTHOR]

The Pliocene Model Intercomparison Project (PlioMIP) was initiated in 2008. Over two phases PlioMIP has helped co-ordinate the experimental design and publication strategy of the community, which has included an increasing number of climate models and modelling groups from around the world. It has engaged with palaeoenvironmental scientists to foster new data synthesis supporting the construction of new model boundary conditions, as well as to facilitate new data-model comparisons. The work has advanced our understanding of Pliocene climates and environments, enhanced our knowledge regarding the ability of complex climate and Earth System models to accurately simulate climate change, and helped to refine our estimates of how sensitive the climate system is to forcing conditions. In this community protocol paper, we outline the scientific plan for PlioMIP Phase 3 (PlioMIP3). This plan provides the required guidance to participating modelling groups from around the world to successfully set up and perform PlioMIP3 climate model experiments. The project is open to new participants from the scientific community (both from the climate modelling and geosciences communities). In PlioMIP3, we retain the PlioMIP2 Core experiments (Eoi 400 , E 280 ) and extend the Core requirements to include either an experiment focussed on the Early Pliocene or an alternative Late Pliocene simulation (or both). These additions (a) allow a comparison of Early and Late Pliocene warm intervals and help build research connections and synergy with the MioMIP (Miocene Model Intercomparison Project - also known as DeepMIP-Miocene) and PlioMioVAR projects (Pliocene-Miocene Variability Working Group), and (b) create an alternative time slice simulation for 3.205 Ma (MIS KM5c) through removal of some of the largest palaeogeographic differences introduced between PlioMIP1 and 2 resulting in minimal land-sea mask variations from the modern. In addition, we present ten optional experiments designed to enhance our assessment of climate sensitivity and to explore the uncertainty in greenhouse gas-related forcing. For the first time, we introduce orbital sensitivity experiments into the science plan, as well as simulations incorporating dynamic vegetation-climate feedbacks and an experiment designed to examine the potential significance of East Antarctic Ice Sheet boundary condition uncertainty. These changes enhance palaeo-to-future scientific connections and enable an exploration of the significance of palaeogeographic uncertainties on climate simulations. • This paper presents the community agreed science plan for the 3rd phase of the Pliocene Model Intercomparison Project (PlioMIP3). • Experiments are prioritised/designed to enhance our knowledge of Pliocene and its use in understanding future climate change. • Guidance on model set-up, timescales, format of the model outputs and where these should be stored is outlined. • Information for modelling groups to access the required boundary conditions underpinning model experiments is provided. • Linkages between the climate modelling effort and ongoing co-ordinated geological proxy synthesis is described. [ABSTRACT FROM AUTHOR]

Aims: Our objective was to establish a relationship between long-term variation in the climatic environment, tree canopy decline and observed effects on the population dynamics of avifauna in the Dryandra Woodlands in southwestern Australia. These geographically isolated remnant woodlands are rich in endemic species and sustain a diverse range of ecological communities, but are threatened by habitat degradation and a decline in rainfall. Methods: We used annual rainfall data, averaged from a series of weather stations within 100 km of the Dryandra Woodlands and a time series analysis to investigate long-term changes in annual rainfall. Satellite spectral observations of eight study sites at Dryandra was used to measure changes in Projected Foliage Cover (PFC) of old growth Eucalyptus wandoo at all sites. Our mist-net trapping study across three years and all eight sites, targeted two focal species; the rufous treecreeper (Climacteris rufa) and yellow-plumed honeyeater (Ptilotula ornata). We investigated the relationship between the captures of each species and variation in PFC, between sites and across years. Also in a separate demographic study, capture-mark-recapture data was used to estimate the apparent survival rate of each species, following the robust design for open and closed populations. Key results: We demonstrate a long-term and continuing decline in average annual rainfall that is accelerating. We found the rainfall trend is concomitant with a long-term decline in PFC of E. wandoo and that the previous year's annual rainfall is a predictor of average PFC across all sites. Additionally, we discovered that the PFC at each site, in each year, is a predictor of the number of yellow-plumed honeyeaters which prefer feeding on canopy insects and not a predictor of the predominantly ground-foraging rufous treecreeper. We also found a substantial difference in the apparent survival rates between the two species, with the apparent survival of yellow-plumed honeyeaters being approximately half that of rufous treecreepers. This difference was partially attributed to the likely movement outside of the study area due to decreasing habitat quality. Conclusions and implications: Overall, our results do suggest that some impacts of long-term rainfall trends can be traced to particular species through PFC variation, but the response between species to habitat change will differ and depend on species-specific habitat requirements. As increasing greenhouse emissions are associated with declining rainfall in southwestern Australia, this study shows if rainfall decline and habitat degradation continue, it will have catastrophic consequences for woodland ecosystems. In this paper, we explorehow declining rainfall in southwestern Australia is impacting old growtheucalypts and resident avifauna of the Dryandra woodlands. Using long term dataon rainfall and satellite imagery of Eucalyptuswandoo canopy cover, results show a continuing declining trend inaverage rainfall that is accelerating. Also, we found that rainfall is a predictor oftree foliage cover, which is also declining over time. Our analysis of bird mist-net trapping data and tree canopy data indicate that foliagecover is a predictor of the number of yellow-plumed honeyeaters captured, butnot a predictor of rufous treecreepers. The apparent survival rate of the yellow-plumedhoneyeater was half that of the rufous treecreeper. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a variant of hidden Markov models in which the transition probabilities between the states, as well as the emission distributions, are not constant in time but vary in a periodic manner. This class of models, which we will call seasonal hidden Markov models (SHMMs), is particularly useful in practice, as many applications involve a seasonal behaviour. However, up to now, there is no theoretical result regarding this kind of model. We show that under mild assumptions, SHMMs are identifiable: we can identify the transition matrices and the emission distributions from the joint distribution of the observations on a period, up to state labelling. We also give sufficient conditions for the strong consistency of the maximum likelihood estimator (MLE). These results are applied to simulated data, using the EM algorithm to compute the MLE. Finally, we show how SHMM can be used in real-world applications by applying our model to precipitation data, with mixtures of exponential distributions as emission distributions. [ABSTRACT FROM AUTHOR]

