GML Publications for 2026

Abstract

Riihimaki et al. (2021) (R21) [1] developed a machine learning model that predicts surface solar irradiance variability from cloud type and cloud cover from five years of cloud radar, lidars, and surface radiation observations at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site in Oklahoma. This study complements that study by evaluating R21 model s performance and applicability in different climates at 15 additional sites. The additional sites include other ARM sites located globally and National Oceanic and Atmospheric Administration (NOAA) Surface Radiation Network (SURFRAD) sites located across the continental United States. The observed relationship of the standard deviation of the minute-to-minute change in effective transmissivity (sigma(Delta ET)) varying with cloud type and cloud cover was found to be site agnostic and agreed with R21.

Abstract

Aerosol particles resulting from both wildfires and dust events introduce considerable uncertainty into both climate research and public health assessments. These challenges are becoming particularly evident in the western US. To gain a deeper understanding of western US aerosol properties, we analyzed 13 years (2011-2024) of surface in-situ aerosol optical data from Storm Peak Laboratory (SPL) in northwestern Colorado, and 6 years (2019-2024) of surface in-situ aerosol optical data from Table Mountain (BOS) in central Colorado. The aerosol optical properties at both sites demonstrate a strong summer wildfire smoke signal (peaking in August) and evidence of springtime dust events. BOS exhibited higher aerosol loading than SPL, particularly during spring and winter, consistent with the proximity of BOS to urban sources and its lower elevation. While the general patterns observed for SPL are consistent with a previous climatological analysis (covering the period 2011-2016) for the site, the longer SPL dataset used here shows that there has been a significant increase in extreme wildfire smoke events for 2017-2024 relative to 2011-2016. Both summer and fall exhibit statistically significant positive trends in the upper percentiles of scattering coefficient with trends of 10 +/- 1 \% yr(-1) at the 98th percentile in the summer and 2.4 +/- 0.4 \%yr(-1) at the 96th percentile in the fall. Co-variability among some of the aerosol optical properties is used to further identify aerosol types and temporal patterns, demonstrating similarities between the two sites.

Abstract

Improving our understanding of Antarctic glacial dynamics is essential for accurately predicting ice sheet behavior and its contribution to global sea level rise under future climate scenarios. The Weddell Sea Embayment, which channels ice from East Antarctica, West Antarctica, and the Antarctic Peninsula into the Filchner-Ronne Ice Shelf, is a critical region for such investigations. Yet, considerable uncertainty remains about the ice sheet evolution since the last glacial period, which limits the ability to robustly constrain earth system models across deglacial intervals. To address this, we present new marine geological evidence from Hughes Trough, near the calving front of the modern Ronne Ice Shelf. Geomorphic evidence suggests that grounded ice existed here during the last glacial period, with neodymium (Nd) and lead (Pb) isotope compositions of subglacially-derived sediments suggesting ice originated from either East Antarctica or a province in West Antarctica that is relatively unradiogenic isotopically. Radiocarbon dating of grounding line-proximal sediments using the ramped pyrolysis-oxidation suggests that local ice retreat may have already commenced by 16.8 cal ka BP. Radiogenic isotopes preserve evidence of ice stream provenance and the progressive establishment of oceanic connectivity between Hughes and Ronne Troughs, followed by linkage to Filchner Trough. The development of inter-trough seaways facilitated oceanic circulation and sediment transport throughout the embayment. However, a subsequent temporary re-isolation of the Ronne and Filchner sectors occurred during the early-Holocene, associated with glacial readvance in the Filchner Trough and ice stream reconfiguration.

Abstract

Accurate quantification of hazardous material releases in cities is critical for emergency managers aiming to mitigate health impacts and mortality in the population. Here, a study on the development and evaluation of a high-resolution (1-km, 1-hr) urban-scale atmospheric inverse modeling system for the Washington, DC, and Baltimore, MD, metropolitan area (DCBA) is presented to advance surface flux quantification in urban and industrial areas where the potential for a hazardous release is high. The system employs an inert tracer as a proof of concept for January 2019 and builds upon HYSPLIT atmospheric transport and dispersion simulations driven by high-resolution Weather Research and Forecasting (WRF) model simulations that ingest urban meteorological observations, coupled with the CarbonTracker-Lagrange (CT-L) inverse model tailored to account for hourly spatiotemporal fluxes. The system assimilates tower-based tracer observations from the National Institute of Standards and Technology (NIST) Northeast Corridor Urban Test Bed and utilizes the 1-km Vulcan and 4-km GRA2PES bottom-up inventories as prior knowledge of the tracer fluxes. Numerical experiments using synthetic and actual data reveal that the system significantly improves the quantification of flux strength (mean flux) and total mass released across the urban cores of Washington, DC, and Baltimore, MD. Hourly flux variations are fairly well resolved when originating from a broad territory (city scale), while the accuracy of source retrieval improves when flux estimates are aggregated to coarser spatial resolutions (e.g., 4 km). This work has important implications for estimating hazardous releases from urban areas for emergency response and hazard analysis.

Abstract

The atmospheric methane (CH4) growth rate surged after 2019, peaking at 16.2 parts per billion per year (ppb year-1) in 2020 before declining to 8.6 ppb year-1 in 2023. Using multiple atmospheric inversions constrained by observation- and model-based prescribed hydroxyl radical (OH) fields and CH4 atmospheric data, we show that a drop of OH radicals in 2020-2021, followed by recovery in 2022-2023, accounted for 83\% of year-on-year variations in the CH4 growth rate, the rest being explained by wetland and inland water emissions, which increased between 2019 and 2020-2022 [+8.6 +/- 2.6 teragrams of CH4 per year (TgCH4 year-1)] and then decreased between 2022 and 2023 (-9.9 +/- 3.3 TgCH4 year-1). Most emission changes from 2019 to 2023 occurred in northern tropical wetlands in Africa and Asia, whereas South American wetlands emissions declined and Arctic emissions increased after 2019.

Abstract

Methane (CH4) is a potent greenhouse gas; however, the causes of its growth since 2006 are a subject of debate. While measurements of CH4 mole fraction and carbon isotopic composition (delta 13C-CH4) have been extensively used to investigate the global CH4 budget, the hydrogen isotopic composition (delta D-CH4) remains underutilised despite its unique sensitivity to source types and oxidation processes. Here, we assimilate a newly harmonised 35-year dataset of dual isotope measurements from high-latitude monitoring stations in both hemispheres within a two-box Bayesian inversion to quantify global CH4 sources and sinks. The model integrates prior emissions from five source categories based on global bottom-up inventories. Methane removal processes are represented by sink-specific kinetic isotope effects as tropospheric and stratospheric loss, and soil uptake.We find that the inclusion of delta D-CH4 improves the model s ability to constrain emission apportionment between biogenic and thermogenic sources, particularly for fossil fuel emissions during the late 1990s and early 2000s, which affects CH4 lifetime estimate. CH4 increase post-2006 is driven mainly by rising wetland emissions, while fossil-fuel growth is modest, biomass burning declines, and agriculture and waste make smaller, regionalised contributions. The optimised inversion results favour a strong 13C kinetic isotope effect in total tropospheric CH4 removal and a net shortening of the NH lifetime of CH4 by 0.2 years. This study demonstrates the added value of incorporating delta D-CH4 into inverse modelling frameworks and underscores the importance of long-term delta D-CH4 measurements for advancing our understanding of CH4 biogeochemistry and its role in the global carbon cycle.

