Abstract This study examines the combined effects of sudden stratospheric warming events (SSWs) and El Niño and Southern Oscillation (ENSO) on late winter (January–March) climate in China. It is found that SSWs significantly modulate El Niño’s impact over China. During El Niño winters with SSWs, southern China tends to experience notable warming; conversely, without SSWs, the surface air temperatures there are generally colder. However, SSWs do not effectively alter La Niña’s impact; southern China remains anomalously colder during La Niña winters even when SSWs occur. The net warming effect of SSWs over much of China during La Niña, defined as the difference between scenarios with and without SSWs, is found considerably weaker than during El Niño. These discrepancies arise from the contrasting tropospheric pathway of ENSO teleconnection over the East Asia–Pacific region. Specifically, El Niño influences the occurrence of SSWs primarily by enhancing the tropospheric planetary wave 1. This enhancement corresponds to an emergence of a dipole pattern of geopotential height anomalies, characterized by an anomalous low over northeastern Eurasia and an anomalous high over China. In contrast, La Niña contributes to SSW occurrences via an increase in the tropospheric wave 2, which corresponds to only an anomalous low over northeastern Eurasia. The consistently significant high over China both before and after SSWs during El Niño, but much weakened or even absent during La Niña, is mainly responsible for the stronger net warming in late winter over China in El Niño years.

Urban green spaces are recognized as essential elements of cities. They offer multiple benefits, including mitigating the urban heat island effect and its negative impact on public health. They also present opportunities for people to interact, recreate, and connect with nature. Rapid urbanization leads to a significant transformation of green spaces to impervious surfaces and urban infrastructures. A large number of cities throughout the world have experienced “urban heat island” (UHI) effects. UHI are characterized by a temperature difference between urban and rural regions. Urban green spaces can contribute to a broad range of ecosystem services, among which temperature mitigation is regarded as an important ecosystem regulating service. Understanding the influences of green space dynamics on the temperature variability is therefore of great interest for mitigating the UHI effect in cities. The UHI effect can be assessed by measuring surface air temperature and land surface temperature in the system. This study investigated green space dynamics and land surface temperature in the Vijayawada City, Andhra Pradesh, India. This research study addresses the pressing concern of environmental stress and green infrastructure (GI) deficiency, a rapidly urbanizing Tier-II study city. The central empirical concern is to assess spatial patterns of ecological degradation by integrating satellite-derived indices viz., Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Urban Heat Island (UHI), Air Quality Index (AQI), and City Biodiversity Index (CBI). These indicators are employed to diagnose areas with inadequate green cover, extreme thermal exposure, and air quality, which often overlap with low-income and high-density urban zones. The researchers have made systematic analysis and employed geospatial approach using multi-temporal Landsat imagery for quantification of NDVI and LST for the study region. UHI is computed by comparing urban LST with rural baselines. The biodiversity metrics are assessed using the Singapore Index Framework. Spatial overlays, zonal statistics, and descriptive ward-level synthesis are applied to integrate these indicators within ArcGIS 10.8. version. The result reveals 79% decrease in average NDVI during 1990 to 2024, with built-up areas increasing from 37% to more than 60%. LST values surpass 30°C in multiple wards, and UHI intensities reach up to 9°C, in thermally stressed zones like, Wards 2, 8, and 54. AQI values consistently exceed the permissible PM₂.₅ limit, especially in industrial and commercial corridors. Biodiversity analysis yields a critically low CBI score of 32/92, reflecting habitat fragmentation and weak urban ecology governance in the system. These findings highlight the zones with cumulative environmental burdens, particularly in low-income wards, which are lacking access to GI. Based on the results, the study evolves a Green Infrastructural Planning Framework and to recommend strategies/guidelines for mitigation of Environmental Stress. Finally, the study concludes that spatially disaggregated, multi-indicator diagnostics are vital for prioritizing GI interventions in the system. The proposed framework can guide municipal administrators, urban planners, policy makers in allocating green resources equitably in cities might provide greater benefits for climate mitigation.

