Atmospheric Grid Research Articles

JWST-TST High Contrast: Spectroscopic Characterization of the Benchmark Brown Dwarf HD 19467 B with the NIRSpec Integral Field Spectrograph

We present the atmospheric characterization of the substellar companion HD 19467 B as part of the pioneering James Webb Space Telescope Guaranteed Time Observer program to obtain moderate resolution spectra (R ∼ 2700, 3–5 μm) of a high-contrast companion with the NIRSpec integral field unit (IFU). HD 19467 B is an old, ∼9 Gyr, companion to a solar-type star with multiple measured dynamical masses. The spectra show detections of CO, CO2, CH4, and H2O. We forward model the spectra using Markov Chain Monte Carlo methods and atmospheric model grids to constrain the effective temperature and surface gravity. We then use NEWERA-PHOENIX grids to constrain nonequilibrium chemistry parameterized by K zz and explore molecular abundance ratios of the detected molecules. We find an effective temperature of 1103 K, with a probable range from 1000 to 1200 K, a surface gravity of 4.50 dex, with a range of 4.14–5.00, and deep vertical mixing, log10(K zz ), of 5.03, with a range of 5.00–5.44. All molecular mixing ratios are approximately solar, leading to a C/O ∼ 0.55, which is expected from a T5.5 brown dwarf. Finally, we calculate an updated dynamical mass of HD 19467 B using newly derived NIRCam astrometry, which we find to be 71.6−4.6+5.3MJup , in agreement with the mass range we derive from evolutionary models, which we find to be 63–75 M Jup. These observations demonstrate the excellent capabilities of the NIRSpec IFU to achieve detailed spectral characterization of substellar companions at high contrast close to bright host stars, in this case at a separation of ∼1.″6 with a contrast of 10−4 in the 3–5 μm range.

Young stellar objects from the LAMOST and ZTF surveys: Physical properties, classification, and light curve analysis

Context. The study of young stellar objects (YSOs) not only enhances our understanding of star formation and stellar evolution, but also contributes to broader areas of astrophysics, including planetary science, galactic dynamics, and astrochemistry. Aims. We aimed to comprehensively analyse 657 YSOs and provide their physical parameter measurements using data from Zwicky Transient Facility (ZTF) g- and r-band light curves and the Gaia, WISE, 2MASS, and LAMOST databases. Specifically, we sought to identify periodicity in the light curves and classify the YSOs based on the Q – M variability plane, which enabled us to quantify flux asymmetry and quasi-periodicity. Methods. To achieve our objectives, we conducted a meticulous examination of the light curves obtained from the ZTF and estimated the physical parameters of the YSOs. These parameters were discerned by integrating stellar model atmosphere grids, photometric data, Gaia DR3 parallaxes, and pre-main-sequence evolutionary tracks. We employed the Q – M variability plane to classify the YSOs and determine the presence of periodic patterns. Additionally, we analysed the distribution of variability slope angles in the colour-magnitude diagram (CMD) to discern patterns associated with extinction-driven and accretion-related variability. Results. Our analysis revealed significant findings regarding the variability patterns and physical characteristics of the YSOs. Among the 657 objects analysed, 37 exhibited periodic variability and 2 displayed multi-period behaviour. Furthermore, we identified distinct variability patterns, including quasi-periodic symmetry, quasi-periodic dipping, aperiodic dipping, bursting behaviour, stochastic variability, and long-timescale variations. Notably, the distribution of variability slope angles in the CMD varied between dippers and bursters, indicating different underlying variability drivers. Additionally, we observed that YSOs classified as classical T Tauri stars and weak-line T Tauri stars exhibited contrasting light curve characteristics, with Class II YSOs displaying asymmetry and Class III YSOs showing (quasi-)periodic variations. These findings underscore the importance of considering variability patterns when classifying and determining the nature of YSOs.

Direct-imaging Discovery of a Substellar Companion Orbiting the Accelerating Variable Star HIP 39017