Abstract

Black carbon (BC) aerosol is an important driver of Arctic warming, and China used to be a major contributor to the Arctic BC burden through long-range atmospheric transport. Here we show that China s contribution declined significantly from 2009 to 2022, primarily due to reductions in domestic BC emissions following the implementation of clean air policies. Global chemistry-transport model simulations indicate a relative decline of similar to 3\% yr(-1) (p < 0.05) in China s Arctic BC contribution, exceeding the decrease rate in the underlying emission inventory. Sensitivity simulations further suggest that climate change-induced shifts in atmospheric transport may have amplified this decline. Observations of aerosol absorption coefficients (sigma(ap)) at Arctic background observatories revealed steeper declines in sigma(ap) when modeled China-to-total BC ratios were higher. Moreover, sigma(ap) correlated positively with modeled BC from China, with stronger relationships as the modeled China-to-total BC ratios increased. Together, these results provide robust evidence that China s emission reductions have diminished its role in Arctic BC, contributing an estimated 0.02 W m(-2) decrease in the direct radiative effect during the Arctic haze season. Plain Language Summary Black carbon (BC) is a short-lived pollutant that warms the Arctic by absorbing sunlight and darkening snow and ice. Most Arctic BC originates in lower latitudes and is carried northward by winds. Around 2010, China was a major contributor to Arctic BC. Here we show that China s contribution decreased strongly from 2009 to 2022, mainly due to clean air policies that reduced domestic BC emissions, with additional decreases linked to climate-driven changes in transport. Computer model simulations indicate an approximately 3\% yr(-1) decline in China s Arctic BC contribution, and long-term measurements at Arctic observatories confirm this trend. These findings show that China s BC emission reductions have played an important role in lessening Arctic air pollution and warming, demonstrating that emission controls in mid-latitude regions can bring clear climate benefits to the Arctic.

Abstract

Nitrogen oxides (NOx = NO + NO2) in the troposphere form an array of secondary pollutants that are detrimental to air quality, ecosystems, and climate. The family of reactive oxidized nitrogen (NOy) in the atmosphere consists of NOx and its reservoir species (e.g. HNO3, PAN). Our understanding of the processes underlying the transformation of NOy has advanced considerably over recent decades, however, the relative importance of NOy partitioning and loss pathways remain uncertain. In this study, we use the GEOS-Chem global chemical transport model and observations from the ATom flight campaign to assess the simulated global budget of tropospheric NOy, and the production and loss fluxes between key NOy species. Our simulation indicates that the mean global chemical lifetime of NOx is similar to 23 h and the mean global deposition lifetime of NOy is 5.5 d. The global mean NOx:NOy ratio is 0.23 at the surface (over continents it is 0.34) and is 0.10 at 500 hPa. In addition to the four most prevalent gas-phase species (NO, NO2, HNO3, PAN) that have been central to previous descriptions of tropospheric NOy chemistry, we find that other species play key roles in driving overall chemical cycling. The model representation of organic nitrate chemistry is highly simplified and likely overestimates the importance of hydrolysis as a sink while underestimating deposition. Finally, the photolytic loss of particulate nitrate (pNO3-) to form NO2 and HONO, as represented in our simulations, is comparable to its depositional loss, indicating the importance of further constraining this photolysis sink.

Abstract

In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. We track twelve key sets of indicators of the state of the climate system, closely following Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment report (AR6) methods, to produce our fourth annual publication. One of the indicators, the Earth s energy imbalance (EEI) provides a crucial integrative measure of the overall heating of the planet and the pace of climate change - this has more than doubled since the 1976-1995 period. A newly added indicator of temperature extremes, the number of days experiencing marine heatwaves, has more than tripled between 1991 and 2025.For the 2016-2025 decade average, observed warming relative to 1850-1900 was 1.26 [1.13 to 1.36] degrees C, of which 1.24 [1.0 to 1.5] degrees C was human-induced. Human-induced warming reached 1.37 degrees C relative to 1850-1900 in the year 2025, increasing at a rate of 0.27 [0.2-0.4] degrees C per decade over 2016-2025. This high rate of warming, which matches the all-time high seen last year in the instrumental record, was caused by a combination of greenhouse gas emissions being at an all-time high of 54.6 +/- 5.5 GtCO2e yr-1 over the last decade (2015-2024), as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that CO2 emission growth is slowing. The continuation of these annual updates could track decreases or increases in the rate of human influence and climatic changes presented here, reflecting the outcomes of societal choices during the critical 2020s decade.The data presented herein can provide a useful reference point for the drafting of the IPCC seventh assessment report. In total, we employ analysis from over 40 global datasets (10.5281/zenodo.20499280, Smith et al., 2026a). Future monitoring of these indicators, such as ocean and satellite measurements of the Earth s energy imbalance, are threatened by geopolitical and public funding decisions. Our ability to consistently track many of the indicators requires the continuity of observation programs and coordination mechanisms, including the Global Climate Observing System (GCOS) program, that enable their effective integration and use.

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (E-FOS) are based on energy and cement production data. Emissions from land-use change (E-LUC) are estimated by bookkeeping models based on land-use data. The global atmospheric CO2 growth rate (G(ATM)) is computed from changes in concentration measured at surface stations. The global net uptake of CO2 by the ocean (S-OCEAN) is estimated with global ocean biogeochemistry models and observation-based fCO(2)-products. The global net uptake of CO2 by the land (S-LAND) is estimated with dynamic global vegetation models. Additional lines of evidence are provided by atmospheric inversions, atmospheric oxygen measurements, ocean interior observation-based estimates, and Earth System Models. This year, we introduced corrections on the E-LUC, S-OCEAN and S-LAND estimates. The sum of all sources and sinks results in the carbon budget imbalance (B-IM), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as +/- 1 sigma. For the year 2024, E-FOS increased by 1.1 \% relative to 2023, with fossil emissions at 10.3 +/- 0.5 GtC yr(-1) (including the cement carbonation sink, 0.2 GtC yr(-1)), E-LUC was 1.3 +/- 0.7 GtC yr(-1), for total anthropogenic CO2 emissions of 11.6 +/- 0.9 GtC yr(-1) (42.4 +/- 3.2 GtCO(2) yr(-1)). Also, for 2024, G(ATM) was 7.9 +/- 0.2 GtC yr(-1) (3.73 +/- 0.1 ppm yr(-1)), 2.2 GtC above the 2023 growth rate. S-OCEAN was 3.4 +/- 0.4 GtC yr(-1) and S-LAND was 1.9 +/- 1.1 GtC yr(-1), leaving a large negative B-IM (-1.7 GtC yr(-1)), suggesting that the total sink or G(ATM) is strongly overestimated in 2024. The global atmospheric CO2 concentration averaged over 2024 reached 422.8 +/- 0.1 ppm. Preliminary data for 2025 suggest an increase in E-FOS relative to 2024 of +1.0 \% (0.2 \% to 1.7 \%) globally, and atmospheric CO2 concentration increasing by 2.1 ppm reaching 425.6 ppm, 53 \% above the pre-industrial level (around 278 ppm in 1750). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959-2024, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr(-1) persist for the representation of annual to decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink.