The European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) is one of the most widely used atmospheric reanalysis datasets provided by the ECMWF. However, the transition in the sea ice dataset between 1978 and 1979 may introduce inconsistencies that affect various surface meteorological variables. This study evaluated ERA5 sea ice data in the Sea of Okhotsk (SO), focusing on the years 1978 and 1979. Furthermore, the impact of this sea ice transition on meteorological variables was evaluated. In 1979, ERA5 sea ice coverage reached the coastal areas of Hokkaido in the southern SO, with an extent of approximately 1.1 × 10 6 km². In contrast, an unrealistically low sea ice cover of approximately 0.5 × 10 6 km² was observed before 1978. This discontinuity in sea ice stems primarily from issues with assimilated sea ice data used in ERA5. In 1978, the unrealistic negative bias in sea ice cover arguably contributed to positive biases in significant wave height, sea surface temperature, surface air temperature, and surface winds. In the case of wave observations, from 1975 to 1978, ERA5 overestimated significant wave height by more than 60% compared to observations from February to April when sea ice was present. These findings highlight the need for caution when analyzing long-term changes in ice-covered areas when using ERA5 data, particularly for periods before 1979.

Urbanisation and climate change are intensifying heat risks in cities worldwide through the combined effects of global warming and the urban heat island (UHI) phenomenon. Elevated urban temperatures threaten human health, strain infrastructure, increase energy demand and exacerbate socio-spatial inequalities. While architectural and urban design decisions are central to the formation and mitigation of UHI, moving from UHI mitigation to heat-resilient cities requires linking physical interventions with governance capacity, equity, and adaptive learning over time. This paper, therefore, develops a conceptual framework for resilient and sustainable urban environments that embeds built-environment strategies within a broader resilience-oriented governance context. The study combines a narrative review of UHI mechanisms, impacts and mitigation approaches with a systematic review of local-government strategies implemented between 2015 and 2025. Following preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and a population, intervention, comparison, and outcome (PICO)-based search strategy, 100 studies were selected from Scopus and Web of Science and analysed thematically. The review identifies four main domains of local action: green infrastructure; cool and permeable materials; water-based and blue–green infrastructure; and policy, governance and technology. Within these domains, the paper highlights architectural and design-relevant interventions, including shade-oriented streetscapes, climate-responsive building envelopes, ventilation-sensitive urban form, and blue–green corridors, while also examining institutional, financial and social factors that shape implementation and effectiveness. The findings show that combinations of green infrastructure, cool materials and blue–green systems can reduce surface and near-surface air temperatures and improve thermal comfort, with co-benefits for public health, energy efficiency, biodiversity and liveability. However, implementation is frequently constrained by limited financial and technical capacity, fragmented institutions, context-specific trade-offs, and insufficient attention to equity. Building on these insights, the paper proposes a conceptual framework comprising ten components that connect context and drivers; assessment and diagnosis; intervention strategies; implementation mechanisms; enablers; barriers; equity operationalisation; outcomes and effectiveness; monitoring and evaluation; and feedback and iteration. The paper concludes that advancing from urban heat islands to resilient cities requires design innovation supported by enabling governance, equity-centred prioritisation, and iterative monitoring and learning.

ABSTRACT The accurate simulation of courtyard microclimates remains a critical challenge in evaluating passive cooling strategies in dense urban environments, particularly under variable window operation. This study investigates the combined effect of courtyard geometry and natural ventilation control on indoor thermal comfort in a Mediterranean urban block, using a hybrid experimental – numerical approach. A 1:10 scaled physical model of a courtyard building was constructed and monitored under summer conditions in northern Morocco, capturing indoor and courtyard air temperatures, surface temperatures, and meteorological data. A detailed multizone thermal and airflow model was developed using TRNSYS 18 coupled with CONTAM, incorporating bidirectional airflow modeling at window openings and radiative interactions based on Gebhart factors. Model validation against experimental measurements yielded high accuracy, with mean absolute errors below 1.5 °C and coefficients of determination (R²) exceeding 0.96 for both air and surface temperatures.Parametric simulations explored three courtyard configurations (W/L = 1.0, 0.67, 0.5), seven orientations (0°-90°), and four window control strategies (closed, open, night ventilation, conditional). Results indicate that night ventilation reduced cumulative indoor discomfort by up to 56% compared to sealed conditions, while compact courtyards improved ventilation and decreased UTCI by up to 3 °C during peak hours. Orientations aligned with prevailing winds (15-30°) significantly enhanced airflow rates. This study demonstrates the applicability of validated TRNSYS-CONTAM coupling for modeling courtyard-scale microclimates. The proposed methodology provides a replicable framework for assessing passive cooling efficiency through geometry - ventilation interactions in warm climate contexts.

