Atmospheric Model Intercomparison Project Research Articles

The Summer North Atlantic Oscillation, Arctic sea ice, and Arctic jet Rossby wave forcing.

We use Coupled Model Intercomparison Project Phase 6 (CMIP6) coupled and Atmospheric Model Intercomparison Project (AMIP) climate models, dynamical analyses, and observations to investigate interactions between summer Arctic sea ice concentration (SIC) variations and the Summer North Atlantic Oscillation (SNAO). Observations suggest that SIC-SNAO relationships mainly come from the East Siberian to Arctic Canada (ESAC) region where a weak atmospheric jet stream exists in summer. Twelve CMIP6 models with the most realistic atmospheric climatologies over the North Atlantic and Europe agree well with reanalyses on relationships between SIC and Northern Hemisphere atmospheric circulation. CMIP6 model data indicate that ESAC SIC influences the SNAO with a lead time of several weeks. However, AMIP simulations do not reproduce the observed atmospheric circulation when observed sea ice is prescribed. Rossby wave analyses do though support observed ESAC SIC influences on the SNAO. We conclude that ESAC Arctic SIC modestly influences the SNAO, and such investigations require the use of coupled models.

Impacts of the new UM convection scheme, CoMorph-A, over the Indo-Pacific and Australian regions

A new convection scheme, ‘CoMorph-A’, has been introduced into the latest UK Met Office coupled (GC4) and atmosphere-only (GA8) models. In this study, the impact of CoMorph-A is assessed in atmosphere-only Atmospheric Model Intercomparison Project simulations, as well as in sets of initialised 28-day forecasts with both the coupled and uncoupled models. Initial results show improvements over the Indo-Pacific and northern Australian regions, as well as improvements in the rainfall bias, Madden–Julian Oscillation simulation and prediction, tropical cyclone forecasts and the diurnal cycle of rainfall over the Maritime Continent. The improvements are mostly consistent across the initialised forecasts and the climate simulations, indicating the effectiveness of the new scheme across applications. The use of this new convection scheme is promising for future model configurations, and for improving the simulation and prediction of Australian weather and climate. The UK Met Office is continuing to develop CoMorph and will soon release version B.

Drivers of the mean biases of the tropical atmospheric circulation in a moist static energy framework

In this study, we apply the moist static energy for first baroclinic mode (MSEB) model to examine the drivers of the mean tropical atmospheric circulation biases over oceanic regions. The model diagnoses the vertical motion in an air column of the tropical regions based on net energy heat flux and advection of moisture or heat into the air column in relation to the stability of the air column due to the gradients in moist static energy. Analysis of Coupled Model Intercomparison Project (CMIP) and Atmospheric Model Intercomparison Project (AMIP) simulations helped to identified errors intrinsic to the atmospheric models or errors due to atmosphere–ocean coupling process. Despite some limitations of the MSEB model, our multi-model mean analysis over the entire tropical ocean reveals that the primary drivers of the tropical circulation biases mostly result from intrinsic atmospheric model errors in top of the atmosphere longwave radiation and surface latent heats fluxes, suggesting a link to biases in the hydrological cycle. Oceanic coupling significantly enhanced some of the biases. Biases in the advection of moist static energy also play an important role, while biases in the gross moist stability profiles play only a minor role. Further, we examine the inter-model variations in four main regional large-scale biases (double-ITCZ, Pacific cold tongue, southward shift of ITCZ over the Atlantic, and dipole bias over the Indian Ocean). The analysis suggests that regional bias patterns across general circulation models are primarily driven by coupling errors, except for the bias in the Indian Ocean, which is intrinsic to the atmospheric model but amplified by coupling. Notably, longwave radiation biases at the top of the atmosphere are prevalent among the four bias patterns, as well as biases in moisture advection over the Atlantic. Our results underscore the significant role of net longwave radiation at the top of the atmosphere, an aspect not sufficiently emphasized in previous studies.

