Brown carbon (BrC), a subset of light-absorbing organic aerosols, contributes significantly to global warming not only by absorbing atmospheric radiation but also by accelerating snowmelt in the cryosphere through reducing surface albedo. However, accurately quantifying its global distribution and absorption remains challenging for numerical models, stemming from its complex composition, variable optical properties, and dynamic atmospheric transformations. This study developed an absorptivity basis set module for BrC (ABS-BrC) simulation, which categorizes BrC into four classes based on light-absorbing ability and accounts for chemical aging processes to better represent the variability in BrC absorption. Global simulations using ABS-BrC reveal notable disparities between source contributions to BrC concentrations and their associated absorption aerosol optical depth (AAOD). While secondary formation dominates global BrC concentrations (45.8%), its contribution to AAOD is disproportionately small (16.6%). In contrast, wildfire-sourced BrC, despite contributing less than a third of the total concentration, is responsible for the majority (54.2%) of global BrC AAOD. Notably, dark BrC (d-BrC), a strongly absorbing and water-insoluble subset, contributes 30-64% to global BrC AAOD. Its contribution is particularly critical in the Arctic during JJA and SON, where it accounts for 67% of BrC absorption, highlighting its critical role in polar warming. Implementing the ABS-BrC module in Earth system models is recommended for a more accurate assessment of BrC's radiative impact on the atmosphere and cryosphere.

Ambient temperature, solar radiation and sickness absence due to mental disorders in Finland: A distributed lag non-linear regional analysis.

Spatiotemporal variations and environmental behavior of activity concentrations of natural and artificial radionuclides in soils of Fukuoka, Japan (1980-2019).

In West Africa, accurate predictions of temperature are very essential for agriculture, health and energy planning, where climate change and increasing heat pose a high risk. This study develops an open and propagative pipeline for predicting monthly surface temperature anomalies using the ERA 5 Reanalysis inputs and interpretable machine-learning models. The predicting variables include land -atmosphere flux, soil moisture, radiation conditions, circulation fields, and oceanic indices, which are processed into anomalies and lagged features to capture persistence and memory. The results show that machine-learning models continues leading the climatological and persistence baselines, With the strongest gains occurring during transition seasons and over semi-arid regions where land–atmosphere coupling is strong. Interpretive analysis reveals physically relevant relationships: deficits of soil moisture operate positive anomalies through lowered cooling by evaporation; Shortwave radiation and cloud cover modulate surface energy balance; And the lagged anomalies encode land-split memory. Water-borne countries, especially the Gulf of the Guinea SST, contribute during the transitional months, but are secondary to local reactions. Case studies and sensitivity analysis confirm the strength of these mechanisms by identifying coastal gradients and strongly convection periods. The findings suggest that machine learning provides efficient and physically consistent predictions of West African temperature discrepancies, providing practical value for climatic services in agriculture, health and energy fields. The released pipelines and artifacts carry forward the route towards fertility, integration with regional institutions, and integration with dynamic forecasts, operating climate-informed decision support in the region.

PDRC technology is of great significance for improving the surface thermal environment and achieving regional energy conservation. However, its core material, polydimethylsiloxane (PDMS), has limitations such as insufficient spectral selectivity and weak shielding against near-surface ambient thermal radiation, which restrict its engineering application. Based on the "surface-atmosphere radiative transfer" theory, this study employed the TMM to establish a spectral emissivity model of PDMS films, revealing the coupling mechanism among wavelength, thickness, and optical properties. Subsequently, by integrating the steady-state thermal balance equation of geographical factors, an energy exchange framework of "surface-film-atmosphere" was constructed. Results showed that PDMS films exhibit high emissivity in the atmospheric window and certain cooling effects under standard working conditions, but the lack of a high-reflectivity backsheet leads to significant parasitic thermal loads. This cross-scale integrated model provides theoretical support for enhancing the geographical adaptability and engineering feasibility of PDRC technology, contributing to the optimization of urban and rural microclimates.