ABSTRACT In this study, changes in the Indian Summer Monsoon (ISM) mean state have been examined in the future period (2071–2100 using the SSP5‐8.5 scenario with respect to the historical 1985–2014) and past period (mid‐Pliocene with respect to the pre‐industrial), having a similar global surface air temperature increase. The ensemble of six models from the Coupled Model Intercomparison Project phase 6 (CMIP6) has been considered based on the common availability of variables from these models' outputs. In the annual cycle of precipitation over the Indian landmass, by the end of the 21st century, a shift has been projected in the peak rainfall month from July to August. It is also found that the monsoon precipitation rate increases over the Indian region in the future warm climate and past mid‐Pliocene with respect to their reference periods; however, the increase rate is slightly lower in the future climate in comparison with the past warm climate. These changes are elucidated through dynamic and thermodynamic aspects of the monsoons. Our results reveal that the simulated moisture amount over the Indian region is found to be higher in the future warm climate as compared to the mid‐Pliocene period. Subsequently, enhanced surface and tropospheric temperatures in the Indian region in a future warm climate relative to the past are also noticeable. From a dynamical perspective, the large‐scale low‐level wind circulation changes and convection over the Indian subcontinent are simulated to be stronger in the mid‐Pliocene compared to the future warm climate. Furthermore, moisture budget analysis reveals that during the past warm climate, both the thermodynamic and dynamic components have contributed to intensified ISM conditions. However, by the end of the 21st century, the projected ISM rainfall increase is dominated by thermodynamic components (based on the extent of warming).

Abstract. Including sophisticated aerosol schemes in the models of the sixth Coupled Model Inter-comparison Project (CMIP6) has not improved historical climate simulations. In particular, the models underestimate the surface air temperature anomaly (SATa) when anthropogenic sulfur emissions increased in 1960–1990, making the reliability of the CMIP6 projections questionable. This cooling bias is largely attributable to the unreasonable simulated atmospheric sulfate burden changes. Sulfate burden anomaly are closely linked to both sulfate and SO2 deposition processes. Intensified sulfate deposition directly reduces atmospheric sulfate loading, while enhanced SO2 deposition limits precursor availability for sulfate formation by oxidation. These deposition processes regulate sulfate concentrations directly and indirectly. The systematically underestimated sulfate turnover time in CMIP6 models suggests that refining SO2 deposition process rather than sulfate deposition would be a more scientific approach for model improvement. This is supported by two post-CMIP6 models that show better SATa reproduction after improving the SO2 deposition parameterizations. Strong correlations between sulfate burden anomaly and SATa persist before, during, and after the 1960–1990 period. Such temporal consistency confirms the dominant role of sulfate-related physical processes across all examined time intervals.

Abstract As the dominant atmospheric circulation pattern over the western Tibetan Plateau (TP), the Western Tibetan Vortex (WTV) exerts substantial control on springtime 2 m surface air temperature ( T 2m ). However, its underlying radiative processes remain unclear. This study integrates GEWEX satellite observations with ERA5 and MERRA‐2 reanalysis, applying surface energy balance diagnostics to quantify the WTV's radiative forcing on T 2m variability. We find the WTV explains ∼66% of T 2m variance ( R = 0.81) across the western TP and the adjacent Southwest Asia. Downward shortwave radiation (DSW) emerges as the primarily radiative factor modulated by the WTV via cloud radiative forcing (CRF) processes. Specifically, anticyclonic WTV events reduce cloudiness, generating positive CRF anomalies that enhancing surface DSW and cause warming. Conversely, cyclonic events increase cloudiness, producing negative CRF anomalies that diminish DSW and induce cooling. These findings advance understanding of the radiative processes by which the upper circulations modulate the surface climate over the TP.