Modulation of the Pacific Meridional Mode on the Dipole Pattern of the CONUS Summertime Precipitation

AbstractHistorically, the precipitation trend over the past few decades in the Contiguous United States (CONUS) exhibits a “Dry‐West Wet‐East” pattern; this is manifested by recent droughts/floods in the western/eastern US. However, it remains elusive what atmospheric phenomenon has potentially driven such a remarkable, and impactful precipitation pattern. Here we found that a coupled climate mode—the Pacific Meridional Mode (PMM) exerted strong impacts on the precipitation pattern over the CONUS during the summer season. We discovered a significant association between the PMM index and precipitation across the majority of the CONUS; this was manifested as a zonal dipole pattern—negative correlations in the western U.S. along with positive correlations in the eastern and central U.S. Overall, the physical mechanisms based on observations were supported by using Atmospheric Model Intercomparison Project simulations available from the Coupled Model Intercomparison Project Phase 6.

Extreme Tibetan Plateau cooling caused by tropical volcanism

The extreme cooling of the Tibetan Plateau (TP) during the boreal winter typically poses threats to the local environment and people’s safety, and it is usually attributed to internal climate variability. Here we demonstrate that the five recent large tropical volcanic eruptions since 1880 have caused an average extreme cooling of up to −0.80 K on the TP in observations during the first boreal winter following the eruptions. This cooling effect is much larger than the global average terrestrial cooling of −0.30 K after the eruptions. The multi-model ensemble mean (MME) of the Atmospheric Model Intercomparison Project (AMIP) runs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), in which realistic sea surface temperatures (SST) were specified, can simulate an extreme TP cooling response of up to −0.79 K, which is much larger than the direct aerosol cooling of −0.36 K simulated by the historical runs. The positive North Atlantic Oscillation (NAO) anomaly during the post-eruption winter after the eruptions plays a key role in amplifying the TP cooling through atmospheric teleconnection, which overwhelms the warming response associated with the frequently occurring El Niños. The results from this study provide a perspective on the potential contribution of volcanic activity or stratospheric sulfur injection scenarios to specific TP cooling.

A New GFSv15 With FV3 Dynamical Core Based Climate Model Large Ensemble and Its Application to Understanding Climate Variability, and Predictability

AbstractNOAA Climate Prediction Center (CPC) has generated a 100‐member ensemble of atmospheric model simulations from 1979 to present using the Global Forecast System version 15 (GFSv15) with FV3 dynamical core. The intent of this study is to document a development in an infrastructure capability with a focus to demonstrate the quality of these new simulations is on par with the previous GFSv2 Atmospheric Model Intercomparison Project simulations. These simulations are part of CPC's efforts to attribute observed seasonal climate variability to sea surface temperature (SST) forcings and get updated once a month by available observed SST. The performance of these simulations in replicating observed climate variability and trends, together with an assessment of climate predictability and the attribution of some climate events is documented. A particular focus of the analysis is on the US climate trend, Northern Hemisphere winter height variability, US climate response to three strong El Niño events, the analysis of signal to noise ratio, the anomaly correlation for seasonal climate anomalies, and the South Asian flooding of 2022 summer, and thereby samples wide aspects that are important for attributing climate variability. Results indicate that the new model can realistically reproduce observed climate variability, trends, and extreme events, better capturing the US climate response to extreme El Niño events and the 2022 summer South Asian record‐breaking flooding than GFSv2. The new model also shows an improvement in the wintertime simulation fidelity of US surface climate, mainly confined in the Northern and Southeastern US for precipitation and in the east for temperature.

Dynamical Constraint on Precipitation Biases Over the Indo‐Pacific Region During Boreal Summer in AMIP6 Models

AbstractClimate models suffer from longstanding precipitation biases, much of which has been attributed to their atmospheric component owing to unrealistic parameterizations. Here we investigate precipitation biases in 37 Atmospheric Model Intercomparison Project Phase 6 (AMIP6) models, focusing on the Indo‐Pacific region during boreal summer. These models remain plagued by considerable precipitation biases, especially over regions of strong precipitation. In particular, 22 models overestimate the Asian‐Pacific monsoon precipitation, while 28 models underestimate the southern Indian Ocean Intertropical Convergence Zone precipitation. The inter‐model spread in summer precipitation is decomposed into Empirical Orthogonal Functions (EOFs). The leading EOF mode features an anomalous anticyclone circulation spanning the Indo‐northwest Pacific oceans, which we show is energized by barotropic conversion from the confluence of the background monsoonal westerlies and trade‐wind easterlies. Our results suggest precipitation biases in atmospheric models, though caused by unrealistic parameterizations, are organized by dynamical feedbacks of the mean flow.

