Methane, the second most important greenhouse gas, has attracted a lot of attention due to significant uncertainties in its sources and sinks. Currently, methane emission estimation relies on the inverse modeling approach, whose accuracy heavily depends on the accuracy of the atmospheric transport model. The lowermost stratosphere is a region where transport processes are complex, and methane models are usually biased. These biases can propagate downward and degrade the model at the surface. This study investigates the sensitivity of these transport processes to model vertical resolution. The results reveal that transport by the transition branch of the Brewer–Dobson circulation (BDC) and horizontal mixing along isentropes have the most significant influence in this region. According to results here, correctly simulating methane in the lowermost stratosphere requires correctly representing the transition branch and horizontal mixing at the outset. Secondly, a realistic representation of the shallow and deep branches of the BDC is important. While increasing vertical resolution improves the simulated BDC, it degrades the simulated methane in this region due to the weakened mixing.摘要甲烷作为第二重要的温室气体而备受关注. 目前, 甲烷排放反演估算的准确性取决于大气传输模式的准确度. 最低层平流层是一个受复杂传输过程影响的区域, 大气传输模式通常存在偏差且会传递至地表. 本研究探讨了这些传输过程对模式垂直分辨率的依赖性. 结果表明, Brewer–Dobson环流 (BDC) 的过渡支及其沿等熵面的水平混合对该区域的影响最为显著. 根据结果, 要正确模拟最低层平流层的甲烷, 首先需要准确刻画过渡支和水平混合过程. 其次, 真实描述BDC的浅层和深层两支环流也很重要. 虽然提高垂直分辨率能够改善BDC的模拟效果, 但由于混合过程被削弱, 该区域的甲烷模拟效果反而会变差.

The intensity and position of the westerly jet influence precipitation in Central Asia, while the impact of its structural changes on precipitation remains underexplored. This study defines a Jet Break Index based on ERA5 reanalysis data to examine how jet break events affect summer precipitation in the region. Results show that the index, derived using relative vorticity at 200 hPa, effectively identifies jet break events. The convergence and southward strengthening of Rossby waves as they propagate into Central Asia lead to jet break and trigger tropopause folding events. As stratospheric air intrudes into the troposphere, the resulting disturbance induces ascending (descending) motion in the downstream (upstream) region and is accompanied by positive (negative) vertical moisture advection contributions, thereby enhancing (suppressing) precipitation accordingly. These findings highlight the significant impact of jet break on precipitation anomalies and its implications for forecasting over Central Asia.

Ozone transported from the stratosphere to the troposphere is a key component of the source of tropospheric ozone, and this transport is related to the residual circulation in the stratosphere. The impacts of stratospheric Quasi‐Biennial Oscillation (QBO) and tropospheric El Niño‐Southern Oscillation (ENSO) events on stratospheric circulation will affect the stratosphere‐to‐troposphere transport of ozone. In this study we use average of stratosphere‐tagged ozone tracer (O 3 S) from two chemistry‐climate models to quantify the downward transport of stratospheric ozone. We found that under the westerly QBO (WQBO) phase, less than the average stratospheric ozone is transported to the troposphere (2.5–6 ppbv O 3 S anomaly from 500 to 200 hPa in mid‐high latitudes). The opposite is true under the easterly QBO (EQBO) phase, accompanied by more stratospheric ozone transport to the troposphere (5–10 ppbv O 3 S anomaly from 500 to 200 hPa). The impact of ENSO events on the stratosphere‐to‐troposphere ozone transport shows a hemispheric asymmetry. The ozone transported into the troposphere decreases by about 2.5–6 ppbv from 500 to 200 hPa in the Northern Hemisphere under the warm ENSO phase, but shows almost the same amount of anomalous increase in the Southern Hemisphere. The situation is opposite during the cold ENSO phase. This variation in ozone transport in response to the QBO and ENSO is related to the stratospheric residual circulation variations. In a warming future climate, the frequency of El Niño events will increase while the amplitude of QBO is expected to decrease, thus affecting the stratospheric source of tropospheric ozone.