Abstract The dominant intraseasonal modes of winter surface air temperature in extratropical Northern Hemisphere are identified through an empirical orthogonal function (EOF) analysis. The first mode is characterized by a dipole temperature pattern over the North America-North Pacific sector. The upper-tropospheric circulation associated with this mode is a zonally oriented Rossby wave train propagating westward. The second mode exhibits an in-phase relationship between the temperature anomaly over Eurasia and North America. The large-scale circulation associated with this mode is featured by same-sign geopotential height anomalies moving at an opposite zonal direction (eastward in Eurasia and westward in North America). The third mode shows an out-of-phase relationship between the temperature anomaly in Eurasia and North America. This out-of-phase temperature pattern is linked to the similar low-frequency wave train but with opposite signals in geopotential height anomalies. The sum of the three leading modes explains 40% of the total intraseasonal temperature variance. The distinctive wave propagations in Eurasia and North America are rooted in barotropic Rossby wave dynamics and determined by both the zonal wavelength and the background flow, with the former playing a larger role. An anomalous temperature budget analysis shows that the southeastward (westward) shifting of the lower-tropospheric temperature tendency in Eurasia (North America) results primarily from anomalous meridional temperature advection.

Compound dry-hot extremes exert stronger environmental impacts than individual dry or hot extremes. While evidence for increasing meteorological compound dry-hot extremes (defined using surface air temperature and vapor pressure deficit or precipitation) is growing, the impacts and evolving risks of soil-based compound dry-hot extremes remain poorly understood. Using homogenized soil temperature observations and observationally constrained soil moisture dataset for China, we show that the adverse effects of soil-based compound dry-hot extremes on vegetation productivity are more severe than their meteorological counterparts. From 1980 to 2017, the frequency and coverage area of soil-based compound dry-hot extremes in China increased by 3.0 days and 141.9 104 km2, respectively, with the most pronounced increases occurring in northern China. These increases are primarily attributed to anthropogenic soil warming. Under a fossil-fueled development scenario, the mean frequency of such extremes is projected to increase by 13.3 days by the end of the twenty-first century relative to the 1981-2010 baseline, potentially reducing China's terrestrial vegetation gross primary production by approximately 0.025 Pg C a-1. Our findings highlight an anthropogenic escalation of soil-based compound dry-hot extremes and their growing threats to terrestrial carbon sinks and food security.

Abstract Aerosols have played an important role in defining the climate over the historical period, due to their net cooling effect in the atmosphere. However, as their emissions are expected to decrease in upcoming decades, they will be associated with reduced cooling, i.e. future warming, of the planet. Despite their importance and high uncertainty associated with their radiative forcing, aerosols inclusion in simple climate models, impact models and carbon-based climate assessment metrics requires simplifications and assumptions. Typically, interactions between physical and biogeochemical processes are disregarded by such. By varying the spatial implementation of aerosols in an intermediate complexity model we explore the variability in Earth system responses under an ambitious mitigation scenario due to aerosols-radiation interactions. When aerosols are implemented disregarding their spatial distribution, surface air temperature is higher by almost 0.1 °C when compared to a regionally heterogeneous implementation, corresponding to an uncertainty of ca . 200 GtCO 2 of remaining carbon budgets. The main processes driving these responses are the land surface temperature and its effect on soil respiration, as well as changed ocean heat fluxes due to differences in incoming shortwave radiation at the surface. The spatial distribution of aerosols triggers important climate-carbon feedbacks, which should be specifically considered when assessing climate evolution and simulated Earth system responses. Even if aerosol-cloud interactions aren’t explored, the results already indicate that aerosols should be deliberately accounted for in simple models and assessment tools, as their triggered feedbacks will be instrumental in defining pathways for temperature stabilisation and evaluating, for example, remaining carbon budgets.

Abstract The interdecadal changes in climate under accelerating global warming have a profound impact on various countries in the Northern Hemisphere (NH). Using ERA5 reanalysis data, the interdecadal changes of Rossby wave energy propagation (RWEP) pathways and their impacts are examined in the present work. The results demonstrate that the NH means of 500 hPa geopotential height anomalies vary with large interdecadal trends that keep in step with global warming, exhibiting a negative-to-positive phase transition from period I (1950/51–1996/97) to period II (1997/98–2024/25). Pronounced interdecadal eastward shifts occur systematically in interannual variabilities of apparent wave sources, which correspondingly result in large interdecadal changes of RWEP pathways in regions from the northeast Atlantic to Eurasia and from the northeast Pacific to North America. Significant interannual surface air temperature anomalies with extremes of around ±5 °C are induced by circulation variations in regions around these pathways, facilitating possible occurrences of climate extremes in Eurasia and North America with different spatial patterns between period II and period I.

