Atmospheric Measurements Research Articles

Winter Intrusions of Atlantic Water in Kongsfjorden: Oceanic Preconditioning and Atmospheric Triggering

AbstractKongsfjorden, an Arctic fjord in Svalbard, is largely influenced by the West Spitsbergen Current (WSC), transporting warm and salty Atlantic Water (AW) into the Arctic region. Despite the geostrophic control preventing AW from entering the fjord in winter, AW intrusions occasionally occur during energetic local wind events in this season. However, recent intrusions remain poorly characterized, and the underlying mechanism(s) and large‐scale precursors are only partly understood. This study uses in‐situ oceanographic and atmospheric measurements, alongside reanalysis data covering 2011–2020, to describe recent wintertime AW intrusions in Kongsfjorden. By discerning common traits in the observed events, the main triggering factors and controls of the phenomenon are described. Our results indicate that AW intrusions are typically triggered by wind reversals over the shelf, consisting of the sudden transition from a strong southerly to a northerly circulation linked to the setup and damping of a high‐pressure anomaly over the Barents Sea. Ocean density is a critical preconditioning factor influencing the nature of the intrusion: when fjord waters exhibit a lower density compared to WSC waters, wind reversals induce AW intrusions by upwelling; in contrast, when fjord waters present higher or similar densities compared to WSC waters, reversals force AW inflows near the surface or at intermediate depths, respectively. Another mechanism was observed only in winter 2014: southerly winds prevailed for 2 months, transporting surface AW from the WSC into the fjord, promoting its intrusion near the surface, on top of denser local waters.

Mechanical and Thermal Forcing for Upslope Flows and Cumulus Convection over the Sierras de Córdoba

Abstract The upslope flow processes affecting the vertical extent of orographic cumulus convection are examined using observations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) Field Campaign. Specifically, clear-air returns from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) C-band radar (CSAPR2) are used to characterize the structure and variability of the ridge-normal (i.e., up/downslope) flow components, which transport mass to the crest of Argentina’s Sierras de Córdoba and contribute to convective initiation. Data are compiled for the entire CACTI period (Oct-Apr), including days with clear skies, shallow cumuli, cumulus congestus, and deep convection. To examine shared variability amongst >70,000 radar scans we use (a) a principal component analysis (PCA) to isolate modes of variability in the upslope flow, and (b) composite analysis based on convective outcomes, determined from GOES16 satellite observations. These data are contextualized with observed surface sensible heat fluxes, thermodynamic profiles, and synoptic-scale analysis. Results indicate distinct thermally and mechanically forced upslope flow modes, modulated by diurnal heating and synoptic-scale variations, respectively. In some instances, there is a superposition of thermal and mechanical forcing, yielding either deeper or shallower upslope flow. The composite analyses based on satellite data show that successively deeper convective outcomes are associated with successively deeper upslope flow layers that more readily transport mass to the ridge crest in conjunction with lower lifting condensation levels, facilitating convective initiation. These results help to isolate the forcing mechanisms for orographic convection, and thus provide a foundation for parameterizing orographic convective processes in coarse resolution models.

Lagrangian particle tracking in the atmospheric surface layer

Abstract Field measurements in the atmospheric surface layer (ASL) are key to understanding turbulent exchanges in the atmosphere, such as fluxes of mass, water vapor, and momentum. However, current field measurement techniques are limited to single-point time series or large-scale flow field scans. Extending image-based laboratory measurement techniques to field-relevant scales is a promising route to more detailed atmospheric flow measurements, but this requires significant increases in the attainable measurement volume while keeping the spatiotemporal resolution high. Here, we present an adaptable particle tracking system using helium-filled soap bubbles, mirrorless cameras, and high-power LEDs enabling volumetric ASL field measurements. We conduct analyses pertinent to image-based field measurement systems and develop general guidelines for their design. We validate the particle tracking system in a field experiment. Single-point Eulerian velocity statistics are presented and compared to data from concurrently operated sonic anemometers. Lagrangian displacement statistics are also presented with a comparison to Taylor’s theory of dispersion. The system improves the state-of-the-art in field measurements in the lower atmosphere and enables unprecedented insights into flow in the ASL.

