Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

No abstract

Abstract:Ukraine is a country of the Mid-Latitude ecotone-a transition zone between forest zone and forestless dry lands. Availability of water defines distribution of the country's forests and decreases their productivity towards the south. Climate change generates a particular threat for Ukrainian forests and stability of agroforestry landscapes. This paper considers the impacts of expected climate change on vulnerability of Ukrainian forests using ensembles of global and regional climatic models (RCM) based on Scenarios B1, A2, A1B of the Intergovernmental Panel for Climate Change, and a "dry and warm" scenario A1B+T−P (increasing temperature and decreasing precipitation). The spatially explicit assessment was provided by RCM for the WMO standard period (1961-1990), "recent" (1991-2010) and three future periods: 2011-2030, 2031-2050 and 2081-2100. Forest-climate model by Vorobjov and model of amplitude of flora's tolerance to climate change by Didukh, as well as a number of specialized climatic indicators, were used in the assessment. Different approaches lead to rather consistent conclusions. Water stress is the major limitation factor of distribution and resilience of flatland Ukrainian forests. Within Scenario A1B, the area with unsuitable growth conditions for major forest forming species will substantially increase by end of the century occupying major part of Ukraine. Scenario A1B+T−P projects even a more dramatic decline of the country's forests. It is expected that the boundary of conditions that are favorable for forests will shift to north and northwest, and forests of the xeric belt will be the most vulnerable. Consistent policies of adaptation and mitigation might reduce climate-induced risks for Ukrainian forests.Keywords: Ukrainian forests; climate change; xeric belt; predictions of state and distribution of forests over 21st century; Mid-Latitude ecotone

Abstract. Several sets of reference regions have been proposed in the literature for the regional synthesis of observed and model-projected climate change information. A popular example is the set of reference regions introduced in the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX) based on a prior coarser selection and then slightly modified for the 5th Assessment Report of the IPCC. This set was developed for reporting sub-continental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes (the typical resolution of the 5th Climate Model Intercomparison Projection, CMIP5, climate models was around 2º). These regions have been used as the basis for several popular spatially aggregated datasets, such as the seasonal mean temperature and precipitation in IPCC regions for CMIP5. Here we present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher model resolution (around 1º for CMIP6). As a result, the number of regions increased to 43 land plus 12 open ocean, better representing consistent regional climate features. The paper describes the rationale followed for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and shapefile together with companion R and Python notebooks to illustrate their use in practical problems (trimming data, etc.). We also describe the generation of a new dataset with monthly temperature and precipitation spatially aggregated in the new regions, currently for CMIP5 (for backwards consistency) and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter diagrams to offer guidance on the likely range of future climate change at the scale of reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository; https://github.com/SantanderMetGroup/ATLAS, doi:10.5281/zenodo.3688072 (Iturbide et al., 2020).

Abstract. Drought events and their impacts vary spatially and temporally due to diverse pedo-climatic and hydrologic conditions, as well as variations in exposure and vulnerability, such as demographics and response actions. While hazard severity and frequency of past drought events have been studied in detail, little is known about the effect of drought management strategies on the actual impacts and how the hazard is perceived by relevant stakeholders. In a continental study, we characterised and assessed the impacts and the perceptions of two recent drought events (2018 and 2019) in Europe and examined the relationship between management strategies and drought perception, hazard, and impact. The study was based on a pan-European survey involving national representatives from 28 countries and relevant stakeholders responding to a standard questionnaire. The survey focused on collecting information on stakeholders' perceptions of drought, impacts on water resources and beyond, water availability, and current drought management strategies on national and regional scales. The survey results were compared with the actual drought hazard information registered by the European Drought Observatory (EDO) for 2018 and 2019. The results highlighted high diversity in drought perception across different countries and in values of the implemented drought management strategies to alleviate impacts by increasing national and sub-national awareness and resilience. The study identifies an urgent need to further reduce drought impacts by constructing and implementing a European macro-level drought governance approach, such as a directive, which would strengthen national drought management and mitigate damage to human and natural assets.

