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Changes in the phenology of physical and ecological variables associated with climate change are likely to have significant effect on many aspects of the Baltic ecosystems. We apply a set of phenological indicators to multiple environmental variables measured by satellite sensors for 17-35 years to detect possible changes in the seasonality in the Baltic Sea environment. We detect significant temporal changes such as earlier start of the summer season and prolongation of the productive season in multiple variables ranging from basic physical drivers to ecological status indicators. While increasing trends in the absolute values of variables like sea-surface temperature (SST), diffuse attenuation of light (Ked490) and satellite-detected chlorophyll concentration (CHL) are detectable, the corresponding changes in their seasonal cycles are more dramatic. For example, the cumulative sum of 30 000Wm-2 of surface incoming shortwave irradiance (SIS) was reached 23 days earlier in 2014 compared to the beginning of the time series in 1983. The period of the year with SST of at least 17 °C has almost doubled (from 29 days in 1982 to 56 days in 2014), the period with Ked490 over 0.4m-1 has increased from about 60 days in 1998 to 240 days in 2013, i.e. quadrupled. The period with satellite-detected CHL of at least 3mgm-3 has doubled from approximately 110 days in 1998 to 220 days in 2013. While the timing of both the phytoplankton spring and summer blooms have advanced, the annual CHL maximum that in the 1980s corresponded to the spring diatom bloom in May has now switched to the summer cyanobacteria bloom in July. [ABSTRACT FROM AUTHOR]

Reproducibility is a fundamental principle of scientific research. Bitwise identical reproducibility, i.e., bitwise computational results can be reproduced, guarantees the reproduction of exactly the same results. Here we show the importance of bitwise identical reproducibility to Earth system modeling but the importance has not yet been widely recognized. Modeled mean climate states, variability and trends at different scales may be significantly changed or even lead to opposing results due to a slight change in the original simulation setting during a reproduction. Out of the large body of Earth system modeling publications, few thoroughly describe the whole original simulation setting. As a result, the reproduction of a particular simulation experiment by fellow scientists heavily depends on the interaction with the original authors, which is often inconvenient or even impossible. We anticipate bitwise identical reproducibility to be promoted as a worldwide standard, to guarantee the independent reproduction of simulation results and to further improve model development and scientific research. [ABSTRACT FROM AUTHOR]

The objective of the present work is to analyse how changes in wave patterns due to the effect of climate change can affect harbour agitation (oscillations within the port due to wind waves). The study focuses on 13 harbours located on the Catalan coast (NW Mediterranean) using a methodology with general applicability. To obtain the patterns of agitation, a Boussinesq-type model is used, which is forced at the boundaries by present/future offshore wave conditions extracted from recently developed highresolution wave projections in the NW Mediterranean. These wave projections were obtained with the SWAN model forced by present/future surface wind fields projected, re spectively, by 5 different combinations of global and regional circulation models (GCMs and RCMs) for the A1B scenario. The results show a general slight reduction in the annual average agitation for most of the ports, except for the northernmost and southernmost areas of the region, where a slight increase is obtained. A seasonal analysis reveals that the tendency to decrease is accentuated in winter. However, the inter model variability is large for both the winter and the annual analysis and many ports present at least one model configuration showing a rise in the agitation. Conversely, a general increase is found during summer, which is the period with greater activity in most of the studied ports (marinas). The latter result is more consistent among models, which illustrates the lower inter-model variability in summer. [ABSTRACT FROM AUTHOR]

More intense rainfall may cause a range of negative impacts upon society and the environment. In this study we analyzed trends in extreme ETCCDI (Expert Team on Climate Change Detection and Indices) rainfall indices in Montenegro for the period 1951-2010. Montenegro has been poorly studied in terms of rainfall extremes, yet it contains the wettest Mediterranean region known as Krivo²ije. Several indices of precipitation extremes were assessed including the number of dry days and rainfall totals, and their trends to identify possible changes. The results generally suggest that the number of days with precipitation decreased while rainfall intensity increased particularly in south-western parts of the country. A slight tendency towards intense rainfall events is suggested. Calculated trends for each index are spatially presented and examined using a plotGoogleMaps software package. This study also examined spatial pattern of relationship between extreme rainfall indices and North Atlantic Oscillation. Results suggested negative, mainly statistically significant correlations at annual, winter and autumn scale. [ABSTRACT FROM AUTHOR]

Among the most critical issues, climatic abnormalities caused by global warming also affect Taiwan significantly for the past decade. The increasing frequency of extreme rainfall events, in which concentrated and intensive rainfalls generally cause geohazards including landslides and debris flows. The extraordinary Typhoon Morakot hit Southern Taiwan on 8 August 2009 and induced serious flooding and landslides. In this study, the Kao-Ping River watershed was adopted as the study area, and the typical events 2007 Krosa Typhoon and 2009 Morakot Typhoon were adopted to train the susceptibility model. This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the Kao-Ping River watershed. The rainfall estimates were introduced in the landslide susceptibility model to produce the predictive landslide susceptibility for various rainfall scenarios, including abnormal climate conditions. These results can be used for hazard remediation, miti gation, and prevention plans for the Kao-Ping River watershed. [ABSTRACT FROM AUTHOR]

The Global Terrestrial Network for Permafrost (GTN-P) provides the first dynamic database associated with the Thermal State of Permafrost (TSP) and the Circumpolar Active Layer Monitoring (CALM) programs, which extensively collect permafrost temperature and active layer thickness data from Arctic, Antarctic and Mountain permafrost regions. The purpose of the database is to establish an "early warning system" for the consequences of climate change in permafrost regions and to provide standardized thermal permafrost data to global models. In this paper we perform statistical analysis of the GTN-P metadata aiming to identify the spatial gaps in the GTN-P site distribution in relation to climate-effective environmental parameters. We describe the concept and structure of the Data Management System in regard to user operability, data transfer and data policy. We outline data sources and data processing including quality control strategies. Assessment of the metadata and data quality reveals 63% metadata completeness at active layer sites and 50% metadata completeness for boreholes. Voronoi Tessellation Analysis on the spatial sample distribution of boreholes and active layer measurement sites quantifies the distribution inhomogeneity and provides potential locations of additional permafrost research sites to improve the representativeness of thermal monitoring across areas underlain by permafrost. The depth distribution of the boreholes reveals that 73% are shallower than 25 m and 27% are deeper, reaching a maximum of 1 km depth. Comparison of the GTN-P site distribution with permafrost zones, soil organic carbon contents and vegetation types exhibits different local to regional monitoring situations on maps. Preferential slope orientation at the sites most likely causes a bias in the temperature monitoring and should be taken into account when using the data for global models. The distribution of GTN-P sites within zones of projected temperature change show a high representation of areas with smaller expected temperature rise but a lower number of sites within arctic areas were climate models project extreme temperature increase. This paper offers a scientific basis for planning future permafrost research sites on large scales. [ABSTRACT FROM AUTHOR]

This paper investigates the impact and potential use of the cut cell vertical discretisation for forecasts of 5 days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 by forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut cell model LMZ provides a much more accurate representation of mountains on model forecasts than the terrain following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalaya, over South East China, Korea and Japan. The LMZ has been tested so far extensively for one-day forecasts on an European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut cell discretisation on forecast quality. The cut cell model is available only of an older (2003) Version of the model LM. It was compared using a control model differing by the use of the terrain following coordinate only. The cut cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved version of the terrain following model LM has been developed since then under the name CLM. The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of cut cell model were compared also to the CLM. As the cut cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalaya, the cut cell model improved the prediction of the monthly precipitation forecast even in comparison with the modern model version CLM considerably. The cut cell discretisation seems to improve in particular the localisation of precipitation, while the improvements leading from LM to CLM had a positive effect mainly on amplitude. [ABSTRACT FROM AUTHOR]