Refining Planetary Boundary Layer Height Retrievals From Micropulse‐Lidar at Multiple ARM Sites Around the World

AbstractKnowledge of the planetary boundary layer height (PBLH) is crucial for various applications in atmospheric and environmental sciences. Lidar measurements are frequently used to monitor the evolution of the PBLH, providing more frequent observations than traditional radiosonde‐based methods. However, lidar‐derived PBLH estimates have substantial uncertainties, contingent upon the retrieval algorithm used. In addressing this, we applied the Different Thermo‐Dynamic Stabilities (DTDS) algorithm to establish a PBLH data set at five separate Department of Energy's Atmospheric Radiation Measurement sites across the globe. Both the PBLH methodology and the products are subject to rigorous assessments in terms of their uncertainties and constraints, juxtaposing them with other products. The DTDS‐derived product consistently aligns with radiosonde PBLH estimates, with correlation coefficients exceeding 0.77 across all sites. This study delves into a detailed examination of the strengths and limitations of PBLH data sets with respect to both radiosonde‐derived and other lidar‐based estimates of the PBLH by exploring their respective errors and uncertainties. It is found that varying techniques and definitions can lead to diverse PBLH retrievals due to the inherent intricacy and variability of the boundary layer. Our DTDS‐derived PBLH data set outperforms existing products derived from ceilometer data, offering a more precise representation of the PBLH. This extensive data set paves the way for advanced studies and an improved understanding of boundary‐layer dynamics, with valuable applications in weather forecasting, climate modeling, and environmental studies.

Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?

Abstract. NOx is an important primary air pollutant of major environmental concern which is predominantly produced by anthropogenic combustion activities. NOx needs to be accounted for in national emission inventories, according to international treaties. Constructing accurate inventories requires substantial time and effort, resulting in reporting delays of 1 to 5 years. In addition to this, difficulties can arise from temporal and country-specific legislative and protocol differences. To address these issues, satellite-based atmospheric composition measurements offer a unique opportunity for the independent and large-scale estimation of emissions in a consistent, transparent, and comprehensible manner. Here we test the multi-source plume method (MSPM) to assess the NOx emissions over Germany in the COVID-19 period from 2019–2021. For the years where reporting is available, the differences between satellite estimates and inventory totals were within 75–100 kt (NO2) NOx (<10 % of inventory values). The large reduction in the NOx emissions (∼15 %) concurrent with the COVID-19 lockdowns was observed in both the inventory and satellite-derived emissions. The recent projections for the inventory emissions of 2021 pointed to a recovery of the 2021 emissions towards pre-COVID-19 levels. In the satellite-derived emissions, however, such an increase was not observed. While emissions from the larger power plants did rebound to pre-COVID-19 levels, other sectors such as road transport did not, and the change in emissions is likely due to a reduction in the number of heavier transport trucks compared to the pre-COVID-19 numbers. This again illustrates the value of having a consistent satellite-based methodology for faster emission estimates to guide and check the conventional emission inventory reporting. The method described in this work also meets the demand for independent verification of the official emission inventories, which will enable inventory compilers to detect potentially problematic reporting issues, bolstering transparency and comparability, which are two key values for emission reporting.

Revealing the significant acceleration of hydrofluorocarbon (HFC) emissions in eastern Asia through long-term atmospheric observations