As the surface ozone (O3) 3 ) concentration is increasing despite emission control measures, it is urgent to clarify the impact of dynamic transport, such as quantifying the impact of stratosphere-to-troposphere transport (STT) on the surface O3 3 budget. Based on observations and numerical models, this study explores the relationship between the surface O3 3 concentration in eastern China (30 degrees-38 degrees N, 112 degrees-122 degrees E) degrees- 38 degrees N, 112 degrees- 122 degrees E) and the location and intensity of the Northeast China cold vortex (NCCV), a predictable weather system. The results show that when the NCCV occurs in the southeastern region (35 degrees-47.5 degrees N, 125 degrees-140 degrees E), degrees- 47.5 degrees N, 125 degrees- 140 degrees E), there is a corresponding increase in the surface O3 3 concentration in eastern China. The stronger the intensity of the NCCV is, the greater the increase in surface O3. 3 . The strongest 10% of the NCCV may cause an increase in the surface O3 3 concentration of 12-18 ppbv (30%-45% of the summer average surface O3 3 concentration). NCCV events and enhanced O3 3 are related to the STT. Anomalies in the 200-hPa wind fi eld induce downward motion in the NCCV region and its west side. The cold O3 3-rich stratospheric air is transported southeastward and downward during the NCCV period, leading to an increase in the surface O3 3 concentration. The correlation and predictability between 500-hPa meteorological fi elds and surface O3 3 concentrations are also highlighted in this work. SIGNIFICANCE STATEMENT: Despite the emission control measures taken in the past, the surface O3 3 concentration continues to increase in most regions of the world. It is urgent to quantify all the factors that impact the surface O3 3 concentration. This study focuses on a predictable weather system, the Northeast China cold vortex (NCCV), and its connection with stratosphere-to-troposphere transport (STT) that induces enhanced surface O3 3 concentrations. Our fi ndings provide a fresh perspective for studying the sources and forecasting of O3 3 concentrations by linking upper-level weather systems and meteorological fi elds with changes in surface O3 3 concentrations.

Simulation of dust aerosol optical property is rather difficult, due to its extremely irregular shape, which often brings about difficulties in transforming its physical properties (such as size distribution) into optical properties (such as scattering phase function) in remote sensing retrieval and atmospheric radiation model. Some recent researches reveal that homogeneous spheroids seem to be an applicable optical model when dust particles are not much bigger than the wavelength, spheroids with reasonable shape distribution can simulate the scattering phase function of dust particles quite well. Based on the existed dual-wavelength lidar inversion algorithms, a modified method is proposed in the paper. Assuming the size distributions of dust aerosol can be modeled by bimodal lognormal distributions dominated by particles ranged in coarse mode, the size distributions and lidar ratios of dust aerosol at two wavelengths can be derived from dual-wavelength lidar measurement. By applying this algorithm to the data of dual-wavelength lidar at Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL), preliminary results show that for the case of pure dust the retrieved size distribution agree with that observed by Aerodynamic Particle Sizer Spectrometer, and the derived mean lidar ratios are 45.7 ± 5.3 sr at 532 nm and 33.9 ± 1.5 sr at 1064 nm.

Tropopause fold events are one of the major processes in stratosphere-troposphere exchange (STE) in the mid-latitudes. The Tibetan Plateau (TP) is a hotspot of STE in the world. It has been proved that the tropopause fold events over the TP could impact on tropospheric ozone concentration in summer, yet most of these studies only focus on tropopause fold events at individual stations. In this study, we use ozone soundings data over Minle County (38.41°N, 100.65°E) and surface observations in the TP to verify the effect of tropopause fold events on surface ozone concentration. The stratospheric ozone tracers (O3S) simulation by the WACCM model and the passive tracers simulation by the WRF model indicate that the tropopause fold event observed on 11 July 2020 contributed to surface ozone in the northern regions of TP. In addition, we identified all the tropopause fold events that occurred over the TP in each July from 2015 to 2020 and quantified their impacts on surface ozone concentration. The results show that the average increase in surface ozone concentration is 15.94 ppbv during the period affected by the tropopause fold events. The site most affected by tropopause fold events is Shannan City, followed by Nyingchi City. This study revealed the importance of the influence of tropopause fold event on surface ozone concentration in the TP in summer.