We present the direct-imaging discovery of a substellar companion (a massive planet or low-mass brown dwarf) to the young, γ Doradus (γ Dor)-type variable star HIP 39017 (HD 65526). The companion’s SCExAO/CHARIS JHK (1.1–2.4 μm) spectrum and Keck/NIRC2 L′ photometry indicate that it is an L/T transition object. A comparison of the JHK+L ′ spectrum to several atmospheric model grids finds a significantly better fit to cloudy models than cloudless models. Orbit modeling with relative astrometry and precision stellar astrometry from Hipparcos and Gaia yields a semimajor axis of 23.8−6.1+8.7 au, a dynamical companion mass of 30−12+31 M J, and a mass ratio of ∼1.9%, properties most consistent with low-mass brown dwarfs. However, its mass estimated from luminosity models is a lower ∼13.8 M J due to an estimated young age (≲115 Myr); using a weighted posterior distribution informed by conservative mass constraints from luminosity evolutionary models yields a lower dynamical mass of 23.6−7.4+9.1 M J and a mass ratio of ∼1.4%. Analysis of the host star’s multifrequency γ Dor-type pulsations, astrometric monitoring of HIP 39017 b, and Gaia Data Release 4 astrometry of the star will clarify the system age and better constrain the mass and orbit of the companion. This discovery further reinforces the improved efficiency of targeted direct-imaging campaigns informed by long-baseline, precision stellar astrometry.

The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios

Disequilibrium chemistry due to vertical mixing in the atmospheres of many brown dwarfs and giant exoplanets is well established. Atmosphere models for these objects typically parameterize mixing with the highly uncertain K zz diffusion parameter. The role of mixing in altering the abundances of C-N-O-bearing molecules has mostly been explored for atmospheres with a solar composition. However, atmospheric metallicity and the C/O ratio also impact atmospheric chemistry. Therefore, we present the Sonora Elf Owl grid of self-consistent cloud-free 1D radiative-convective equilibrium model atmospheres for JWST observations, which includes a variation in K zz across several orders of magnitude and also encompasses subsolar to supersolar metallicities and C/O ratios. We find that the impact of K zz on the T(P) profile and spectra is a strong function of both T eff and metallicity. For metal-poor objects, K zz has large impacts on the atmosphere at significantly higher T eff than in metal-rich atmospheres, where the impact of K zz is seen to occur at lower T eff. We identify significant spectral degeneracies between varying K zz and metallicity in multiple wavelength windows, in particular, at 3–5 μm. We use the Sonora Elf Owl atmospheric grid to fit the observed spectra of a sample of nine early to late T-type objects from T eff = 550–1150 K. We find evidence for very inefficient vertical mixing in these objects, with inferred K zz values lying in the range between ∼101 and 104 cm2 s−1. Using self-consistent models, we find that this slow vertical mixing is due to the observations, which probe mixing in the deep detached radiative zone in these atmospheres.

Representing the Subgrid Surface Heterogeneity of Precipitation in a General Circulation Model

AbstractPrecipitation is highly variable on spatial scales smaller than a typical general circulation model (GCM) grid box. Neglecting this subgrid‐scale variability can impact the simulation of the underlying land surface and its coupling with the atmosphere. In this study we present a scheme to stochastically disaggregate precipitation from an atmospheric grid to an underlying mosaic of surface tiles, using an assumed probability distribution of subgrid precipitation derived from observations. Unlike previous GCM‐based schemes, our approach includes a treatment of memory to allow persistence of subgrid features. In single column model experiments, we demonstrate the ability of the scheme to reproduce observed precipitation statistics at the spatial scale of the surface tiles. The root mean square error of hourly spatial standard deviation of precipitation is reduced from 1.90 to 0.96 mm hr−1 when disaggregation is applied. The scheme increases the spatial standard deviations of surface heat fluxes, soil moisture and temperature, and we show that incorporating memory amplifies these increases by a factor of 2–4. We also document increases in mean precipitation runoff and the Bowen ratio.

Hydrological modelling on atmospheric grids: using graphs of sub-grid elements to transport energy and water

Abstract. Land surface models (LSMs) use the atmospheric grid as their basic spatial decomposition because their main objective is to provide the lower boundary conditions to the atmosphere. Lateral water flows at the surface on the other hand require a much higher spatial discretization as they are closely linked to topographic details. We propose here a methodology to automatically tile the atmospheric grid into hydrological coherent units which are connected through a graph. As water is transported on sub-grids of the LSM, land variables can easily be transferred to the routing network and advected if needed. This is demonstrated here for temperature. The quality of the river networks generated, as represented by the connected hydrological transfer units, are compared to the original data in order to quantify the degradation introduced by the discretization method. The conditions the sub-grid elements impose on the time step of the water transport scheme are evaluated, and a methodology is proposed to find an optimal value. Finally the scheme is applied in an off-line version of the ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) LSM over Europe to show that realistic river discharge and temperatures are predicted over the major catchments of the region. The simulated solutions are largely independent of the atmospheric grid used thanks to the proposed sub-grid approach.