Abstract. Hydrofluorocarbons (HFCs) are powerful anthropogenic greenhouse gases (GHGs) with high global-warming potentials (GWPs). They have been widely used as refrigerants, insulation foam-blowing agents, aerosol propellants, and fire suppression agents. Since the mid-1990s, emissions of HFCs have been increasing rapidly as they are used in many applications to replace ozone-depleting chlorofluorocarbons (CFCs) and hydrochlorofluorocarbons (HCFCs) whose consumption and production have been phased out under the Montreal Protocol (MP). Due to the high GWP of HFCs, the Kigali Amendment to the MP requires the phasedown of production and consumption of HFCs to gradually achieve an 80 %–85 % reduction by 2047, starting in 2019 for non-Article 5 (developed) countries with a 10 % reduction against each defined baseline and later schedules for Article 5 (developing) countries. In this study, we have examined long-term high-precision measurements of atmospheric abundances of five major HFCs (HFC-134a, HFC-143a, HFC-32, HFC-125, and HFC-152a) at Gosan station, Jeju Island, South Korea, from 2008 to 2020. Background abundances of HFCs gradually increased, and the inflow of polluted air masses with elevated abundances from surrounding source regions were detected over the entire period. From these pollution events, we inferred regional and country-specific HFC emission estimates using two independent Lagrangian particle dispersion models and Bayesian inversion frameworks (FLEXPART-FLEXINVERT+ and NAME-InTEM). The spatial distribution of the derived “top-down” (measurement based) emissions for all HFCs shows large fluxes from megacities and industrial areas in the region. Our most important finding is that HFC emissions in eastern China and Japan have sharply increased from 2016 to 2018. The contribution of East Asian HFC emissions to the global total increased from 9 % (2008–2014) to 13 % (2016–2020). In particular, HFC emissions in Japan (Annex I country) rose rapidly from 2016 onward, with accumulated total inferred HFC emissions being ∼ 114 Gg yr−1, which is ∼ 76 Gg yr−1 higher for 2016–2020 than the “bottom-up” (i.e., based on activity data and emission factors) emissions of ∼ 38 Gg yr−1 reported to the United Nations Framework Convention on Climate Change (UNFCCC). This is likely related to the increase in domestic demand in Japan for refrigerants and air-conditioning-system-related products and incomplete accounting. A downward trend of HFC emissions that started in 2019 reflects the effectiveness of the F-gas policy in Japan. Eastern China and South Korea, though not obligated to report to the UNFCCC, voluntarily reported emissions, which also show differences between top-down and bottom-up emission estimates, demonstrating the need for atmospheric measurements, comprehensive data analysis, and accurate reporting for precise emission management. Further, the proportional contribution of each country's CO2-equivalent HFC emissions has changed over time, with HFC-134a decreasing and HFC-125 increasing. This demonstrates the transition in the predominant HFC substances contributing to global warming in each country.

A new photoionization-induced substitution reaction chemical ionization time-of-flight mass spectrometry for highly sensitive detection of trace exhaled ethylene

Highly sensitive and rapid detection of ethylene, the smallest alkene of great significance in human physiological metabolism remains a great challenge. In this study, we developed a new photoionization-induced substitution reaction chemical ionization time-of-flight mass spectrometry (PSCI-TOFMS) for trace exhaled ethylene detection. An intriguing ionization phenomenon involving a substitution reaction between the CH2Br2+ reactant ion and ethylene molecule was discovered and studied for the first time. The formation of readily identifiable [CH2Br·C2H4]+ product ion greatly enhanced the ionization efficiency of ethylene, which led to approximately 800-fold improvement of signal intensity over that in single photon ionization mode. The CH2Br2+ reactant ion intensity and ion-molecule reaction time were optimized, and a Nafion tube was employed to eliminate the influence of humidity on the ionization of ethylene. Consequently, a limit of detection (LOD) as low as 0.1 ppbv for ethylene was attained within 30 s at 100 % relative humidity. The application of PSCI-TOFMS on the rapid detection of trace amounts of exhaled ethylene from healthy smoker and non-smoker volunteers demonstrated the satisfactory performance and potential of this system for trace ethylene measurement in clinical diagnosis, atmospheric measurement, and process monitoring.

Evaluation of the hyperspectral radiometer (HSR1) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site