Abstract. Solar ultraviolet radiation (UV) plays a fundamental role in the Earth's energy balance, influencing a wide range of processes, including material degradation, biophysical reactions, ecological dynamics, or public health. In this context, the first high-resolution (10×10 km) hourly dataset of surface solar UV under clear-sky conditions over mainland China from 1981 to 2023 is introduced, derived from ERA5 and MERRA2 reanalysis data and a reconstruction based on the SMARTS (Simple Model of the Atmospheric Radiative Transfer of Sunshine) spectral model. Leveraging the SMARTS model's accuracy and capabilities, this dataset provides UV data at 0.5 nm intervals between 280 and 400 nm, offering enhanced granularity for wavelength-specific analysis, thus filling a key gap in high-resolution hourly UV data for China. Validation of the UV dataset against ground observations at 37 stations of the Chinese Ecosystem Research Network (CERN) demonstrates strong performance, with a correlation coefficient (R), root mean square error (RMSE), and mean bias error (MBE) of 0.919, 5.07 W m−2 and −0.07 W m−2, respectively. Compared with the Clouds and the Earth's Radiant Energy System (CERES) UV product, this dataset offers higher spatial and temporal resolution as well as higher accuracy in comparison with observations, thus enhancing data quality for a wide range of applications. The spatial and temporal distribution of clear-sky UV radiation exhibits distinct regional and seasonal variations, with higher values in the west and south, and lower values in the east and north. Over the past 43 years, the annual mean clear-sky broadband UV radiation averaged over China was 20.05 W m−2, showing a slightly increasing trend (+0.0237 W m−2 yr−1). This dataset is now available at https://doi.org/10.6084/m9.figshare.28234298 (Qi et al., 2025), offering a valuable resource for addressing regional challenges related to UV radiation.

Abstract Until recently, advection profiles in the planetary boundary layer have been difficult to quantify from observations. As a result, not much is known about its basic characteristics like magnitude and diurnal cycles, or how these differ as a function of large-scale environments. To provide insight into advective characteristics, a Green’s Theorem-based method for calculating profiles of advection in the lowest 3 km from an array of ground-based thermodynamic and kinematic profiling instruments has been applied to two years of observations from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observing site. Since advection largely depends on synoptic scale forcing, a self-organizing map (SOM) was used to classify days based on mean sea level pressure analyses; from that, the diurnal evolution of vertical profiles of advection for different synoptic environments was quantified. The overall mean magnitude of the potential temperature advection is approximately ± 3 K hr −1 while the moisture advection is approximately ±1.5 g kg −1 hr −1 , with substantial variability in the sign and magnitude of the advective tendencies at different heights and throughout the diurnal cycle. Advection magnitude is strongly connected to the strength of synoptic-scale forcing, which varies depending on the time of year. Variability in advection is larger for potential temperature than it is for moisture, and strongly-forced environments like mid-latitude cyclones feature greater variability in the advection magnitude than weakly forced or quiescent environments.

Abstract. Ice nucleating particles (INPs) play a critical role in cloud microphysics and precipitation formation, yet long-term, spatially extensive observational datasets remain limited. Here, we present one of the most comprehensive publicly available datasets of immersion-mode INP concentrations using a single analytical method, generated through the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility. INP filter samples have been collected across a broad range of environments – including agricultural plains, Arctic coastlines, high-elevation mountain sites, marine regions, and urban areas – via fixed observatories, mobile facility deployments, and vertically-resolved tethered balloon system operations. We describe the standardized processing and quality assurance pipeline, from filter collection and processing using the Ice Nucleation Spectrometer to final data products archived on the ARM Data Discovery portal. The dataset includes both total INP concentrations and selectively treated samples, allowing for classification of biological, organic, and inorganic INP types. It features a continuous 5-year record of INP measurements from a central U.S. site, with data collection still ongoing. Seasonal and site-specific differences in INP concentrations are illustrated through intercomparisons at −10 and −20 °C, revealing distinct regional sources and atmospheric drivers. We also outline mechanisms for researchers to access existing data, request additional sample analyses, and propose future field campaigns involving ARM INP measurements. This dataset supports a wide range of scientific applications, from observational and mechanistic studies to model development, and provides critical constraints on aerosol-cloud interactions across diverse atmospheric regimes (Creamean et al., 2024, 2020b; https://doi.org/10.5439/1770816).