Climate model development, testing, and analysis involve running the model extensively to tune the subgrid- scale parameters that provide closure to the system. This process demands substantial time and computational resources even for typical spatial resolutions and becomes in feasibly expensive for high-resolution studies. This paper presents alternative, computationally feasible methods to emulate the simulations within acceptable error bounds. This strategy can be easily implemented to obtain an ensemble of model runs. The paper outlines three approximation strategies: (1) interpolation with Lagrange basis functions, (2) least-squares (LS) approximation, and (3) interpolation with radial basis functions. As a proof of concept, a suite of relevant physical quantities are evaluated at unknown grid points of parameters, space, and time. The values obtained by emulation are compared against the simulated values to check the feasibility of the method. The advantages and shortcomings of the above-mentioned approximation schemes are discussed, including the savings of time and computational resources. [ABSTRACT FROM AUTHOR]

Climate change is expected to have a vigorous impact on soils and ecosystems due to elevated temperature and changes in precipitation (amount and frequency), thereby altering biogeochemical and hydrological cycles. Several phenomena associated with climate change and anthropogenic activity affect soils indirectly via ecosystem functioning (such as higher atmospheric CO2 concentration and N deposition). Continuous interactions between climate and soils determine the transformation and transport processes. Long-term gradual changes in abiotic environmental factors alter naturally occurring soil forming processes by modifying the soil water regime, mineral composition evolution, and the rate of organic matter formation and degradation. The resulting physical and chemical soil properties play a fundamental role in the productivity and environmental quality of cultivated land, so it is crucial to evaluate the potential outcomes of climate change and soil interactions. This paper attempts to review the underlying long-term processes influenced by different aspects of climate change. When considering major soil forming factors (climate, parent material, living organisms, topography), especially climate, we put special attention to soil physical properties (soil structure and texture, and consequential changes in soil hydrothermal regime), soil chemical properties (e.g. cation exchange capacity, soil organic matter content as influenced by changes in environmental conditions) and soil degradation as a result of longterm soil physicochemical transformations. The temperate region, specifically the Carpathian Basin as a heterogeneous territory consisting of different climatic and soil zones from continental to mountainous, is used as an example to present potential changes and to assess the effect of climate change on soils. The altered physicochemical and biological properties of soils require accentuated scientific attention, particularly with respect to significant feedback processes to climate and soil services such as food security. [ABSTRACT FROM AUTHOR]

The magnitude and frequency of hydrological events are expected to increase in coming years due to climate change in megacities of Asia. Intensity-Duration-Frequency (IDF) curves represent essential means to study effects on the performance of drainage systems. Therefore, the need for updating IDF curves comes from the necessity to gain better understanding of climate change effects. The present paper explores an approach based on spatial downscaling-temporal disaggregation method (DDM) to develop future IDFs using stochastic weather generator, Long Ashton Research Station Weather Generator (LARS-WG) and the rainfall disaggregation tool, Hyetos. The work was carried out for the case of Bangkok, Thailand. The application of LARS-WG to project extreme rainfalls showed promising results and nine global climate models (GCMs) were used to estimate changes in IDF characteristics for future time periods of 2011-2030 and 2046-2065 under climate change scenarios. The IDFs derived from this approach were corrected using higher order equation to mitigate biases. IDFs from all GCMs showed increasing intensities in the future for all return periods. The work presented demonstrates the potential of this approach in projecting future climate scenarios for urban catchment where long term hourly rainfall data are not readily available. [ABSTRACT FROM AUTHOR]