Abstract. The Peak Design Ltd hyperspectral radiometer (HSR1) was tested at the Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site in Lamont, Oklahoma, for 2 months from May to July 2022. The HSR1 is a prototype instrument that measures total (Ftotal) and diffuse (Fdiffuse) spectral irradiance from 360 to 1100 nm with a spectral resolution of 3 nm. The HSR1 spectral irradiance measurements are compared to nearby collocated spectral radiometers, including two multifilter rotating shadowband radiometers (MFRSRs) and the Shortwave Array Spectroradiometer–Hemispheric (SASHe) radiometer. The Ftotal at 500 nm for the HSR1 compared to the MFRSRs has a mean (relative) difference of 0.01 W m−2 nm−1 (1 %–2 %). The HSR1 mean Fdiffuse at 500 nm is smaller than the MFRSRs' by 0.03–0.04 (10 %) W m−2 nm−1. The HSR1 clear-sky aerosol optical depth (AOD) is also retrieved by considering Langley regressions and compared to collocated instruments such as the Cimel sunphotometer (CSPHOT), MFRSRs, and SASHe. The mean HSR1 AOD at 500 nm is larger than the CSPHOT's by 0.010 (8 %) and larger than the MFRSRs' by 0.007–0.017 (6 %–18 %). In general, good agreement between the HSR1 and other instruments is found in terms of the Ftotal, Fdiffuse, and AODs at 500 nm. The HSR1 quantities are also compared at other wavelengths to the collocated instruments. The comparisons are within ∼ 10 % for the Ftotal and Fdiffuse, except for 940 nm, where there is relatively larger disagreement. The AOD comparisons are within ∼ 10 % at 415 and 440 nm; however, a relatively larger disagreement in the AOD comparison is found for higher wavelengths.

In-flight characterization of a compact airborne quantum cascade laser absorption spectrometer

Abstract. Here, we report on the development of a new quantum cascade laser infrared absorption spectroscopy (QLAS) instrument, the Airborne Tropospheric Tracer In-situ Laser Absorption spectrometer (ATTILA), for atmospheric trace-gas measurements on board of the German High-Altitude Long-range Observatory (HALO) aircraft. Its small and light design makes it suitable for airborne measurements up to approximately 150 hPa of ambient pressure (13–14 km). The dual laser instrument can measure several trace gases simultaneously in two 36.4 m path astigmatic Herriott cells with a data acquisition frequency of 1 Hz. We describe the measurement method and the data acquisition of ATTILA and its in-flight performance by focusing on potential sources of influences on the signal, which we investigated with a dedicated test flight during which the instrument sampled from a constant source. We show that linear critical influences associated with challenging movement patterns can be corrected afterwards, while nonlinear limitations can be minimized by appropriate calibration frequencies and integrated time intervals. During the recent aircraft campaign CAFE Brazil (Chemistry of the Atmosphere Field Experiment in Brazil) from December 2022 to January 2023, carbon monoxide (CO) measurements from ATTILA show a good agreement of a R2 of 0.89 with simultaneous CO measurements from an established IR spectrometer for airborne measurements, the TRacer In Situ TDLAS (tunable diode laser absorption spectroscopy) for Atmospheric Research (TRISTAR), at a 10 s time resolution. First dynamical characteristics and tracer distributions of CO and methane (CH4) over the Amazon rainforest can be identified with ATTILA measurements with a total measurement uncertainty of 10.1 % and 17.5 % for calibration gas mixing ratios of 153 and 1990 ppbv and a data accuracy of 0.3 % and 5.5 % for a data acquisition frequency of 1 Hz for CO and CH4, respectively.

Conceptual design of a tilt-rotor unmanned aerial vehicle for Mars exploration

Measurements of Martian magnetic field, atmosphere and sampling are core missions of Martian exploration. Since the successful demonstration of the Ingenuity Helicopter, a large amount of researches have emerged on Mars rotor-craft. However, Mars rotor-crafts have short endurance and limited detection range. This paper proposes a solar-powered tilt-rotor unmanned aerial vehicle (UAV) named Archaeopteryx-I, which can perform vertical take-off and landing (VTOL) and long-endurance level flight. Its general concepts are first elucidated. Then, a multidisciplinary modeling and optimization method is proposed. Considering the harsh magnetic field and atmospheric environment of Mars, the detailed designation of mission system is carried out to further enhance the performance of Archaeopteryx-I, including avionics, energy flow, control system and electromagnetic compatibility (EMC) design. Finally, the conceptual design scheme is validated through simulation and ground testing. The results illustrate the efficaciousness and applicability of Archaeopteryx-I for Mars exploration.

Broadband and filter radiometers at Ross Island, Antarctica: detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation

Abstract. Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.

