Science Systems and Applications (United States)

Abstract Increased aerosol concentrations can brighten low‐level clouds and extend their lifetimes, but aerosol–cloud interactions (ACI) remain highly uncertain and difficult to quantify. We show that part of this uncertainty is caused by topographical influences on clouds, that is, those arising from land–water contrasts. This is demonstrated using satellite retrievals in regions with extensive river networks, such as the Amazon Basin. 15 years of MODerate resolution Imaging Spectroradiometer (MODIS) satellite data show cloud formation over the Amazon River basin is suppressed by 26% with warm low clouds above the river exhibiting a 22% smaller droplet effective radius and 18% higher droplet concentration () compared to adjacent land clouds. Thus, clouds above the river may appear polluted but are actually influenced by river‐breeze circulations driven by the thermal contrast between the river and the surrounding land. These responses are robust in both wet and dry seasons, and tests using an improved MODIS retrieval product show cloud differences are unlikely due to retrieval artifacts. In situ measurements from the Green Ocean Amazon Experiment (GoAmazon) confirm that is elevated above rivers and are also higher when carbon monoxide concentrations are elevated near the large city of Manaus. Lagrangian airmass tracking over Manaus shows that regional‐scale river‐breeze circulations impact as much as the urban aerosol plume, complicating ACI attribution and highlighting the need to isolate land‐surface effects to assess ACI in continental regions.

Oceans remain severely under-sampled in aerosol optical properties, limiting our ability to assess marine aerosol–climate feedbacks, long-range transport and to validate satellite products over two-thirds of Earth’s surface. The Sun–sky–lunar photometer CIMEL CE318-T has been successfully adapted for autonomous shipborne operation through the PHOTONS Observation Service (ACTRIS, Univ. Lille, CNRS) in collaboration with CIMEL and within ACTRIS-CARS activities. The system is fully compatible with AERONET processing. Here we summarize recent developments and multi-year results supporting the deployment of a global network of automatic ship-based photometers.Since 2021, a CE318-T has operated continuously on the research vessel (R.V.) Marion Dufresne under the framework of MAP-IO program. Between July 2021 and June 2024, it collected >25,000 Level 1.5 measurements in the southwestern Indian Ocean, with mean AOD (Aerosol Optical Depth) of 0.09 ± 0.07 (440 nm) and 0.05 ± 0.03 (870 nm), and EAE (Extinction Angstrom Exponent) of 0.7 ± 0.4, typical of clean marine conditions. A biomass-burning aerosol (BBA) event allowed retrieval of microphysical properties (size distribution, refractive index), showing the capability of the system under real ship-motion.During TRANSAMA campaign (La Réunion–Barbados, Apr–May 2023), two CE318-T photometers combined with a micropulse lidar aboard R.V. Marion Dufresne provided complementary column and vertical information. Despite low AOD (0.08 ± 0.04 at 440 nm) in the remote South Atlantic, the lidar detected transported continental layers not evident from column-integrated data alone. Photometer intercomparison showed excellent agreement (R > 0.96; RMSE = 0.005–0.008). Motion-induced degradation on data quality highlighted the need for the ongoing instrumental tests, using a motion-simulation hexapode platform.A second permanent site aboard the R.V. Gaia Blu (CNR, Italy) has collected >20,000 measurements mainly in the Mediterranean since Feb 2024. Mean AOD (0.19 ± 0.14 at 440 nm) and EAE (1 ± 0.4) reflect more variable aerosol regimes, including BBA and Saharan dust. Comparisons with nearby AERONET ground-based stations validated retrieval quality. In addition, the installation of a 3D scanning lidar (Sep 2025) further enhances observations of aerosol vertical structure and air–sea interactions.These first results demonstrate the capability of ship-based photometers, and their synergy with lidar, to fill critical observational gaps over the oceans. Improved data acquisition strategies addressing vessel structure and motion are ongoing. To date, five ship-photometers operate across major maritime regions: R.V. Marion Dufresne-France (Indian Ocean), R.V. Gaia Blu-Italy (Mediterranean Sea), R.V. Sarmiento de Gamboa-Spain (Atlantic Ocean), R.V. Perseverance-France (currently Pacific Ocean), and MS Richard With-Norway (Arctic/Norwegian coast). These installations represent a major European step toward the first global network of automatic shipborne photometers to improve aerosol characterization over remote oceans and support satellite CAL/VAL.