Climate change has intensified the effects of habitat fragmentation in many ecosystems, particularly exacerbated in riparian habitats. Therefore, there is an urgent need to identify keystone connectivity spots to ensure long-term conservation and sustainable management of riparian systems as they play a crucial role for landscape connectivity. This paper aims to identify critical areas for connectivity under two contrasting climate change scenarios (RCP 4.5 and RCP 8.5 models) for the years 2030, 2050 and 2100 and to group these critical areas by similar connectivity in keystone spots for sustainable management. A set of analyses comprising climate analysis, drainage network analysis, configuration of potential riparian habitats, riparian habitat connectivity, data clustering, and statistical analysis within a Spanish river basin (NW Spain) were applied. The node and link connectivity would be reduced under the two climate change scenarios (≈2.5 % and 4.4 % reduction, respectively), intensifying riparian habitat fragmentation. Furthermore, 51 different clusters (critical areas) were obtained and classified in five classes (keystone spots) with similar connectivity across the different scenarios of climate change. Each keystone spot obtained by hierarchical classification was associated with one or more climate scenarios. One of these keystone spots was especially susceptible to the worst climate change scenario. Key riparian connectivity spots will be crucial for the management and restoration of highly threatened riparian systems and to ensure long-term biodiversity conservation. • Connectivity importance was reduced under different climate change scenarios. • Critical area detection for connectivity conservation is threatened by climate change. • Critical areas were classified with similar connectivity keystone spots against climate change. • Keystone spots with high PC index will be priority for conservation management. [ABSTRACT FROM AUTHOR]

A number of authors, including me, have argued that the output of our most complex climate models, that is, of global climate models and Earth system models, should be assessed possibilistically. Worries about the viability of doing so have also been expressed. I examine the assessment of the output of relatively simple climate models in the context of discovery and point out that this assessment is of epistemic possibilities. At the same time, I show that the concept of epistemic possibility used in the relevant studies does not fit available analyses of this concept. Moreover, I provide an alternative analysis that does fit the studies and broad climate modelling practices as well as meshes with my existing view that climate model assessment should typically be of real possibilities. On my analysis, to assert that a proposition is epistemically possible is to assert that it is not known to be false and is consistent with at least approximate knowledge of the basic way things are. I, finally, consider some of the implications of my discussion for available possibilistic views of climate model assessment and for worries about such views. I conclude that my view helps to address worries about such assessment and permits using the full range of climate models in it. [ABSTRACT FROM AUTHOR]

Winter chilling is a key environmental trigger of floral induction in temperateEucalyptus. Over the past two decades, considerable site × eucalypt flowering interaction research has been undertaken over a range of high elevation (>1 100 m asl) forestry sites in the South African summer rainfall area. A practical method of accurately monitoring eucalypt bud temperature at remote sites in these areas was needed for this research. Utilisation of traditional methods of air and bud temperature measurement were not viable, due to significant risks of data and meteorological equipment loss posed by severe weather, vandalism and theft. Between 1996 and 2004, a robust structure for housing the miniature Hobo® temperature logger (hereafter termed ‘Hobo pole’) was designed and utilised for in-field monitoring of air temperature in the research trials. During 2009 and 2010, an experiment was conducted to investigate the relationship betweenE. nitensbud temperature (BudT), Hobo pole air temperature (HoboAT) and radiation screen air temperature (ScrnAT), and develop appropriate calibration models. Attempts to develop a single model for predicting hourly BudT from hourly HoboAT over the entire annual period yielded unsatisfactory results (maximumR 2 value 0.49). Separate winter and summer regression models were subsequently developed for predicting BudT from HoboAT, ScrnAT from HoboAT, and BudT from ScrnAT. In these regressions,R 2 values were generally slightly higher, and SE values lower, for mid-winter data than for mid-summer data. In mid-winter, BudT on HoboAT gave the highestR 2 value (0.99) and lowest SE value (0.49 °C) of all regressions. The Hobo logger/Hobo pole combination, together with developed regression models (presented in this paper), offers one practical, cost-effective solution for accurately monitoring eucalypt bud temperature at remote, high-elevation forestry sites in South Africa. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor announces the appointment of Rosie A. Fisher as the member of the periodical's Editorial Board.

Earth system models (ESMs) simulate the complex interactions and feedbacks between the atmosphere, land, ocean, ice, and biosphere for climate and environmental applications. Atmospheric chemistry forms an important component of current ESMs by controlling the magnitudes, lifetimes and distributions of a large number of short-lived climate forcing agents, such as ozone, methane and aerosols. The Australian Community Climate and Earth-System Simulator (ACCESS) is currently used for climate and weather applications, and is being developed into an ESM with one component being reactive chemistry and aerosols based on the UK Chemistry and Aerosol (UKCA) model. We have compiled a multi-decadal, annuallyvarying, emissions database for reactive gases and aerosols that includes both anthropogenic and natural components with important seasonal variations for use in ACCESS-UKCA. This paper examines Australian emissions of reactive gases, namely methane, oxides of nitrogen, carbon monoxide and sulphur dioxide, from this dataset and compares them with those available from the Australian National Greenhouse Gas Inventory (NGGI) for the years 1990-2012. These emission data include various anthropogenic source sectors and also biomass burning. Generally, there is good agreement between the two datasets for the reference year 2000, but there are significant interannual variations in the NGGI data, especially for carbon monoxide from biomass burning, that are not accounted for in the gridded data. Australian anthropogenic emissions account for between 0.5-2.6% of global anthropogenic emissions, and between 3.6-23.9% of Southern Hemisphere anthropogenic emissions depending on the species. Early model results for carbon monoxide, ozone and aerosol optical depth are presented and compared with observations, which point to the need for a better understanding of atmospheric chemistry in the Southern Hemisphere. [ABSTRACT FROM AUTHOR]