ABSTRACT Airborne remote sensing has facilitated high-resolution canopy and soil water assessment, especially in agriculture-intensive regions. This study presents a field-scale assessment of crop water stress index (CWSI) and soil moisture (SM) using unmanned aerial vehicle (UAV)-mounted thermal imagery combined with in-situ hydrometeorological data over a key agricultural site in India’s Ganga basin. The UAV-based LST (LST-Aerial) is modelled using the spectral emissivity from ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) spectral library and atmospheric radiances from a radiative transfer model. The LST-Aerial is subsequently utilized to estimate field-scale CWSI (CWSI-Aerial) and SM (SM-Aerial) across two principal crop seasons (paddy and wheat) using an empirical and multiple linear regression model, respectively. While the radiometer data reveals a significant correlation (R2 = 0.58 to 0.76, p < 0.001) between canopy – air temperature difference and vapour pressure deficit, a temperature difference of ~ 5°C was noticed between non-transpiring baselines of paddy and wheat for the airborne window. The radiometer-derived CWSI (CWSI-Rad) showed a relatively higher value (0.57) during the wheat season compared to paddy (0.19), reflecting the influence of monsoon-fed cropping in north India. Partial least squares regression reveals solar radiation and relative humidity as major meteorological drivers of CWSI-Rad during the paddy and wheat growing period, respectively. While CWSI-Aerial demonstrated superior accuracy (R2 = 0.85, p < 0.05) to CWSI-Rad, it exhibited a high negative correlation (R = −0.75 to −0.97) to concurrent SM and SM-Aerial. Additionally, the predicted SM-Aerial agrees well with ground-based SM with errors ranging from 0.01–0.14 m3.m−3, showcasing the robust UAV-based SM prediction. Findings of this study offer valuable insights into smart and precision agriculture, enabling well-informed regulation of crop water resources in tropical water-limited regions.

Abstract. Aerosol hygroscopicity plays a significant role in atmospheric chemistry, radiation, and climate effects. While previous studies have investigated regional differences in aerosol hygroscopicity, long-term observational studies focusing on seasonal variations in specific regions remain scarce. This study explores size-resolved and seasonal variations in aerosol hygroscopicity in northern Nanjing, using one-year hygroscopicity-tandem differential mobility analyser (H-TDMA) measurements in 2021. Aerosols in the region show relatively low hygroscopicity due to a high organic content (annual average mass fraction: 42.92 % in PM2.5) in fine particles. The mean hygroscopicity parameter (κmean) increases with particle size across all seasons. Particles (40–200 nm) show seasonal κmean variations: winter (0.12–0.24) and spring (0.14–0.25) display relatively higher values attributable to relatively higher secondary inorganic content, while summer (0.12–0.21) and autumn (0.10–0.20) exhibit relatively weaker hygroscopicity due to enhanced contributions from less hygroscopic components. Diurnal patterns are shaped by photochemical aging and aqueous-phase reactions, leading to κmean slight enhancement for larger particles in the afternoon and evening. New particle formation (NPF) events occur most frequently in spring. During spring NPF days, Aitken-mode particles exhibit slightly low hygroscopicity, whereas accumulation-mode particles demonstrate relatively higher hygroscopicity compared to non-NPF days. Regional transport analysis reveals distinct controlling factors: hygroscopicity of 40 nm particles may be mainly controlled by local sources, while 200 nm particles are more influenced by seasonal air mass transport. These results improve understanding of aerosol–cloud interactions and support regional climate modeling and air quality management in urbanizing areas.