Greenhouse gases (GHG), accumulated in the atmosphere, are the main cause of climate change. In 2017, the increase in average temperature was about 1 °C (between 0.8 °C–1.2 °C) above pre-industrial levels. Global warming refers to the increase in air surface, sea surface, and soil surface temperature and according to IPCC (Intergovernmental Panel Climate Change), since the industrial revolution, C emissions are due to land use changes like deforestation, biomass burning, conversion of natural lands, drainage of wetlands, soil cultivation, and tillage. As the world population has increased, world food production has risen too with a subsequent increase in GHG emissions and agricultural production, which is worsened by climate change. Negative consequences are well known such as the loss in water availability and in soil fertility, and pest infestations which are climate change’s effects on agriculture activity. Climate change’s main aftermath is the frequency of extreme weather events influencing crop yields. As climate change exacerbates degradation processes, land management can mitigate its impact and aid adaptation strategies for climate change. About 21–37% of GHGs have been caused by the agriculture activity, so the application of Nature-based Solutions (NbS) like sustainable agriculture could be a way to reduce GHGs worldwide. The aim of this article is to review how NbS may mitigate GHG emissions from soil, with solutions defined as an integrated approach to tackle climate change and to sustainably restore and manage ecosystems, delivering multiple benefits. NbS is a low-cost tool working within and with nature, which holds many benefits for people and the environment.

Abstract The frequency and intensity of extreme weather events have risen with climate change, affecting multiple sectors worldwide. This study examines the influence of anthropogenic warming on intense tropical cyclones (TCs) over the Arabian Sea using convection‐permitting simulations with the Weather Research and Forecasting (WRF) model. In particular, we provide the first quantitative assessment of the impact of anthropogenic forcing on recently observed TC‐induced extreme rainfall. Human‐induced changes were assessed through two experiments: all forcings (ALL) and natural forcings only (NAT). Anthropogenic warming “delta” patterns of sea surface temperature, relative humidity, and air temperature were derived from CMIP6 models and applied in WRF under a pseudo‐global warming framework. Three major TCs—Ockhi (2017), Kyarr (2019), and Maha (2019)—were simulated, and the model reproduced their tracks, intensities, and rainfall with high fidelity. Comparison of ALL and NAT runs shows a clear anthropogenic signal: TC‐induced total and extreme rainfall both increases, linked to stronger vertical motion and greater moisture availability that enhance latent heat release and deep convection. Furthermore, there is a statistically significant expansion in the area experiencing extreme rainfall by ∼16%–34%, and an enhanced intensity of extreme rainfall by ∼4%–12% under anthropogenic warming. Additional differences in vertical thermal profiles and warm‐core structures further highlight the impact of human‐induced climate change on TC dynamics.

As global warming intensifies, pollinators such as bumblebees may experience increasing exposure to temperatures near their thermal limits. Heat stress impairs foraging and survival, making it essential to understand bumblebee body temperature in natural conditions. This study tested the feasibility of using infrared (IR) thermography as a non-invasive technique to measure the thoracic temperature of wild, foraging bumblebees and to evaluate how body temperature relates to environmental variables, including ambient air and floral surface temperatures. Thermographic measurements were validated against internal thoracic temperatures recorded by thermocouples in static bees, revealing a strong correlation (r=0.98) with an average absolute difference of <1°C. We analysed thermal images of live Bombus individuals (n=98) collected over five observation days in late summer. Bee body temperatures routinely exceeded both ambient and floral temperatures and approached the critical thermal maximum (CTmax) during midday foraging. A linear mixed-effects model revealed that bee temperature increased significantly with both ambient air and floral temperature, and a significant interaction term indicated that warmer floral surfaces amplified the effect of high ambient temperatures. These findings demonstrate that IR thermography can reliably measure bumblebee body temperature in-situ, bridging the gap between laboratory-derived thermal limits and field conditions. By capturing the combined effects of microclimate and physiology, this method offers new insight into pollinator heat stress at the organismal level and highlights the importance of fine-scale thermal data for assessing species' responses to climate change.

Putative drivers of maritime Antarctic soil resistomes in the early 21st century: A baseline for monitoring environmental change and human influence.