In this paper, we study how uncertainties weighing on the climate system impact the optimal technological pathways the world energy system should take to comply with stringent mitigation objectives. We use the TIAM-World model that relies on the TIMES modelling approach. Its climate module is inspired by the DICE model. Using robust optimization techniques, we assess the impact of the climate system parameter uncertainty on energy transition pathways under various climate constraints. Unlike other studies we consider all the climate system parameters which is of primary importance since: (i) parameters and outcomes of climate models are all inherently uncertain (parametric uncertainty); and (ii) the simplified models at stake summarize phenomena that are by nature complex and non-linear in a few, sometimes linear, equations so that structural uncertainty is also a major issue. The use of robust optimization allows us to identify economic energy transition pathways under climate constraints for which the outcome scenarios remain relevant for any realization of the climate parameters. In this sense, transition pathways are made robust. We find that the abatement strategies are quite different between the two temperature targets. The most stringent one is reached by investing massively in carbon removal technologies such as bioenergy with carbon capture and storage (BECCS) which have yields much lower than traditional fossil fuelled technologies. [ABSTRACT FROM AUTHOR]

This paper adopts a technique common in the dynamical climate modelling literature, that of pattern scaling, and applies it to previously available statistically downscaled station level data for Ireland for two climatically relevant variables, that of temperature and precipitation. This technique allows for the rapid development of climate scenarios for additional emissions scenarios not previously available from the GCM modelling centres. Having derived the end of century (2080s) change in both these variables for four marker emissions scenarios (A1FI, A2, B2, B1), regional response rates, or the regional rate of warming per °C global warming at each station, were calculated. The estimated ranges in regional responses at each station were then compared to regional response rates for the Irish ‘grid box’ derived from a larger sample of 14 GCMs, in order to determine if the calculated response rates were illustrative of a wider suite of GCMs. A Monte Carlo (MC) resampling approach was then employed to sample regional response rates for selected stations and for different estimates of future warming. On the basis of the MC approach, probability distribution functions (pdfs) of simulated changes in temperature and precipitation were constructed and compared to the original statistically downscaled data. The methodology and results presented represent a significant contribution to the traditional approach of statistical downscaling through the development of associated likelihoods, rather than just a change in the mean value. While the methodology presented should enable the rapid development of probabilistic based climate projections, based on a limited availability of downscaled climate scenarios, caution needs to be exercised in the interpretation of the results. While they provide a basis for risk or policy assessment, estimates of the level of risk are not independent of the method employed. [ABSTRACT FROM AUTHOR]

Abstract: The global surface air temperature record of the last 150 years is characterized by a long-term warming trend, with strong multidecadal variability superimposed. Similar multidecadal variability is also seen in other (societal important) parameters such as Sahel rainfall or Atlantic hurricane activity. The existence of the multidecadal variability makes climate change detection a challenge, since global warming evolves on a similar timescale. The ongoing discussion about a potential anthropogenic signal in the Atlantic hurricane activity is an example. A lot of work was devoted during the last years to understand the dynamics of the multidecadal variability, and external and internal mechanisms were proposed. This review paper focuses on two aspects. First, it describes the mechanisms for internal variability using a stochastic framework. Specific attention is given to variability of the Atlantic Meridional Overturning Circulation (AMOC), which is likely the origin of a considerable part of decadal variability and predictability in the Atlantic Sector. Second, the paper discusses decadal predictability and the factors limiting its realization. These include a poor understanding of the mechanisms involved and large biases in state-of-the-art climate models. Enhanced model resolution, improved subgrid scale parameterisations, and the inclusion of additional climate subsystems, such as a resolved stratosphere, may help overcome these limitations. [Copyright &y& Elsevier]

When assessing the magnitude of climate signals in a regional scale, a host of optional approaches is feasible. This encompasses the use of regional climate models (RCM), nested into global climate models (GCM) for an area of interest as well as employing empirical statistical downscaling methods (ESD). In this context the question is addressed: Is an empirical statistical downscaling method capable of yielding results that are comparable to those by dynamical RCMs? Based on the presented ESD method, the comparison of RCM and ESD results show a high amount of agreement. In addition the empirical statistical downscaling can be applied directly to a GCM or a GCM-RCM cascade. The paper aims at comparing the consequences of employing various CGM-RCM-ESD combinations on the derived future changes of temperature and precipitation. This adds to the insight on the scale dependency of downscaling strategies. Results for one GCM with several scenario runs driving several RCMs with and without subsequent empirical statistical downscaling are presented. It is shown that there are only small differences between using the GCM results directly or as a GCM-RCM-ESD cascade. [ABSTRACT FROM AUTHOR]

There are a range of local weather- and climate-related factors that contribute to the degradation of cultural heritage buildings, structures, and sites over time. Some of these factors are influenced by changes in climate and some of these changes manifest themselves through a speeding up of the rate of degradation. It is the intention of this paper to review this situation with special reference to the Nordic Countries, where typical trends resulting from climate change are shorter winters and increased precipitation all year round. An attempt is made to initially draw up a classification of materials and structures relevant to cultural heritage that are affected, with a proposed numeric scale for the urgency to act. The intention is to provide information on where best to concentrate cultural heritage site preservation resources in the future. [ABSTRACT FROM AUTHOR]

