Intercomparison Study Research Articles

Results from a multi-laboratory ocean metaproteomic intercomparison: effects of LC-MS acquisition and data analysis procedures

Abstract. Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecology and biogeochemical studies. A blinded multi-laboratory intercomparison was conducted to assess comparability and reproducibility of taxonomic and functional results and their sensitivity to methodological variables. Euphotic zone samples from the Bermuda Atlantic Time-series Study (BATS) in the North Atlantic Ocean collected by in situ pumps and the autonomous underwater vehicle (AUV) Clio were distributed with a paired metagenome, and one-dimensional (1D) liquid chromatographic data-dependent acquisition mass spectrometry analysis was stipulated. Analysis of mass spectra from seven laboratories through a common bioinformatic pipeline identified a shared set of 1056 proteins from 1395 shared peptide constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R2 values averaged 0.62±0.11, and a Sørensen similarity analysis of the top 1000 proteins revealed 70 %–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. A bioinformatic intercomparison study, involving 10 laboratories using eight software packages, successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. Lessons learned and potential improvements in methods were described. Future efforts could examine reproducibility in deeper metaproteomes, examine accuracy in targeted absolute quantitation analyses, and develop standards for data output formats to improve data interoperability. Together, these results demonstrate the reproducibility of metaproteomic analyses and their suitability for microbial oceanography research, including integration into global-scale ocean surveys and ocean biogeochemical models.

B-020 Study of Method Intercomparison between Atellica Solution® and CI® Analyzers for T4L, β-HCG Total, and PSA Total

Abstract Background Method intercomparison is an essential requirement in Clinical Laboratories before changing a method or instrument to verify the interchangeability of results. After validating a new Siemens device, the CI®, we conducted an intercomparison study with the Atellica Solution® for T4 free (T4L), β-HCG total, and PSA total assays. Objectives To check the interchangeability of results between the methods of T4L, β-HCG total, and PSA total, as determined on the Atellica Solution® and CI® analyzers, to evaluate the behavior of both equipment in our laboratory as a single virtual team. Methods A total of 120 serum samples from patients with T4L values between 0.41 and 7.5 ng/dL, β-HCG total between 0.5 and 1000 mIU/mL, and PSA total between 0.01 and 78.4 ng/mL were processed on both analyzers. Passing-Bablok regression, Bland-Altman analysis, and Pearson correlation coefficient were used to evaluate the sample size. Results are expressed with a 95% confidence interval. The intercomparison study was conducted using Method Validator Version 1.19. Results See table Conclusions After evaluating the results, we conclude that the Atellica Solution® and CI® analyzers behave as a single virtual team for the T4L, β-HCG total, and PSA total assays. Although there are systematic errors, they do not exceed the quality specifications established in our laboratory, based on the Total Error allowable according to Biological Variability.

A-220 Method Intercomparison Study between Atellica Solution® and CI® Analyzers for HDL and LDL Methods

Abstract Background After validating a new Siemens equipment, the Atellica CI®, it is essential to ensure result interchangeability in our laboratory accredited by ISO 15189:2012. Objectives verify if the results of the HDL and LDL methods measured by Atellica Solution® and CI® analyzers are interchangeable and could be used interchangeably on both instruments Methods 40 patient samples were selected for each assay, with results distributed across the entire measurement range and analyzed by both instruments. Result evaluation was conducted using the statistical program Method Validator v.19. To determine the degree of agreement between the instruments, a Bland-Altman mean difference analysis and a Passing-Bablok regression were performed. Statistics are expressed with their 95% confidence intervals (CI). Results HDL: After analyzing the Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica Solution® and CI® was 0.686, with higher results in CI 1900®. Regarding the Passing Bablok analysis, constant systematic differences were observed as the confidence interval of the intercept does not include the zero value, and statistically significant proportional differences based on the slope whose 95% CI does not include the value 1.LDL: After analyzing the Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica and CI® was -3.16, with higher results in Atellica Solution®. Regarding the Passing Bablok analysis, there were no systematic differences of constant type as the confidence interval of the intercept includes the zero value, but there were proportional differences based on the slope whose 95% CI does not include the value 1. Conclusions After evaluating the results, it is concluded that Atellica Solution® and CI® analyzers are interchangeable for HDL and LDL assays despite the presence of a systematic error, as the observed difference is not clinically significant.