From qualitative prediction to quantitative insight: combined meteorological patterns and regional dynamics of severe fever with thrombocytopenia syndrome in Liaoning Province, China, 2010–2024

Abstract Large volcanic eruptions are known to significantly impact global climate for several years, yet a comprehensive comparison across the growing number of paleoclimate datasets has not been performed. Here we assess the impacts of major eruptions over the Last Millennium on surface air temperature (SAT), Palmer Drought Severity Index (PDSI), and 500-hPa geopotential height using tree-ring reconstructions, nine data assimilation (DA) products, and two climate model ensembles. We confirm robust global SAT cooling but find large differences in magnitude and persistence: reconstructions based on tree-ring density show shorter, physically consistent cooling, whereas products dominated by tree-ring widths show longer persistence, likely reflecting biological memory. PDSI responses reveal coherent wetting over the western U.S., the Mediterranean basin, and southern South America, and coherent drying over northern and European Russia, Central Asia, and southern Siberia, with divergence elsewhere. El Niño-Southern Oscillation responses differ across products, suggesting that any volcanically forced signal is weak relative to internal variability and highly sensitive to the background climate state. Geopotential height anomalies reveal widespread post-eruption tropospheric contraction and robust extratropical circulation shifts, including negative height anomalies over mid-to-high latitudes and wave-like patterns in the Southern Hemisphere. These anomalies are dynamically consistent with the spatial patterns of wetting and drying in PDSI, suggesting that volcanic forcing reorganizes large-scale atmospheric circulation in ways that influence hydroclimate. Together, these findings provide a comprehensive framework for interpreting volcanic impacts, strengthen confidence in regions with robust signals, and identify priority areas—particularly in the tropics and Southern Hemisphere—where additional proxy coverage could reduce current uncertainties.

&lt;p class="MsoNormal" style="text-align: justify;"&gt;The paper presents a quantitative study analyzing how Classical Chinese Gardens (CCGs) have the capacity to regulate the microclimate and the potential effects on the productivity of staff through the Humble Administrator Garden at Suzhou. The study uses a combination of field measurements and Ordinary Least Squares (OLS) regression analysis to determine the effect of important landscape features, such as vegetation, water bodies, architecture, pathways, and corridors, on vital microclimate attributes, such as the air temperature, surface temperature, wind speed, and relative humidity. The study results show that vegetation has a strong cooling effect (&amp;beta; =0.875), humidity control effect (&amp;beta; = 0.250) and all water bodies have a strong cooling effect (&amp;beta; = 0.875) but a weak warming effect (&amp;beta; = 0.125) and Buildings and hard surfaces have a strong cooling effect (&amp;beta; = 0.875) and a weak effect (&amp;beta; = &amp;minus;0.008) of reducing the wind speeds and surface temperatures in corridors, respectively. Among them, trees would offer the best cooling (score 5), grasslands would do the best at controlling the humidity and wind speed (score 5), and water bodies would also contribute to the humidity regulation (score 4) significantly. Combining these results with an existing scheme of thermal sensation and work efficiency, the paper demonstrates the capacity of the microclimate changes to be applied to cognitive functioning and productivity. The study reveals practical recommendations in implementing the traditional Chinese garden design framework to the modern urban space and workspace setting, and presents approaches to enhancing the environmental sustainability, the thermal comfort and finally, the well-being of the staff and their productivity.&lt;/p&gt;

Abstract Artificial intelligence has improved the accuracy and efficiency of weather forecasting, surpassing traditional numerical weather prediction models. However, the coarse spatial resolution of global weather forecasting systems limits their ability to capture fine-scale surface heterogeneity and localized extremes, particularly in regions with complex terrain or urban heat island effects. Here, we introduce SR-Weather, a deep learning-based super-resolution framework that converts coarse 0.25° forecasts into 1-km surface air temperature fields using MODIS-derived temperature targets and high-resolution auxiliary inputs. SR-Weather outperforms existing super-resolution methods by explicitly incorporating spatial context, such as topography, impervious surface fraction, and seasonal climatology maps of air temperature. When SR-Weather was applied to the FuXi global weather forecast, the 7-day forecast error in South Korea decreased by more than 20%, which was comparable to the 1-day forecast error from low-resolution prediction using simple spatial interpolation. In addition, SR-Weather effectively reconstructs missing pixels in MODIS-derived air temperature maps under heavy cloud contamination by leveraging auxiliary variables and climatologically smoothed fields. Although validated over South Korea, the framework relies on globally available MODIS products and minimal auxiliary inputs, making it feasible to retrain for other regions. These results indicate that SR-Weather is a scalable and high-fidelity tool for enhancing machine learning-based weather forecasts at fine spatial scales.