Glacial lake outburst floods (GLOFs) are among the most concerning consequences of retreating glaciers in mountain ranges worldwide. GLOFs have attracted significant attention amongst scientists and practitioners in the past 2 decades, with particular interest in the physical drivers and mechanisms of GLOF hazard and in socioeconomic and other human-related developments that affect vulnerabilities to GLOF events. This increased research focus on GLOFs is reflected in the gradually increasing number of papers published annually. This study offers an overview of recent GLOF research by analysing 594 peer-reviewed GLOF studies published between 2017 and 2021 (Web of Science and Scopus databases), reviewing the content and geographical focus as well as other characteristics of GLOF studies. This review is complemented with perspectives from the first GLOF conference (7–9 July 2021, online) where a global GLOF research community of major mountain regions gathered to discuss the current state of the art of integrated GLOF research. Therefore, representatives from 17 countries identified and elaborated trends and challenges and proposed possible ways forward to navigate future GLOF research, in four thematic areas: (i) understanding GLOFs – timing and processes; (ii) modelling GLOFs and GLOF process chains; (iii) GLOF risk management, prevention and warning; and (iv) human dimensions of GLOFs and GLOF attribution to climate change. [ABSTRACT FROM AUTHOR]

The carbon budget concept states that the global mean temperature (GMT) increase is roughly linearly dependent on cumulative emissions of CO 2. The proportionality is measured as the transient climate response to cumulative emissions of carbon dioxide (TCRE). In this paper, the deviations of the carbon budget from the strict linear relationship implied by the TCRE are examined through the lens of a temperature response to an emission pulse (i.e., pulse response) and its relationship with a nonlinear TCRE. Hereby, two sources of deviation are distinguished: emission scenario and climate state dependence. The former stems from the scenario choice, i.e., the specific emission pathway for a given level of cumulative emissions and the latter from the change in TCRE with changing climatic conditions. Previous literature argues for scenario independence using a stylized set of emission scenarios, and offers a way to fit a nonlinear carbon budget equation. This paper shows how the pulse response, viewed as a Green's function, gives a unifying perspective on both scenario and state dependence. Moreover, it provides an optimization program that tests the scenario independence under the full range of emission pathways for a given set of constraints. In a setup chosen in this paper, the deviations stemming from emission pathway choices are less than 10 % of the overall temperature increase and gradually diminish. Moreover, using the pulse response as a Green's function, the scenario-dependent effects of a reduced-complexity climate model were replicated to a high degree, confirming that the behavior of scenario-dependent deviations can be explained and predicted by the shape of the pulse response. Additionally, it is shown that the pulse response changes with climatic conditions, through which the carbon budget state dependency is explained. Using a pulse response as an approximation for a state-dependent TCRE, an alternative method to derive a nonlinear carbon budget equation is provided. Finally, it is shown how different calibrations of a model can lead to different degrees of carbon budget nonlinearities. The analysis is done using FaIRv2.0.0, a simple climate emulator model that includes climate feedback modifying the carbon cycle, along with a one-box model used for comparison purposes. The Green's function approach can be used to diagnose both models' carbon budget scenario dependency, paving the way for future investigations and applications with other and more complex models. [ABSTRACT FROM AUTHOR]

The current scenario of understanding spatial objects with regards to land and marine environment seems lacking. Inevitably, the scenario in line with the global warming issues as being highly mentioned by world-bodies such as the United Nations (UN) on climate change, etc. Recently the statistics on earth surface temperature point towards high record temperatures that lead to sea-level rise and degradation of land surface area, in general. These situations caused other spatial objects (land and marine properties) to be affected by their physical properties' changes (including geometries and locations). Thus, this paper attempts to review various aspects related to digital twins of land and marine spatial objects with respect to issues and challenges of multiple data acquisition techniques considering accuracy, data standard, seamless and integrated georeferenced data within the scenario as being reported in the 6th IPCC document. The situation warrants us to explore different types of land and marine properties (static and dynamic) where static properties are defined as immovable objects and vice versa for the dynamic environment. This paper also discusses on a brief experiment utilizing MERIT DEM (Multi-Error-Removed Improved-Terrain Digital Elevation Model), existing building footprints, simulated bathymetry, and land use datasets. The experiment reveals the prediction of the sea level rise according to the IPCC report. The gist of this paper to serve a motivation for our near-future research in the context of geospatial components and sea level rise (SLR). [ABSTRACT FROM AUTHOR]

The heating of drinking water in households contributes for a significant amount to the emission of greenhouse gases. As a water utility aiming to operate climate neutral by 2020, Waternet needs to reduce its CO2 emission by 53 kton yr-1. To contribute to this ambition, a pilot project was carried out in Uilenstede, Amstelveen, the Netherlands, to recover the shower heat energy with a shower heat exchanger from Dutch Solar Systems. An experimental set up was built in the Waternet laboratory to compare field conditions and lab conditions. The energy recovery efficiency observed in the lab was 61-64% under winter conditions and 58-62% under summer conditions, while the energy recovery efficiency observed in Uilenstede was 57% in December 2014. Based on the observations, 4% of the total energy consumption of households in Amsterdam (electricity and gas) can be recovered with a shower heat exchanger installed in all households in Amsterdam, which also means a 54 kton yr-1 CO2 emission reduction. [ABSTRACT FROM AUTHOR]

Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multimodel predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation. [ABSTRACT FROM AUTHOR]

A newly developed global climate model FESOM-ECHAM6 with an unstructured mesh and high resolution is applied to investigate to what degree the area-thickness distribution of new ice formed in open water affects the ice and ocean properties. A sensitivity experiment is performed which reduces the horizontal-to-vertical aspect ratio of open-water ice growth. The resulting decrease in the Arctic winter sea-ice concentration strongly reduces the surface albedo, enhances the ocean heat release to the atmosphere, and increases the sea-ice production. Furthermore, our simulations show a positive feedback mechanism among the Arctic sea ice, the Atlantic Meridional Overturning Circulation (AMOC), and the surface air temperature in the Arctic, as the sea ice transport affects the freshwater budget in regions of deep water formation. A warming over Europe, Asia and North America, associated with a negative anomaly of Sea Level Pressure (SLP) over the Arctic (positive phase of the Arctic Oscillation (AO)), is also simulated by the model. For the Southern Ocean, the most pronounced change is a warming along the Antarctic Circumpolar Current (ACC), especially for the Pacific sector. Additionally, a series of sensitivity tests are performed using an idealized 1-D thermodynamic model to further investigate the influence of the open-water ice growth, which reveals similar results in terms of the change of sea ice and ocean temperature. In reality, the distribution of new ice on open water relies on many uncertain parameters, for example, surface albedo, wind speed and ocean currents. Knowledge of the detailed processes is currently too crude for those processes to be implemented realistically into models. Our sensitivity experiments indicate a pronounced uncertainty related to open-water sea ice growth which could significantly affect the climate system. [ABSTRACT FROM AUTHOR]

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high spatial density network of 99 silicon photodiode pyranometers was set up around Jülich (10km×12km area) from April to July 2013, to capture the variability in the radiation field at the surface induced by small-scale cloud inhomogeneity. Each of these autonomously operated pyranometer stations was equipped with weather sensors for simultaneous measurements of ambient air temperature and relative humidity. In this paper, we provide the details of this unique setup of the pyranometer network and the data analysis with initial quality screening procedure we adopted. We also present some exemplary cases consisting of the days with clear, broken cloudy and overcast skies to assess our spatio-temporal observations from the network, and validate their consistency with other collocated radiation measurements available during the HOPE period. [ABSTRACT FROM AUTHOR]