A-219 Method Intercomparison Study between Atellica Solution® and CI® Analyzers for Total Cholesterol and Triglycerides

Abstract Background Method intercomparison is an essential requirement that every Laboratory must perform when considering a method or instrument change for a specific analyte. Objective verify if the results of two analytical techniques (Total Cholesterol and Triglycerides) measured by Atellica Solution® and CI® analyzers (Siemens Healthineers) are interchangeable. Methods 40 patient samples were selected for each assay, with results distributed across the entire measurement range and analyzed by both instruments. Estatistical program Method Validator was used. To determine the degree of agreement between both instruments, Bland-Altman difference analysis and Passing-Bablok regression were performed. Statistics are expressed with their 95% confidence intervals. Results Total Cholesterol: After analyzing Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica Solution® and CI 1900® was 13.8 with a 95% CI that does not include the null value. Regarding Passing Bablok analysis, a constant systematic difference was observed as the confidence interval of the intercept does not include the zero value, and also a proportional difference based on the 95% CI of the slope that does not include the value 1.• Triglycerides: After analyzing the Bland-Altman differences, a systematic error was found as the mean difference between the results obtained by Atellica Solution® and CI 1900® was -15.6, with higher results in Atellica Solution®. Regarding the Passing Bablok analysis, constant systematic differences were observed as the confidence interval of the intercept does not include the zero value, and also proportional differences based on the slope, whose 95% CI does not include the value 1 Conclusions It´s concluded that Atellica Solution® and CI® analyzers are not interchangeable for Total Cholesterol and Triglycerides assays due to the presence of a constant systematic error. To use them on both instruments, it would be advisable to modify the reference values for both methods.

B-010 Intercomparison Study of Methods between Atellica Solution® and CI® Analyzers for Sodium, Potassium, and Chloride

Abstract Background Method verification is an essential analysis routinely conducted in accredited Clinical Laboratories whenever a change of method or instrument for a specific analyte is desired. Objectives The aim of the study is to verify that the results measured by the Atellica Solution® analyzer (Siemens) and the new CI® analyzer (Siemens) for Sodium, Potassium, and Chloride are interchangeable. Methods To conduct the intercomparison study of Sodium, Potassium, and Chloride, the techniques were properly calibrated and controlled on both analyzers. For each assay, 40 patient samples were selected, covering the entire measurement range, and analyzed by both instruments. To determine the degree of agreement between the instruments, a Bland Altman analysis of mean differences and a Passing Bablok regression were performed. Statistics are expressed with their 95% confidence intervals (CI). The evaluation of results was carried out using the statistical program Method Validator. Results In both the Bland-Altman and Passing Bablok regression analyses, a slight constant systematic error was detected for all three assays, as the 95% confidence interval of the observed mean difference and the 95% confidence interval of the intercept of the regression line do not include zero. No systematic proportional differences were observed based on the slope, as the 95% confidence interval includes the value one Conclusions The small constant systematic differences found in the analyses should be re-evaluated after performing a new calibration of the methods. In none of the cases are the differences clinically significant, as they do not exceed the total error established in our quality specification. Therefore, it can be concluded that the Atellica Solution® and CI 1900® analyzers are interchangeable for Sodium, Potassium, and Chloride assays

Inter-comparison of GNSS- IPWV with ERA-5 IPWV and monitoring of convective events over the Indian region