This paper reviews the current state of knowledge pertaining to the interactions of lake ice and climate. Lake ice has been shown to be sensitive to climate variability through observations and modelling, and both longterm and short-term trends have been identified from ice records. Ice phenology trends have typically been associated with variations in air temperatures while ice thickness trends tend to be associated more to changes in snow cover. The role of ice cover in the regional climate is less documented and with longer ice-free seasons possible as a result of changing climate conditions, especially at higher latitudes, the effects of lakes on their surrounding climate (such as increased evaporation, lake-effect snow and thermal moderation of surrounding areas, for example) can be expected to become more prominent. The inclusion of lakes and lake ice in climate modelling is an area of increased attention in recent studies. An important step in improving predictions of ice conditions in models is the assimilation of remote sensing data in areas where in-situ data is lacking, or non-representative of the lake conditions. The ability to accurately represent ice cover on lakes will be an important step in the improvement of global circulation models, regional climate models and numerical weather forecasting. [ABSTRACT FROM AUTHOR]

Despite tremendous interest in the topic and decades of research, the origins of the major losses of biodiversity in the history of life on Earth remain elusive. A variety of possible causes for these mass-extinction events have been investigated, including impacts of asteroids or comets, large-scale volcanic eruptions, effects from changes in the distribution of continents caused by plate tectonics, and biological factors, to name but a few. Many of these suggested drivers involve or indeed require changes of Earth's climate, which then affect the biosphere of our planet, causing a global reduction in the diversity of biological species. It can be argued, therefore, that a detailed understanding of these climatic variations and their effects on ecosystems are prerequisites for a solution to the enigma of biological extinctions. Apart from investigations of the paleoclimate data of the time periods of mass extinctions, climate-modelling experiments should be able to shed some light on these dramatic events. Somewhat surprisingly, however, only a few comprehensive modelling studies of the climate changes associated with extinction events have been undertaken. These studies will be reviewed in this paper. Furthermore, the role of modelling in extinction research in general and suggestions for future research are discussed. [ABSTRACT FROM AUTHOR]

Abstract: Climate modelling, to a great extent, is based on simulating air–sea interactions at larger scales. Small-scale interactions and related phenomena, such as wind-generated waves and wave-induced turbulence are sub-grid processes for such models and therefore cannot be simulated explicitly. In the meantime, the waves play the principal role in the upper-ocean mixing. This role is usually parameterized, mostly to account for the wave-breaking turbulence and to describe downward diffusion of such turbulence. The main purpose of the paper is to demonstrate that an important physical mechanism, that is the ocean mixing due to waves, is presently missing in the climate models, whereas the effect of this mixing is significant. It is argued that the mixing role of the surface waves is not limited to the mere transfer of the wind stress and energy across the ocean interface by means of breaking and surface currents. The waves facilitate two processes in the upper-ocean which can deliver turbulence to the depths of the order of 100m directly, rather than diffusing it from the surface. The first process is due to capacity of the waves to generate turbulence, unrelated to the wave breaking, at all depths where the wave orbital motion is significant. The second process is Langmuir circulation, triggered by the waves. Such wave-controlled mixing should cause seasonal variations of the mixed-layer depth, which regulates the thermodynamic balance between the ocean and atmosphere. In the present paper, these variations are parameterized in terms of the global winds. The variable mixed-layer depth is then introduced in the climate model of intermediated complexity CLIMBER-2 with a purpose of reproducing the pre-industrial climate. Comparisons are conducted with the NRL global atlas of the mixed layer, and performance of the wave-mixing parameterisations was found satisfactory in circumstances where the mixing is expected to be dominated by the wind-generated waves. It is shown that as a result the seasonal temperature modulations and extremes are significantly enhanced. This effect combines with changes in the global pressure patterns and leads to large localized alterations of precipitation. Possible future scenarios are also simulated. Finally, importance of the wave-mixing physics and its relevance for the general circulation models is discussed. [Copyright &y& Elsevier]

The terrestrial carbon cycle plays a critical role in determining levels of atmospheric CO2 that result from anthropogenic carbon emissions. Elevated atmospheric CO2 is thought to stimulate terrestrial carbon uptake, through the process of CO2 fertilization of vegetation productivity. This negative carbon cycle feedback results in reduced atmospheric CO2 growth, and has likely accounted for a substantial portion of the historical terrestrial carbon sink. However, the future strength of CO2 fertilization in response to continued carbon emissions and atmospheric CO2 rise is highly uncertain. In this paper, the ramifications of CO2 fertilization in simulations of future climate change are explored, using an intermediate complexity coupled climate–carbon model. It is shown that the absence of future CO2 fertilization results in substantially higher future CO2 levels in the atmosphere, as this removes the dominant contributor to future terrestrial carbon uptake in the model. As a result, climate changes are larger, though the radiative effect of higher CO2 on surface temperatures in the model is offset by about 30% due to reduced positive dynamic vegetation feedbacks; that is, the removal of CO2 fertilization results in less vegetation expansion in the model, which would otherwise constitute an important positive surface albedo-temperature feedback. However, the effect of larger climate changes has other important implications for the carbon cycle – notably to further weaken remaining carbon sinks in the model. As a result, positive climate–carbon cycle feedbacks are larger when CO2 fertilization is absent. This creates an interesting synergism of terrestrial carbon cycle feedbacks, whereby positive (climate–carbon cycle) feedbacks are amplified when a negative (CO2 fertilization) feedback is removed. [ABSTRACT FROM AUTHOR]