As one of the major processes in stratosphere-to-troposphere transport (STT) in the mid-latitudes, tropopause folds have drawn widespread attention. The Tibetan Plateau (TP) is a hotspot of tropopause folds. Existing studies have shown that tropopause folds over the TP may have an impact on tropospheric ozone concentration in summer, yet most of these studies only focus on the impact of tropopause folds at individual stations. In this study, we use ozone soundings data over Minle County (38.41°N, 100.65°E), which is located in the northeast of TP, and surface observations in the TP verified the effect of tropopause folds on surface ozone concentration. The O3S simulation by the WACCM model, the passive tracer simulation by the WRF model indicate that the tropopause fold event observed in July 2020 contributed to surface ozone in the western and northern regions of TP. In addition, we further identify all the tropopause folds that occurred over the TP from 2015 to 2020 and quantified their impacts on surface ozone. The results show that the average increase in surface ozone concentration is 15.9 ppbv during the tropopause folds. The site most affected by tropopause folds is Shannan City, followed by Nyingchi City.

Methane (CH 4 ) is the second most important greenhouse gas. At the global scale, inverse modeling is usually applied to infer CH 4 fluxes on the surface. In the inverse model, the chemistry transport model (CTM) is used to link CH 4 fluxes to its concentration in the atmosphere. Any uncertainties in the transport and chemical processes modeled by the CTM can lead to biases in the inferred fluxes. Therefore, diagnosing transport processes in the CTM is important for improving the accuracy of inferred fluxes. It is well‐known that the inverse model‐calculated total columns of CH 4 contain latitude‐dependent biases when compared to observations. Previous studies revealed that these biases mostly occur in the troposphere. However, we demonstrate in the present study that the model biases in the troposphere can originate in the stratosphere, especially in the lowermost stratosphere, and propagate downward to the troposphere. The propagated biases in the simulations of the atmospheric model TM5‐CAMS are estimated to be about 25 ppb in the mid‐troposphere above the northern high‐latitudes and about 2 ppb over the tropics. At the surface the propagated biases are estimated to be about 20 and 7 ppb in the above two regions, respectively. In addition, the propagated biases display an important zonal asymmetry in the troposphere, especially over the Tibetan‐Plateau, Southeast Asia and tropical South America. It is recommended that some correction functions should be considered in inverse modeling that use surface observations only.

The present study investigates the influences of stratospheric quasi-biennial oscillation (QBO) and El Niño–Southern Oscillation (ENSO) on the intensity of stratospheric isentropic mixing based on ERA-Interim and MERRA-2 reanalysis products. It is found that isentropic mixing in the stratosphere is modulated by QBO and ENSO. An analysis of the QBO basis function in the multiple regression model reveals that isentropic mixing in the lower stratosphere is suppressed in the equatorial region in the WQBO phase, while the mixing enhances in the subtropical and mid-latitude regions. This result is not consistent with the Holton–Tan mechanism. However, isentropic mixing in the mid-latitudes becomes stronger in the middle stratosphere in the EQBO phase, which agrees well with the Holton–Tan effect. Composite analysis indicates that QBO-induced changes in the direction and speed of the stratospheric zonal wind can affect wave propagation and wave breaking. In the WQBO phase, zonal wind weakens, and a planetary wave is anomalously converging near 30°N, which leads to an increase in isentropic mixing; on the contrary, wind speed becomes large, and the upward propagation of planetary wave divergence, which lead to the isentropic mixing, becomes weak near 60°N. In the EQBO phase, the wind is relatively weak around 60°N, and the isentropic mixing is strong. Multiple regression analysis reveals the ENSO impact on the intensity of isentropic mixing, which shows weak mixing in the middle and high latitudes and strong mixing in the low latitudes of the lower stratosphere in the El Niño years. In the middle stratosphere, isentropic mixing enhances in the mid-latitude region due to intensified upward propagation of planetary waves but weakens in the polar region. Composite analysis reveals a clear relationship between the mixing strength zones of the El Niño and La Niña years with the position of the polar jet and changes in zonal wind speed.