Analysis of Ionospheric VTEC Retrieved from Multi-Instrument Observations

This study examines the Vertical Total Electron Content (VTEC) estimation performance of multi-instruments on a global scale during different ionospheric conditions. For this purpose, GNSS-based VTEC data from Global Ionosphere Maps (GIMs), COSMIC (F7/C2)—Feng–Yun 3C (FY3C) radio occultation (RO) VTEC, SWARM–VTEC, and JASON–VTEC were utilized. VTEC assessments were conducted on three distinct days: geomagnetic active (17 March 2015), solar active (22 December 2021), and quiet (11 December 2021). The VTEC values of COSMIC/FY3C RO, SWARM, and JASON were compared with data retrieved from GIMs. According to the results, COSMIC RO–VTEC is more consistent with GIM–VTEC on a quiet day (the mean of the differences is 4.38 TECU), while the mean of FY3C RO–GIM differences is 7.33 TECU on a geomagnetic active day. The range of VTEC differences between JASON and GIM is relatively smaller on a quiet day, and the mean of differences on active/quiet days is less than 6 TECU. Besides the daily comparison, long-term results (1 January–31 December 2015) were also analyzed by considering active and quiet periods. Results show that Root Mean Square Error (RMSE) values of COSMIC RO, FY3C RO, SWARM, and JASON are 5.02 TECU, 6.81 TECU, 16.25 TECU, and 5.53 TECU for the quiet period, and 5.21 TECU, 7.07 TECU, 17.48 TECU, and 5.90 TECU for the active period, respectively. The accuracy of each data source was affected by solar/geomagnetic activities. The deviation of SWARM–VTEC is relatively greater. The main reason for the significant differences in SWARM–GIM results is the atmospheric measurement range of SWARM satellites (460 km–20,200 km (SWARM A, C) and 520 km–20,200 km (SWARM B), which do not contain a significant part of the ionosphere in terms of VTEC estimation.

Increasing Methane Emissions and Widespread Cold‐Season Release From High‐Arctic Regions Detected Through Atmospheric Measurements

AbstractRising Arctic temperatures pose a threat to the large carbon stores trapped in Arctic permafrost. To assess methane emissions in high‐Arctic regions, we analyzed atmospheric data from Alaska and Siberia using two methods: (a) a wind sector approach to calculate emission changes based on concentration enhancements using wind direction, and (b) an inversion method utilizing a high‐resolution atmospheric transport model. Incorporating data after 2015, we observed a significant rise in methane emissions (0.018 ± 0.005 Tg yr−2 from 2000 to 2021) from Alaska's North Slope, indicating a shift from previous analyses. We find 34%–50% of yearly emissions occurred in the late season (September–December) consistently across multiple years and regions, which is historically underestimated in models and inventories. Our findings reveal significant changes occurring in the Arctic, highlighting the crucial role of long‐term atmospheric measurements in monitoring the region, especially during the cold season.

Constrained synthetic wind fields from high-resolution 3D WindScanner measurements

The limited spatial and temporal resolution of wind measurements within the inflow of a wind turbine requires statistical modeling of synthetic wind fields, integrating actual measurements or derived statistics along with selected turbulence models. The short-range WindScanner technology enhances atmospheric wind measurements with high resolution in both spatial and temporal dimensions. This contribution utilizes 3D turbulent inflow measurements from three synchronized WindScanner to generate synthetic turbulent wind fields. Both, mean wind field parameters and turbulent time series are analyzed, and different input configurations for the constrained wind field generation are evaluated.Our findings indicate the presence of periods characterized by dominant horizontal shear and veer events, with wind speed and direction differences up to 1.53 ms−1 or 8.45° across the rotor span. Additionally, the study reveals that the optimal measurement configuration for constrained turbulence modeling varies depending on the specific evaluated location and velocity component being analyzed. Another observation is that excessive constraints, placed too closely, may lead to overfitting, thereby diminishing the representativeness of the synthetic field for the lateral velocity component.