The present study deals with (i) An Inter-comparison study of ground based Global Navigation Satellite System (GNSS) derived Integrated Precipitable Water Vapour (IPWV) with 5th generation global climate reanalysis data of European Centre for Medium Range Weather Forecast (ERA-5) (ii) IPWV thresholds of GNSS data (iii) case studies of IPWV analysis. It is found that both the datasets (GNSS and ERA-5) are strongly correlated & the correlation coefficient ranging between 0.97 and 0.99. Monthly Thresholds of IPWV (MTI) are generated with 2017 -2020 data sets from Indian GNSS station having continuous data and found very useful input as value addition to know the possibility of building up /decaying of convection in day to day daily forecast issued to the public. Case studies shows an increase of IPWV, 3 to 4 hour prior to the occurrence of convective event around the GNSS station and found very useful for nowcasting. Therefore, utilization of IPWV (model as wells GNSS based) have incremented value in enriching the understanding about the weather event and its forecasting. This supplement information along with other analysis products (model, surface, upper air, satellite or radar etc) can support further in appropriate decision making to the forecasters, decision makers and the end users of the society.

The crucial representation of deep convection for the cyclogenesis of Medicane Ianos

Abstract. This paper presents a model intercomparison study to improve the prediction and understanding of Mediterranean cyclone dynamics. It is based on a collective effort with five mesoscale models to look for a robust response among 10 numerical frameworks used in the community involved in the networking activity of the EU COST Action “MedCyclones”. The obtained multi-model, multi-physics ensemble is applied to the high-impact Medicane Ianos of September 2020 with a focus on the cyclogenesis phase, which was poorly forecast by numerical weather prediction systems. Models systematically perform better when initialised from operational IFS analysis data compared to the widely used ERA5 reanalysis. Reducing horizontal grid spacing from 10 km with parameterised convection to convection-permitting 2 km further improves the cyclone track and intensity. This highlights the critical role of deep convection during the early development stage. Higher resolution enhances convective activity, which improves the phasing of the cyclone with an upper-level jet and its subsequent intensification and evolution. This upscale impact of convection matches a conceptual model of upscale error growth in the midlatitudes, while it emphasises the crucial interplay between convective and baroclinic processes during medicane cyclogenesis. The 10 numerical frameworks show robust agreement but also reveal model specifics that should be taken into consideration, such as the need for a parameterisation of deep convection even at 2 km horizontal grid spacing in some models. While they require generalisation to other cases of Mediterranean cyclones, the results provide guidance for the next generation of global convection-permitting models in weather and climate.

RADIOCARBON MORTAR DATING INTERCOMPARISON MODIS2—APPROACH FROM THE ZAGREB RADIOCARBON LABORATORY, CROATIA

ABSTRACT The Second International Mortar Dating Intercomparison Study (MODIS2) took place in 2020. Three mortar samples from different sites and chronologies were distributed among various research groups in form of bulk mortar and grain fraction smaller than 150 µm. This is the first time the Zagreb Radiocarbon Laboratory, with support of the Center of Applied Isotope Studies, University of Georgia, took part in the international mortar intercomparison. The initial approach of the Laboratory to mortar dating was to separate 32–63 µm grain fraction and collect three CO2 gas portions by sequential dissolution with acid. After checking the 14C date trends of the gas portions, which should be ascending with later fractions, the one for the first and shortest gas portion was reported as the age of the mortar. However, the first gas portion might not be true age of the mortar, since it still might contain some “dead” carbon. Therefore, data extrapolation from the first two initial CO2 portions was also conducted on the results, but not reported to the intercomparison. Though in general, all the intercomparison reported dates fit the expected historical ages, for one sample, the extrapolated result showed a better match to the historical data.

Feasibility of peak temperature targets in light of institutional constraints

Despite faster-than-expected progress in clean energy technology deployment, global annual CO2 emissions have increased from 2020 to 2023. The feasibility of limiting warming to 1.5 °C is therefore questioned. Here we present a model intercomparison study that accounts for emissions trends until 2023 and compares cost-effective scenarios to alternative scenarios with institutional, geophysical and technological feasibility constraints and enablers informed by previous literature. Our results show that the most ambitious mitigation trajectories with updated climate information still manage to limit peak warming to below 1.6 °C (‘low overshoot’) with around 50% likelihood. However, feasibility constraints, especially in the institutional dimension, decrease this maximum likelihood considerably to 5–45%. Accelerated energy demand transformation can reduce costs for staying below 2 °C but have only a limited impact on further increasing the likelihood of limiting warming to 1.6 °C. Our study helps to establish a new benchmark of mitigation scenarios that goes beyond the dominant cost-effective scenario design.