Abstract. Isentropic stirring and mixing are important processes that determine the distribution of long-lived trace gases in the stratosphere. Stirring stretches tracer contours into filaments and mixing dissipates tracer variance. The combined effects on tracer transport by stirring and mixing are quantified by the effective diffusivity in the modified Lagrangian-mean (MLM) theory that diagnoses tracer transport in an areal coordinate. Here a method is developed to diagnose transport processes based on tracer contours in geographic coordinates. Compared to the MLM theory this method has resolving ability along tracer contours and quantifies stirring and mixing separately. Also, the influence of diabatic motion on the diagnosed stirring is reduced, which is useful for stratospheric analysis where diabatic motion is uncertain. The developed method is validated in a methane simulation experiment. The diagnosed stirring effects are consistent with established knowledge about stratospheric dynamics. Finally, stirring and mixing effects on trace gases in the polar vortex are diagnosed during a northern polar vortex period. According to the diagnosis stirring and mixing always increase the methane concentration in the polar vortex. However, their effects are reversed by vortex movement and deformation in most cases. Only in a few cases, planetary waves can penetrate into the vortex and stirring increases the methane concentration in the vortex. The developed method is readily applicable to diagnose stratospheric transport processes from satellite observed trace gas distributions.

The entrainment and detrainment rates are important quantities characterizing airmass exchange between clouds and the environment. One of the challenges in calculating the rates is the need to know the velocity vector of the cloud interface in relation to that of the cloud-free air; however, the interface is not well resolved in most cloud model simulations and so the precise value of the vector is not known. Here a new method is described to approximately calculate mass fluxes across the cloud surface in well-resolved simulations of cumulus convection. The method does away with the need to calculate a cloud interface velocity and instead uses gradients of a defined cloud scalar across the cloud interface. As a result, the entrainment and detrainment rates are expressed as an integration over a small region around the cloud interface. The integrand is composed of the total derivative of the cloud scalar. The new method is applied to large-eddy simulations (LES) of a shallow cumulus case and a deep convection case. Compared to a previous method, the approach described here gives 1.5–2 times smaller exchange rates and shows less noise. The smaller exchange rates are explained as the result of differences in how the two methods correct for the advective contribution to variations of cloud volume. Derived two-dimensional distributions of the exchange rates agree well for both methods. Spatial correlation coefficients are about 0.69–0.88 for entrainment and 0.55–0.78 for detrainment.

Isentropic mixing properties in the stratosphere modeled by the forward calculation of an inverse model (TM5-4DVAR) are evaluated against Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and Microwave Limb Sounder (MLS) observations. The isentropic mixing processes are separated into large-scale stirring described by the "equivalent length" and small-scale diffusion described by the diffusivity. Compared to the measurements, we find that the modeled stirring is not strong enough and that the small-scale diffusivity is too large. TM5-4DVAR produces excessive mixing-induced poleward flux for stratospheric CH4. The flux convergence presents negative biases in the tropics and positive biases in the polar regions. The biases cannot be reduced by improving the horizontal resolution only. Modeled isentropic mixing depends on the horizontal as well as the vertical resolution of the model. An increase in vertical resolution reduces numerical diffusion of the model in the vertical. The decreased vertical diffusion leads to reduction in the modeled isentropic diffusivity. Biases in modeled total column-averaged mixing ratios of CH4 are significant for both models with a coarse vertical resolution of 4 degrees x 6 degrees x 25 (and 2 degrees x 3 degrees x 25, 1 degrees x 1 degrees x 25) and an improved one of 1 degrees x 1 degrees x 40. They are estimated to be 7-14 and 3-7 ppb in the winter extratropics under the assumption that isentropic mixing is dominant over vertical transport on a time scale of 3 days. Correspondingly, resulted biases in inverted CH4 surface emissions are estimated to be 0.5-1 and 0.2-0.5 mg/m(2)/hr, respectively, in the extratropics.

The height of the atmospheric boundary layer ( ABLH) or the mixing layer height ( MLH) is a key parameter characterizing the planetary boundary layer, and the accurate estimation of that is critically important for boundary layer related studies, which include air quality forecasts and numerical weather prediction. Aerosol lidar is a powerful remote sensing instrument frequently used to retrieve the ABLH through detecting the vertical distributions of aerosol concentration. Presently available methods for ABLH determination from aerosol lidar are summarized in this review, including a lot of classical methodologies as well as some improved versions of them. Some new recently developed methods applying advanced techniques such as image edge detection, as well as some new methods based on multi- wavelength lidar systems, are also summarized. Although a lot of techniques have been proposed and have already given reasonable results in several studies, it is impossible to recommend a technique which is suitable in all atmospheric scenarios. More accurate instantaneous ABLH from robust techniques is required, which can be used to estimate or improve the boundary layer parameterization in the numerical model, or maybe possible to be assimilated into the weather and environment models to improve the simulation or forecast of weather and air quality in the future.