Abstract

China is a major source of anthropogenic emissions, with important implications for chemical composition and aerosol processes in the upper troposphere and lower stratosphere (UTLS), particularly within the Asian Summer Monsoon (ASM) anticyclone. Carbon monoxide (CO) is a robust tracer of anthropogenic influence and is routinely observed by remote platforms. In the ASM region, the GEOS-FP forecast system predicts frequent, rapid convective transport of boundary-layer CO into the UTLS. During the 2022 Asian Summer Monsoon Chemical and Climate Impact Project (ACCLIP), five in-situ spectrometers aboard two coordinated research aircraft provided some of the first vertically resolved UTLS CO measurements in the ASM region, providing generally good agreement with forecast abundances. On 19 August 2022, exceptionally enhanced UTLS CO, exceeding 325 ppb, was recorded by both ACCLIP research aircraft over the Yellow Sea west of Korea, exceeding GEOS-FP predictions and producing a pronounced C-shaped vertical profile indicative of strong convective outflow. None of the satellite profile products examined (MLS, MOPITT, AIRS, CrIS, or IASI) captured the magnitude or vertical structure of this enhancement, highlighting limitations in remote-sensing sensitivity to sharp UTLS gradients. Simulations from global models with sophisticated chemistry schemes, GEOS-GOCART and CESM2-WACCM, attribute the sampled plume to a local convective outbreak approximately 12 hr before in-situ sampling. GEOS-GOCART better reproduced the observed profile, while CESM2-WACCM simulated weaker lofting; however, both underestimated the magnitude of CO in the UTLS. This case underscores challenges in validating localized deep-convective transport and demonstrates the continued need for high-resolution (spatial and temporal) in-situ UTLS observations.

Abstract

In situ carbonyl sulfide (OCS) measurements from the Stratospheric Aerosol processes, Budget and Radiative Effects (SABRE) 2023 airborne campaign are used to evaluate the sulfate budget in the Arctic stratosphere during boreal winter. The strong correspondence between these measurements and remote retrievals from the Atmospheric Chemistry Experiment-Fourier Transform Spectrometer provide robust validation of the satellite s capability to monitor stratospheric OCS globally. We demonstrate how trends in the tropical tropopause layer and National Oceanic and Atmospheric Administration OCS surface data reveal a post-2016 similar to 8\% global decline in OCS abundance, which is absent from many global climate models. New simulations with a revised planetary boundary layer OCS abundance show improved agreement with remote retrievals and in situ data across multiple stratospheric layers, but remaining model biases highlight the need for additional in situ OCS observations. The revised representation reduces the stratospheric sulfate burden, resulting in an increased shortwave solar flux at the tropical tropopause by as much as 0.3 Wm-2 locally, with implications for stratospheric circulation, radiative forcing, and climate feedbacks.

Abstract

Atmospheric methane concentrations increased at a rate of 0.7\% year-1 over 2019-2024, but the causes are unclear. We conducted an analytical inversion of bias-corrected TROPOspheric Monitoring Instrument (TROPOMI) satellite observations to quantify 2019-2024 annual mean methane emissions and hemispheric OH concentrations. We find that the methane rise from 2019 to 2024 reflects an approach to steady state between 2019 sources and sinks (59\% of the rise), augmented by increasing emissions (25\%) and decreasing OH concentrations (16\%). Global emissions increased from 571 teragrams (Tg) per year in 2019 to 601 Tg per year in 2021 and back to 575 Tg per year in 2024. 2019-2024 emission decreases from oil/gas and rice were offset by increases from livestock and waste. East Africa and South America were most responsible for the 2019-2024 increase in emissions. The weaker methane rise over 2022-2024 was driven mostly by increasing OH concentrations rather than decreasing emissions.

Abstract

Global emission inventories often fail to capture the complexities of vehicular pollution in regions with unique fuel mixes, such as Brazil s extensive biofuel use, leading to significant uncertainties in atmospheric modeling. This study presents a century-long (1960-2100) bottom-up vehicular emission inventory for Brazil, leveraging locally derived emission factors. Our estimates reveal substantial discrepancies in magnitude, timing, and speciation of non-CO2 pollutants (CO, NMHC, PM2.5) compared to leading global inventories (EDGAR, CEDS, CAMS), highlighting critical inaccuracies in widely used data sets. More critically, future projections under Shared Socioeconomic Pathways (SSPs) uncover a novel positive feedback mechanism: rising temperatures significantly enhance vehicular evaporative nonmethane hydrocarbon (NMHC) emissions. This temperature-dependent increase and subsequent NMHC oxidation to CO2 suggest an overlooked pathway that could amplify climate warming and air pollution globally, particularly after a breakpoint around 2050 (p < 0.05). While historical emissions peaked in the 1990s-2000s, nonexhaust PM becomes increasingly important. Air quality simulations using our inventory in the MUSICA model show good regional PM2.5 agreement but highlight challenges in resolving local primary pollutant peaks. This comprehensive inventory provides crucial data for Brazil and uncovers globally relevant climate-chemistry interactions, urging a re-evaluation of regional specificities in global emission assessments.

Abstract

The coronavirus disease 2019 (COVID-19) pandemic disrupted normal human activities worldwide, and mobility reductions resulted in reduced levels of air pollutants and greenhouse gases emissions. Here, we examine the impact of these disruptions on a potent greenhouse gas, methane (CH4), over the U.S. In this study, we quantified CH4 emissions from the contiguous U.S. between 2019 and 2021 by analyzing inverse modeling results derived from atmospheric measurements made at 35 sites across the country. Our estimates indicate emission reductions of -2.5 (+/- 0.43) Tg year-1 CH4 in 2020 and -2.9 (+/- 1.63) Tg year-1 in 2021, relative to 2019. The respective percentage change was a -4.3 (-5.1 to -3.5) \% reduction in 2020 and -4.8 (-8.3 to -0.7) \% in 2021, relative to 2019. Combining with process-based inventory emission datasets, we found that this reduction was primarily due to decreased fossil fuel and agricultural emissions; however, record-breaking forest fires resulted in an increase of 0.4 (0.1 to 0.8) Tg year-1 in 2020-2019, equal to a 20 (3 to 46) \% increase in CH4 emissions from the western U.S.

Abstract

Methane is a powerful greenhouse gas with a shorter lifetime than carbon dioxide (CO2), making it an important target for near-term climate action. The Global Methane Pledge (GMP) aims to cut anthropogenic methane emissions by 30\% from 2020 levels by 2030. Using an Earth system model with interactive CH4 sources and sinks, we assess the Pledge s impact through 2050. Results show that current GMP commitments deliver only a 10\% cut by 2030-well below the target. Only the maximum technically feasible reduction (MTFR) pathway can achieve the 30\% goal. By 2050, current GMP commitments lowers methane concentrations by 3\% relative to 2025, while MTFR achieves 8\%. Both pathways slow warming slightly, avoiding about 0.1 degrees C of global temperature rise, with the Arctic seeing the greatest benefits (up to 2 degrees C less warming). Without wider participation, the GMP with current signatories will fall short of its targets and Paris Agreement goals.