The international research program "ReNovRisk-CYCLONE" (RNR-CYC, 2017–2021) directly involves 20 partners from 5 countries of the south-west Indian-Ocean. It aims at improving the observation and modelling of tropical cyclones in the south-west Indian Ocean, as well as to foster regional cooperation and improve public policies adapted to present and future tropical cyclones risk in this cyclonic basin. This paper describes the structure and main objectives of this ambitious research project, with emphasis on its observing components, which allowed integrating numbers of innovative atmospheric and oceanic observations (sea-turtle borne and seismic data, unmanned airborne system, ocean gliders), as well as combining standard and original methods (radiosoundings and global navigation satellite system (GNSS) atmospheric soundings, seismic and in-situ swell sampling, drone and satellite imaging) to support research on tropical cyclones from the local to the basin-scale. [ABSTRACT FROM AUTHOR]

This paper considers the extent and usefulness of reviewing existing literature on the significance of direct and indirect impacts of climate change on groundwater resources with emphasis on examples from the Olifants River basin. Here, the existing literature were extensively reviewed, with discussions centred mainly on the impacts of climate change on groundwater resources and challenges in modelling climate change impacts on groundwater resources. Since in the hydrological cycle, the hydrological components such as evaporation, temperature, precipitation, and groundwater, are the major drivers of the present and future climate, a detailed discussion is done on the impact of climate change on these hydrological components to determine to what extent the hydrological cycle has already been affected as a result of climate change. The uncertainties, constraints and limitations in climate change research have also been reviewed. In addition to the research gaps discussed here, the emphasis on the need of extensive climate change research on the continent, especially as climate change impacts on groundwater, is discussed. Overall, the importance of conducting further research in climate change, understanding the significance of the impact of climate change on water resources such as groundwater, and taking actions to effectively meet the adaptation needs of the people, emerge as an important theme in this review. [ABSTRACT FROM AUTHOR]

The best method so far devised for testing the ability of a general circulation model (GCM) to simulate climates very different from today is to conduct 'snapshot' experiments for specific times in the past at which the climatic forcing can be prescribed in detail. This paper focuses on the period from the last glacial maximum through the Holocene. During this interval, changes in atmospheric circulation were driven primarily by variations in the seasonality of insolation and secondarily by variations in surface-boundary conditions accompanying deglaciation. Changes in atmospheric transparency are usually neglected, apart from lower CO2 at 18 ka BP.Palaeoclimatic simulations have yielded important insights into the dynamics of glacial/interglacial climate change. The results have been tested in three main ways: 1) qualitative comparison of the spatial patterns of climate anomalies; 2) comparison of the simulated climate at individual grid points or groups of grid points with quantitative estimates derived from geological data; and 3) further processing of the model output to yield simulated values of palaeoclimatic indicators such as pollen spectra. The first approach makes effective use of qualitative data, for example, aeolian evidence. The second is largely confined to data-rich areas such as Europe and North America. The third technique, which capitalises on the relative strengths of both approaches, deserves much greater attention. [ABSTRACT FROM PUBLISHER]

The effect of anthropogenic climate change in the ocean is challenging to project because atmosphere-ocean general circulation models (AOGCMs) respond differently to forcing. This study focuses on changes in the Atlantic Meridional Overturning Circulation (AMOC), ocean heat content (Δ OHC), and the spatial pattern of ocean dynamic sea level ( Δ ζ ). We analyse experiments following the FAFMIP protocol, in which AOGCMs are forced at the ocean surface with standardised heat, freshwater and momentum flux perturbations, typical of those produced by doubling CO 2 . Using two new heat-flux-forced experiments, we find that the AMOC weakening is mainly caused by and linearly related to the North Atlantic heat flux perturbation, and further weakened by a positive coupled heat flux feedback. The quantitative relationships are model-dependent, but few models show significant AMOC change due to freshwater or momentum forcing, or to heat flux forcing outside the North Atlantic. AMOC decline causes warming at the South Atlantic-Southern Ocean interface. It does not strongly affect the global-mean vertical distribution of Δ OHC, which is dominated by the Southern Ocean. AMOC decline strongly affects Δ ζ in the North Atlantic, with smaller effects in the Southern Ocean and North Pacific. The ensemble-mean Δ ζ and Δ OHC patterns are mostly attributable to the heat added by the flux perturbation, with smaller effects from ocean heat and salinity redistribution. The ensemble spread, on the other hand, is largely due to redistribution, with pronounced disagreement among the AOGCMs. [ABSTRACT FROM AUTHOR]