To achieve high-precision retrieval of water vapor concentration profiles in the near-space region, this study utilizes the high-resolution spectral radiative transfer model SCIATRAN to simulate water vapor observation spectra under different observational geometric parameters and atmospheric aerosol conditions. A comprehensive analysis is conducted on the influence of these parameters on spectral radiance. The results demonstrate that when the tangent height exceeds 40 km, water vapor absorption features significantly weaken. Spectral data acquired under conditions combining small solar zenith angles with large relative azimuth angles exhibit greater stability. Middle and upper atmospheric aerosols, predominantly composed of volcanic ash and particulate matter, induce strong sensitivity of water vapor spectral radiance to stratospheric and mesospheric aerosols. Notably, under extreme volcanic aerosol loading conditions, the differential-to-background ratio of spectral radiance surpasses 2000%. This investigation identifies key sensitive parameters and their mechanistic influences on near-space water vapor observation spectra. The findings provide a theoretical foundation for optimizing the design parameters of near-space sounders, while offering scientific guidance for formulating data screening strategies and conducting error traceability analysis during water vapor concentration retrieval processes.

A novel robust adaptive decomposition approach for solar energy potential using atmospheric transparency and UV radiation indicators

Octafluoropropane (C 3 F 8 ) is widely used as etching agent in refrigeration, air conditioning and semiconductor industries. However, due to its long lifespan and strong infrared absorbing ability, once C 3 F 8 is emitted, the atmospheric radiation absorbing ability will be permanently altered, which will result in a serious greenhouse effect. Therefore, the efficient removal technology of C 3 F 8 is crucial in protecting the environment and alleviating the greenhouse effect. In this work, a series of X-ETS-4 (X: Mg, Ca, Sr, Ba) molecular sieves were synthesized by solvothermal and ion-exchange method. The morphology and structure of the prepared X-ETS-4 were characterized by FT-IR, XRD, and SEM, etc. The adsorption performance of the X-ETS-4 on C 3 F 8 are determined by fixed-bed adsorption breakthrough experiments and single-component isothermal adsorption experiments. The adsorption mechanism was investigated using different adsorption theoretical models. The results show that Ba-ETS-4 exhibits high adsorption capacity and high adsorption selectivity for C 3 F 8 , achieving C 3 F 8 adsorption separation at very low concentration (C 3 F 8 /N 2 volume ratio = 1:400). The saturated adsorption capacity of Ba-ETS-4 on C 3 F 8 reaches 155.17 mg/g (298 K, 170 kPa), which is 15.49 times more than that of Na-ETS-4. In addition, the ideal adsorption solution theory (IAST) separation selectivity of C 3 F 8 /N 2 reaches 341–941 in the pressure range of 0–170 kPa.

Abstract The physical origin of little red dots (LRDs)—compact extragalactic sources with red rest-optical continua and broad Balmer lines—remains elusive. The redness of LRDs is likely intrinsic, suggesting optically thick gas emitting at a characteristic effective temperature of ∼5000 K. Meanwhile, many LRD spectra exhibit a Balmer break, often attributed to absorption by a dense gas shell surrounding an active galactic nucleus. Using semianalytical atmosphere models and radiation transport calculations, we show that a super-Eddington accretion system can give rise to a Balmer break and a red optical color simultaneously, without invoking external gas absorption for the break or dust reddening. The break originates from a discontinuity in opacity across the Balmer limit, similar to that of early-type stars, but the lower photosphere density of super-Eddington systems, ρ &lt; 10 −9 g cm −3 , implies a significant opacity contrast even at a cool photosphere temperature of ∼5000 K. Furthermore, while accretion in the form of a standard thin disk requires fine tuning to match the optical color of LRDs, an alternative scenario of a geometrically thick, roughly spherical accretion flow implies an effective temperature of 4000 K ≲ T eff ≲ 6000 K that is very insensitive to the accretion rate (analogous to the Hayashi line in stellar models). The continuum spectra from the latter scenario align with the Balmer break and optical color of currently known LRDs. We discuss the predictions of our model and the prospects for more realistic spectra based on super-Eddington accretion simulations.