We present the latest developments in SPEXone aerosol products. Firstly, the RemoTAP-Hybrid algorithm is developed, combining Multiple Collaborated Neural Networks (MCNN) with a full physics inversion. RemoTAP-Hybrid improves SPEXone global aerosol retrievals regarding accuracy and speed. Secondly, following an analysis on AERONET data, we extend the aerosol description to a parametric 4 mode by adding a fine non-spherical mode, in addition to a fine spherical, coarse non-spherical, and coarse spherical mode. The new aerosol description extends retrieval capability for scenes dominated with non-spherical fine particles. Thirdly, higher level products are developed for aerosol composition (black carbon, brown carbon, dust, fine/coarse water/non-absorbing components, fine non-spherical non-absorbing component) based on the retrieved complex refractive index and aerosol volume per mode. We will present the global and seasonal distribution of chemical composition and aerosol microphysics retrieved from SPEXone.We validate the retrieved aerosol properties with AERONET data for AOD, Angstrom Exponent, absorption AOD, and SSA, showing unprecedented accuracy. The RMSE for AOD is 0.051 (0.037) over land (ocean), and 78.3% (80.8%) of the AOD retrievals are within the Global Climate Observing System (GCOS) requirement. The RMSE for Angstrom Exponent is 0.186 (0.207), for absorption AOD is 0.023 (0.014), and for SSA is 0.038 (0.044) over land (ocean). Finally, we present our latest results on aerosol retrievals above cloud from SPEXone.

Tropospheric Emissions: Monitoring of Pollution (TEMPO) is observing air quality andatmospheric composition over North America from a geostationary orbit since its operationsstarted in August 2023. TEMPO observes the continent every 40 to 60 minutes at a spatialresolution on the order of ~ 2 x 4.5 km 2 . Together with the Geostationary EnvironmentMonitoring Spectrometer (GEMS, launch 2020) monitoring Asia and the Sentinel-4/UVN(launch 2025) monitoring Europe, TEMPO is part of the current global constellation ofgeostationary sensors devoted to the observation of air quality. Like GEMS and Sentinel-4/UVN,TEMPO uses backscattered ultraviolet and visible solar radiation to retrieve atmosphericamounts of key trace gases and aerosols associated with air quality and atmospheric chemistry.Among the species retrieved from TEMPO observations of nitrogen dioxide and formaldehydeare important to understand emissions and atmospheric chemistry, including the formation anddestruction of tropospheric ozone.After multiple version updates over the first two years of the mission, the TEMPO Level 2 NO 2and HCHO products have undergone significant enhancements to improve the performance andaccuracy of the slant column retrievals, air mass factor calculations and post-processingcorrections including destriping for NO 2 and background for HCHO. We illustrate theperformance of both retrievals (version 3 & 4), evaluating their fitting uncertainty and showingcomparisons with independent correlative measurements and other satellite products showcasingsmall noise levels and remarkable accuracy with well quantified biases. We continue byillustrating the capacity of TEMPO products focusing on different case studies showingTEMPO’s high temporal and spatial resolution. We finalize discussing aspects of the retrievalsubject to improvement and our plans to address them.