Abstract

Contrary to the Antarctic, where ozone recovery has been observed for about a decade, the detection of positive ozone trends in the Arctic remains challenging due to higher natural variability of ozone in that region.Using a merging of long-term ozone data from Fourier transform infrared spectrometers, ozonesondes, and Dobson and Brewer spectrophotometers, we present regional long-term trends (2000-2024) for total, stratospheric and tropospheric ozone. First, ground-based measurements are cross-compared to two satellite data sets (MEGRIDOP and IASI-CDR). This enables the detection of drifts in ground-based data sets we further exclude from our study. We then use a representativeness study based on CAMS re-analysis data to define regions for which representative trends with reduced uncertainties are obtained by combining data sets from different instruments and stations. Annual and seasonal trends are calculated using a multiple linear regression technique involving a set of proxies that represent physical processes influencing the natural ozone variability.Annual trends indicate increasing total ozone over the Arctic, and are statistically significant over Canada and Reykjavik (+2.1 \% per decade) and North-West Europe (Harestua and Lerwick, +0.7 \% per decade). Ozone recovery is also observed over Canada in the mid-stratosphere (+2.0 \% per decade) and over the North Pole region (Canada and Ny-\& Aring;lesund) in the upper stratosphere (+2.1 \% per decade to +3.8 \% per decade). By analyzing the sensitivity of the ozone trends to the proxies, we observe a slow down of the expected ozone recovery, especially in the lower stratosphere, due to stratospheric cooling (-0.6 \% per decade) and to the increase of volume of polar stratospheric clouds (-0.8 \% per decade).

Abstract

Increasing atmospheric CO2 seasonal cycle amplitudes in boreal regions have been attributed to climate-driven changes in land ecosystems, but terrestrial biosphere models (TBMs) are unable to replicate observations, leading to large uncertainties in future predictions of carbon cycle changes. Accurately partitioning net ecosystem exchange into its component fluxes-gross primary production (GPP) and respiration-is essential for understanding impacts of changing climate on the Arctic and boreal carbon balance, yet these component fluxes cannot be measured directly. Carbonyl sulfide (OCS) has been used to infer GPP at site to global scales, because its one-way uptake by plants is an analog for photosynthesis. However, expanding site-level process understanding to regional scales remains challenging. Here, we use atmospheric OCS mole fraction observations representative of Alaskan boreal forests to evaluate simulations of OCS fluxes in a state-of-the-science TBM. We use TBM-estimated OCS fluxes and surface influence functions on the order of 100-1000 km to simulate OCS mole fractions at the NOAA Global Monitoring Laboratory s CRV tower site in central Alaska. By comparing with atmospheric observations, we can evaluate the TBM over much larger scales than is possible using eddy covariance data while still providing valuable information about underlying mechanisms. Comparisons reveal a missing ecosystem sink corresponding to a concentration difference of 22.3 +/- 9.1 ppt OCS for July-November relative to observed concentrations of 433 +/- 26 ppt at CRV. Solely improving the temperature sensitivity of apparent mesophyll conductance reduces the July-November mismatch between modeled and observed OCS concentration data by similar to 5.3 +/- 2.7 ppt. Consideration of alternate land cover maps provides an additional similar to 5.3 +/- 3.0 ppt towards the mismatch. These results demonstrate a strong decoupling of OCS and GPP, especially after the end of the growing season. Our analyzes demonstrate the limitations of using OCS as a proxy for GPP and highlight potential missing processes that need to be incorporated into future OCS modeling efforts to maximize its potential as a photosynthetic tracer.

Abstract

The 2023/24 El Ni \& ntilde;o strongly reduced land carbon uptake, but the persistence of this anomaly after surface cooling remains uncertain. Here we quantify the July 2024-June 2025 global CO2 budget using low-latency fossil emission estimates, three DGVMs, machine learning ocean flux emulators and OCO-2-constrained atmospheric inversions. The atmospheric CO2 growth rate was 2.62 +/- 0.08 ppm yr-1, 6.5\% above the 2013-2022 July-to-June mean. DGVMs estimate that the net land sink was 1.32 +/- 0.19 GtC yr-1 weaker than the 2015-2022 July-to-June mean, whereas combining bottom-up and top-down constraints gives a smaller deficit of 0.49 GtC yr-1. The annual anomaly is dominated by late-2024 land carbon losses. Early-2025 recovery, however, is method-dependent: DGVMs retain a weak annual land-sink deficit, while all inversions indicate fluxes close to the reference mean and a stronger-than-normal northern sink in late spring 2025. Ocean uptake shows no global weakening. A statistical decomposition links global land flux variability mainly to temperature, with terrestrial water storage contributing more strongly at regional scales. These results identify Northern Hemisphere land-sink recovery as a central uncertainty in low-latency carbon-budget assessments.

Abstract

Concurrent measurements of methane (CH4) and ethane (C2H6) can be used to identify and separate methane sources, as ethane is present in thermogenic sources (e.g., oil and natural gas) but not in biogenic sources (e.g., agriculture). In this study, we evaluated the performance of multiple Aeris MIRA Ultra instruments (Versions 1 and 2) through controlled laboratory tests and tower-based deployments under field conditions. The systems were modified with an external pump, flow control, a Nafion dryer, and a custom-built auxiliary box to automate the system and transmit near real-time data. We determined the best calibration approach for our application, given practical limitations, to be a full calibration cycle (with ambient and high calibration cylinders) about once per day and an ambient calibration cylinder sampled hourly. Measurement uncertainty was assessed, including the uncertainty due to instrument noise as a function of calibration frequency, uncertainty in the water vapor correction, and cylinder assignment uncertainty. Instrument noise was the dominant source of uncertainty for C2H6, while the water vapor correction dominated the CH4 uncertainty. For Version 2 systems with hourly calibrations and a Nafion dryer with counterflow, the mean total uncertainty, including both systematic errors and noise, of hourly averages was 0.8-3.0 ppb CH4 and 0.35-0.37 ppb C2H6. Laboratory intercomparisons showed network compatibility within 1.2 ppb CH4 and 0.23 ppb C2H6, and a collocated deployment with a NOAA Picarro system agreed within 1.8 ppb CH4. Instrument noise varied substantially amongst the instruments, with errors reaching up to 11 ppb CH4 and 2 ppb C2H6 for hourly means, with similar variability indicated in a 50 h cylinder test. With appropriate engineering and calibration, the Aeris MIRA Ultra has the potential to distinguish regional methane emission sources in many field settings.

Abstract

Analysis of recent in situ data reveals a persistent mode of organic-rich aerosol particles in the stratosphere below 19 kilometers at nitrous oxide (N2O) > 270 parts per billion by volume, with a number geometric mean diameter of similar to 0.03 to 0.11 mu m (0.08 to 0.2 mu m in surface and 0.11 to 0.3 mu m in volume). This mode, composed mostly of organic-rich particles transported from the troposphere, is poorly sensed by satellites and most balloon-borne optical measurements but dominates the surface area for heterogeneous reactions and the sink for condensable vapors. These small particles grow in size and decrease in concentration as they mix with older stratospheric air. A global chemistry-climate model fails to replicate the characteristics of these particles, suggesting that model improvements are necessary for accurate assessment of proposed geoengineering efforts.