In this paper, consideration has focused mainly on the extent and usefulness of the existing literature available so far on the understanding of the impact of climate change on water resources in Africa, focusing mainly on the Olifants River basin in South Africa. Here, the existing literature on the impact of climate change on the hydrological cycle (particularly the hydrological processes like temperature, precipitation and runoff) has been reviewed. The uncertainties, constraints and limitations in climate change research have been discussed at great length. A detailed discussion has been highlighted on the remaining knowledge gaps in climate change research, especially in Africa. In addition to the research gaps highlighted here, the emphasis on the need of climate change research by African scientists is included as part of lessons learnt. Overall, the importance of conducting further research in climate change, understanding the potential impact of climate change on our lives, and taking actions to effectively meet the adaptation needs of the people, emerge as an important theme in this review. [ABSTRACT FROM AUTHOR]

This paper aims at providing insight about bromine (Br) cycle in four Portuguese estuaries: Minho, Lima (in the NW coast) and Sado, Mira (in the SW coast). The focus is on their tidal marsh environments, quite distinct with regard to key biophysicochemical attributes. Regardless of the primary bromide (Br − ) common natural source, i.e., seawater, the NW marshes present relatively higher surface soil/sediment Br concentrations than the ones from SW coast. This happens in close connection with organic matter (OM) content, and is controlled by their main climatic contexts. Yet, the anthropogenic impact on Br concentrations cannot be discarded. Regarding [Br] spatial patterns across the marshes, the results show a general increase from tidal flat toward high marsh. Maxima [Br] occur in the upper driftline zone, at transition from highest low marsh to high marsh, recognized as a privileged setting for OM accumulation. Based on the discovery of OM ubiquitous bromination in marine and transitional environments, it is assumed that this Br occurs mainly as organobromine. Analysis of two dated sediment cores indicates that, despite having the same age (AD ~ 1300), the Caminha salt marsh (Minho estuary) evidences higher Br enrichment than the Casa Branca salt marsh (Mira estuary). This is related to a greater Br storage ability, which is linked to OM build-up and rate dynamics under different climate scenarios. Both cores evidence a fairly similar temporal Br enrichment pattern, and may be interpreted in light of the sun–climate coupling. Thereby, most of the well-known Grand Solar Minima during the Little Ice Age appear to have left an imprint on these marshes, supported by higher [Br] in soils/sediments. Besides climate changes driven by solar activity and impacting marsh Br biogeodynamics, those Br enrichment peaks might also reflect inputs of enhanced volcanic activity covarying with Grand Solar Minima. [ABSTRACT FROM AUTHOR]

This work is devoted to the comparison of one- (1-D) and zero-dimensional (0-D) models of sea ice thermodynamics. 1-D thermodynamics solvers imply the solution of the diffusion equation with penetrating radiation in the moving domain (moving boundary problem), while 0-D implementations neglect the heat capacity of ice and penetrating radiation, that leads to a linear temperature profile by the construction. So far, some climate models use 0-D implementation of thermodynamics in a block of sea ice, while other models use 1-D implementation with a small number of nodes. In this work we present our fully implicit 0-D and 1-D version of snow–ice thermodynamics, which relieves the model of Courant-type time step constraints. Implicitness is achieved by the relaxation method for nonlinear heat capacity and thermal conductivity coefficients with simultaneous search for the temperature that satisfies the boundary conditions. We introduce the experiment with analytical forcing to compare evolution of temperature profiles. This model experiment shows that 0-D model underestimates ice thickness and overestimates the amplitude of temperature profile variation compared to 1-D solution. Despite the large differences in thickness and internal temperatures, the surface temperatures are very close. The models were also validated on the data of the SHEBA field experiment. According to comparison with observation data, the 0-D model predicts ice thickness and spatiotemporal temperature distribution much worse compared to 1-D model, but the amplitude of error in surface temperature is slightly greater for 0-D code. It can be concluded that 0-D model of sea ice thermodynamics is a good tool for predicting surface temperature, but it gives a large error in thickness and temperature distribution. [ABSTRACT FROM AUTHOR]

Wind is an infinitely renewable energy source that is not evenly distributed in space and time. The interconnection of energy‐demanding and energy‐resourceful (yet remote) regions would help prevent energy scarcity in a world where fossil fuels are no longer used. Previous studies have shown that South Greenland and West Europe have complementary wind regimes. In particular, the southern tip of Greenland, Cape Farewell, has gained growing interest for wind farm development as it is one of the windiest places on Earth. In order to gain new insights about future wind speed variations over South Greenland, the Modèle Atmosphérique Régional (MAR), validated against in situ observations over the tundra where wind turbines are most likely to be installed, is used to build climate projections under the emission scenario SSP5‐8.5 by downscaling an ensemble of CMIP6 Earth System Models (ESMs). It appeared that between 1981 and 2100, the wind speed is projected to decrease by ~−0.8 m·s−1 at 100 m a.g.l. over the tundra surrounding Cape Farewell. This decrease is particularly marked in winter while in summer, a wind speed acceleration is projected along the ice sheet margins. An analysis of two‐dimensional wind speed changes at different vertical levels indicates that the winter decrease is likely due to a large‐scale circulation change while in summer, the katabatic winds flowing down the ice sheet are expected to increase due to an enhanced temperature contrast between the ice sheet and the surroundings. As for the mean annual maximum wind power a turbine can yield, a decrease of ~−178.1 W is projected at 100 m a.g.l. Again, the decrease is especially pronounced in winter. Considering the very high winter wind speeds occurring in South Greenland which can cut off wind turbines if too intense, the projected wind speed decrease might be beneficial for the establishment of wind farms near Cape Farewell. [ABSTRACT FROM AUTHOR]