Abstract. NASA's Tropospheric Emissions: Monitoring of Pollution (TEMPO) geostationary satellite sensor provides high temporal and spatial resolution measurements critical for monitoring air quality. During the Synergistic TEMPO Air Quality Science (STAQS) component of the 2023 AGES+ campaign, extensive surface, airborne, and remote-sensing observations were collected over the New York City/Long Island Sound region, enabling comprehensive investigation of ozone and its precursors, including nitrogen dioxide (NO2) and formaldehyde (HCHO). Evaluating TEMPO (version 3) NO2 and HCHO column retrievals against Pandora and GEO-CAPE Airborne Simulator (GCAS) observations shows TEMPO can capture urban-suburban pollution gradients and exhibits biases comparable to previous satellite validation studies with strong agreements for NO2 (R ≈ 0.79–0.81), though sharp transitions between high and low emission regions remain challenging. The high-resolution (1.33 km × 1.33 km) WRF-Chem simulation reproduces the major spatiotemporal patterns of surface ozone and NO2 (R ≈ 0.56–0.73), supporting its use to fill observational gaps. By integrating TEMPO, WRF-Chem, in situ measurements, and Tropospheric Ozone Lidar network and Doppler wind lidar observations, we characterize the spatiotemporal dynamics of ozone under different pollution regimes. High-pollution days involve early urban precursor accumulation, entrainment of pollutant-rich residual-layer air, and sea-breeze-driven recirculation toward coastal regions. Moderate days exhibit localized enhancements driven by transport, such as downwind plume transport, while low-pollution days show efficient dispersion and limited ozone formation. This multi-platform framework highlights the importance of resolving fine-scale variability in coastal and transition zones and demonstrates TEMPO's value for improving ozone forecasting and mitigation in complex environments

Abstract. A variety of chemical and dynamical processes in the troposphere and stratosphere affect tropical total column ozone (TCO), the net effect of which may cause changes in surface UV radiation and impact human and ecosystem health. We use dynamical linear modeling to estimate tropical trends in TCO and partial column ozone (PCO) in the troposphere and three stratospheric layers to assess agreement between satellite observational composites and chemistry–climate model (CCM) simulations from two multi-model experiments (CCMI-1 and CCMI-2022). While both model experiments show tropical TCO increases over 2000–2021, CCMI–2022 trends (+2.5 DU) agree slightly better with observations than CCMI-1 (+1.6 DU). However, this overall agreement obscures multiple systematic differences in PCO trends between the models and observations across atmospheric layers. For example, since 2000 tropical tropospheric PCO increased significantly in CCMI-2022 (+1.5 DU) but not in CCMI–1 (+0.3 DU), largely explaining the difference in TCO trends. Also, despite nearly identical stratospheric PCO trends, CCMI-2022 trends are slightly more negative in the lower stratospheric (by ~0.5 DU), compensated by more positive middle/upper stratosphere trends compared to CCMI-1. Crucially, substantial differences exist across observational PCO trends, particularly in the troposphere and middle/upper stratosphere, and these disagreements limit the ability to evaluate CCM fidelity. Furthermore, while the inter-model correlation between late and early 21st century trends is suggestive of a potential emergent constraint on future ozone trends, the spread in observational trends precludes its observational implementation.

Abstract. The MISR Research Aerosol retrieval algorithm (RA) was developed in parallel with the MISR standard operational algorithm (SA), to explore innovative retrieval ideas for possible implementation in the SA, and to provide higher-spatial-resolution results with enhanced sensitivity to particle properties, where possible. Whereas the SA was designed to run automatically on the entire MISR dataset, the RA, a research code, had to be run on a case-by-case basis, with considerable user involvement. We present here a version of the RA, the MISR Research Product Algorithm (MRPA), that has been streamlined and automated for wider use, along with validation results for this algorithm. The compromises required to automate the RA result in somewhat diminished particle-type sensitivity. However, the MRPA provides 1.1 km pixel resolution (compared to 4.4 km for the SA), and comparing the AOD data statistically with AERONET, it offers about half the statistical RMSE, significantly higher correlation coefficient, though somewhat higher bias, for mid-visible AOD compared to the SA over land, along with better Ångström exponent statistics, especially at higher AOD. Statistical validation of particle shape and single-scattering albedo is more difficult, but for sufficiently high AOD, retrievals in smoke-dominated regions show a preponderance of small-medium, spherical, light-absorbing particles, whereas dust-dominated regions tend to have larger, weakly absorbing, non-spherical particles.