Abstract

This study evaluates the performance of eleven Planetary Boundary Layer (PBL) schemes within the Weather Research and Forecasting (WRF) model over the Central Amazon Basin, focusing on contrasting wet and dry season conditions observed during the GoAmazon2014/5 campaign. High-resolution (1 km) simulations were conducted for representative periods in each season and validated against in situ observations. Model performance was assessed using multiple statistical metrics with the explicit separation of daytime convective and nighttime stable PBL regimes. Results reveal substantial variability among PBL schemes, strongly modulated by the season and diurnal cycle. Overall performance was higher during the wet period, whereas dry period simulations exhibited larger uncertainties, particularly under nocturnal conditions. The Shin-Hong (SH) PBL scheme had the best skill on average to reproduce the observed PBL height (PBLH) during the wet period, while the University of Washington (UW) PBL scheme was the best during the dry period. The Mellor-Yamada-Janjic (MYJ) PBL scheme had the best skill for daytime PBLH in both periods. Spatial analysis demonstrated how PBL schemes impact the PBLH distribution over the Central Amazon Basin, revealing a river-influenced pattern. These findings highlight the strong sensitivity of the Amazon PBL depth to PBL schemes and underscore the importance of appropriate PBL parameterizations and the vertical resolution for tropical applications.

Abstract

The Eppley Precision Infrared Radiometer (PIR) is widely used for broadband (3.5-50 mu m), thermal infrared wavelength measurements of the downwelling and upwelling radiation from the atmosphere and surface, respectively. The field of view of the instrument is 2 pi steradians with a receiver that has an approximate cosine response. In this paper we examine four equations suggested by the literature that have been used to transfer irradiance calibrations from our standard PIRs that are calibrated at the World Radiation Center to field units used for network operations. We first discuss various equations used to convert the resistance measurements of the thermistors to temperatures of the body and dome that are used in the derivation of incoming irradiance. We then use the four related, but distinct, equations for the transfer of the calibration from standard PIRs to field instruments. A clear choice for the preferred equation to use for calibration and transfer of calibration to field PIRs emerges from this study.

Abstract

Large uncertainties and variability in individual ground-based instrument records limit the detection of statistically significant ozone trends, particularly in the lower stratosphere. Available merging studies are typically performed by latitude bands on satellite-based data records. This study derives correlation-based regional composites of ground-based timeseries towards reducing trend uncertainties. We address fundamental heterogeneities resulting from grouping individually homogenized ground-based datasets to enable robust merging. Uneven temporal and vertical resolutions of five ozone measurement techniques (Ozonesondes, FTIR, Dobson Umkehr, Lidar and Microwave radiometers) are handled by integrating monthly mean ozone profiles in two sets of four independent partial columns. Spatial heterogeneity is resolved by defining coherent regions using the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. Regional timeseries are merged by the BAyeSian Integrated and Consolidated (BASIC) algorithm, adapted to consider propagated measurement uncertainties and the agreement between individual timeseries by Principal Component Analysis (PCA). Trends for the 2000-2024 period are then estimated by Multiple Linear Regression using the LOTUS model. We compare BASIC with a conventional weighted mean. While the weighted mean fails to capture variability during periods of low instrument consensus, BASIC produces more representative timeseries by robustly handling outliers. Accordingly, for the selected regions, BASIC reduces average uncertainties of the trend estimates by 9.4 \% relative to the weighted-mean approach. Our results support positive trends in the upper stratosphere, predominantly negative trends in the middle stratosphere and non-significant trends in the lower stratosphere. This study establishes a consolidated ground-based reference to be used for comparison with global satellite-based ozone trends.

Abstract

Monitoring annual atmospheric CO2 growth rates is a key constraint on assessing the long-term effectiveness of emission reduction strategies. We analyzed annual growth rates of column-averaged dry-air mole fractions of CO2 (XCO2) using long-term data from 12 sites within the Total Carbon Column Observing Network (TCCON), spanning four regions: the Arctic, two Northern Hemisphere midlatitude bands (40-50 and 30-40 degrees N), and the Southern Hemisphere. While in situ ground-based measurements provide detailed records of near-surface CO2 concentrations, XCO2 reflects the column-averaged abundance across the entire atmosphere, offering a complementary perspective.We compared TCCON-derived growth rates with ground-based in situ observations from the Mauna Loa Observatory (MLO). Three calculation methods - Monthly Mean (MM), Fourier Fit residuals (FF), and Dynamic Linear Model (DLM) - were evaluated, with particular attention to the Eureka site, where polar night introduces substantial data gaps. In addition, the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis product was used to assess consistency with TCCON-based growth rates and to evaluate each method s robustness to missing data. Among the methods tested, the DLM approach proved most resilient to data gaps.Regionally averaged CO2 growth rates, calculated from 2010 or from the earliest available data through 2024, ranged from approximately 2.33 to 2.40 ppmyr-1. The most prominent signal was associated with the 2015-2016 El Ni \& ntilde;o - Southern Oscillation (ENSO) event, during which growth rates increased by up to 1.7 ppmyr-1. The impact of COVID-19-related emission reductions in 2020 was also examined: a decline of 0.4 ppmyr-1 was observed in the 30-40 degrees N region, whereas other regions showed no significant decline. Correlation analysis between growth rates and ENSO strength revealed significant relationships in the Southern Hemisphere and at Mauna Loa, but not in northern mid- or high-latitude regions.

Abstract

Methane (CH4) oxidation by microbes is the largest biological sink of global methane, yet its magnitude and long-term variability remain uncertain. Here, we combined process-based (PB), machine-learning (ML), and atmospheric inversion approaches to evaluate the global methane soil sinks and its implication for the atmospheric CH4 budget in this study. Both PB and ML approaches estimated annual global methane soil sink to be 40-45 Tg CH4 yr-1, 30\%-50\% larger than conventional estimates. Although the two approaches agreed on total magnitude, they differ in their representation of variability. PB models simulate stronger spatial heterogeneity, seasonality, and long-term increases in CH4 uptake because environmental sensitivities are explicitly represented through mechanistic equations. In contrast, ML models reproduce site-level observations more closely but exhibit muted spatial and temporal variability due to their limited environmental sensitivities from sparse and discrete observations used for model training. Atmospheric inversions further indicate that incorporating the larger soil sink improves agreement with observed atmospheric CH4 and its stable carbon isotope changes and requires larger microbial CH4 emissions. Together, these results suggest that the global methane soil sink may have been underestimated and demonstrate the value of integrating PB and ML modeling, and atmospheric constraints to improve understanding of global methane cycling.

Abstract

Accurately separating the contributions of different sources to recent atmospheric methane (CH4) growth is crucial for better quantifying the present and future responses of CH4 emissions to changing climate and anthropogenic activity. Here, we run atmospheric inversions to assess global and regional CH4 emissions from microbial, fossil, and pyrogenic sources from 2000 to 2022, using measurements of atmospheric CH4 and its stable carbon isotope ratio (13C:12C, expressed relative to a standard as delta 13C-CH4). We confirm that global total CH4 emissions has increased by 15\% from 2000 to 2022, with dominated contribution from microbial emissions. Both microbial and fossil emissions increased during 2007-2013 relative to 2000-2006, with the largest contributions from temperate Asia. From 2014-2017, microbial emissions from tropical regions, particularly South America and Africa, were the dominant driver of the overall increase, while fossil emissions remained stable in Europe and North America. Between 2020 and 2022, microbial emissions surged in the African and Asian tropics, whereas fossil emissions declined across most industrial regions. Notably, inversions constrained only by CH4 observations did not capture the decline in fossil emissions during 2020-2022, a decline potentially related to the COVID-19 pandemic, policy-driven changes, and decreases in CH4 emissions intensity, highlighting the critical role of isotopic measurements in independently verifying changes in fossil emissions. Further, our inversion with isotopic constraints estimates a more prominent increase in wetland emissions that is 20-30\% more strongly correlated with variations in terrestrial water storage during 2003-2022, demonstrating the importance of climate-driven natural sources in explaining long-term CH4 growth.

