Quantifying Uncertainty in High-Resolution Near-Surface Wind Projections over Southeast Asian Seas

Historical Climate and Future Projection in the North Atlantic and Arctic: Insights from EC-Earth3 High-Resolution Simulations

Abstract. This study presents a new set of high-resolution global climate simulations conducted with the EC-Earth3 model, including a 350 year pre-industrial, followed by historical (1850–2014) and future (2015–2100, SSP2-4.5) simulations. The model features a horizontal resolution of ∼ 40 km in the atmosphere and 0.25° in the ocean. The high-resolution EC-Earth3 (EC-Earth3-HR) is compared to the standard-resolution version used in CMIP6 to assess the impact of increased resolution on the representation of key climate variables, focusing particularly on the Arctic and North Atlantic regions. The high-resolution model aligns more closely with reanalysis data, particularly for global mean surface temperature and sea surface temperature. Both model resolutions exhibit similar biases in North Atlantic sea surface temperature and salinity, and in Arctic sea ice concentration, although the higher-resolution version shows regional improvements. The EC-Earth3-HR model captures the observed AMOC variability in the early 2000s, along with the trend and rapid loss event in Arctic sea ice. For future projection under SSP2-4.5, the high-resolution model projects a nearly ice-free Arctic by 2040 – earlier than the standard-resolution model – while simulating less Arctic warming and a more pronounced weakening of the AMOC. We also introduce a framework to diagnose deep-water formation (DWF) in the Labrador, Irminger, and Greenland Seas and to quantify their regional contributions to the AMOC. Applying this framework, we find that projected DWF weakens across all regions, with the largest reduction in the Labrador Sea, making it the dominant contributor to long-term AMOC weakening. By 2100, diagnosed DWF ceases in the Labrador Sea, compared with declines of 62 % in the Greenland Sea and 13 % in the Irminger Sea.

Borey: A High-Resolution Regional Atmosphere-Ocean-Sea Ice-Wave Forecasting System and Hindcast Dataset for the Barents and Kara Seas

Borey is a high-resolution regional modeling and operational forecasting system for the Barents and Kara Seas. It combines WRF for the atmosphere, NEMO-SI3 for the ocean and sea ice, and WW3 for waves on approximately 3--6\,km grids, and generates daily forecasts to 72 hours. We describe the model chain and production workflow and present an accompanying hourly hindcast of surface conditions from August 2015 to August 2023. The archive provides aligned atmosphere, ocean, sea ice, and wave fields for regional marine studies and a baseline for evaluating the operational system. Comparisons with observations and observation-based products show that Borey captures much of the variability in near-surface atmospheric conditions and ocean temperature. Skill in the evaluated WRF, NEMO, and SI3 forecasts changes only modestly across the three-day window. The main limitations are persistent rather than rapidly growing errors: sea surface temperature is generally too cold, sea ice concentration and occurrence are overestimated during seasonal retreat, and significant wave height is underestimated. Borey should therefore complement observation-constrained products. The planned public release will provide hourly surface fields, native grids, provenance information, and validation outputs for regional analysis, model development, and carefully evaluated data-driven forecasting and data-assimilation research.

High-Resolution Climatology of Near-Surface Wind over Greece (1991–2020) Based on a Regional Reanalysis

Wind influences human activities both directly and indirectly. Directly, it affects, among others, transportation and wind energy systems through its direction and intensity, while extreme wind events can cause severe damage to infrastructure and buildings and even casualties. Indirectly, the movement of air masses is strictly associated with all meteorological phenomena, highlighting the crucial role of wind in shaping weather conditions. In the context of climate change, anomalies in global and regional circulation patterns modify the characteristics of surface winds. Consequently, investigating long-term wind variability and trends is essential for assessing climate change impacts on the environment and society. The climatology of near-surface (10 m) winds over Greece for the period 1991–2020 is examined using a high-resolution regional reanalysis dataset, focusing on the mean wind speed, mean daily maximum wind gust, and the frequency of strong-wind days. The results reveal substantial spatial and temporal variability, with the most pronounced upward trends of these parameters observed over the Aegean Sea and northeastern Greece. Statistically significant trends are detected mainly during winter and summer. In particular, January and August exhibit the strongest positive trends, locally exceeding 0.05 m s−1 per year for mean wind speed and 0.1 m s−1 per year for mean daily maximum wind gust. Moreover, the frequency of strong-wind days increases in several regions with local trends exceeding 0.2 days per year. These findings highlight the value of high-resolution regional reanalyses for characterizing near-surface wind variability and trends over areas of complex terrain.

Assessing the variability and relationship of West Pacific subtropical high and Indian summer monsoon rainfall based on CMIP6 models

Observed and Simulated Mesoscale Convective Systems over High Mountain Asia: 1. Model Evaluation

Mesoscale convective systems (MCSs) are key drivers of the hydrological cycle over High Mountain Asia (HMA), delivering essential warm-season rainfall but also triggering flash floods and landslides. Their simulation over this complex region remains challenging for coarse-resolution models, and regional convection-permitting models cannot fully capture large-scale feedback. In this two-part study, we use global models at 25-km and 3-km resolution (the latter storm-resolving) to assess MCS characteristics and climate response over HMA. Part 1 provides a comprehensive evaluation against satellite observations. Both models capture the spatial distribution and seasonality of MCSs but overestimate warm-season frequency, with underestimation at low elevations and overestimation at high elevations. The storm-resolving model better reproduces the diurnal cycle. At the event scale, simulated MCSs are slightly larger, longer-lived, and more intense than observed. Both reproduce the dominant eastward propagation and speeds, but exaggerate a secondary southwestward mode. They capture broad precipitation patterns, including the dry zone north of the Himalayas, though the 25-km model retains a wet bias along the southern slopes that is reduced in the 3-km simulation. These findings highlight both the promise and limitations of current high-resolution global models in representing MCSs over complex terrain, providing a basis for assessing historical and future changes (Part 2) and guiding future model development.

Uncertainty in California Winter Precipitation Linked to Future Projections of North Pacific Large‐Scale Atmospheric Circulation

Accurate estimates of future changes in California winter precipitation are essential for informed water management in the region. In this study, we evaluate projected changes in winter precipitation and their uncertainties over California using the high‐resolution LOCA2‐HybridCA data set, downscaled from the Coupled Model Intercomparison Project 6 projections. Although this data set corrects model mean biases and realistically captures climatological orographic precipitation patterns, substantial inter‐model diversity remains in future projections. This diversity is closely related to the uncertainty in changes of the North Pacific Subtropical High (NPSH). Their relationship is strongest along the Central Coast, where 53% of the diversity in winter precipitation changes among models is explained by the diversity in NPSH latitude changes, which is largely linked to changes in extratropical North Pacific sea surface temperature. This result suggests that California winter precipitation changes in a warming climate are significantly influenced by North Pacific air–sea coupling. It highlights that accurately representing the North Pacific ocean and its interaction with the atmosphere is essential for reducing uncertainty in California's future hydroclimate.