The Weddell Gyre plays a crucial role in the modification of climate by advecting heat poleward to the Antarctic ice shelves and by regulating the density of water masses that feed the lowest limb of the global ocean overturning circulation. However, our understanding of Weddell Gyre water mass properties is limited to regions of data availability, primarily along the Prime Meridian. The aim of this paper is to provide a dataset of the upper water column properties of the entire Weddell Gyre. Objective mapping was applied to Argo float data in order to produce spatially gridded, time composite maps of temperature and salinity for fixed pressure levels ranging from 50 to 2000 dbar, as well as temperature, salinity and pressure at the level of the subsurface temperature maximum. While the data are currently too limited to incorporate time into the gridded structure, the data are extensive enough to produce maps of the entire region across three time composite periods (2002-2005, 2006-2009 and 2010-2013), which can be used to determine how representative conclusions drawn from data collected along general RV transect lines are on a gyre scale perspective. The work presented here represents the technical prerequisite in addressing climatological research questions in forthcoming studies. These data sets are available in netCDF format at doi:10.1594/PANGAEA.842876. [ABSTRACT FROM AUTHOR]

In this paper a new process-based, weather-driven model for ammonia (NH3) emission from a urine patch has been developed and its sensitivity to various factors assessed. This model, the GAG model (Generation of Ammonia from Grazing) was developed as a part of a suite of weather-driven NH3 exchange models, as a necessary basis for assessing the effects of climate change on NH3 related atmospheric processes. GAG is capable of simulating the TAN (Total Ammoniacal Nitrogen) content, pH and the water content of the soil under a urine patch. To calculate the TAN budget, GAG takes into account urea hydrolysis as a TAN input and NH3 volatilization as a loss. In the water budget, in addition to the water content of urine, precipitation and evaporation are also considered. In the pH module we assumed that the main regulating processes are the dissociation and dissolution equilibria related to the two products of urea hydrolysis: ammonium and bicarbonate. Finally, in the NH3 exchange flux calculation we adapted a canopy compensation point model that accounts for exchange with soil pores and stomata as well as deposition to the leaf surface. We validated our model against measurements, and carried out a sensitivity analysis. The validation showed that the simulated parameters (NH3 exchange flux, soil pH, TAN budget and water budget) are well captured by the model (r > 0.5 for every parameter at p < 0.01 significance level). We found that process-based modelling of pH is necessary to reproduce the temporal development of NH3 emission. In addition, our results suggested that more sophisticated simulation of CO2 emission in the model could potentially improve the modelling of pH. The sensitivity analysis highlighted the vital role of temperature in NH3 exchange; however, presumably due to the TAN limitation, the GAG model currently provides only a modest overall temperature dependence in total NH3 emission compared with the values in the literature. Since all the input parameters can be obtained for study at larger scales, GAG is potentially suitable for larger scale application, such as in regional atmospheric and ecosystem models. [ABSTRACT FROM AUTHOR]

Motivated by the need to predict how the Arctic atmosphere will change in a warming world, this article summarizes recent advances made by the research consortium NETCARE (Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments) that contribute to our fundamental understanding of Arctic aerosol particles as they relate to climate forcing. The overall goal of NETCARE research has been to use an interdisciplinary approach encompassing extensive field observations and a range of chemical transport, earth system, and biogeochemical models. Several major findings and advances have emerged from NETCARE since its formation in 2013. (1) Unexpectedly high summertime dimethyl sulfide (DMS) levels were identified in ocean water (up to 75 nM) and the overlying atmosphere (up to 1 ppbv) in the Canadian Arctic Archipelago (CAA). Furthermore, melt ponds, which are widely prevalent, were identified as an important DMS source (with DMS concentrations of up to 6 nM and a potential contribution to atmospheric DMS of 20 % in the study area). (2) Evidence of widespread particle nucleation and growth in the marine boundary layer was found in the CAA in the summertime, with these events observed on 41 % of days in a 2016 cruise. As well, at Alert, Nunavut, particles that are newly formed and grown under conditions of minimal anthropogenic influence during the months of July and August are estimated to contribute 20 % to 80 % of the 30–50 nm particle number density. DMS-oxidation-driven nucleation is facilitated by the presence of atmospheric ammonia arising from seabird-colony emissions, and potentially also from coastal regions, tundra, and biomass burning. Via accumulation of secondary organic aerosol (SOA), a significant fraction of the new particles grow to sizes that are active in cloud droplet formation. Although the gaseous precursors to Arctic marine SOA remain poorly defined, the measured levels of common continental SOA precursors (isoprene and monoterpenes) were low, whereas elevated mixing ratios of oxygenated volatile organic compounds (OVOCs) were inferred to arise via processes involving the sea surface microlayer. (3) The variability in the vertical distribution of black carbon (BC) under both springtime Arctic haze and more pristine summertime aerosol conditions was observed. Measured particle size distributions and mixing states were used to constrain, for the first time, calculations of aerosol–climate interactions under Arctic conditions. Aircraft- and ground-based measurements were used to better establish the BC source regions that supply the Arctic via long-range transport mechanisms, with evidence for a dominant springtime contribution from eastern and southern Asia to the middle troposphere, and a major contribution from northern Asia to the surface. (4) Measurements of ice nucleating particles (INPs) in the Arctic indicate that a major source of these particles is mineral dust, likely derived from local sources in the summer and long-range transport in the spring. In addition, INPs are abundant in the sea surface microlayer in the Arctic, and possibly play a role in ice nucleation in the atmosphere when mineral dust concentrations are low. (5) Amongst multiple aerosol components, BC was observed to have the smallest effective deposition velocities to high Arctic snow (0.03 cm s -1). [ABSTRACT FROM AUTHOR]

The Coupled Model Intercomparison Project (CMIP) is one of the biggest international efforts aimed at better understanding the past, present, and future of climate changes in a multi-model context. A total of 21 model intercomparison projects (MIPs) were endorsed in its sixth phase (CMIP6), which included 190 different experiments that were used to simulate 40 000 years and produced around 40 PB of data in total. This paper presents the main findings obtained from the CPMIP (the Computational Performance Model Intercomparison Project), a collection of a common set of metrics, specifically designed for assessing climate model performance. These metrics were exclusively collected from the production runs of experiments used in CMIP6 and primarily from institutions within the IS-ENES3 consortium. The document presents the full set of CPMIP metrics per institution and experiment, including a detailed analysis and discussion of each of the measurements. During the analysis, we found a positive correlation between the core hours needed, the complexity of the models, and the resolution used. Likewise, we show that between 5 %–15 % of the execution cost is spent in the coupling between independent components, and it only gets worse by increasing the number of resources. From the data, it is clear that queue times have a great impact on the actual speed achieved and have a huge variability across different institutions, ranging from none to up to 78 % execution overhead. Furthermore, our evaluation shows that the estimated carbon footprint of running such big simulations within the IS-ENES3 consortium is 1692 t of CO 2 equivalent. As a result of the collection, we contribute to the creation of a comprehensive database for future community reference, establishing a benchmark for evaluation and facilitating the multi-model, multi-platform comparisons crucial for understanding climate modelling performance. Given the diverse range of applications, configurations, and hardware utilised, further work is required for the standardisation and formulation of general rules. The paper concludes with recommendations for future exercises aimed at addressing the encountered challenges which will facilitate more collections of a similar nature. [ABSTRACT FROM AUTHOR]