Aerosol trace element solubility determined using ultrapure water batch leaching: an intercomparison study of four different leaching protocols

Abstract. Solubility of aerosol trace elements, which determines their bioavailability and reactivity, is operationally defined and strongly depends on the leaching protocol used. Ultrapure water batch leaching is one of the most widely used leaching protocols, while the specific leaching protocols used in different labs can still differ in agitation methods, contact time, and filter pore size. It is yet unclear to which extent the difference in these experimental parameters would affect the aerosol trace element solubility reported. This work examined the effects of agitation methods, filter pore size, and contact time on the solubility of nine aerosol trace elements and found that the difference in agitation methods (shaking vs. sonication), filter pore size (0.22 vs. 0.45 µm), and contact time (1 vs. 2 h) only led to small and sometimes insignificant difference in the reported solubility. We further compared aerosol trace element solubility determined using four ultrapure water leaching protocols, which are adopted by four different labs and vary in agitation methods, filter pore size, and/or contact time, and observed good agreement in the reported solubility. Therefore, our work suggests that although ultrapure water batch leaching protocols used by different labs vary in specific experimental parameters, the determined aerosol trace element solubility is comparable. We recommend that ultrapure water batch leaching be one of the reference leaching schemes and emphasize that additional consensus in the community on agitation methods, contact time, and filter pore size is needed to formulate a standard operating procedure for ultrapure water batch leaching.

Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2

Abstract. Solar radiation modification by a sustained deliberate source of SO2 into the stratosphere (strat-SRM) has been proposed as an option for climate intervention. Global interactive aerosol–chemistry–climate models are often used to investigate the potential cooling efficiencies and associated side effects of hypothesized strat-SRM scenarios. A recent model intercomparison study for composition–climate models with interactive stratospheric aerosol suggests that the modeled climate response to a particular assumed injection strategy depends on the type of aerosol microphysical scheme used (e.g., modal or sectional representation) alongside host model resolution and transport. Compared to short-duration volcanic SO2 emissions, the continuous SO2 injections in strat-SRM scenarios may pose a greater challenge to the numerical implementation of microphysical processes such as nucleation, condensation, and coagulation. This study explores how changing the time steps and sequencing of microphysical processes in the sectional aerosol–chemistry–climate model SOCOL-AERv2 (40 mass bins) affects model-predicted climate and ozone layer impacts considering strat-SRM by SO2 injections of 5 and 25 Tg(S) yr−1 at 20 km altitude between 30° S and 30° N. The model experiments consider the year 2040 to be the boundary conditions for ozone-depleting substances and greenhouse gases (GHGs). We focus on the length of the microphysical time step and the call sequence of nucleation and condensation, the two competing sink processes for gaseous H2SO4. Under stratospheric background conditions, we find no effect of the microphysical setup on the simulated aerosol properties. However, at the high sulfur loadings reached in the scenarios injecting 25 Tg(S) yr−1 of SO2 with a default microphysical time step of 6 min, changing the call sequence from the default “condensation first” to “nucleation first” leads to a massive increase in the number densities of particles in the nucleation mode (R<0.01 µm) and a small decrease in coarse-mode particles (R>1 µm). As expected, the influence of the call sequence becomes negligible when the microphysical time step is reduced to a few seconds, with the model solutions converging to a size distribution with a pronounced nucleation mode. While the main features and spatial patterns of climate forcing by SO2 injections are not strongly affected by the microphysical configuration, the absolute numbers vary considerably. For the extreme injection with 25 Tg(S) yr−1, the simulated net global radiative forcing ranges from −2.3 to −5.3 W m−2, depending on the microphysical configuration. Nucleation first shifts the size distribution towards radii better suited for solar scattering (0.3 µm <R< 0.4 µm), enhancing the intervention efficiency. The size distribution shift, however, generates more ultrafine aerosol particles, increasing the surface area density and resulting in 10 DU (Dobson units) less ozone (about 3 % of the total column) in the northern mid-latitudes and 20 DU less ozone (6 %) over the polar caps compared to the condensation first approach. Our results suggest that a reasonably short microphysical time step of 2 min or less must be applied to accurately capture the magnitude of the H2SO4 supersaturation resulting from SO2 injection scenarios or volcanic eruptions. Taken together, these results underscore how structural aspects of model representation of aerosol microphysical processes become important under conditions of elevated stratospheric sulfur in determining atmospheric chemistry and climate impacts.