Comparison of Short‐Term Cloud Feedbacks at Top of the Atmosphere and the Surface in Observations and AMIP6 Models

AbstractWe compared short‐term cloud feedback, defined at the top of the atmosphere (TOA), the atmospheric column (ATM), and the surface (SFC), between observations and models participating in Atmospheric Model Intercomparison Project Phase 6 (AMIP6) for the period 2000–2014. The globally averaged net cloud feedbacks observed at TOA, ATM, and SFC are −0.06 ± 0.63, −0.17 ± 0.70, and 0.11 ± 0.81 W m−2 K−1, respectively. While most models produced TOA cloud feedbacks that agreed with the observations within uncertainty ranges, the intermodel spread at SFC and within ATM was relatively larger. This demonstrates that models are diverse in how their TOA feedback is distributed between ATM and SFC. Because short‐term cloud feedback is mainly driven by El Niño–Southern Oscillation (ENSO), the global‐mean cloud feedback was further decomposed into components from the ENSO and non‐ENSO regions. Results show that cloud feedback in these two regions tends to be inversely related. Compared to observations, almost all models overestimated the longwave cloud feedback in the ENSO region due to the overestimation of cloud amount changes for high‐topped clouds. For these models, it is the offset between deviations in ENSO and non‐ENSO regions that leads to the overall agreement of global mean with observations. Sensitivity tests show that the main conclusions still hold when alternative kernels are used in estimating cloud feedback.

Decadal modulation of temperature pattern over East Asia by Pacific Decadal Oscillation

The decadal surface air temperature (SAT) variation over East Asia (EA) is characterized by an opposite pattern, warming over the northern EA along with cooling over the southern EA, and vice versa, fluctuating on decadal time scale. We found that Pacific Decadal Oscillation (PDO) has been largely responsible for the opposite decadal SAT variation. Positive (negative) phase of the PDO is related to the northern warming (cooling) and southern cooling (warming) over EA, and the decadal variation of the opposite SAT pattern is highly correlated with the PDO decadal variability, implying a decadal modulation of SAT by PDO. We investigated the influence of PDO on the opposite decadal SAT pattern by employing a dynamical adjustment method based on constructed circulation analogues. The results showed that the PDO associated variability in the large-scale atmospheric circulation over Eurasia, characterized by a dipole structure with cyclonic circulation occupying the northern Eurasia but anticyclonic circulation over the southern Eurasia when in positive PDO phase, is responsible for the opposite decadal SAT pattern. Further analysis on the origin of the anomalous atmospheric circulation was performed by combining observations and climate model simulations. Based on observations and the multi-model simulations of Atmospheric Model Intercomparison Project (AMIP) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we found a contribution of intrinsic atmospheric dynamics, which was further suggested by the results using the Community Atmosphere Model simulations.

Simulation of MJO with improved deep convection scheme in different resolutions of BCC-CSM2 models

AbstractThis study investigates the impacts of modifying the deep convection scheme on the ability to simulate the Madden–Julian Oscillation (MJO) in the Beijing Climate Center Climate System Model version 2 with a medium resolution (BCC-CSM2-T159) and a high resolution (BCC-CSM2-T382). On the basis of the original deep convection scheme, a modified scheme is suggested, which involves the transport processes of deep convective cloud water. The liquid cloud water that is detrained is transferred horizontally to its neighboring grids, and a portion of the cloud water that is horizontally transported is allowed to be transported downward into the lower troposphere. Both BCC-CSM2-T159 and BCC-CSM2-T382 with the modified deep convection scheme perform better than that used the original deep convection scheme in reproducing the major features of the MJO, such as its spectrum, period, intensity, eastward propagation and life cycle. Further analysis shows that those pronounced improvements in the MJO features in both BCC-CSM2-T159 and BCC-CSM2-T382 with the modified scheme are caused by transport processes of deep convective cloud water. The modified deep convection scheme enhances moisture and energy exchange from the lower troposphere to the upper troposphere around convective cloud, and promotes the convergence of moisture in the lower troposphere to the east of the MJO convection center, and then induces eastward propagation of the MJO. The comparisons between the coupled experiments and their corresponding experiments following Atmospheric Model Intercomparison Project (AMIP) simulations indicated that atmosphere–ocean interactions are also important to improve MJO simulations in the models.