A new microwave satellite water vapour retrieval for use in polar winter conditions is presented. The retrieval employs a priori information and an iterative approach. It is tested using simulated and actual measurements from the Microwave Humidity Sounder (MHS) satellite instruments. Ground truth is provided by the G-band vapor radiometer (GVR) at Barrow, Alaska. For water vapour columns less than 6kgm-2, comparison with the GVR gives a standard deviation of 0.39kgm-2 and a systematic bias of 0.08kgm-2. The errors are shown to be significantly less than for other satellite measurement systems. The errors are comparable to those from atmospheric reanalyses; however, the MHS data come at much higher horizontal resolution (< 40km) and are shown to reveal more structure. The retrieval can be used to obtain pan-Arctic maps of water vapour columns of unprecedented quality. The retrieval may also be applied to the Special Sensor Microwave Imager/Sounder (SSMIS) and the Advanced Technology Microwave Sounder (ATMS). [ABSTRACT FROM AUTHOR]

As part of the terrestrial branch of the Japan-funded Arctic Climate Change Research Project (GRENE-TEA), which aims to clarify the role and function of the Arctic terrestrial system in the climate system, and assess the influence of its changes on a global scale, this model intercomparison project (GTMIP) is planned and being conducted to (1) enhance communication and understanding between the "minds and hands" (i.e., between the modelling and field scientists) and (2) assess the uncertainty and variations stemming from variability in model implementation/design and in model outputs due to climatic and historical conditions in the Arctic terrestrial regions. This paper provides an overview and the experiment protocol of Stage 1 of the project, site simulations driven by statistically fitted data created using the GRENE-TEA site observations for the last three decades. The target metrics for the model evaluation cover key processes in both physics and biogeochemistry, including energy budgets, snow, permafrost, phenology, and carbon budgets. The preliminary results on four metrics (annual mean latent heat flux, annual maximum snow depth, gross primary production, and net ecosystem production) already demonstrate the range of variations in reproducibility among existing models and sites. Full analysis on annual as well as seasonal time scales, to be conducted upon completion of model outputs submission, will delineate inter-dependence among the key processes, and provide the clue for improving the model performance. [ABSTRACT FROM AUTHOR]

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE Project (Spruce and Peatland Responses Under Climatic and Environmental Change, http: //mnspruce.ornl.gov) is such an experiment funded by the Department of Energy's (DOE), Oce of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, the cycling and release of CO2 and CH4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. To successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are: 1. Data acquisition and control system - set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components. 2. Data collection system - set of hardware and software to deliver data to a central depository for storage and further processing. 25 3. Data management plan - set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an eficient data system for managing high volume sources of in-situ observations in a remote, harsh environmental location. The approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data. [ABSTRACT FROM AUTHOR]

This paper advances understanding of the impacts of climate change on crops in China by moving from ex-post analysis to forecasting, and by demonstrating how the effects of climate change will affect the growth period and the planting boundaries of winter wheat. Using a multiple regression model based on agricultural meteorological observations and the IPCC AR5 GCMs simulations, we find that the sowing date of winter wheat in the base period, 2040s and 2070s, shows a gradually delayed trend from north to south and the growth period of winter wheat in China will be shortened under climate change. The simulation results also show that (i) the north planting boundaries of winter wheat in China will likely move northward and expand westward in the future, while the south planting boundary will rise and spread in south Hainan and Taiwan; and (ii) the Xinjiang Uygur Autonomous Region and the Inner Mongolia Autonomous Region will have the largest increases in planting areas in 2040s and 2070s. Our simulation implies that Xinjiang and Inner Mongolia are more sensitive to climate change than other regions in China and priority should be given to design adaptation strategies for winter wheat planting for these provinces. [ABSTRACT FROM AUTHOR]

Turkana, in northwest Kenya, is the country's poorest and least developed county. Pastoralism in Turkana is well adapted to the harsh climatic conditions but an increase in drought frequency associated with global climate change and intensifying violent conflicts between pastoral groups, poses significant challenges for local communities. The conflicts are especially violent in the border region between the Turkana and the Pokot communities. In this very region significant oil reserves have been found recently. The first aim of this paper is to analyse how the oil exploration affects the communities' vulnerability to climate change. Secondly, the paper explores the risk of the oil explorations to create new conflicts or aggravate existing ones. The primary method of the study is qualitative field research supplemented with a geo-spatial analysis of conflict data. The field research was conducted in October 2013 and April 2014 in three villages with different levels of engagement with the oil exploration. At the time of the research, oil exploration was expected close to Lokwamosing while it had recently started in the vicinity of Lopii and had been ongoing for a longer time close to Nakukulas. The findings suggest that the oil exploration increases the community's vulnerability to climate change. Further, unmet community expectations for water, employment and development pose a significant risk for violent conflict between local communities and the operating oil company. Intercommunal conflict over water and land could increase as well. [ABSTRACT FROM AUTHOR]

This paper proposes a method that allows the detection of trends in the frequency of extreme events and its attribution to changes in atmospheric dynamics characterized through Circulation Types (CTs). The method is applied to summer Extremely Hot Days (EHD) in Spain during the period 1958-2008. For carrying out this exercise, regional series of daily maximum temperature are derived from the regional dataset Spain02. Eight regions with different daily maximum temperature variability are identified. All of them exhibit important trends in the occurrence of EHDs, especially in inner regions. Links between the probability of EHD occurrence in the regions and CTs have been cal10 culated. Furthermore, the consistency of the results to the atmospheric variables used in defining the CTs is analyzed. Sea Level Pressure (SLP), Temperature at 850 hPa Level (T850) and Geopotential Height at 500 hPa Level (Z500) from the ERA40 dataset have been used for the six CT classifications obtained using the variables separately and in different combinations of pairs. The optimum choice of large scale variables depends on the region under consideration, being the combination SLP-T850 the one giving the most suitable characterization for most of them. Finally, an attribution exercise of the regional EHD trends to the dynamics is proposed. Results show that the maximum of attributable EHD trends to changes in dynamics in every region is always below 50%, being even lower than 20% in those regions with the largest EHD trends, mainly located in the center of the Iberian Peninsula (IP). [ABSTRACT FROM AUTHOR]

Coccolithophores are sensitive recorders of environmental change. The size of their coccosphere varies in the ocean along gradients of environmental conditions and provides a key for understanding the fate of this important phytoplankton group in the future ocean. But interpreting field changes in coccosphere size in terms of laboratory observations is hard, mainly because the marine signal reflects the response of multiple morphotypes to changes in a combination of environmental variables. In this paper I examine the large corpus of published laboratory experiments with coccolithophores looking for relations between environmental conditions, metabolic rates and cell size (a proxy for coccosphere size). I show that growth, photosynthesis, and to a lesser extent calcification, co-vary with cell size when pCO2, irradiance, temperature, nitrate, phosphate and iron conditions change. With the exception of phosphate and temperature, a change from limiting to non-limiting conditions always results in an increase in cell size. An increase in phosphate or temperature produces the op15 posite effect. The magnitude of the coccosphere size changes observed in the laboratory is comparable to that observed in the ocean. If the biological reasons behind the environment-metabolism-size link are understood, it will be possible to use coccosphere size changes in the modern ocean and in marine sediments to investigate the fate of coccolithophores in the future ocean. This reasoning can be extended to the size of coccoliths if, as recent experiments are starting to show, coccolith size reacts to environmental change proportionally to coccosphere size. I introduce a simple model that simulates the growth rate and the size of cells forced by nitrate and phosphate concentrations. By considering a simple rule that allocates the energy flow from nutrient acquisition to cell structure (biomass) and cell maturity (biological complexity, eventually leading to cell division), the model is able to reproduce the co-variation of growth rate and cell size observed in the laboratory when these nutrients become limiting. These results support ongoing efforts to interpret coccosphere and coccolith size measurements in the context of climate change. [ABSTRACT FROM AUTHOR]