Abstract

Understanding new particle formation (NPF) and the fate of nanoparticles is crucial because of their close links to air quality, cloud formation, and climate. These effects vary spatially and temporally owing to diverse aerosol sources and their relatively short atmospheric lifetime. Here, we present a comprehensive analysis of long-term trends in NPF-associated nucleation-mode particles and cloud condensation nuclei (CCN) concentrations across diverse observation environments using quality-controlled particle number size distribution (PNSD) and CCN data from 37 sites, primarily from Global Atmosphere Watch (GAW) stations. We identify declining decadal trends in both NPF occurrences and nucleated particle concentrations across most site types, with the strongest declines in urban areas. We observe simultaneous reductions in both CCN concentrations and nucleation-mode particles, suggesting that newly formed particles are a potential source of CCN. This, in turn, suggests that cloud microphysical properties and radiative effects can be indirectly influenced through aerosol-cloud interactions that modify cloud droplet formation. These findings indicate that decreasing anthropogenic emissions could influence the climate forcing potential of aerosol-cloud interactions, with important implications for future climate projections.

Abstract

Since 1991, continuous, consistently calibrated and openly archived ground-based measurements from the Network for the Detection of Atmospheric Composition Change (NDACC) have been collected to investigate processes responsible for decadal-scale changes, anomalies in atmospheric composition, and to validate satellite observations and model simulations. These measurements, from nearly 120 stations, support fundamental research in the area of stratospheric and tropospheric processes impacting ozone chemistry, greenhouse gases, atmospheric radiative forcing, air quality, and interactions with solar radiation and the entire Earth system. NDACC data are supplemented by observations from eleven global Cooperating Networks. The operational principles of Cooperating Networks are well aligned with NDACC objectives and protocols, focusing on data that (a) are high-quality, uniformly processed and traceable to reference standards; and (b) capture short-term (daily to interannual) anomalies and long-term trends. This paper summarizes the NDACC organizational structure. We also review the major accomplishments of NDACC since De Mazi \& egrave;re et al. (2018), collaborative research with Cooperating Networks, and interactions with the satellite and modeling communities. Ground-based atmospheric composition monitoring is at a crossroads. Challenges include sustainability of human and financial resources required for complex and intensive data collection, technical issues including aging instrumentation, requirements for FAIR (findable, accessible, interoperable, reusable) data, and lack of data over large parts of Asia, Africa and South America. NDACC is well-positioned to adopt a three-pronged strategy going forward: protecting and modernizing existing stations; promoting the growing use of NDACC data; expanding the number of measured species and network coverage in under-sampled or under-reporting regions.

Abstract

A multi-year analysis of aerosol optical depth (AOD, tau) and \& Aring;ngstr \& ouml;m exponent (alpha) was conducted using ground-based photometer data from 15 Arctic and 11 Antarctic sites. Extending the dataset of through December 2024, the study incorporates stellar and lunar photometric observations to fill data gaps during the polar night. Daily mean values of tau at 0.500 mu m and alpha (0.440-0.870 mu m) were used to derive monthly means and seasonal histograms.In the Arctic, persistent haze events in winter and early spring lead to peak tau values. A decreasing trend in Arctic tau suggests the impact of European emission regulations, while biomass-burning aerosols are becoming more significant. In Antarctica, tau increases from the plateau to the coast. Fine-mode aerosols dominate in summer-autumn, while coarse-mode particles are more prevalent in winter-spring. Shipborne photometer data align well with ground-based measurements, confirming the reliability of mobile observations.Trend analyses using the Mann-Kendall test and Theil-Sen regression indicate a significant negative trend in tau at Andenes (-2.43 \% per year), likely driven by reduced anthropogenic emissions. Antarctic stations such as Syowa and South Pole show positive trends (+3.84 \% and +3.54 \% per year), though these are subject to uncertainties from data limitations and instrument changes.This work contributes to the Polar-AOD network (https://polaraod.net/, last access: 15 May 2025), enhancing the understanding of aerosol variability and long-term trends in polar regions while promoting open data access for the scientific community.

Abstract

Effective co-control of air pollution and carbon emissions yields substantial environmental and climate benefits, yet direct observational evidence of policy impacts remains scarce. Here we use tree-ring radiocarbon to reconstruct annual fossil fuel carbon dioxide concentrations from 2000 to 2021 in Beijing and Xi an, China. These data, combined with records of fine particles, black carbon, and carbon monoxide, reveal their initial parallel rises, followed by substantial declines after 2013 clean air action plans. From 2013 to 2021, ratios of fine particles, black carbon, and carbon monoxide enhancement to fossil fuel carbon dioxide fell by 58 +/- 25\%, 54 +/- 19\%, and 44 +/- 19\% in Beijing, and 36 +/- 21\%, 56 +/- 10\%, and 65 +/- 24\% in Xi an, respectively. These trends provide observational evidence of co-benefits achieved through integrated air quality and carbon mitigation policies, highlighting the value of tree-ring radiocarbon for evaluating emission dynamics and policy effectiveness.

Abstract

Earth s arid and semi-arid regions have been hypothesized to contribute significantly to interannual variability of the global terrestrial carbon sink. Arid and semi-arid regions such as the Western U.S. also show high vulnerability to climate extremes in the form of droughts, heatwaves, and large forest fires, compelling a need to quantify their climate-carbon responses. We quantify the net ecosystem exchange of (NEE) using a high-resolution regional inverse model with constraints from both in situ and space-based observations during 2015-2016. Posterior fluxes are evaluated against withheld aircraft observations across the North American observation network. Observationally constrained fluxes suggest moisture-driven seasonal compensation in NEE across the 2 years, evidenced by a decrease in NEE of 244-262 [Tg C] during the early carbon uptake period and an increase in NEE of 281-389 [Tg C] later during the carbon uptake period, relative to 2016. Atmospheric constraints on NEE, combined with remote sensing and machine learning-based upscaled gross primary productivity (GPP) products, allow for benchmarking of net and gross fluxes as estimated by a suite of terrestrial biosphere models. These benchmarks allow us to link changes in NEE and GPP constrained by atmospheric and space-based observations to changes in stomatal conductance and water use efficiency. High-precision in situ observations, such as those from the Global Greenhouse Gas Reference Network, are key constraints for bias-free carbon flux estimates.