Accurate estimation of the atmospheric boundary layer height (ABLH) is critically important and it mainly relies on the detection of the vertical profiles of atmosphere variables (temperature, humidity,’ and horizontal wind speed) or aerosols. Aerosol Lidar is a powerful remote sensing instrument frequently used to retrieve ABLH through the detection of the vertical distribution of aerosol concentration. A challenge is that cloud, residual layer (RL), and local signal structure seriously interfere with the lidar measurement of ABLH. A new objective technique presenting as giving a top limiter altitude is introduced to reduce the interference of RL and cloud layer on ABLH determination. Cloud layers are identified by looking for the rapid increase and sharp attenuation of the signal combined with the relative increase in the signal. The cloud layers whether they overlay the ABL are classified or are decoupled from the ABL are classified by analyzing the continuity of the signal below the cloud base. For cloud layer capping of the ABL, the limiter is determined to be the altitude where a positive signal gradient first occurs above the cloud upper edge. For a cloud that is decoupled from the ABL, the cloud base is considered to be the altitude limiter. For RL in the morning, the altitude limiter is the greatest positive gradient altitude below the RL top. The ABLH will be determined below the top limiter altitude using Haar wavelet (HM) and the curve fitting method (CFM). Besides, the interference of local signal noise is eliminated through consideration of the temporal continuity. While comparing the lidar-determined ABLH by HM (or CFM) and nearby radiosonde measurements of the ABLH, a reasonable concordance is found with a correlation coefficient of 0.94 (or 0.96) and 0.79 (or 0.74), presenting a mean of the relative absolute differences with respect to radiosonde measurements of 10.5% (or 12.3%) and 22.3% (or 17.2%) for cloud-free and cloudy situations, respectively. The diurnal variations in the ABLH determined from HM and CFM on four selected cases show good agreement with a mean correlation coefficient higher than 0.99 and a mean absolute bias of 0.22 km. Also, the determined diurnal ABLH are consistent with surface turbulent kinetic energy (TKE) combined with the time-height distribution of the equivalent potential temperature.

Atmospheric carbon monoxide (CO) and methane (CH4) mole fractions are measured by ground-based in situ cavity ring-down spectroscopy (CRDS) analyzers and Fourier transform infrared (FTIR) spectrometers at two sites (St Denis and Maido) on Reunion Island (21 degrees S, 55 degrees E) in the Indian Ocean. Currently, the FTIR Bruker IFS 125HR at St Denis records the direct solar spectra in the near-infrared range, contributing to the Total Carbon Column Observing Network (TCCON). The FTIR Bruker IFS 125HR at Maido records the direct solar spectra in the mid-infrared (MIR) range, contributing to the Network for the Detection of Atmospheric Composition Change (NDACC). In order to understand the atmospheric CO and CH4 variability on Reunion Island, the time series and seasonal cycles of CO and CH4 from in situ and FTIR (NDACC and TCCON) measurements are analyzed. Meanwhile, the difference between the in situ and FTIR measurements are discussed. The CO seasonal cycles observed from the in situ measurements at Maldo and FTIR retrievals at both St Denis and Maldo are in good agreement with a peak in September-November, primarily driven by the emissions from biomass burning in Africa and South America. The dry-air column averaged mole fraction of CO (X-CO) derived from the FTIR MIR spectra (NDACC) is about 15.7 ppb larger than the CO mole fraction near the surface at Maido, because the air in the lower troposphere mainly comes from the Indian Ocean while the air in the middle and upper troposphere mainly comes from Africa and South America. The trend for CO on Reunion Island is unclear during the 2011-2017 period, and more data need to be collected to get a robust result. A very good agreement is observed in the tropospheric and stratospheric CH4 seasonal cycles between FTIR (NDACC and TCCON) measurements, and in situ and the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite measurements, respectively. In the troposphere, the CH4 mole fraction is high in August-September and low in December-January, which is due to the OH seasonal variation. In the stratosphere, the CH4 mole fraction has its maximum in March-April and its minimum in August-October, which is dominated by vertical transport. In addition, the different CH4 mole fractions between the in situ, NDACC and TCCON CH4 measurements in the troposphere are discussed, and all measurements are in good agreement with the GEOS-Chem model simulation. The trend of X-CH4 is 7.6 +/- 0.4 ppb yr(-1) from the TCCON measurements over the 2011 to 2017 time period, which is consistent with the CH4 trend of 7.4 +/- 0.5 ppb yr(-1) from the in situ measurements for the same time period at St Denis.