The catastrophic Zhouqu debris flows, which were induced by heavy rainfall, occurred at approximately midnight of 7 August 2010 (Beijing time, UTC+8) and claimed 1765 lives. Broadband seismic signals recorded by the Zhouqu seismic station nearby are acquired and analyzed in this paper. The seismic signals are divided into two separate parts for the first time using the crucial time of 23:33:10 (Bejing time, UTC +8), with distinctly different frequency characteristics on time-by-time normalized spectrograms and amplitude increasing patterns on smoothed envelopes. They are considered to be generated by the development stage and the maturity stage of the Sanyanyu debris flow respectively. Seismic signals corresponding to the development stage have a broader main frequency band of approximately 0-15 Hz than that of the maturity stage, which is around 1-10 Hz. The N-S component can detect the development stage of the debris flow about 3 min earlier than other components due to its southward flow direction. Two sub-stages within the maturity stage are recognized from best-fitted amplitude increasing velocities and the satellite image of the Sanyanyu flow path and the mean movement velocities of the Sanyanyu debris flow during these two sub-stages are estimated to be 9.2 and 9.7ms-1 respectively. [ABSTRACT FROM AUTHOR]

The realization of national climate change commitments, as agreed through international negotiations, requires local action. However, data is still insufficient to make accurate statements about the scale of urban emissions (UNHABITAT, 2011). The need of comparable emission inventories at city level, including smaller cities, is widely recognized to develop evidence-based policies accounting for the relation between emissions and institutional, socio-economic and demographic characteristics at city level. This paper presents a collection of harmonized greenhouse gases (GHG) emission inventories (the "CoM sample 2013") at municipal level directly computed by the cities and towns that participate in the EU Covenant of Mayors initiative. This is the mainstream European movement of local and regional authorities who voluntarily commit to reduce GHG emissions by 20% or more by 2020. The "CoM sample 2013" (http://edgar.jrc.ec.europa.eu/com/data/index.php? SECURE=123, doi:10.2904/EDGARcom2013) has been carefully checked to ensure its internal consistency and its congruity with respect to internationally accepted guide values for emission factors. Overall, it provides valuable data for the analysis of the heterogeneity of final energy consumption and greenhouse gas emissions of cities. [ABSTRACT FROM AUTHOR]

Management of temperate forests has the potential to increase carbon sinks and mitigate climate change. However, those opportunities may be confounded by negative climate change impacts. We therefore need a better understanding of climate change alterations to temperate forest carbon dynamics before developing mitigation strategies. The purpose of this project was to investigate the interactions of species composition, fire, management and climate change on the Copper–Pine creek valley, a temperate coniferous forest with a wide range of growing conditions. To do so, we used the LANDIS-II modelling framework including the new Forest Carbon Succession extension to simulate forest ecosystems under four different productivity scenarios, with and without climate change effects, until 2050. Significantly, the new extension allowed us to calculate the Net Sector Productivity, a carbon accounting metric that integrates above and below-ground carbon dynamics, disturbances, and the eventual fate of forest products. The model output was validated against literature values. The results implied that the species optimum growing conditions relative to current and future conditions strongly influenced future carbon dynamics. Warmer growing conditions led to increased carbon sinks and storage in the colder and wetter ecoregions but not necessarily in the others. Climate change impacts varied among species and site conditions and this indicates that both of these components need to be taken into account in when considering climate change mitigation activities and adaptive management. The introduction of a new carbon indicator – Net Sector Productivity, promises to be useful in assessing management effectiveness and mitigation activities. [ABSTRACT FROM AUTHOR]

We applied a coupled, marine water column model to three sites in the North Sea. The three sites represent different hydrodynamic regimes and are thus representative of a wider area. The model consists of a hydro-biogeochemical model (GOTM-ERSEM-BFM) coupled one way upwards to a size-structured model representing pelagic predators and detritivores (Blanchard et al., 2009). Thus, bottom-up pressures like changing abiotic environment (climate change, chemical cycling) impact on fish biomass across the size spectrum. Here, we studied three different impacts of future conditions on fish yield: climatic impacts (medium emission scenario), abiotic ocean acidification impacts (reduced pelagic nitrification) and biotic ocean acidification impacts (reduced detritivore growth rate). The three impacts were studied separately and combined, and showed that sites within different hydrodynamic regimes responded very differently. The seasonally stratified site showed an increase in fish yields (occuring in winter and spring), with acidification effects of the same order of magnitude as climatic effects. The permanently mixed site also showed an increase in fish yield (increase in summer, decrease in winter), due to climatic effects moderated by acidification impacts. The third site, which is characterised by large interannual variability in thermal stratification duration, showed a decline in fish yields (occuring in winter) due to decline of the benthic system which forms an important carbon pathway at this site. All sites displayed a shift towards a more pelagic oriented system. [ABSTRACT FROM AUTHOR]

By coordinating the design and distribution of global climate model simulations of the past, current and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima experiments) and the CMIP Historical Simulation (1850-near-present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP, (2) common standards, coordination, infrastructure and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble, and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and the CMIP Historical Simulation to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP Historical Simulation, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. The participation in the CMIP6-Endorsed MIPs will be at the discretion of the modelling groups, and will depend on scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: (i) how does the Earth system respond to forcing?, (ii) what are the origins and consequences of systematic model biases?, and (iii) how can we assess future climate changes given climate variability, predictability and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and the CMIP6 Historical Simulation, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs. [ABSTRACT FROM AUTHOR]

Common ragweed (Ambrosia artemisiifolia L.) is a highly allergenic and invasive plant in Europe. Its pollen can be transported over large distances and has been recognized as a significant cause of hayfever and asthma (D'Amato et al., 2007; Burbach et al., 2009). To simulate production and dispersion of common ragweed pollen, we implement a pollen emission and transport module in the Regional Climate Model (RegCM) version 4 using the framework of the Community Land Model (CLM) version 4.5. In the online model environment where climate is integrated with dispersion and vegetation production, pollen emissions are calculated based on the modelling of plant distribution, pollen production, species-specific phenology, flowering probability, and flux response to meteorological conditions. A pollen tracer model is used to describe pollen advective transport, turbulent mixing, dry and wet deposition. The model is then applied and evaluated on a European domain for the period 2000-2010. To reduce the large uncertainties notably due to ragweed density distribution on pollen emission, a calibration based on airborne pollen observations is used. Resulting simulations show that the model captures the gross features of the pollen concentrations found in Europe, and reproduce reasonably both the spatial and temporal patterns of flowering season and associated pollen concentrations measured over Europe. The model can explain 68.6, 39.2, and 34.3 % of the observed variance in starting, central, and ending dates of the pollen season with associated root mean square error (RMSE) equal to 4.7, 3.9, and 7.0 days, respectively. The correlation between simulated and observed daily concentrations time series reaches 0.69. Statistical scores show that the model performs better over the central Europe source region where pollen loads are larger. From these simulations health risks associated common ragweed pollen spread are then evaluated through calculation of exposure time above health-relevant threshold levels. The total risk area with concentration above 5 grains m-3 takes up 29.5 % of domain. The longest exposure time occurs on Pannonian Plain, where the number of days per year with the daily concentration above 20 grains m-3 exceeds 30. [ABSTRACT FROM AUTHOR]