Abstract. We previously developed the Cloud Height Retrieval from O2 Molecular Absorption (CHROMA) algorithm for the Ocean Color Instrument (OCI) on the new NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Here, we apply CHROMA to observations from the Ocean Land Colour Instrument (OLCI) to guide expectations for PACE, as it will take some time to obtain large-scale validation data for OCI. We use cloud top height (CTH), phase, and (for liquid clouds) cloud optical thickness (COT) data from the ground-based Atmospheric Radiation Measurement (ARM) network to evaluate the OLCI retrievals. We found that OLCI and Moderate Resolution Imaging Spectroradiometer (MODIS) CTH compare similarly well to the ARM reference. OLCI has a tendency to underestimate CTH as CTH increases, and algorithm assumptions about cloud geometric thickness may contribute to this. ARM COT from multifilter shadowband radiometers (MFRSR) and Sun photometers are well-correlated with one another, albeit with a roughly 30 % offset on average; OLCI and MODIS COT agree more closely with the MFRSR data. OLCI retrieval uncertainty estimates show skill at telling low-uncertainty cases from high-uncertainty ones, although CTH uncertainties are underestimated. Additionally, we compare the OLCI data to satellite retrievals based on thermal infrared measurements from MODIS and Sea and Land Surface Temperature Radiometer (SLSTR) data. Differences are broadly consistent with physical expectations based on the A-band vs. thermal techniques, although one key challenge in such aggregated comparisons is different cloud masking sensitivities and algorithm failure rates meaning additional sampling differences are introduced. We conclude by discussing the transition to and possible enhancements for PACE OCI.

Abstract We investigate temperature tendency mechanisms operating over northern Africa following midlatitude upper‐level winter troughs. A case study sequence reveals how Iberia and Central Mediterranean troughs perturb the prevailing cold advection of the Harmattan winds, leading to a several‐day warming event over northeastern Africa, especially marked over the eastern Sahel (ESL). Data used includes a reanalysis product that attributes three‐hour temperature tendency to specific mechanisms. Focused over Days 3–5 (Day 0 is the strong Iberia trough), ESL experiences strong anomalous low‐level warming due to dynamics, attributable to anomalous meridional advection, with partial damping by turbulence, leaving a net low‐level tendency of about +1°C/day. However, these tendency features are confined to the lowest layers; by 700 hPa, they are absent. Net tendency behaves differently, and remains positive up to near 650 hPa, where the boundary layer anomalously rises to in the afternoon, allowing turbulence to share some of the anomalous warm advection to these levels. In this winter case study, there is no evidence of any other substantial forcing or feedback (e.g., from atmospheric moisture radiation, surface latent heating, surface solar radiation), therefore we propose that over ESL, the land‐surface—boundary‐layer system adjusts towards a new equilibrium, driven by the several‐day reduced cold advection from near‐surface to about 850 hPa. The trough sequence induces a continental‐scale cold front, that approaches ESL with distinct advection properties; however, on average, extended warming in ESL events is attributed to advection by the climatological meridional wind operating on the anomalous temperature gradient. During build‐up (e.g. Day 0), anomalous descent over ESL contributes a modest adiabatic compression warming tendency at low levels. In contrast, averaged over Days 3–5, there is modest anomalous ascent, one aspect of the boundary‐layer characteristics during the reduced cold advection that are explored. Generalization of highlighted processes now requires more cases.

Abstract This study develops and evaluates a Random Forest (RF) model for estimating planetary boundary layer height (PBLH) using 9 years of data from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) user facility, with potential application in the NOAA Surface Radiation (SURFRAD) Network. The model integrates ceilometer, surface meteorology, and radiation measurements, and is trained using thermodynamic PBLH estimates derived from radiosondes. This approach aims to bridge gaps between aerosol‐based and thermodynamic‐based PBLH estimates. The RF model outperformed traditional methods during daytime and better captured transition periods, demonstrating improved accuracy and robustness. At ARM SGP, it showed a substantial reduction in both bias and RMSE, with a bias near zero (−4.9 m) compared with traditional Haar Wavelet (HW) (70.9 m) and Vaisala BL‐View software (124.1 m), and an RMSE of 303.2 m, lower than both BL‐View (566.9 m) and HW (404.6 m). During daytime hours, RF consistently outperformed both alternatives, maintaining lower bias and RMSE across all periods. At a second evaluation site, RF achieved the lowest overall RMSE (323.7 m), similar to HW (326.4 m) and significantly better than BL‐View (738.3 m). However, all models showed reduced accuracy under stable nighttime conditions, limiting the reliability of PBLH estimates. Key predictors for the model included the lifting condensation level height (LCLH), aerosol gradients, and month for seasonal variability. The study underscores the potential of integrating machine learning with multiple data sets such as surface energy and thermodynamic data to advance PBLH estimation.