Objective. This paper deals with an estimation of the climate change at the Antarctic Peninsula region. During last decades, the most significant warming is observed in Polar regions, particularly in the Antarctic Peninsula region, where the Ukrainian Antarctic Akademik Vernadsky station is located. Therefore, the providing of the complex estimation of climate change trend is an important task for the region. These changes are taking place nowadays and will happen in the future. So, the main objective of the study is to estimate changes of climate characteristics in the Antarctic Peninsula region in the 21 st century, based on calculation of the relevant climate indices. The projections of the temperature and precipitation characteristics in the Antarctic Peninsula region and Akademik Vernadsky station area for RCP4.5 and RCP8.5 scenarios are the objects of the research. Methods of the research are numerical simulation and statistical analysis of the regional climate model data for the Antarctic Peninsula region from the International Project Polar-CORDEX. Spatial distribution of this data is 0.44° and three periods are under consideration: historical climatic period (1986-2005) and two future periods 2041-2060 and 2081-2100. The R-code language and the modified computing code developed by Climate4R Hub project in Jupiter Notebook environment were used for climate data analysis in this research. Six parameters were chosen to estimate climate change in the Antarctic Peninsula region: number of frost days with minimal air temperature (Т) less 0 °C, number of ice days with maximal Т less 0 °C, annual total precipitation, mean precipitation rate, maximum yearly duration of periods without precipitation, maximum yearly duration of periods with precipitation more than 1 mm per day. Results as an analysis of the cold temperature indices are presented in the Part I of the paper, while an analysis of the wet/dry indices will be presented in the Part II of the paper. Conclusions. Over the Antarctic Peninsula region, both scenarios project an average decrease in the cold season period. This process will be more pronounced for the RCP 8.5 scenario, when even to the middle of the century the period with negative temperatures is rapidly decreasing over the Larsen Ice Sheet area, which may cause its total or partial collapse. Over Akademik Vernadsky station area, the climate indices changes will almost triple as high as the averaged values over the Antarctic Peninsula for the two scenarios, indicating a greater vulnerability to the climate change in the area.

The Antarctic Peninsula (AP) experienced a new extreme warm event and record high surface melt in February 2022, rivaling the recent temperature records from 2015 and 2020, and contributing to an alarming series of extreme warm events there. The northern/northwestern AP was directly impacted by an intense atmospheric river (AR) bringing anomalous heat and rainfall, while AR-enhanced foehn effect further warmed its northeastern side. The event was triggered by multiple large-scale atmospheric circulation patterns linking the AR formation to tropical convection anomalies and stationary Rossby waves, with anomalous Amundsen Sea low and record-breaking blocking high. The cascade of impacts culminated in widespread and intensive surface melt across the AP. The event was statistically attributed to global warming. Increasing frequency of such events can undermine the stability of the AP ice shelves, with multiple local to global impacts, including acceleration of the AP ice mass loss and changes in sensitive ecosystems.

Objective of the study is an assessment of possible climate change in the region of the Antarctic Peninsula from 1986 until the end of the 21st century projected by the RCMs' ensemble. During the last decades Antarctica has undergone predominantly warming, with the highest rate of surface air temperature increase found over the Antarctic Peninsula, where the Ukrainian Antarctic Akademik Vernadsky station is located. There is a unique ecosystem in the region which is vulnerable and under the growing impact of a changing weather regime due to rapid climate changes with consequent changes in sea ice, land distribution under snow/ice, etc. Thus, an important task for the region is an estimation of climate change trends and definition of possible subregionalization. Data and methods. Data of two regional climate models HIRHAM5 and RACMO21P forced by two global climate models EC-EARTH and HadGEM from the Polar-CORDEX (Coordinated Regional Downscaling Experiment -Arctic and Antarctic Domains) as part of the international CORDEX initiative were used in the study. Spatial distribution of the model output is 0.44°. Set of scripting codes developed by Climate4R project (An R Framework for Climate Data Access and Postprocessing) was modified in order to extract data for the Antarctic Peninsula region from the Antarctic domain and obtain climatological characteristics for individual RCMs and their ensemble mean. Projected changes in wet/dry climate indices for scenarios RCP4.5 and RCP8.5 for two periods 2041-2060 and 2081-2100 were assessed with respect to the historical experiment 1986-2005. Results. An analysis of projected wet/dry climate indices for both RCP4.5 and RCP8.5 scenarios is presented in Part II of the paper. An analysis of the cold temperature indices (FD, ID) is presented in Part I of the study. In the historical experiment Larsen Ice Shelf and leeward east coast are the regions with the lowest total precipitation in wet days (PRCPTOT, 200-300 mm) and simple daily intensity index (SDII, about 5 mm/day) with under 10 days of consecutive wet days (CWD) and up to 30 days consecutive dry days (CDD). In the cross of the 21st century, duration of dry spell is projected to shorten for the whole peninsula and for Akademik Vernadsky station by about 7-10% under the scenario RCP4.5 and 10-15% under the RCP8.5. Projected SDII changes are up to +20% till the end of the century under the scenario RCP8.5 at north-west coast of the Antarctic Peninsula. Conclusions. Over the Antarctic Peninsula region both scenarios project an average increase in total PRCPTOT and SDII; overall the maximum length of CWD is extended while the maximum length of the CDD is reduced. In combination with decreasing number of frost (FD) and ice (ID) days, the pattern of changes differs notably across the peninsula. It is shown in the first part of the paper that over the Antarctic Peninsula region, both scenarios project an average decrease in the cold season period. The most pronounced changes of ID and FD climate indices are for the Larsen Ice Sh...