The DEEP site sediment sequence obtained during the ICDP SCOPSCO project at Lake Ohrid was dated using tephrostratigraphic information, cyclostratigraphy, and orbital tuning through marine isotope record. Although this approach is suitable for the generation of a general chronological framework of the long succession, it is insufficient to resolve more detailed paleoclimatological questions, such as leads and lags of climate events between marine and terrestrial records or between different regions. In this paper, we demonstrate how the use of different tie points can affect cyclostratigraphy and orbital tuning for the period between ca. 140 and 70 ka and how the results can be correlated with directly/indirectly radiometrically-dated Mediterranean marine and continental proxy records. The alternative age model obtained shows consistent differences with that proposed by Francke et al. (2015) for the same interval, in particular at the level of the MIS6-5e transition. According to this age model, different proxies from the DEEP site sediment record support an increase of temperatures between glacial to interglacial conditions, which is almost synchronous with a rapid increase in sea surface temperature observed in the western Mediterranean. The results show how important a detailed study of independent chronological tie points is for synchronizing different records and to highlight asynchronisms of climate events. [ABSTRACT FROM AUTHOR]

A new generation of an Earth System Model now includes a number of land surface processes directly relevant to analyzing potential impacts of climate change. This model, HadGEM2-ES, allows us to assess the impacts of climate change, multiple interactions, and feedbacks as the model is run. This paper discusses the results of century-scale HadGEM2-ES simulations from an impacts perspective--specifically, terrestrial ecosystems and water resources--for four different scenarios following the Representative Concentration Pathways (RCPs), being used for next assessment report of the Intergovernmental Panel on Climate Change (IPCC). Over the 21st Century, simulated changes in global and continential-scale terrestrial ecosystems due to climate change appear to be very similar in all 4 RCPs, even though the level of global warming by the end of the 21st Century ranges from 2°C in the lowest scenario to 5.5°in the highest. A warming climate generally favours broadleaf trees over needleleaf, needleleaf trees over shrubs, and shrubs over herbaceous vegetation, resulting in a poleward shift of temperate and boreal forests and woody tundra in all scenarios. Although climate related changes are slightly larger in scenarios of greater warming, the largest differences between scenarios arise at regional scales as a consequence of different patterns of anthropogenic land cover change. In the model, the scenario with the lowest global warming results in the most extensive decline in tropical forest cover due to a large expansion of agriculture. Under all four RCPs, fire potential could increase across extensive land areas, particularly tropical and sub-tropical latitudes. River outflows are simulated to increase with higher levels of CO2 and global warming in all projections, with outflow increasing with mean temperature at the end of the 21st Century at the global scale and in North America, Asia, and Africa. In South America, Europe, and Australia, the relationship with climate warming and CO2 rise is less clear, probably as a result of land cover change exerting a dominant effect in those regions. [ABSTRACT FROM AUTHOR]

The article presents a study which describe the Pliocene Model Intercomparison Project (PlioMIP) using the Hadley Centre Model both in atmosphere-ocean coupled mode and atmosphere-only mode. It states that a greater overall warming relative to the control than the atmosphere-only was predicted by the coupled model. The result of the study shows that a reduction in equatorial precipitation and south Asian monsoon was predicted by the atmospheric-only model.

Wave climates are fundamental drivers of coastal vulnerability and changing trends in wave height, period and direction can severely impact coastlines. In a diverse storm environment, the changes in these parameters are difficult to detect and quantify. Since wave climates are linked to atmospheric circulation patterns an automated and objective classification scheme was developed to explore links between synoptic scale circulation patterns and wave climate variables, specifically wave heights. The algorithm uses a set of objective functions based on wave heights to guide the classification. Fuzzy rules define classification types that are used to detect locally high and low pressure anomalies through a process of simulated annealing. The optimized classification focuses on extreme wave events. The east coast of South Africa was used as a case study. The results show that three dominant patterns drive extreme wave events. The circulation patterns exhibit some seasonality with one pattern present throughout the year. Some 50-80% of the extreme wave events are explained by these three paterns. It is evident that strong low pressure anomalies east of the country drive a wind towards the KwaZulu-Natal coastline which results in extreme wave conditions. We conclude that the methodology can be used to link circulation patterns to wave heights within a diverse storm environment. The circulation patterns agree with qualitative observations of wave climate drivers. There are applications to the assessment of coastal vulnerability and the management of coastlines worldwide. [ABSTRACT FROM AUTHOR]

The annual average CO2 difference between baseline data from Mauna Loa and the southern Hemisphere increased by ~ 0.8 µmolmol-1 (0.8 ppm) between 2009 and 2010, a step unprecedented in over 50 years of reliable data. We find no evidence for coinciding, sufficiently large and rapid, source/sink changes. A statistical anomaly is unlikely due to the highly systematic nature of the variation in observations. An explanation for the step, and the subsequent 5 year stability in this north-south difference, involves inter-hemispheric atmospheric exchange variation. The selected data describing this episode provide a critical test for studies that employ atmospheric transport models that interpret global carbon budgets and inform management of anthropogenic emissions. [ABSTRACT FROM AUTHOR]

Mussel shells are potential bioarchives of proxies for changes of the physico-chemical conditions in the bivalve's habitat. One such proxy is the distribution of the Rare Earths and Yttrium (REY) in seawater, as REY speciation in seawater is sensitive to pH and temperature variations, due to the impact of these parameters on the activity of CO32 in seawater. We present a new protocol for sample preparation and determination of REY concentrations in bivalve shells, that includes sample treatment with NaOCl followed by REY separation and preconcentration. The data obtained was further used to calculate REY partition coefficients between shells of M. edulis and ambient seawater, and acquired results were then used in the investigation of the potential effects of pH and temperature on REY partitioning. Shells of M. edulis mussels from the North Sea show consistent shale-normalized ("SN") REY patterns that increase from the light REY to the middle REY and decrease from the middle REY to the heavy REY. Despite being different to the general seawater REYSN pattern, the shells still display distinct REY features of seawater such as a negative CeSN anomaly and small positive YSN and GdSN anomalies. Apparent partition coefficients for the REY between the shell and seawater (appDREYshell/seawater) are low and decrease strongly from the light REY (4.04 for La) to the heavy REY (0.34 for Lu). However, assuming that only the free REY3+ are incorporated into the shell, appDREY3+shell/seawater values are higher and rather similar for all REY (102.46 for La; 113.44 for Lu), but show a slight maximum at Tb (199.18). Although the impact of vital effects i.e. REY speciation in a mussel's extrapallial fluid from which the carbonate minerals precipitate, cannot be quantified yet, it appears that M. edulis shells are bioarchives of some REY features of seawater. We modelled the REYSN patterns of a hypothetical mussel shell at pH 8.2 and 7.6 and at temperatures of 25 and 5 °C assuming that only REY3+ are incorporated into the carbonate's crystal lattice. The results suggest that with lower pH, REY concentrations in a shells increase, but with little effect on the shape of the REYSN patterns, while a temperature change has an impact on the REYSN pattern, but only minor effects on REY concentrations. [ABSTRACT FROM AUTHOR]

Models used to investigate impacts of climatic changes on spatio-temporal vegetation dynamics need to balance required accuracy with computational feasibility. To enhance the computational efficiency of these models, upscaling methods are required that maintain key fine-scale processes influencing vegetation dynamics. In this paper, an adjustable method - the dynamic two-layer classification concept (D2C) - for the upscaling of time- and space-discrete models is presented. D2C aims to separate potentially repetitive calculations from those specific to single grid cells. The underlying idea is to extract processes that do not require information about a grid cell's neighbourhood to a reduced-size non-spatial layer, which is dynamically coupled to the original two-dimensional layer. The size of the non-spatial layer is thereby adaptive and depends on dynamic classifications according to pre-specified similarity criteria. I present how D2C can be used in a model implementation on the example of TreeMig-2L, a new, efficient version of the intermediate-complexity forest-landscape model TreeMig. To discuss the trade-off between computational expenses and accuracy, as well as the applicability of D2C, I compare different model stages of TreeMig-2L via simulations of two different application scenarios. This comparison of different model stages demonstrates that applying D2C can strongly reduce computational expenses of processes calculated on the new non-spatial layer. D2C is thus a valuable upscaling method for models and applications in which processes requiring information about the neighbourhood constitute the minor share of the overall computational expenses. [ABSTRACT FROM AUTHOR]