Understanding the seasonal dynamics of surface PM2.5 mass distribution and source contributions over Thailand

The escalating levels of aerosols have emerged as a significant concern for climate extremes in the Southeast Asian regions, particularly accentuated during El Nino Years. In this study, we utilized a combination of atmospheric measurements and modeling to investigate the seasonal and geographical distribution of PM2.5 mass concentrations and its primary contributors across Thailand during La Nina (2017) and El Nino (2019) years. Our findings revealed the highest daily mean surface PM2.5 mass concentration during the summer season across most regions, followed by winter, and the lowest levels during the rainy season. Notably, a significant shift in daily mean PM2.5 mass was observed from 2017 to 2019 across all seasons, with a pronounced increase of 70.9% over northern Thailand during the summer, attributed to heightened biomass burning (BB) contributions. In terms of source attribution for PM2.5 mass, the primary contributors in 2017 were BB at 34.3%, followed by anthropogenic emissions (AE) at 32.4%, and natural emissions (NE) at 30.1%. However, in 2019, the BB contribution surged to 47.4% nationwide. During El Nino years, BB played a significant role in shaping concentrations during summer and winter, while NE dominated the rainy season. An important implication of our findings is the significant potential for reducing daily and annual mean PM2.5 mass levels throughout Thailand by effectively reducing BB emissions.

Full characterization and calibration of a transfer standard monitor for atmospheric radon measurements

Abstract. In this work, a full characterization of the new user-friendly version of the Atmospheric Radon MONitor (ARMON), used to measure very low activity concentrations of the radioactive radon gas in the outdoor atmosphere, is carried out. The ARMON is based on the electrostatic collection of 218Po+ particles on a semiconductor detector surface. A main advantage of this instrument is that it offers high-resolution alpha-energy spectra, which will allow us to separate radon progeny (210Po, 218Po, and 214Po). The monitor feature may also allow measurements of thoron (220Rn) by collection of 216Po+, although the instrument is not calibrated for this gas. In the paper, the physical principle; the hardware configuration; and the software development of the automatic and remotely controlled ARMON, conceived and constructed within the MAR2EA and the traceRadon projects, are described. The monitor efficiency and its linearity over a wide span of radon concentration activities have been evaluated and tested here using theoretical and experimental approaches. Finally, a complete budget analysis of the total uncertainty of the monitor was also achieved. Results from the application of a simplified theoretical approach show a detection efficiency for 218Po+ of about 0.0075 (Bq m−3)−1 s−1. The experimental approach, consisting of exposing the ARMON at controlled radon concentrations between a few hundreds to a few thousands of becquerels per cubic metre (Bq m−3), gives a detection efficiency for 218Po+ of 0.0057 ± 0.0002 (Bq m−3) s−1. This last value and its independence from the radon levels were also confirmed thanks to a new calibration method which allows us, using low-emanation sources, to obtain controlled radon levels of a few tens of becquerels per cubic metre (Bq m−3). The total uncertainty of the ARMON detection efficiency obtained for hourly radon concentrations above 5 Bq m−3 was lower than 10 % (k= 1). The characteristic limits of the ARMON – being those dependent on the presence of thoron in the sampled air – were also calculated. A detection limit of 0.132 Bq m−3 was estimated in the absence of thoron. At a typical thoron concentration at atmospheric sites of 0.017 min−1, the detection limit was calculated to be 0.3 Bq m−3, but this can be reduced if using a delay volume, obtaining a decision threshold of 0.0045 Bq m−3. Current results may allow us to confirm that the ARMON is suitable to measure low-level radon activity concentrations (1–100 Bq m−3) and to be used as a transfer standard to calibrate secondary atmospheric radon monitors.

Underestimation of Thermogenic Methane Emissions in New York City.

Recent studies have shown that methane emissions are underestimated by inventories in many US urban areas. This has important implications for climate change mitigation policy at the city, state, and national levels. Uncertainty in both the spatial distribution and sectoral allocation of urban emissions can limit the ability of policy makers to develop appropriately focused emission reduction strategies. Top-down emission estimates based on atmospheric greenhouse gas measurements can help to improve inventories and inform policy decisions. This study presents a new high-resolution (0.02 × 0.02°) methane emission inventory for New York City and its surrounding area, constructed using the latest activity data, emission factors, and spatial proxies. The new high-resolution inventory estimates of methane emissions for the New York-Newark urban area are 1.3 times larger than those for the gridded Environmental Protection Agency inventory. We used aircraft mole fraction measurements from nine research flights to optimize the high-resolution inventory emissions within a Bayesian inversion. These sectorally optimized emissions show that the high-resolution inventory still significantly underestimates methane emissions within the New York-Newark urban area, primarily because it underestimates emissions from thermogenic sources (by a factor of 2.3). This suggests that there remains a gap in our process-based understanding of urban methane emissions.