Model sensitivity of Tibetan Plateau surface potential vorticity and the Asian summer monsoon system to Asian orographic perturbation in FGOALS-f2

The thermodynamic forcing of the Tibetan Plateau (TP) is important for the regulation of the Asian summer monsoon (ASM). However, the monsoon responses to orographic perturbation simulations show controversial results in previously published literature. One reason for this is that the monsoon responses to orographic forcing differ among climate models. Another reason is that the quantitative changes in the TP thermodynamic forcing remain unknown when the orography is modified. Therefore, the relationship between the TP forcing and the ASM may be different among climate models. In this paper, the surface potential vorticity (SPV) is used to quantify the surface thermodynamic forcing on the TP in the FGOALS-f2 climate model for both the standard Atmospheric Model Intercomparison Project (AMIP) and Coupled Model Intercomparison Project (CMIP) experiments with a modified orography, and various aspects of the ASM responses are also examined. Finally, their relationships with TP-SPV changes are quantitively estimated. The results indicate that the intensity of TP-SPV is reduced by nearly 100% in the AMIP runs, while it is reduced by 68% in the CMIP runs when the Asian mountains are removed. Overall, the responses of the monsoon system are more sensitive when air-sea interactions are considered. When the mountains are removed, the precipitation over the southern slope of the TP decreases by 73% and increases by nearly 30% over the tropical Indian Ocean in the CMIP runs. Moreover, the precipitation responses exhibit the largest difference between the AMIP and CMIP runs over the East Asian and Western Pacific regions. The precipitation over the Western Pacific remains almost unchanged when the orography is removed in the AMIP runs but is reduced by 20% in the CMIP runs. We propose that the calculation of SPV over the TP is helpful for understanding the TP orographic forcing and monsoon dynamics in the future.

A Strengthened Teleconnection of the Quasi‐Biennial Oscillation and Tropical Easterly Jet in the Past Decades in E3SMv1

AbstractThe Energy Exascale Earth System Model version 1 (E3SMv1) is a new global model that can generate a weakened tropical easterly jet (TEJ) during the easterly quasi‐biennial oscillation (EQBO) and a strengthened TEJ during the westerly QBO (WQBO), which is referred to as the QBO‐TEJ teleconnection. Although the longitudinal structure of the QBO‐TEJ teleconnection is different between reanalysis and simulations, we hypothesize that simulations can still provide insights into the observed long‐term changes in the QBO‐TEJ teleconnection. The Atmospheric Model Intercomparison Project historical simulations (AMIP‐historical) generate a strengthened trend in the correlation between the QBO and TEJ indices in the period of 1950–2014 as in reanalysis. The comparison of the AMIP‐historical and the Coupled Model Intercomparison Project coupled historical simulations (coupled‐historical) shows that the warming of the Indian Ocean has played a vital role in the strengthened QBO‐TEJ teleconnection over the past six decades.

A Process Model for ITCZ Narrowing under Warming Highlights Clear-Sky Water Vapor Feedbacks and Gross Moist Stability Changes in AMIP Models