In recent years, research on climate change and human security has received much attention among policy makers and academia alike. Communities in the Global South that rely on an intact resource base will especially be affected by predicted changes in temperature and precipitation. The objective of this article is to better understand under what conditions local communities can adapt to anticipated impacts of climate change and avoid conflict over the loss of resources. The empirical part of the paper answers the question to what extent local communities in the Chilwa Basin in Malawi have experienced climate change and how they are affected by it. Further, it assesses one of Malawi's adaptation projects designed to build resilience to a warmer and more variable climate, and points to some of its limitations. This research shows that not all adaptation strategies are suited to cope with a warmer and more variable climate. [ABSTRACT FROM AUTHOR]

Natural wetlands are among the most important sources of methane; thus, these areas are important for better understanding long-term temporal variations in atmospheric methane concentration. During the last 60 years, wetlands have experienced extensive conversion and global impacts from climate warming, which makes the estimation of methane emission from wetlands highly uncertain. In this paper, we present a modeling framework, integrating CH4MODWETLAND, TOPMODEL and TEM models, to analyze the temporal and spatial variations in CH4 emissions from natural wetlands (including inland wetlands, coastal wetlands, lakes and rivers) in China. Our analysis revealed an increase of 25.5 %, averaging 0.52g m-2 per decade, in national CH4 fluxes from 1950 to 2010, which was mainly induced by climate warming. Higher rates of increasing CH4 fluxes occurred in northeastern, northern and northwestern China, associated with large temperature increases. However, decreases in precipitation due to climate warming o_set the increase in CH4 fluxes in these regions. The CH4 fluxes from the wetland on the Qinghai Tibetan Plateau exhibited a lower rate of increase, which was approximately 25% of that simulated in northeastern China. Although climate warming has accelerated CH4 fluxes, the total amount of national CH4 emissions decreased by approximately 2.35 Tg (1.91-2.81 Tg), i.e., from 4.50 Tg in the early 1950s to 2.15 Tg in the late 2000s, due to a large wetland loss of 17.0 million ha. Of this reduction, 0.26 Tg 0.24-0.28 Tg) was derived from lakes and rivers, 0.16 Tg (0.13-0.20 Tg) from coastal wetlands, and 1.92 Tg (1.54-2.33 Tg) from inland wetlands. Northeastern China had the largest contribution to this reduction, with a loss of 1.68 Tg. The CH4 emissions were reduced by more than half in most regions in China except for the Qinghai Tibetan Plateau, where only a 23.3% decrease in CH4 was observed. [ABSTRACT FROM AUTHOR]

This study evaluates three different metrics of vegetation water content estimated from proximal sensing and MODIS satellite imagery: Fuel Moisture Content (FMC), Equivalent Water Thickness (EWT) and Canopy Water Content (CWC). Dry matter (Dm) and Leaf area Index (LAI) were also analyzed in order to connect FMC with EWT and EWT with CWC, respectively. This research took place in a Fluxnet site located in Mediterranean wooded grassland (dehesa) ecosystem in Las Majadas del Tietar (Spain). Results indicated that FMC and EWT showed lower spatial variation than CWC. The spatial variation within the MODIS pixel was not as critical as its temporal trend, so to capture better the variability, fewer plots should be sampled but more times. Due to the high seasonal Dm variability, a constant annual value would not work to predict EWT from FMC. Relative root mean square error (RRMSE) evaluated the performance of nine spectral indices to compute each variable. VARI provided the worst results in all cases. For proximal sensing, GEMI worked best for both FMC (RRMSE = 34.5 %) and EWT (RRMSE = 27.43 %) while NDII and GVMI performed best for CWC (RRMSE = 30.27% and 31.58% respectively). For MODIS data, results were a bit better with EVI as the best predictor for FMC (RRMSE = 33.81 %) and CWC (RRMSE = 27.56 %) and GEMI for EWT (RRMSE = 24.6 %). To explain these differences, proximal sensing measures only grasslands at nadir view angle, but MODIS includes also trees, their shades, and other artifacts at up to 20_ view angle. CWC was better predicted than the other two water content variables, probably because CWC depends on LAI, which is highly correlated to the spectral indices. Finally, these empirical methods outperformed FMC and CWC products based on radiative transfer model inversion. [ABSTRACT FROM AUTHOR]

Pacific Islanders have been exposed to risks associated with climate change. Samoa as one of the Pacific Islands are prone to climatic hazards that will likely increase in coming decades, affecting coastal communities and infrastructure around the is- lands. Climate models do not predict a reduction of such disaster events in the future in Samoa; indeed, most predict an increase in such events. This paper identifies key infrastructure and their functions and status in order to provide an overall picture of relative vulnerability to climate-related stresses of such infrastructure on the island. By reviewing existing reports as well as holding a series of consultation meetings, a list of critical infrastructures were developed and shared with stakeholders for their consideration. An indicator-based vulnerability model (SIVM) was developed in collaboration with stakeholders to assess the vulnerability of selected infrastructure systems on the Samoan Islands. Damage costs were extracted from the Evan cyclone recovery needs document. On the other hand, criticality and capacity to repair data were collected from stakeholders. Having stakeholder perspectives on these two issues was important because (a) criticality of a given infrastructure could be viewed differently among different stakeholders, and (b) stakeholders were the best available source (in this study) to estimate the capacity to repair non-physical damage to such infrastructure. Analysis of the results suggested rankings from most vulnerable to least vulnerable sectors are the transportation sector, the power sector, the water supply sector and the sewerage system. [ABSTRACT FROM AUTHOR]

Strong diurnal variation of aerosol has been observed in many heavy polluted regions in China. This variation could alter the distribution of the direct aerosol radiative forcing (DARF) during the whole daytime that could increase the uncertainty of the normally used averaged values To quantify the effect of using the daily averaged DARF, 196 days of high temporal resolution ground-based data collected in SKYNET Hefei site during the period from 2007 to 2013 is used to perform an assessment. We demonstrate that strong diurnal changes of heavy aerosol loading have an impact on the 24 h averaged DARF when daily averaged optical properties are used to retrieve this quantity. Though there is a high temporal sampling of aerosol properties to be used for calculation of daily averaged ones, statistical errors (up to 5.3Wm-2 absolutely and 14.6% relatively) in the computed DARF still occur. These errors increase with increasing daily aerosol optical depth (AOD) is also found which indicated the high temporal resolution DARF dataset should be used in the model instead of the normal daily-averaged one, especially under heavy aerosol loading condition. [ABSTRACT FROM AUTHOR]

This paper develops a method for determining whether two vector time series originate from a common stochastic process. The stochastic process considered incorporates both serial correlations and multivariate annual cycles. Specifically, the process is modeled as a vector autoregressive model with periodic forcing, referred to as a VARX model (where X stands for exogenous variables). The hypothesis that two VARX models share the same parameters is tested using the likelihood ratio method. The resulting test can be further decomposed into a series of tests to assess whether disparities in the VARX models stem from differences in noise parameters, autoregressive parameters, or annual cycle parameters. A comprehensive procedure for compressing discrepancies between VARX models into a minimal number of components is developed based on discriminant analysis. Using this method, the realism of climate model simulations of monthly mean North Atlantic sea surface temperatures is assessed. As expected, different simulations from the same climate model cannot be distinguished stochastically. Similarly, observations from different periods cannot be distinguished. However, every climate model differs stochastically from observations. Furthermore, each climate model differs stochastically from every other model, except when they originate from the same center. In essence, each climate model possesses a distinct fingerprint that sets it apart stochastically from both observations and models developed by other research centers. The primary factor contributing to these differences is the difference in annual cycles. The difference in annual cycles is often dominated by a single component, which can be extracted and illustrated using discriminant analysis. [ABSTRACT FROM AUTHOR]