Ultra-violet (UV) and near-UV wavelengths are necessary for many important optical transitions for quantum technologies and various sensing mechanisms for biological and chemical detection. However, all well-known photonic platforms have excessively high losses in the UV, which has prevented photonic integrated circuits (PICs) being used to address these and other important application spaces. Photonic waveguides using low-loss alumina cores and silicon dioxide cladding have emerged as a promising solution because of alumina’s large optical bandgap and the high quality of films enabled by atomic layer deposition. These properties allow passive, low-loss waveguide operation down to at least 266 nm using multimode widths. However, to the best of our knowledge, active alumina PICs have only been realized using thermo-optic tuning, which precludes switching speeds shorter than approximately 100 microseconds, high circuit densities, and cryogenically compatible operation. Here, we introduce a CMOS-fabricated, piezo-optomechanical PIC platform using alumina waveguides and piezoelectric aluminum nitride strain actuators. The platform allows for sub-microsecond switching times, high circuit densities, and cryogenic operation which is desired in many UV PIC applications. We demonstrate a high-performance, reconfigurable optical filter operating at wavelengths as low as 320 nm. The filter has a 6-nanosecond switching time, a loaded linewidth of 3.3 GHz, tuning rate of 28 V/linewidth, and a hold power of less than 20 nW at one linewidth detuning. This work establishes the foundations for a new class of CMOS-fabricated, rapidly reconfigurable, and low-power UV photonic circuits compatible with wavelengths as low as 225 nm.

Abstract. The boreal forest has experienced the fastest warming of any forested biome in recent decades. While vegetation–climate models predict a northward migration of boreal tree cover, the long-term studies required to test the hypothesis have been confined to regional analyses, general indices of vegetation productivity, and data calibrated to other ecoregions. Here we report a comprehensive test of the magnitude, direction, and significance of changes in the distribution of the boreal forest based on the longest and highest-resolution time-series of calibrated satellite maps of tree cover to date. From 1985 to 2020, boreal tree cover expanded by 0.844 million km2, a 12 % relative increase since 1985, and shifted northward by 0.29° mean and 0.43° median latitude. Gains were concentrated between 64–68° N and exceeded losses at southern margins, despite stable disturbance rates across most latitudes. Forest age distributions reveal that young stands (up to 36 years) now comprise 15.4 % of forest area and hold 1.1–5.9 Pg of aboveground biomass carbon, with the potential to sequester an additional 2.3–3.8 Pg C if allowed to mature. These findings confirm the northward advance of the boreal forest and implicate the future importance of the region's greening to the global carbon budget.

<strong class="journal-contentHeaderColor">Abstract.</strong> We present an updated evaluation of stratospheric ozone profile trends in the 60&deg;S&ndash;60&deg;N latitude range using long-term ground-based and satellite climate data records, as well as simulations by chemistry-climate models. The trends are evaluated using the LOTUS (Long-term Ozone Trends and Uncertainties in the Stratosphere) regression model. Analyses of satellite data confirm statistically significant positive ozone trends in the period 2000&ndash;2024 in the upper stratosphere of ~1&ndash;3% decade^-1, with larger trends at mid-latitudes compared to the tropics. The trends are slightly positive or close to zero in the middle stratosphere, and mostly negative, &minus;1&ndash;2% decade^-1, in the lower stratosphere; but they are not statistically significant. The ozone trends are similar to previous analyses (2000&ndash;2020 trends). Ozone trends in 2000&ndash;2024 predicted by climate model simulations are in good agreement with combined satellite trends. In the upper stratosphere, models predict a slightly stronger ozone recovery than observations. In the lower stratosphere, both models and satellite observations report negative trends of in the tropics, while modelled ozone trends are slightly positive at mid-latitudes. Ozone profile trends over several stations estimated from ground-based records capture the same overall vertical pattern of ozone trends as merged gridded satellite datasets. Analyses of regional ozone trends in 2003&ndash;2024 using merged satellite datasets confirmed the previous observations of a longitudinal structure in ozone trends in the NH mid-latitude stratosphere, with positive trends over Scandinavia and negative trends over Siberia. However, the magnitude of this dipole-like structure is reduced compared to previous analyses.