Abstract Tropical areas with mean upward motion—and as such the zonal-mean intertropical convergence zone (ITCZ)—are projected to contract under global warming. To understand this process, a simple model based on dry static energy and moisture equations is introduced for zonally symmetric overturning driven by sea surface temperature (SST). Processes governing ascent area fraction and zonal mean precipitation are examined for insight into Atmospheric Model Intercomparison Project (AMIP) simulations. Bulk parameters governing radiative feedbacks and moist static energy transport in the simple model are estimated from the AMIP ensemble. Uniform warming in the simple model produces ascent area contraction and precipitation intensification—similar to observations and climate models. Contributing effects include stronger water vapor radiative feedbacks, weaker cloud-radiative feedbacks, stronger convection-circulation feedbacks, and greater poleward moisture export. The simple model identifies parameters consequential for the inter-AMIP-model spread; an ensemble generated by perturbing parameters governing shortwave water vapor feedbacks and gross moist stability changes under warming tracks inter-AMIP-model variations with a correlation coefficient ∼0.46. The simple model also predicts the multimodel mean changes in tropical ascent area and precipitation with reasonable accuracy. Furthermore, the simple model reproduces relationships among ascent area precipitation, ascent strength, and ascent area fraction observed in AMIP models. A substantial portion of the inter-AMIP-model spread is traced to the spread in how moist static energy and vertical velocity profiles change under warming, which in turn impact the gross moist stability in deep convective regions—highlighting the need for observational constraints on these quantities. Significance Statement A large rainband straddles Earth’s tropics. Most, but not all, climate models predict that this rainband will shrink under global warming; a few models predict an expansion of the rainband. To mitigate some of this uncertainty among climate models, we build a simpler model that only contains the essential physics of rainband narrowing. We find several interconnected processes that are important. For climate models, the most important process is the efficiency with which clouds move heat and humidity out of rainy regions. This efficiency varies among climate models and appears to be a primary reason for why climate models do not agree on the rate of rainband narrowing.

Better-constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates

Abstract. The best estimate of equilibrium climate sensitivity (ECS) constrained based on the instrumental record of historical warming becomes coherent with other lines of evidence when the dependence of radiative feedback on the pattern of surface temperature change (pattern effect) is incorporated. Pattern effect strength is usually estimated with atmosphere-only model simulations forced with observed historical sea-surface temperature (SST) and sea-ice change and constant pre-industrial forcing. However, recent studies indicate that pattern effect estimates depend on the choice of SST boundary condition dataset, due to differences in the measurement sources and the techniques used to merge and construct them. Here, we systematically explore this dataset dependency by applying seven different observed SST datasets to the MPI-ESM1.2-LR model covering 1871–2017. We find that the pattern effect ranges from -0.01±0.09 to 0.42±0.10 W m−2 K−1 (standard error), whereby the commonly used Atmospheric Model Intercomparison Project II (AMIPII) dataset produces by far the largest estimate. When accounting for the generally weaker pattern effect in MPI-ESM1.2-LR compared to other models, as well as dataset dependency and intermodel spread, we obtain a combined pattern effect estimate of 0.37 W m−2 K−1 [−0.14 to 0.88 W m−2 K−1] (5th–95th percentiles) and a resulting instrumental record ECS estimate of 3.2 K [1.8 to 11.0 K], which as a result of the weaker pattern effect is slightly lower and better constrained than in previous studies.

Changing Characteristics of Tropical Extreme Precipitation–Cloud Regimes in Warmer Climates

In this study, we investigated the changing characteristics of climatic scale (monthly) tropical extreme precipitation in warming climates using the Energy Exascale Earth System Model (E3SM). The results are from Atmospheric Model Intercomparison Project (AMIP)-type simulations driven by (a) a control experiment with the present-day sea surface temperature (SST) and CO2 concentration, (b) P4K, the same as in (a) but with a uniform increase of 4K in the SST globally, and (c) the same as in (a), but with an imposed SST and CO2 concentration from the outputs of the coupled E3SM forced by a 4xCO2 concentration. We found that as the surface warmed under P4K and 4xCO2, both convective and stratiform rain increased. Importantly, there was an increasing fractional contribution of stratiform rain as a function of the precipitation intensity, with the most extreme but rare events occurring preferentially over land more than the ocean, and more so under 4xCO2 than P4K. Extreme precipitation was facilitated by increased precipitation efficiency, reflecting accelerated rates of recycling of precipitation cloud water (both liquid and ice phases) in regions with colder anvil cloud tops. Changes in the vertical profiles of clouds, condensation heating, and vertical motions indicate increasing precipitation–cloud–circulation organization from the control and P4K to 4xCO2. The results suggest that large-scale ocean warming, that is, P4K, was the primary cause contributing to an organization structure resembling the well-known mesoscale convective system (MCS), with increased extreme precipitation on shorter (hourly to daily) time scales. Additional 4xCO2 atmospheric radiative heating and dynamically consistent anomalous SST further amplified the MCS organization under P4K. Analyses of the surface moist static energy distribution show that increases in the surface moisture (temperature) under P4K and 4xCO2 was the key driver leading to enhanced convective instability over tropical ocean (land). However, a fast and large increase in the land surface temperature and lack of available local moisture resulted in a strong reduction in the land surface relative humidity, reflecting severe drying and enhanced convective inhibition (CIN). It is argued that very extreme and rare “record-breaking” precipitation events found over land under P4K, and more so under 4xCO2, are likely due to the delayed onset of deep convection, that is, the longer the suppression of deep convection by CIN, the more severe the extreme precipitation when it eventually occurs, due to the release of a large amount of stored surplus convective available potential energy in the lower troposphere during prolonged CIN.

