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...

Investigating precipitation phase transitions is crucial for improving our understanding of precipitation formation processes and impacts, particularly in Polar Regions. This study uses observational data and numerical modelling to investigate precipitation phase transitions in the western and northern Antarctic Peninsula (AP) during austral summer. The analysis is based on the ERA5 reanalysis product, dynamically downscaled using the Polar-WRF (Polar Weather Research and Forecasting) model, evaluated using regular meteorological observations and additional measurements made during the Year of Polar Prediction special observing period. We analyse three cases of extra-tropical cyclones bringing precipitation with phase transitions, observed at the Chilean station Professor Julio Escudero (King George Island, north of the AP) and the Ukrainian Antarctic Akademik Vernadsky station (western side of the AP) during the first week of December 2018. We use observed and modelled near-surface air temperature and pressure, precipitation amount and type, and vertical temperature profiles. Our results show that precipitation type (snow or rain) is well-represented by ERA5 and Polar-WRF, but both overestimate the total amount of precipitation. The ERA5 daily variability and vertical air temperature profile are close to the observed, while Polar-WRF underestimates temperature in the lower troposphere. However, ERA5 underestimates the temperature inversion, which is present during the atmospheric river event, while Polar-WRF represents that inversion well. The average weekly temperature, simulated with Polar-WRF, is lower compared to ERA5. The Polar-WRF fraction of snow in the total precipitation amount is higher than for ERA5; nevertheless, Polar-WRF represents the precipitation phase transition better than ERA5 during the event, associated with an atmospheric river. These case studies demonstrated a relationship between specific synoptic conditions and precipitation phase transitions at the AP, evaluated the ability of the state-of-the-art reanalysis and regional climate model to represent these events, and demonstrated the added value of combined analysis of observations from the western and northern AP, particularly for characterizing precipitation during synoptic events affecting the entire AP.

<p>The last decade proved to be the warmest in Ukraine for the whole period of instrumental weather observations. Recent and projected future warming will cause changes in the duration of climatic seasons in Ukraine with corresponding shifts in dates of their start and end.</p> <p>As specified by the Expert Team on Climate Change Detection and Indices, climatic seasons are determined as periods from the first day after the start of a year to the first date after 1 July when at least 6 consecutive days mean daily temperature (t) exceeds (drops under) different thresholds. We analysed four climatic periods: warm period (t>0<sup>o</sup>C), growing season (t>5<sup>o</sup>C), active vegetation (t>10<sup>o</sup>C), and summer season (t>15<sup>o</sup>C).</p> <p>To assess these projected changes bias-adjusted daily data of EuroCORDEX were used from 34 regional climate models for RCP4.5 and RCP8.5 scenarios for 3 future periods: near-term 2021-2040, mid-term 2041-2060 and far-term 2081-2100. Data of ensemble mean for two scenarios firstly were compared with E-Obs v20.0e results in the base period 1991-2010 and showed different biases for different climatic seasons, but very similar behaviour for both scenarios and both variables (length and start of climatic seasons). The least biases (< 0.5 days) were obtained for growing season, while biases reached -10 days for length of warm season and were within 1-3 days for other two seasons.</p> <p>In general by the end of the century, under the RCP4.5 scenario in Ukraine, all analysed climatic season lengths may be the same as in the middle of the century under the RCP8.5 scenario.</p> <p>By the end of the century, for the RCP8.5 scenario, the changes in the climatic seasons range from 40 to almost 70 days, increasing from east to west. As a result, in the coldest in Ukraine region winter is projected to last only from 10 to 30 days, and the vegetation will last throughout the year not only at the southern coast of the Black Sea but also the steppe part of the Crimea and some southern parts of Odesa region. There are almost no differences between scenarios for growing season length, start and end days in the near-term. The area with the longest growing season (from 240 to 260 days) will extend almost 200 km to the north.  </p> <p>Under the RCP8.5 scenario, the length of active vegetation at the end of the century can range from 200 to 240 days, and in the Crimea and the south of Odesa region - 240-285 days, and summer length can vary from 140 days in the north to over half-year in the Crimea and southern Odesa. At the end of the 21<sup>st</sup> century, projected summer in Polissya will be as in the Crimea now - 140-160 days. Such climatic conditions were not observed in Ukraine previously. Increasing the length of the growing season and the period of active vegetation will strengthen the agro-climatic potential of Ukraine and contribute to obtaining higher yields of crops if corresponding measures in providing enough water supply will be implemented.</p>