Abstract

The Montreal Protocol on Substances that Deplete the Ozone Layer has greatly restricted the global production and consumption of long-lived ozone-depleting substances (ODS). However, ODS used or consumed as feedstocks in the manufacture of other chemicals are excluded from restrictions. This exclusion was based on the assumption that emission rates of feedstocks were only 0.5\% of the amount produced and that feedstock production would decline in the future, with remaining emissions too small to significantly affect the stratospheric ozone or its recovery. In sharp contrast, feedstock emissions are now assessed as being substantially higher (typically 3.6\% of production), and feedstock production and use has been rising rather than falling. Here, scenarios in which feedstock-related ODS emissions continue at this current fraction of production, rather than the 0.5\% reference case, are projected until 2100. Without additional measures, these elevated emissions could delay the recovery of the mid-latitude stratospheric ozone layer by 7 (6 - 11) years. Furthermore, limiting ODS feedstock emissions would also reduce their effect on direct radiative forcing and on climate change.

Abstract

High-resolution retrospective simulations of air quality can generate O3 and PM2.5 concentrations to estimate their health effects and establish a baseline to assess the impacts of future climate and emission scenarios. To this end, the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) is applied to a triple-nested domain over Brazil, with a high spatial resolution of 3-km over the metropolitan areas of Sao Paulo (MASP) and Rio de Janeiro (MARJ) for the period of 2012-2016. This work is presented in two-part papers. Part I describes an initial application and evaluation of WRF-Chem for August 2012 to study the impacts of improved inputs and wind speed correction parameterization options on the model performance. These simulations aim to improve the model s accuracy in reproducing the observed meteorological variables and air pollutant levels. The model results with updated land use and cover and urban fraction show a lower positive bias in temperature at 2-m. Updated elevation based on high-resolution (30-m) data reduces the positive bias on wind speed at 10-m for MARJ. The modified wind speed correction reduces the systematic bias of wind speed at 10-m for all domains. WRF-Chem using the combined emissions based on global and local inventories performs well with lower bias and better temporal and spatial representations of historical concentrations of major air pollutants than those using global emissions only. These sensitivity simulations identify the best possible model inputs and wind speed correction parameterization option for simulations for the period of 2012-2016, which will be presented in Part II paper.

Abstract

We present updated evaluation of stratospheric ozone profile trends in the 60 degrees S-60 degrees 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 the statistically significant positive ozone trends in the period 2000-2024 in the upper stratosphere of similar to 1-3 \% per decade, 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, -1 to -2 \% per decade, in the lower stratosphere, but they are not statistically significant. The morphology and magnitude of ozone trends are similar to previous analyses (2000-2020 trends).Ozone trends in 2000-2024 predicted by chemistry-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 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 profile trends in 2003-2024 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.

Abstract

The atmospheric response to the solar eclipse of 8 April 2024 in North America is investigated with a specific focus on the marine atmospheric boundary layer (MABL). We leverage measurements collected during the Third Wind Forecast Improvement Project (WFIP3), including Doppler lidars, sonic anemometers, and thermodynamic profiler data to investigate the atmospheric response across sites that experienced partial eclipse conditions with nearly 90\% obscuration. Using these measurements, we examine eclipse-induced changes in key meteorological parameters, such as temperature, wind speed, and turbulent fluxes. Most previous eclipse studies have been conducted over land, whereas this study provides new observations for both coastal and marine environments, offering additional insight into eclipse-driven variability in the MABL. The findings confirm a notable decrease in downwelling shortwave radiation during the eclipse, which results in rapid cooling of surface air. The temperature reduction ranges from 1.2 degrees C\documentclass[12pt]\minimal\ \usepackage\amsmath\ \usepackage\wasysym\ \usepackage\amsfonts\ \usepackage\amssymb\ \usepackage\amsbsy\ \usepackage\mathrsfs\ \usepackage\upgreek\ \setlength\\oddsidemargin\\-69pt\ \begin\document\\$\$1.2<\^>\circ ext \C\\$\$\end\document\ to 1.4 degrees C\documentclass[12pt]\minimal\ \usepackage\amsmath\ \usepackage\wasysym\ \usepackage\amsfonts\ \usepackage\amssymb\ \usepackage\amsbsy\ \usepackage\mathrsfs\ \usepackage\upgreek\ \setlength\\oddsidemargin\\-69pt\ \begin\document\\$\$1.4<\^>\circ ext \C\\$\$\end\document\ in coastal regions and from 0.3 degrees C\documentclass[12pt]\minimal\ \usepackage\amsmath\ \usepackage\wasysym\ \usepackage\amsfonts\ \usepackage\amssymb\ \usepackage\amsbsy\ \usepackage\mathrsfs\ \usepackage\upgreek\ \setlength\\oddsidemargin\\-69pt\ \begin\document\\$\$0.3<\^>\circ ext \C\\$\$\end\document\ to 0.5 degrees C\documentclass[12pt]\minimal\ \usepackage\amsmath\ \usepackage\wasysym\ \usepackage\amsfonts\ \usepackage\amssymb\ \usepackage\amsbsy\ \usepackage\mathrsfs\ \usepackage\upgreek\ \setlength\\oddsidemargin\\-69pt\ \begin\document\\$\$0.5<\^>\circ ext \C\\$\$\end\document\ over the ocean. This analysis suggests that the MABL s higher thermal inertia compared to coastal regions moderates the temperature decrease during the eclipse. Wind speed exhibits a more complex behavior, as it is influenced by both the MABL and preexisting synoptic conditions. Although a reduction in wind speed is observable up to approximately 140 m above ground level (AGL) at more inland sites, at other locations closer to the coast, this reduction is constrained to the lowest 100 m AGL. Turbulence parameters retrieved from sonic anemometers, such as turbulence kinetic energy, turbulent heat flux, and friction velocity, decrease during the eclipse at coastal sites, accompanied by a brief transition of atmospheric stability from unstable to neutral or weakly stable conditions. For the open-ocean sites, the variability in turbulence statistics and atmospheric stability is minimal during the occurrence of the eclipse.

Abstract

As the hydrogen (H2) economy expands, there is growing interest in understanding the atmospheric lifetime of H2, which affects its impact on atmospheric chemistry and climate. While some global H2 is destroyed via reaction with the hydroxyl radical (OH), most is lost to microbial activity in soils. However, the sources and sinks of H2 are still uncertain on global and local scales. This study focuses on how monthly resolved observations of HFC-152a can help to constrain the seasonal OH cycle and the H2 budget, particularly the seasonal range and phase of H2 oxidation and soil loss. Seasonal observations of HFC-152a are used to constrain OH through a Bayesian inversion in a three-box model comprising the Northern, Tropics, and Southern regions over 2010-2022. In the North, a seasonal range of the soil sink of 18-21 +/- 8 Tg yr-1 is found, peaking in July-August, while the OH loss seasonal range is 8 +/- 1 Tg yr-1, peaking in July. The South has much less land and so displays a smaller soil sink seasonal range of 2-3 +/- 2.5 Tg yr-1, peaking in January-March. The OH loss in the South has a seasonal range of 7 +/- 1 Tg yr-1, peaking in January. The OH and soil sink loss in the Tropics is more consistent across all months, but with larger uncertainty. The results presented here will be a useful comparison for H2 cycles in fully integrated chemistry climate models.