Comparison of Clouds and Cloud Feedback between AMIP5 and AMIP6

We examine the changes in clouds and cloud feedback between Phase 5 (AMIP5) and Phase 6 (AMIP6) of the Atmospheric Model Intercomparison Project. Each model is perturbed by uniformly increasing the sea surface temperature by 4 K. The simulated cloud fraction, the perturbed states and cloud radiative kernels are used to derive cloud feedback in the shortwave (SW), longwave (LW) and their sum (Net). Compared to AMIP5, the cloud fraction in AMIP6 increases by 9.1%, while the perturbation leads to a 0.25% decrease. The Net cloud feedback at the top of the atmosphere (TOA) is almost double (174%). Statistical tests support that this change is mainly due to an increase in the surface SW cloud feedback caused by optically thick, middle and low clouds. The contribution of the atmospheric Net component (12%) stems from the increase in the atmospheric LW cloud feedback, likely to play a role in weakening (strengthening) the northward (southward) meridional atmospheric energy transport, while the opposite is true for the surface LW and Net cloud feedback in the meridional oceanic energy transport. The substantial increase in cloud feedback at the TOA primarily contributes to the higher climate sensitivity. The cloud feedback spread in AMIP6 is comparable to that in AMIP5.

The Relationship between Model Biases in East Asian Summer Monsoon Rainfall and Land Evaporation

The East Asian Summer Monsoon (EASM) provides the majority of annual rainfall to countries in East Asia. Although state-of-the-art models broadly project increased EASM rainfall, the spread of projections is large and simulations of present-day rainfall show significant climatological biases. Systematic evapotranspiration biases occur locally over East Asia, and globally over land, in simulations both with and without a coupled ocean. This study explores the relationship between evapotranspiration and EASM precipitation biases. First, idealized model simulations are presented in which the parameterization of land evaporation is modified, while sea surface temperature is fixed. The results suggest a feedback whereby excessive evapotranspiration over East Asia results in cooling of land, a weakened monsoon low, and a shift of rainfall from the Philippine Sea to China, further fueling evapotranspiration. Cross-model regressions against evapotranspiration over China indicate a similar pattern of behavior in Atmospheric Model Intercomparison Project (AMIP) simulations. Possible causes of this pattern are investigated. The feedback is not explained by an overly intense global hydrological cycle or by differences in radiative processes. Analysis of land-only simulations indicates that evapotranspiration biases are present even when models are forced with prescribed rainfall. These are strengthened when coupled to the atmosphere, suggesting a role for land-model errors in driving atmospheric biases. Coupled atmosphere-ocean models are shown to have similar evapotranspiration biases to those in AMIP over China, but different precipitation biases, including a northward shift in the ITCZ over the Pacific and Atlantic Oceans.

