Xuejie Gao

High latitudes Northern Asia (NAS) is a region very sensitive to the global warming but relatively less studied, in particular concerning the application of high resolution regional climate models. In the study, systematic evaluation of the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model version 5, RegCM5, has been performed to customize its performances over the region. The focus is on mean surface air temperature simulation during December-January-February (DJF), a season with pronounced warm biases under default settings of the model. A set of 24 short-term sensitivity experiments has been conducted to evaluate the model’s performance across different physical parameterization schemes. In the experiments, RegCM5 is driven by ERA-Interim re-analysis at a grid spacing of 25 km. The simulated mean surface air temperature in DJF is compared against observation. Results show the model exhibit substantial warm biases in northeastern part of the domain across all the experiments, centered on the “cold pole” of the northern hemisphere around Oymyakon and Verkhoyansk region. The warm bias is most sensitive to the choice of cloud microphysics schemes, followed by the planetary boundary layer (PBL) parameterizations, with comparatively lower sensitivity to cumulus convection and cloud fraction algorithm choices. Diagnostics of surface energy balance indicates the warm biases are mostly due to the excessive downward longwave radiations while deficiencies in simulating surface sensible heat fluxes also contributes. Based on a variety of validation indexes, the optimal RegCM5 configuration for future application and climate change projections over NAS is identified as: WSM5 cloud microphysics scheme, UW PBL parameterization, Tiedtke cumulus convection scheme, and Xu-Randall empirical Cloud fraction algorithm.

We present a structured multi-criteria framework for the sub-selection of CMIP6 global climate models (GCMs) to support CORDEX-CORE2 dynamical downscaling. The framework integrates five key criteria: historical performance, model independence, regional temperature sensitivity, precipitation spread, and data availability, and is designed to identify a single, consistent subset of GCMs across all CORDEX domains to improve the comparability and interpretability of regional projections. A total of 45 GCMs are evaluated over the historical period (1981–2014), with 31 models further assessed for projected changes over 2015–2100. Application of the framework shows that model performance is systematically higher for large-scale circulation and thermodynamic fields than for precipitation seasonality and monsoon-related processes, which remain a dominant source of uncertainty across regions. Despite the diversity of climates represented across CORDEX domains, model rankings are broadly consistent, with top-performing models exhibiting stable performance across both tropical and extratropical regions, while lower-ranked models show more pervasive deficiencies rather than region-specific weaknesses. Sensitivity analyses demonstrate that rankings are largely insensitive to the choice of aggregation method but depend strongly on the breadth of evaluation metrics, with robust and reproducible rankings emerging only when a large fraction of the full metric suite is retained. Assessment of model independence reveals substantial clustering within the ensemble, indicating that many models share similar performance characteristics, while a smaller subset provides distinct and complementary information. Regional temperature sensitivity exhibits a coherent ordering across domains, suggesting that differences in projected warming are primarily governed by intrinsic model characteristics rather than region-specific effects. In contrast, precipitation spread shows strong regional variability, with both the magnitude and temporal structure of precipitation change differing widely across models. The relationship between precipitation and warming further highlights that, in some regions, precipitation responses scale with temperature, while in others they are dominated by circulation variability. By combining these criteria with data availability constraints, the framework identifies a reduced set of models that retains key aspects of performance, diversity, and projected change. This approach provides a transparent and reproducible basis for GCM selection within CORDEX-CORE2 and offers a generalizable strategy for coordinated regional climate modeling efforts.

We use an ensemble of a regional climate model (RegCM4) projections to assess future changes in surface air temperature, precipitation and Köppen-Trewartha (K-T) climate types in mid-high latitude Northern Asia (NA) under the 1.5-4°C global warming targets. RegCM4 is driven by five CMIP5 global models over an East Asia domain at a grid spacing of 25 km. Validation of the present day (1986-2005) simulations shows that the ensembles of RegCM4 (ensR) and driving GCMs (ensG) reproduce the major characters of the observed temperature, precipitation and K-T climate zones reasonably well. Greater and more realistic spatial detail is found in RegCM4 compared to the driving GCMs. A general warming and overall increases in precipitation are projected over the region, with these changes being more pronounced at higher warming levels. The projected warming by ensR shows different spatial patterns, and is in general lower, compared to ensG in most months of the year, while the percentage increases of precipitation are maximum during the cold months. The future changes in K-T climate zones are characterized by a substantial expansion of Dc (temperature oceanic) and retreat of Ec (sub-arctic continental) over the region, reaching ~20% under the 4°C warming level. The most significant change in climate types in ensR is found over Japan (~60%), followed by Southern Siberia, Mongolia, and the Korea Peninsula (~40%). The largest change in the K-T climate types is found when increasing from 2°C to 3°C.