Micro-PINGUIN: microtiter-plate-based instrument for ice nucleation detection in gallium with an infrared camera

Abstract. Ice nucleation particles play a crucial role in atmospheric processes; for example, they can trigger ice formation in clouds and thus influence their lifetime and optical properties. The quantification and characterization of these particles require reliable and precise measurement techniques. In this publication, we present a novel droplet freezing instrument to measure the immersion freezing of biotic and abiotic ice-nucleating particles within the temperature range of 0 to −25 °C. Immersion freezing of the samples is investigated using 384-well PCR plates with a sample volume of 30 µL. Nucleation events are detected with high precision using a thermal camera that records the increase in infrared emission due to the latent heat release. To maximize the thermal contact between the PCR plate and the surrounding cooling unit, we use a gallium bath as a mount for the PCR plate. The instrument was validated relative to a calibrated temperature standard and through reproducibility measurements employing the same suspension. We find that the combination of good thermal connectivity and precise temperature recording enables accurate (±0.81 °C at −10 °C) and reproducible (±0.20 °C) detection of the nucleation temperatures. Consequently, the results that are produced using the MICROtiter-Plate-based instrument for Ice Nucleation detection in GalliUm with an INfrared camera (micro-PINGUIN) are of good quality and the instrument can be used to study the immersion freezing of various ice-nucleating particles. For comparison with already existing instruments, Snomax® (hereafter Snomax) and illite NX suspensions are measured with the new ice nucleation instrument, micro-PINGUIN. Further, we investigated the reproducibility of experiments using Snomax suspensions and found poor reproducibility when suspensions were prepared freshly even if the same batch of Snomax is used. This could be attributed to substrate heterogeneity, aging effects, and dilution errors. The reproducibility of the measurements is greatly improved for Snomax suspensions that are prepared in advance and stored frozen in aliquots. Thus, we suggest the use of suspensions frozen in aliquots for further reproducibility measurements and intercomparison studies.

Intercomparison study between the measurement of LDL cholesterol in the Atellica Solution® analyser and the estimation of LDL cholesterol using the Martin-Hopkins equation

Intercomparison study between the measurement of LDL cholesterol in the Atellica Solution® analyser and the estimation of LDL cholesterol using the Martin-Hopkins equation

Intercomparison study between the measurement of LDL cholesterol in the atellica solution® analyser and the estimation of LDL cholesterol using the friedewald equation

Intercomparison study between the measurement of LDL cholesterol in the atellica solution® analyser and the estimation of LDL cholesterol using the friedewald equation

Simulation of soil temperature under maize: An inter-comparison among 33 maize models