NeuralCMS: A deep learning approach to study Jupiter's interior

NASA's Juno mission provided exquisite measurements of Jupiter's gravity field that together with the Galileo entry probe atmospheric measurements constrains the interior structure of the giant planet. Inferring its interior structure range remains a challenging inverse problem requiring a computationally intensive search of combinations of various planetary properties, such as the cloud-level temperature, composition, and core features, requiring the computation of sim \(10^9\) interior models. We propose an efficient deep neural network (DNN) model to generate high-precision wide-ranged interior models based on the very accurate but computationally demanding concentric MacLaurin spheroid (CMS) method. We trained a sharing-based DNN with a large set of CMS results for a four-layer interior model of Jupiter, including a dilute core, to accurately predict the gravity moments and mass, given a combination of interior features. We evaluated the performance of the trained DNN (NeuralCMS) to inspect its predictive limitations. NeuralCMS shows very good performance in predicting the gravity moments, with errors comparable with the uncertainty due to differential rotation, and a very accurate mass prediction. This allowed us to perform a broad parameter space search by computing only sim \(10^4\) actual CMS interior models, resulting in a large sample of plausible interior structures, and reducing the computation time by a factor of \(10^5\). Moreover, we used a DNN explainability algorithm to analyze the impact of the parameters setting the interior model on the predicted observables, providing information on their nonlinear relation.

Integration of surface-based and space-based atmospheric CO2 measurements for improving carbon flux estimates using a new developed 3-GAS inversion model

The ongoing necessity and developmental trajectory in atmospheric CO2 assimilation system revolve around enhancing the optimization efficacy of assimilation inversions through the synergistic integration of distinct observational datasets. In this study, we developed an new inversion system-Global Greenhouse-Gases Assimilation System (3-GAS), by coupling the global atmospheric transport model GEOS-Chem with the four-dimensional local ensemble transform Kalman filter (4D-LETKF) algorithm. We compiled an integrated dataset utilizing the widely recognized carbon observation data from ObsPack (Observation Package), GOSAT (The Greenhouse Gases Observing Satellite), and OCO-2 (Orbiting Carbon Observatory-2) to estimate global surface fluxes. The integration of multiple observational data significantly amplifies spatial coverage, enhances the variability in flux inversion, and fosters improvements in localized assimilation efficacy. The spatial distribution of the carbon flux from the combined assimilation emerges as a comprehensive outcome, born from the assimilation with individual observational data. This distribution is primarily influenced by the coverage attributes of the original observations and the meticulous selection of observations during the assimilation process. The validation with surface and aircraft observations reveals that the results of combined assimilation possess composite advantages, which are manifested in alleviating certain intrinsic errors inherent to individual assimilation. The combined assimilation improves the accuracy based on root-mean-square error reduced by 9%, 22% and 33% in comparison to surface-only, GOSAT-only and OCO-2-only assimilation. Eventually, predicated upon preliminary inversion results and regional characteristics, we endeavor to propose a more refined filtration scheme and error determination method for the integrated dataset, as the initiative for the efficient assimilation of multi-source data.

Ozone Monitoring Spectrometer-Limb observation (OMSL) on-orbit polarization correction for atmospheric radiation measurements

OMSL is a passive, space-based spectrometer designed to obtain the vertical profiles of trace gases such as ozone, by measuring atmospheric radiation in limb-viewing mode. Due to the presence of internal components such as gratings and dichroic mirror, OMSL is sensitive to polarization of incident light, which can lead to errors in the radiometric measurements, especially when the incident light is fully polarized. To eliminate the errors, an on-orbit polarization correction method is applied to OMSL. The key to this method is to calculate the polarization correction factor by combining the on-orbit polarization measurement and the pre-flight polarization calibration. In this paper, the on-orbit polarization correction method is introduced in detail. Furthermore, the first results of the on-orbit correction are analyzed and compared with simulation of the SCIATRAN.