Exploring the drivers of tropospheric hydroxyl radical trends in the Geophysical Fluid Dynamics Laboratory AM4.1 atmospheric chemistry–climate model

Abstract. We explore the sensitivity of modeled tropospheric hydroxyl (OH) concentration trends to meteorology and near-term climate forcers (NTCFs), namely methane (CH4) nitrogen oxides (NOx=NO2+NO) carbon monoxide (CO), non-methane volatile organic compounds (NMVOCs) and ozone-depleting substances (ODSs), using the Geophysical Fluid Dynamics Laboratory (GFDL)'s atmospheric chemistry–climate model, the Atmospheric Model version 4.1 (AM4.1), driven by emissions inventories developed for the Sixth Coupled Model Intercomparison Project (CMIP6) and forced by observed sea surface temperatures and sea ice prepared in support of the CMIP6 Atmospheric Model Intercomparison Project (AMIP) simulations. We find that the modeled tropospheric air-mass-weighted mean [OH] has increased by ∼5 % globally from 1980 to 2014. We find that NOx emissions and CH4 concentrations dominate the modeled global trend, while CO emissions and meteorology were also important in driving regional trends. Modeled tropospheric NO2 column trends are largely consistent with those retrieved from the Ozone Monitoring Instrument (OMI) satellite, but simulated CO column trends generally overestimate those retrieved from the Measurements of Pollution in The Troposphere (MOPITT) satellite, possibly reflecting biases in input anthropogenic emission inventories, especially over China and South Asia.

Intercomparison of Atmospheric Carbonyl Sulfide (TransCom‐COS; Part One): Evaluating the Impact of Transport and Emissions on Tropospheric Variability Using Ground‐Based and Aircraft Data

AbstractWe present a comparison of atmospheric transport model (ATM) simulations for carbonyl sulfide (COS), within the framework of the atmospheric tracer transport model intercomparison project “TransCom‐COS.” Seven ATMs participated in the experiment and provided simulations of COS mixing ratios over the years 2010–2018, using state‐of‐the‐art surface fluxes for various components of the COS budget: biospheric sink, oceanic source, sources from fire and industry. The main goal of TransCom‐COS is to investigate the impact of the transport uncertainty and emission distribution in simulating the spatio‐temporal variability of tropospheric COS mixing ratios. A control case with seasonal surface fluxes of COS was constructed. The results indicate that the COS mixing ratios are underestimated by at least 50 parts per trillion (ppt) in the tropics, pointing to a missing tropical source. In summer, the mixing ratios are overestimated by at least 50 ppt above 40°N, pointing to a likely missing sink in the high northern latitudes. Regarding the latitudinal profile, the model spread is greater than 60 ppt above 40°N in boreal summer. Regarding the seasonal amplitude, the model spread reaches 50 ppt at 6 out of 15 sites, compared to an observed seasonal amplitude of 100 ppt. All models simulated a too late minimum by at least 2–3 months at two high northern‐latitude sites, likely owing to errors in the seasonal cycle in the ocean emissions. This study highlighted the shortcomings in the COS global budget that need to be resolved before using COS as a photosynthesis tracer.

Subseasonal variability and the “Arctic warming-Eurasia cooling” trend

The “Arctic warming–Eurasia cooling” trend has significantly affected the changes of weather patterns and climate extremes at lower latitudes and has attached huge attentions. However, this winter trend weakened from 2012 to 2021. In the same time period, subseasonal reversals between the warm Arctic–cold Eurasia (WACE) and cold Arctic–warm Eurasia (CAWE) patterns became more frequent and the subseasonal intensity of the WACE/CAWE pattern was still comparable with that from 1996 to 2011. This study highlighted the co-occurrence of this subseasonal variability and trend changes in the WACE/CAWE pattern based on long-term reanalysis datasets and Coupled Model Intercomparison Project Phase 6 simulations. The preceding sea surface temperature anomalies in the tropical Atlantic and Indian oceans had significant primary impacts on the WACE/CAWE pattern in early and late winter, respectively, which were confirmed by numerical experiments based on the Community Atmosphere Model and Atmospheric Model Intercomparison Project. Their coordination worked to effectively modulate the subseasonal phase reversal between the WACE and CAWE patterns just like what happened in the winters of 2020 and 2021. Findings of the present study imply that subseasonal changes need to be considered in the prediction of climate extremes at mid- to low latitudes.