Accurate simulation of soil temperature can help improve the accuracy of crop growth models by improving the predictions of soil processes like seed germination, decomposition, nitrification, evaporation, and carbon sequestration. To assess how well such models can simulate soil temperature, herein we present results of an inter-comparison study of 33 maize (Zea mays L.) growth models. Among the 33 models, four of the modeling groups contributed results using differing algorithms or “flavors” to simulate evapotranspiration within the same overall model family. The study used comprehensive datasets from two sites - Mead, Nebraska, USA and Bushland, Texas, USA wherein soil temperature was measured continually at several depths. The range of simulated soil temperatures was large (about 10–15 °C) from the coolest to warmest models across whole growing seasons from bare soil to full canopy and at both shallow and deeper depths. Within model families, there were no significant differences among their simulations of soil temperature due to their differing evapotranspiration method “flavors”, so root-mean-square-errors (RMSE) were averaged within families, which reduced the number of soil temperature model families to 13. The model family RMSEs averaged over all 20 treatment-years and 2 depths ranged from about 1.5 to 5.1 °C. The six models with the lowest RMSEs were APSIM, ecosys, JULES, Expert-N, SLFT, and MaizSim. Five of these best models used a numerical iterative approach to simulate soil temperature, which entailed using an energy balance on each soil layer. whereby the change in heat storage during a time step equals the difference between the heat flow into and that out of the layer. Further improvements in the best models for simulating soil temperature might be possible with the incorporation of more recently improved routines for simulating soil thermal conductivity than the older routines now in use by the models.

System for Analysis of Wind Collocations (SAWC): A Novel Archive and Collocation Software Application for the Intercomparison of Winds from Multiple Observing Platforms

Accurate atmospheric 3D wind observations are one of the top priorities for the global scientific community. To address this requirement, and to support researchers’ needs to acquire and analyze wind data from multiple sources, the System for Analysis of Wind Collocations (SAWC) was jointly developed by NOAA/NESDIS/STAR, UMD/ESSIC/CISESS, and UW-Madison/CIMSS. SAWC encompasses the following: a multi-year archive of global 3D winds observed by Aeolus, sondes, aircraft, stratospheric superpressure balloons, and satellite-derived atmospheric motion vectors, archived and uniformly formatted in netCDF for public consumption; identified pairings between select datasets collocated in space and time; and a downloadable software application developed for users to interactively collocate and statistically compare wind observations based on their research needs. The utility of SAWC is demonstrated by conducting a one-year (September 2019–August 2020) evaluation of Aeolus level-2B (L2B) winds (Baseline 11 L2B processor version). Observations from four archived conventional wind datasets are collocated with Aeolus. The recommended quality controls are applied. Wind comparisons are assessed using the SAWC collocation application. Comparison statistics are stratified by season, geographic region, and Aeolus observing mode. The results highlight the value of SAWC’s capabilities, from product validation through intercomparison studies to the evaluation of data usage in applications and advances in the global Earth observing architecture.

Validation of mSOUND using a fully heterogeneous skull model

Transcranial ultrasound has found an increasing number of applications in recent years, including the treatment of neurological conditions through thermal ablation and neuromodulation. Ensuring the success and safety of such treatments necessitates precise numerical simulations of transcranial ultrasound, a pivotal aspect of treatment planning involving phase correction. Addressing this demand, an open-source wave solver named mSOUND (https://m-sound.github.io/mSOUND/home) was developed specifically for modeling focused ultrasound in heterogeneous media. A recent intercomparison study (J. Acoust. Soc. Am. 152, 1003–1019, 2022) scrutinized mSOUND alongside other wave solvers like k-Wave, demonstrating its accuracy in modeling wave propagation through a homogeneous skull. This study extends the assessment to evaluate mSOUND's accuracy in modeling wave propagation through a fully heterogeneous skull, utilizing CT images of an ex vivo human skull. The obtained results are systematically compared with those from k-Wave, revealing a high level of agreement.