This study evaluates the uncertainty of four components of the hydroclimatic modelling chain on flood projections over 96 basins covering contrasting hydrometeorological regimes located in Canada and Mexico. Two ensembles of climate simulations are considered, a large ensemble of 22 global climate model simulations and a smaller ensemble of three high-resolution regional climate model simulations. The other components are two post-processing techniques, three lumped hydrological models and six probability distributions. These four sources are assessed through a method of variance decomposition applied to six flood indicators over a reference period and two future periods: 1976–2005, 2041–2070 and 2070–2099. Systematic differences are observed between basins with contrasting flood-generating processes. Snow-dominated basins consistently show larger variance contributions from hydrological models, while rain-dominated basins show climate simulations as their dominant source. These results underline the need to consider the variability of each component's uncertainty contribution and its link to hydroclimatic conditions and dominant processes. [ABSTRACT FROM AUTHOR]

There is much debate on how social values should influence scientific research. However, the question of practical applicability of philosophers’ normative proposals has received less attention. Here, we test the attainability of Matthew J. Brown’s (2020) Moral Imagination ideal (MI ideal), which aims to help scientists to make warranted value-judgements through reflecting on goals, options, values, and stakeholders of research. Here, the tools of the MI ideal are applied to a climate modelling setting, where researchers are developing aerosol-cloud interaction (ACI) parametrizations in an Earth System Model with the broader goal of improving climate sensitivity estimation. After the identification of minor obstacles to applying the MI ideal, we propose two ways to increase its applicability. First, its tools should be accompanied with more concrete guidance for identifying how social values enter more technical decisions in scientific research. Second, since research projects can have multiple goals, examining the alignment between broader societal aims of research and more technical goals should be part of the tools of the MI ideal. [ABSTRACT FROM AUTHOR]

It is now well established that global to local climate is impacted by volcanic forcing associated with major eruptions. Much attention has been given to the way in which climate is affected by such eruptions, particularly for the Northern Hemisphere, and to a considerably lesser extent for the Southern Hemisphere. Research knowledge gaps remain on such forcing impacts at finer sub‐regional spatial scales. To this end, we explore temperature responses across eight sub‐regions of Australia following three major volcanic eruptions (i.e., Krakatau, 1883; Santa Maria, 1902; Pinatubo, 1991) as simulated by CMIP5 models. We then compare such responses with station and reanalysis datasets. Model outputs indicate strongest temperature responses over more northerly regions than southerly regions of Australia, with weakest responses over Tasmania. Eastern regions of Australia seem to have strongest seasonal cooling during austral autumn, while that for northwestern coastal regions is during austral winter. In contrast, central regions of Australia cool most substantially during austral summer and/or winter, depending on the eruption. Despite such variability, initial temperature responses occur during the warmer austral months (September to February). Uncertainties exist in the reliability of CMIP5 data. For instance, temperature responses from the later Pinatubo eruption seem in stronger agreement with reanalysis data than earlier eruptions (Krakatau and Santa Maria), and while most seasonal temperature responses are stronger than those provided through reanalysis data, they are often weaker in austral spring. [ABSTRACT FROM AUTHOR]

New mathematical results are given for the radiative transfer equations alone and coupled with the temperature equation of a fluid: existence, uniqueness, a maximum principle, and a convergent monotone iterative scheme. Numerical tests for Earth's atmosphere and the heating of a pool by the Sun are included. [ABSTRACT FROM AUTHOR]

A high resolution atmospheric modelling study was done for a 20-year recent historical period. The dynamic downscaling approach adopted used the Max Planck Institute Earth System Model (MPI-ESM) to drive the WRF running in climate mode. Three online nested domains were used covering part of the North Atlantic and Europe, with a resolution 81 km, and reaching 9 km in the innermost domain which covers the Iberian Peninsula. This paper presents the validation of the WRF configuration, which is based on historic simulations between 1986 and 2005 and observational datasets of near surface temperature and precipitation for the same period. The validation was done in terms of comparison of probability distributions between model results and observations, as daily climatologies, spatially averaged inside subdomains obtained with cluster analysis of the observations, for each of the four seasons. In addition, Taylor diagrams are presented for each of the seasons and subdomains. This validation approach was repeated with the results of a new WRF simulation with the same parameterisations but forced by the ERA-Interim reanalysis. The capacity of the MPI-ESM driven WRF configuration to compare with observations and in a manner similar to the ERA-Interim driven WRF, ensures the capacity of the configuration for climate and climate change studies. Considering the difficulty to simulate extremes in long term simulations, the results showed a comfortable comparison of both models (forced by climate model and reanalysis results) with observations. This provides us confidence on the continuity of using the MPI-ESM driven WRF configuration for climate studies. [ABSTRACT FROM AUTHOR]