Tibetan Plateau (TP, with the height > 3000 m) is a region with complex topographical features and a large diversity of climate both in space and time. Future climate change over TP and the surrounding areas is investigated based on the ensemble of a set of the 21st century climate change projections using a regional climate model, RegCM4. The model is driven by five different GCMs at a grid spacing of 25 km. Results show the RegCM4 greatly improves the temperature and precipitation simulations by providing finer scale spatial details of them over the region. The topographic effects are well reproduced by RegCM4 but not the GCMs. General warming and increase in precipitation are found in both GCM and RegCM4 simulation, but with substantial differences in both the spatial distribution and magnitude of the changes. For temperature, RegCM4 projected a more pronounced warming in DJF over TP compared to its surrounding areas. The increase of precipitation is more pronounced and over the basins in DJF for RegCM4. For the extreme indices of snowfall, RegCM4 generally reproduces the spatial distributions although with overestimation in the amount. General decreases in SNOWTOT and S1mm, with greater magnitude over the eastern part are projected. Both S10mm and Sx5day show decrease over the eastern part but increase over the central and western parts. Notably, S10mm shows a marked increase (more than double) with high cross-simulation agreement over the central TP. Significant increases in all four indices are found over the Tarim and Qaidam basins, and northwestern China north of the TP. The projected changes show topographic dependence over the TP in the latitudinal direction, and tend to decrease/increase in low-/high-altitude areas.

The LMRB (LMRB) has experienced significant climate change, particularly over the last 50 years. An increase in the annual precipitation but with significant seasonal differences in the changes, and a remarkable warming are observed over the Basin. The region also experienced more frequent extreme events, such as an increase in extreme precipitation, as well as hot days and warm nights, a decrease in cold days and cold nights, and a more frequent occurrence of droughts. The future climate over the Basin is projected to be continuous warming, which is most significant by the end of the twenty-first century. A general wetting is projected over the region with the spatial pattern of the projected annual total precipitation change show consistencies with the present day condition. Differences are found between the global and regional climate model projections in the precipitation, indicating the uncertainties existing in the projections, and also the importance of the model resolution in projecting future climate.

An analysis is presented of the precipitation bias and change signal in an ensemble of regional climate model (RCM) (RegCM4) projections driven by multiple general circulation models (GCMs) over China. RegCM4 is driven by five different GCMs for the 120‐year period 1979–2099 at 25 km grid spacing, under the representative concentration pathway RCP8.5. We find that the GCMs and RegCM4 reproduce the general spatial pattern of precipitation over China in all four seasons, with RegCM4 providing greater spatial detail, especially over areas with complex terrain. The spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by an underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in northern China, most pronounced in the Northwest basins, by both the GCMs and RegCM4 in all seasons except summer, when more mixed results are found. In addition, weak correlations of the projected change patterns are found in summer between the GCMs and nested RegCM4, indicating the greater role played by the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing.

To support future solar energy deployment in China, long‐term changes in solar energy resources over China were investigated based on high‐resolution dynamical downscaling simulations under three emission scenarios. First, an evaluation of model performance was conducted through comparison with station and ERA5 data, which indicated that although consistent overestimation was found, the spatial distribution and intra‐annual variation of solar radiation were captured well by ensemble simulation, showing added value over regions with complex topography as well. Then, the trends of the solar power output from photovoltaic (PV) systems during 2020–2099 were projected, characterized by an increase in east and central China, and a consistent decrease in the solar‐energy‐abundant regions (e.g., northeast China, the Tibetan Plateau, and northwest China) under the three scenarios. Except for under the low emission scenario, the regional averaged trends of PV were projected to decrease consistently over China in all four seasons, with significant magnitude apparent in both spring and winter. In addition, a more intense magnitude of decline was found under the higher emission scenario, with more subregions with a significant trend and higher intra‐annual and inter‐annual variability. However, it seems that the emission scenarios impact the spatial pattern only remarkably in the late century, however strengthened the decreasing magnitude in all future periods. In addition, results indicate decline in the future PV potential over most of subregions of China due to reduced radiation and increased temperature, but for the decrease over Tibetan Plateau the reduced wind speed also act as an important factor.

The southeast coastal region of China is susceptible to challenges related to extreme precipitation events; hence, projection of future climate extremes changes is crucial for sustainable development in the region. Using the Regional Climate Model Version 4 (RegCM4), the future changes of summer precipitation extremes have been investigated over the Jiulongjiang River Basin (JRB), a coastal watershed in Southeast China. Comparison between the RegCM4 simulated and observed rainy season precipitation over JRB suggests that the RegCM4 can reasonably reproduce the seasonal precipitation cycle, the frequency distribution of precipitation intensity, and the 50-year return levels of precipitation extremes over JRB. Furthermore, the model projects an increase in daily maximum rainfall (RX1day) mostly over the northern part of the basin and a decrease over other parts of the basin, while projecting a widespread decrease for maximum consecutive 5-day precipitation amount (RX5day) relative to the present day. In terms of the 50-year return level of RX1day (RL50yr_RX1day), a general increase is projected over most parts of the basin in the near and far future of the 21st century, but a decrease can be found in the northeast and southwest parts of the JRB in the mid-21st century. The future change of the 50-year return level of RX5day (RL50yr_RX5day) shows a similar spatial pattern with that of RL50yr_RX1day in the near and mid-21st century, but with a larger magnitude. However, a remarkable decrease in RL50yr_RX5day is found in the south basin in the far future. Meanwhile, the projected changes in the 50-year return level for both RX1day and RX5day differ between the first and second rainy seasons in JRB. Specifically, the future increase in RL50yr_RX5day over the north basin is mainly contributed by the changes during the first-half rainy season, while the decrease of RL50yr_RX5day in the south is mostly ascribed to the future changes during the second-half rainy season. All above results indicate that the future changes of precipitation extremes in JRB are complicated, which might differ from extreme indices, seasons, and future projected periods. These will thus be of practical significance for flood risk management, mitigation, and adaptation measures in Jiulongjiang River Basin.