Abstract

The isotopic composition of atmospheric methane (delta 13C-CH4) provides critical constraints for attributing methane emissions to specific sources. In this study, we present updated global maps of delta 13C-CH4 source signatures across five major methane-emitting sectors (fossil fuels and geological, agriculture and waste, biomass and biofuel burning, wetlands, and other natural sources) for the period 1998-2022. These maps integrate recent spatially explicit datasets and literature-derived observations, and include explicit quantification of both intrinsic (within-sector) and aggregation-related uncertainties. Building upon previous global compilations, our dataset extends the temporal coverage to 2022, harmonizes sectoral definitions with the Global Methane Budget framework, and provides a consistent and traceable quantification of uncertainties suitable for atmospheric inversions. We assess the influence of these updated source signatures on the modeled atmospheric delta 13C-CH4 using forward simulations within the Community Inversion Framework (CIF) coupled to the LMDz transport model. A comprehensive sensitivity analysis quantifies the impacts of key drivers of uncertainty, including emission flux datasets, OH sinks, kinetic isotope effects, and isotopic source signatures. We show that uncertainties in methane oxidation chemistry and source signatures, particularly from agriculture and waste, dominate the variability in the modeled delta 13C-CH4 signal, while the impact of flux aggregation choices is comparatively minor. The updated isotopic dataset is provided on a global 1 degrees \& times;1 degrees grid, supporting future atmospheric inversions and improved methane budget assessments at global and regional scales. Practical guidelines for configuring isotopic inversions, including recommended uncertainty specifications and key parameters to optimize, are also provided, offering a framework for next-generation delta 13C-CH4 inversion studies. The final version of the gridded delta 13C-CH4 source signature dataset is available under CC BY 4.0 (, 10.57780/ESA-6D202E9).

Abstract

The Southern Ocean is a key anthropogenic carbon dioxide (CO2) sink, yet the processes governing the rate of uptake remain only partly understood. We use observations of radiocarbon (Delta 14C) in atmospheric CO2 from Southern Ocean shipboard transects to develop latitudinal gradients of Delta 14C in the surface atmosphere. We present eight years of austral summer observations (2016-2023) from ships of opportunity traveling between New Zealand and Antarctica, along with time series measurements from Baring Head New Zealand, Macquarie Island Australia and Arrival Heights Antarctica. We observe lower Delta 14C in the 50 degrees S to 70 degrees S latitude band, consistent with upwelling of 14C-depleted deep waters in this region. We then combine ocean model simulations of CO2 and 14C with atmospheric dispersion model simulations to predict surface atmosphere Delta 14C and compare with the observations. Our model simulations capture the large scale observed spatial patterns with considerable accuracy. However, the model simulation somewhat underestimates the magnitude of the observed atmospheric Delta 14C gradient, particularly between 50 degrees S and 60 degrees S. When we artificially increase the strength of the strongest winds over the Southern Ocean in the ocean model, we find an improved match with the Delta 14C observations, demonstrating that Delta 14C observations with dense spatial resolution across the Southern Ocean can be useful for testing ocean model and CO2 exchange parameters.

Abstract

Atmospheric inversions provide surface CO2 flux estimates based on in situ observed atmospheric CO2 mole fractions or satellite-based column average CO2 (XCO2). Here, we provide a detailed assessment of 14 atmospheric CO2 inversions included in the Global Carbon Budget (GCB2024). We develop tools to further assess and use these inversions in global and regional carbon cycle studies including the GCB and the REgional Carbon Cycle Assessment and Processes (RECCAP2) initiative. We show that the global atmospheric CO2 growth rate and its interannual variability are reproduced well by all inversions. In contrast to bottom-up models, inversions provide carbon flux estimates directly constrained by observations. Our ensemble mean estimates of the global sinks for the period 2015-2023 are -1.410.55 PgC yr-1 for the net land sink (including land-use change emissions) and -2.970.55 PgC yr-1 for the global net ocean sink (uncertainties reported as across inversions; estimates include fossil fuel and river flux adjustments). On regional scales, we find significant spread in flux estimates between inversions across regions, and we present criteria and metrics to derive flux-observation relation constraints or subselect ensembles of inversions based on independent observations. Furthermore, we use the atmospheric inversions to assess the atmospheric growth rate of CO2. We show that the factor used to convert annual observation-based growth rates to net fluxes is variable over time as a result of atmospheric mixing. Finally, we propose guidelines on how to use the inverse results in global and regional carbon budget studies by the wider carbon cycle community.

Abstract

The Montreal Protocol on Substances that Deplete the Ozone Layer requires that the production of long-lived ozone-depleting substances (ODSs) that are intended for use in emissive applications be phased out. The Protocol does not, however, limit the release to the atmosphere of ODSs already existing in such applications and equipment. Accounting for emissions from these banked ODSs (e.g., in insulating foams) is important for monitoring the success of and compliance with the Protocol, for understanding where further mitigation of ODS emissions might be effective, and for estimating future ozone depletion. Here, we present a new bottom-up model that incorporates existing use and life-cycle information to calculate emissions and banks as well as uncertainties in the quantities. To demonstrate the model, we apply it to 1,1-dichloro-1-fluoroethane (HCFC-141b), a chemical used primarily in foam insulation and whose production is currently being phased out. We calculate global emission trends that are qualitatively similar to those derived from atmospheric measurements from 1990 to 2017. After 2017, our calculated emissions no longer track the observationally based trends through the end of the comparison in 2021. This discrepancy suggests either a growing additional source of emissions that is inconsistent with reported production or a model deficiency that was not apparent before 2017. Our calculations also show that the easily recoverable portion of the bank will be smaller in the future than the total bank estimated in other recent work, with implications for the feasibility of recovering banks before the release of HCFC-141b to the atmosphere.

Abstract

Annual increases in atmospheric methane have reached record highs over the past five years, yet the underlying processes and regional sources remain uncertain. Here we quantify the average 2019-2021 global methane budget using Bayesian 4D-Var inversions that assimilate satellite methane retrievals and in-situ delta 13C-CH4 and delta D-CH4 measurements. The methane-isotopic inversion yields total emissions of 623 [585-643] Tg/y, slightly higher than the methane-only inversion. Incorporating isotopic constraints leads to a redistribution of emissions in tropical and subtropical regions. Compared with the methane-only inversion, the methane-isotopic inversion indicates that emission estimates increase by 26 [-3-27] Tg/y in East Asia (primarily China), 7 [-1-8] Tg/y in South Asia (primarily India), and 5 [-3-10] Tg/y in central Africa, while decreasing by 5 [-6-7] Tg/y in Amazon Basin and 12 [-14-20] Tg/y elsewhere. This points to a stronger anthropogenic contribution to the post-2019 methane budget, including higher fossil emissions in China and slightly less wetland emissions in the Amazon Basin. The methane-isotopic inversion also alters inferred emission seasonality, showing less seasonality in China compared with the methane-only inversion, weaker coal-mine phase-out signals, and a delayed summer peak in Southeast Asia, pointing to sources missing from current inventories.

Abstract

This study presents a comprehensive phenomenological analysis of cloud condensation nuclei (CCN) and aerosol properties - including activation properties, microphysical characteristics, chemical composition, and optical properties - across nine surface sites in different environments. Aerosol properties vary widely, reflecting the diverse environments, and controlling the CCN activation characteristics. Despite their critical role in aerosol-cloud interactions, CCN observations remain sparse and unevenly distributed, limiting global assessments of activation behavior. To address this gap, this study presents CCN predictive methods based on chemical composition combined with particle number size distribution (PNSD) data, and aerosol optical properties (AOPs). The chemical composition driven predictions are tested using three hygroscopicity schemes. All schemes overpredict the