Column-averaged dry-air mole fractions of carbon dioxide and methane have been retrieved from spectra acquired by the TANSO-FTS and SCIAMACHY instruments on board GOSAT and ENVISAT using a range of European retrieval algorithms. These retrievals have been compared with data from ground-based high-resolution Fourier Transform Spectrometers (FTS) from the Total Carbon Column Observing Network (TCCON). The participating algorithms are the Weighting Function Modified Differential Optical Absorption Spectroscopy (DOAS) algorithm (WFMD, University of Bremen), the Bremen Optimal Estimation DOAS algorithm (BESD, University of Bremen), the Iterative Maximum A Posteriori DOAS (IMAP, Jet Propulsion Laboratory (JPL) and Netherlands Institute for Space Research algorithm (SRON)), the proxy and full-physics versions of SRON's RemoTeC algorithm (SRPR and SRFP respectively) and the proxy and full-physics versions of the University of Leicester's adaptation of the OCO (Orbiting Carbon Observatory) algorithm (OCPR and OCFP respectively). The goal of this algorithm inter-comparison was to identify strengths and weaknesses of the various so-called Round Robin data sets generated with the various algorithms so as to determine which of the competing algorithms would proceed to the next round of the European Space Agency's (ESA) Greenhouse Gas Climate Change Initiative (GHGCCI) project, which is the generation of the so-called Climate Research Data Package (CRDP), which is the first version of the Essential Climate Variable (ECV) "Greenhouse Gases" (GHG). For CO2, all algorithms reach the precision requirements for inverse modelling (< 8 ppb), with only WFMD having a lower precision (4.7 ppm) than the other algorithm products (2.4-2.5 ppm). When looking at the seasonal relative accuracy (SRA, variability of the bias in space and time), none of the algorithms have reached the demanding< 0.5 ppm threshold. For CH4, the precision for both SCIAMACHY products (50.2 ppb for IMAP and 76.4 ppb for WFMD) fail to meet the< 34 ppb threshold, but note that this work focusses on the period after the 2005 SCIAMACHY detector degradation. The GOSAT XCH4 precision ranges between 18.1 and 14.0 ppb. Looking at the SRA, all GOSAT algorithm products reach the< 10 ppm threshold (values ranging between 5.4 and 6.2 ppb). For SCIAMACHY, IMAP and WFMD have a SRA of 17.2 ppb and 10.5 ppb respectively. [ABSTRACT FROM AUTHOR]

Most future projections forecast significant and ongoing climate change during the 21st century, but with the severity of impacts dependent on efforts to restrain or reorganise human activity to limit carbon dioxide (CO2) emissions. A major sink for atmospheric CO2, and a key source of biological resources, the World Ocean is widely anticipated to undergo profound physical and -- via ocean acidification -- chemical changes as direct and indirect results of these emissions. Given strong biophysical coupling, the marine biota is also expected to experience strong changes in response to this anthropogenic forcing. Here we examine the large-scale response of ocean biogeochemistry to climate and acidification impacts during the 21st century for Representative Concentration Pathways (RCPs) 2.6 and 8.5 using an intermediate complexity global ecosystem model, Medusa--2.0. The primary impact of future change lies in stratification-led declines in the availability of key nutrients in surface waters, which in turn leads to a global decrease (1990s vs. 2090s) in ocean productivity (-6.3%). This impact has knock-on consequences for the abundances of the low trophic level biogeochemical actors modelled by Medusa--2.0 (-5.8%), and these would be expected to similarly impact higher trophic level elements such as fisheries. Related impacts are found in the flux of organic material to seafloor communities (-40.7% at 1000m), and in the volume of ocean suboxic zones (+12.5%). A sensitivity analysis removing an acidification feedback on calcification finds that change in this process significantly impacts benthic communities, suggesting that a better understanding of the OA-sensitivity of calcifying organisms, and their role in ballasting sinking organic carbon, may significantly improve forecasting of these ecosystems. For all processes, there is geographical variability in change, and changes are much more pronounced under RCP 8.5 than the RCP 2.6 scenario. [ABSTRACT FROM AUTHOR]

Based upon seven field surveys conducted between May 2011 and January 2012, we investigated pH, carbonate saturation state of aragonite (Ωarag), and ancillary parameters on the Chinese side of the North Yellow Sea, a western North Pacific continental margin of major economic importance. Subsurface waters were nearly in equilibrium with air in May and June. From July to October, the fugacity of CO2 (fCO2) of bottom water gradually increased to 697±103 µatm and pH decreased to 7.83±0.07 due to respiration/remineralization processes of primary production induced biogenic particles. In November and January, bottom water fCO2 decreased and pH gradually returned to an air-equilibrated level due to cooling enhanced vertical mixing. The corresponding bottom water Ωarag was 1.74±0.17 (May), 1.77±0.26 (June), 1.70±0.26 (July), 1.72±0.33 (August), 1.32±0.31 (October), 1.50±0.28 (November), and 1.41±0.12 (January). Critically low Ωarag values of 1.0 to 1.2 were mainly observed in subsurface waters in a salinity range of 31.5-32.5 psu in October and November, accounting for ~10% of the North Yellow Sea area. Water mass derived from the adjacent Bohai Sea had a typical water salinity of 30.5-31.5 psu, and bottom water Ωarag values ranged mostly between 1.6 and 2.4. This study showed that the carbonate system in the North Yellow Sea was substantially influenced by global atmospheric CO2 increase. The community respiration/remineralization rates in typical North Yellow Sea bottom water mass were estimated at 0.55-1.0 µmol O2 kg-1 d-1 in warm seasons, leading to seasonal drops in subsurface pH and Ωarag. Outflow of the Bohai Sea water mass counteracted the subsurface Ωarag reduction in the North Yellow Sea. [ABSTRACT FROM AUTHOR]

This paper describes an integrated assessment modelling framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyse uncertainties in emissions resulting from both uncertainties in the economic model parameters and uncertainty in future climate policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response: climate sensitivity, net aerosol forcing and ocean heat uptake rate. Thus, the IGSM-CAM is a computationally efficient framework to explore the uncertainty in future global and regional climate change associated with uncertainty in the climate response and projected emissions. This study presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) and three sets of climate parameters. The chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century global climate change. As such, this study presents new estimates of the 90% probability interval of regional climate change for different emissions scenarios. These results underscore the large uncertainty in regional climate change resulting from uncertainty in climate parameters and emissions, especially when it comes to changes in precipitation. [ABSTRACT FROM AUTHOR]

A hydrostatic atmospheric dynamical core is developed for the purpose of global climate modelling. The model applies finite-difference methods to discretize the primitive equations on spherical icosahedral grids, using C-type staggering with triangles as control volumes for mass. This paper documents the numerical methods employed in the baseline version of the model, discusses their properties, and presents results from various idealized test cases. The evaluation shows that the new dynamical core is able to correctly represent the evolution of baroclinic eddies in the atmosphere as well as their role in heat and momentum transport. The simulations compare well with the reference solutions, and show a clear trend of convergence as the horizontal resolution increases. First results from two aqua-planet simulations are also presented, in which the equatorial wave spectra derived from tropical precipitation agree well with those simulated by a spectral transform model. The new dynamical core thus provides a good basis for further model development. Certain aspects of the model formulation that need further investigation and improvement are also pointed out. [ABSTRACT FROM AUTHOR]