Inverse modelling is a useful tool for retrieving CH4 fluxes; however, evaluation of the applied chemical transport model is an important step before using the inverted emissions. For inversions using column data one concern is how well the model represents stratospheric and tropospheric CH4 when assimilating total column measurements. In this study atmospheric CH4 from three inverse models is compared to FTS (Fourier transform spectrometry), satellite and in situ measurements. Using the FTS measurements the model biases are separated into stratospheric and tropospheric contributions. When averaged over all FTS sites the model bias amplitudes (absolute model to FTS differences) are 7.4 ± 5.1, 6.7 ± 4.8, and 8.1 ± 5.5 ppb in the tropospheric partial column (the column from the surface to the tropopause) for the models TM3, TM5-4DVAR, and LMDz-PYVAR, respectively, and 4.3 ± 9.9, 4.7 ± 9.9, and 6.2 ± 11.2 ppb in the stratospheric partial column (the column from the tropopause to the top of the atmosphere). The model biases in the tropospheric partial column show a latitudinal gradient for all models; however there are no clear latitudinal dependencies for the model biases in the stratospheric partial column visible except with the LMDz-PYVAR model. Comparing modelled and FTS-measured tropospheric column-averaged mole fractions reveals a similar latitudinal gradient in the model biases but comparison with in situ measured mole fractions in the troposphere does not show a latitudinal gradient, which is attributed to the different longitudinal coverage of FTS and in situ measurements. Similarly, a latitudinal pattern exists in model biases in vertical CH4 gradients in the troposphere, which indicates that vertical transport of tropospheric CH4 is not represented correctly in the models.

Abstract. The equivalent length, a measure for mixing strength in the atmosphere, in meridional direction in the current application, is used here to investigate the causes of the atmospheric chemistry model (TM3, TM5-4DVAR and LMDz-PYVAR) biases in the stratosphere. Compared to measurements, we find that the modeled surf zone (a strongly stirred region caused by planetary wave breaking in mid-latitude stratosphere in the winter hemisphere), especially in the southern hemisphere, is not strong enough. We assume that this is due to an underestimation of the planetary wave breaking magnitude in the models. Consequently, the region with meridional uniform stratospheric CH4 concentrations has smaller latitudinal coverages in the models than the measurements, especially in the southern hemisphere between June and September. During the southern winter, a region with both vertically and horizontally well mixed CH4 concentrations occur between 450 and 850 K (~ 18 and 30 km) in surf zone latitudes. Such a region is absent in the models, and underestimations of CH4 concentrations within it are visible in comparisons with measured CH4 profiles. The modeled polar vortex breaks too fast and during the vortex period CH4 concentration differences across its barrier are underestimated compared to the measurements.

Abstract. The equivalent length, a measure for mixing strength in the atmosphere, in meridional direction in the current application, is used here to investigate the causes of the atmospheric chemistry model (TM3, TM5-4DVAR and LMDz-PYVAR) biases in the stratosphere. Compared to measurements, we find that the modeled surf zone (a strongly stirred region caused by planetary wave breaking in mid-latitude stratosphere in the winter hemisphere), especially in the southern hemisphere, is not strong enough. We assume that this is due to an underestimation of the planetary wave breaking magnitude in the models. Consequently, the region with meridional uniform stratospheric CH4 concentrations has smaller latitudinal coverages in the models than the measurements, especially in the southern hemisphere between June and September. During the southern winter, a region with both vertically and horizontally well mixed CH4 concentrations occur between 450 and 850 K (~ 18 and 30 km) in surf zone latitudes. Such a region is absent in the models, and underestimations of CH4 concentrations within it are visible in comparisons with measured CH4 profiles. The modeled polar vortex breaks too fast and during the vortex period CH4 concentration differences across its barrier are underestimated compared to the measurements.

The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model–TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH4 fields in place of model simulations improves the model–TCCON XCH4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH4 fields adjusted to ACE-FTS reduces the average XCH4 bias for ACTM (3.3 ppb), but increases the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH4 and, hence, its contribution to XCH4. Therefore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH4 and XCH4.