Abstract Profiles of radiative fluxes simulated from thermodynamic and cloud observations made at the Atmospheric Radiation Measurement (ARM) eastern North Atlantic (ENA) site for a 6-yr period are termed as ENARad. ENARad radiative fluxes are compared to those from the Clouds and the Earth’s Radiant Energy System (CERES) 1°-resolution synoptic product (SYN1deg)-simulated radiative flux profiles as well as the CERES instrument observed top-of-the-atmosphere (TOA) fluxes and ground site broadband radiometer measurements. Monthly average differences between ENARad and surface radiometer reported fluxes and differences between ENARad, SYN1deg, and observed fluxes at TOA were statistically insignificant. SYN1deg significantly overestimated surface downwelling shortwave flux by 12 ± 52 W m−2 and surface downwelling longwave flux by 5 ± 20 W m−2 on monthly time scales. Such overestimations were traced to a moister and warmer subcloud layer, a drier cloud layer, and a moister and colder above-cloud-free troposphere in the ancillary thermodynamic and cloud properties used by SYN1deg than observed. Similarly, low-cloud coverage, boundaries, and liquid water paths utilized by SYN1deg were also significantly higher than observed. Intramodel differences in the hourly values of shortwave fluxes exceeded 100 W m−2 at the TOA and the surface. These differences were also due to inaccuracies in the representation of low-cloud properties within the SYN1deg product relative to those determined by ENA ARM instrumentation and used as ENARad ancillary data. Results presented are relevant to investigations employing the CERES SYN1deg data product, studies that estimate radiative fluxes from surface-based or satellite-borne observations, and comparative analyses of radiative fluxes derived using different methodological approaches.

Radiative cooling can be used to passively cool objects below ambient temperature by exhausting heat toward the sky. The emitted power flux may be used to generate electricity, but devices often require low-bandgap or rare-earth materials that are difficult to scale. Here, we demonstrate an alternative approach that generates mechanical power from Earth’s ambient radiation using a Stirling engine. Outdoor experiments performed throughout the year show that temperature differences >10°C are sustained during most months, resulting in the generation of >400 milliwatts per square meter of mechanical power with a potential for >6 watts per square meter. We further apply this technique for air circulation, achieving >0.3 meters per second with a potential volumetric flow rate that exceeds 5 cubic feet per minute (cfm), which is sufficient for CO2 circulation in greenhouses and for thermal comfort inside residential buildings.

Abstract Solar energy has been a clean and renewable resource that offers a promising solution for water harvesting. Herein, a double slope solar still (DSSS) unified with an external condenser and internal heater was fabricated and tested to enhance freshwater production rates under Malaysian climate conditions. The integrated model was designed to operate both day and night, and its productivity was compared with that of a passive still. The study outcomes revealed that the average increment in the daily production rate of the active still was 56% during the daytime and 510% during the nighttime compared to the passive one. When calculating the cumulative production rates over the five days of the field experiment, the active still demonstrated a notable increase in productivity, reaching approximately 159% as compared to the passive one. This resulted in total production rates of 34.14 and 13.20 kg/m 2 from the active and passive stills, respectively. Compared to the passive still, the active still had a lower relative humidity due to the external condenser. Additionally, the factors such as water and ambient temperatures and solar radiation intensity significantly impact daily distillate output at which strong correlations were observed between these parameters. Finally, the product water demonstrates a significant improvement in desalinated water quality, meeting safety standards outlined by the World Health Organization (WHO).