Inter-comparison study of wind measurement between the three-lidar-based virtual tower and four lidars using VAD techniques

ABSTRACT The accurate three-dimensional wind field obtained from a Doppler lidar not only helps to comprehend the refined structure of complex airflow but also provides important and valuable solutions for many fields. However, the underlying homogeneity assumption of the typical wind retrieval methods, such as Doppler Beam Swinging (DBS) and Velocity Azimuth Display (VAD) based on a single-lidar, will introduce the measurement uncertainty in complex terrain. In this paper, a new design of a wind measurement campaign involving seven lidars was carried out, which contained the three-lidar-based Virtual Tower (VT) using a time-space synchronization technique and four single-lidars with different elevation angles. This study investigates the performance of VT and VAD measurements under various conditions and evaluates the sensitivity of wind measurement uncertainty of VAD to the horizontal spatial- and probe volume-average effects associated with elevation angles of the laser beam. The inter-comparison results between VT and four VADs show consistent trends with small relative errors under neutral atmospheric conditions with weak wind velocity. Under convective or high Turbulence Intensity (TI) conditions, the relative errors between VT and VAD become larger and more fluctuant. Moreover, it is found that the measurement uncertainty of VAD increases at a given elevation angle with the increasing measurement heights, which is caused by the horizontal homogeneity associated with the conical scanning area. Additionally, the simulated and measured results of four VADs indicate that a larger elevation angle corresponds to a lower measurement uncertainty for a given height.

Towards the definition of a solar forcing dataset for CMIP7

Abstract. The solar forcing prepared for Phase 6 of the Coupled Model Intercomparison Project (CMIP6) has been used extensively in climate model experiments and has been tested in various intercomparison studies. Recently, an International Space Science Institute (ISSI) working group has been established to revisit the solar forcing recommendations, based on the lessons learned from CMIP6, and to assess new datasets that have become available, in order to define a road map for building a revised and extended historical solar forcing dataset for the upcoming Phase 7 of CMIP. This paper identifies the possible improvements required and outlines a strategy to address them in the planned new solar forcing dataset. Proposed major changes include the adoption of the new Total and Spectral Solar Irradiance Sensor (TSIS-1) solar reference spectrum for solar spectral irradiance and an improved description of top-of-the-atmosphere energetic electron fluxes, as well as their reconstruction back to 1850 by means of geomagnetic proxy data. In addition, there is an urgent need to consider the proposed updates in the ozone forcing dataset in order to ensure a self-consistent solar forcing in coupled models without interactive chemistry. Regarding future solar forcing, we propose consideration of stochastic ensemble forcing scenarios, ideally in concert with other natural forcings, in order to allow for realistic projections of natural forcing uncertainties.

Spectral Fingerprinting of Methane from Hyper-Spectral Sounder Measurements Using Machine Learning and Radiative Kernel-Based Inversion

Satellite-based hyper-spectral infrared (IR) sensors such as the Atmospheric Infrared Sounder (AIRS), the Cross-track Infrared Sounder (CrIS), and the Infrared Atmospheric Sounding Interferometer (IASI) cover many methane (CH4) spectral features, including the ν1 vibrational band near 1300 cm−1 (7.7 μm); therefore, they can be used to monitor CH4 concentrations in the atmosphere. However, retrieving CH4 remains a challenge due to the limited spectral information provided by IR sounder measurements. The information required to resolve the weak absorption lines of CH4 is often obscured by interferences from signals originating from other trace gases, clouds, and surface emissions within the overlapping spectral region. Consequently, currently available CH4 data product derived from IR sounder measurements still have large errors and uncertainties that limit their application scope for high-accuracy climate and environment monitoring applications. In this paper, we describe the retrieval of atmospheric CH4 profiles using a novel spectral fingerprinting methodology and our evaluation of performance using measurements from the CrIS sensor aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. The spectral fingerprinting methodology uses optimized CrIS radiances to enhance the CH4 signal and a machine learning classifier to constrain the physical inversion scheme. We validated our results using the atmospheric composition reanalysis results and data from airborne in situ measurements. An inter-comparison study revealed that the spectral fingerprinting results can capture the vertical variation characteristics of CH4 profiles that operational sounder products may not provide. The latitudinal variations in CH4 concentration in these results appear more realistic than those shown in existing sounder products. The methodology presented herein could enhance the utilization of satellite data to comprehend methane’s role as a greenhouse gas and facilitate the tracking of methane sources and sinks with increased reliability.