Sensitivity of Ocean Circulation Modeling Results to the Choice of Atmospheric Forcing Data Source and Grid Resolution

Sensitivity of Ocean Circulation Modeling Results to the Choice of Atmospheric Forcing Data Source and Grid Resolution

Modeling Land‐Atmosphere Coupling at Cloud‐Resolving Scale Within the Multiple Atmosphere Multiple Land (MAML) Framework in SP‐E3SM

AbstractRepresenting subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a multiple atmosphere multiple land (MAML) framework in the superparamaterized version of E3SM (SP‐E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud‐resolving scale and their interactions with atmosphere. Comparing to the standard SP‐E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., multiple atmosphere single land (MASL)), the impact of MAML on the strength of land‐atmosphere coupling is limited, partly because the current implementation mainly facilitates one‐way coupling between the cloud‐resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP‐E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (P‐E) is primarily driven by the change in large‐scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P‐E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P‐E by decreasing the NGMS. Finally, future development in the MAML framework is discussed.

Impact of Tropical Cyclone Wind Forcing on the Global Climate in a Fully Coupled Climate Model

Abstract Tropical cyclones (TCs) alter upper-ocean temperature and influence ocean heat content via enhanced turbulent mixing. A better understanding of the role of TCs within the climate system requires a fully coupled modeling framework, where TC-induced ocean responses feed back to the atmosphere and subsequently to the climate mean state and variability. Here, we investigate the impacts of TC wind forcing on the global ocean and the associated feedbacks within the climate system using the fully coupled Community Earth System Model version 1.3 (CESM1.3). Using the low-resolution version of CESM1.3 (1° atmosphere and ocean grid spacing) with no intrinsic TCs, we conduct a suite of sensitivity experiments by inserting TC winds extracted from a high-resolution (0.25° atmosphere grid spacing) TC-permitting simulation into the low-resolution model. Results from the low-resolution TC experiment are compared to a low-resolution control simulation to diagnose TCs’ impact. We found that the added TC winds can increase ocean heat content by affecting ocean vertical mixing, air–sea enthalpy fluxes, and cloud amount. The added TCs can influence mean SST, precipitation, ocean subsurface temperature, and ocean mixed layer depth. We found a strengthening of the wind-driven subtropical cells and a weakening of the Atlantic meridional overturning circulation due to the changes of surface buoyancy fluxes. TCs in the model cause anomalous equatorward ocean heat convergence in the deep tropics and an increase of poleward ocean heat transport out of the subtropics. Our modeling results provide new insights into the multiscale interactions between TCs and the coupled climate system.

Coupled fire-atmosphere simulation of the 2018 Camp Fire using WRF-Fire

Background Accurate simulation of wildfires can benefit pre-ignition mitigation and preparedness, and post-ignition emergency response management. Aims We evaluated the performance of Weather Research and Forecast-Fire (WRF-Fire), a coupled fire-atmosphere wildland fire simulation platform, in simulating a large historic fire (2018 Camp Fire). Methods A baseline model based on a setup typically used for WRF-Fire operational applications is utilised to simulate Camp Fire. Simulation results are compared to high-temporal-resolution fire perimeters derived from NEXRAD observations. The sensitivity of the model to a series of modelling parameters and assumptions governing the simulated wind field are then investigated. Results of WRF-Fire for Camp Fire are compared to FARSITE. Key results Baseline case shows non-negligible discrepancies between the simulated fire and the observations on rate of spread (ROS) and spread direction. Sensitivity analysis results show that refining the atmospheric grid of Camp Fire’s complex terrain improves fire prediction capabilities. Conclusions Sensitivity studies show the importance of refined atmosphere modelling for wildland fire simulation using WRF-Fire in complex terrains. Compared to FARSITE, WRF-Fire agrees better with the observations in terms of fire propagation rate and direction. Implications The findings suggest the need for further investigation of other possible sources of wildfire modelling uncertainties and errors.

Daily precipitation performances of regression-based statistical downscaling models in a basin with mountain and semi-arid climates.

The online version contains supplementary material available at 10.1007/s00477-022-02345-5.

AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model

Abstract. We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing the observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 (Finite-volumE Sea ice–Ocean Model) has the multi-resolution functionality typical of unstructured-mesh models while still featuring a scalability and efficiency similar to regular-grid models. The atmospheric component OpenIFS (CY43R3) enables the use of the latest developments in the numerical-weather-prediction community in climate sciences. In this paper we describe the coupling of the model components and evaluate the model performance on a variable-resolution (25–125 km) ocean mesh and a 61 km atmosphere grid, which serves as a reference and starting point for other ongoing research activities with AWI-CM3. This includes the exploration of high and variable resolution and the development of a full Earth system model as well as the creation of a new sea ice prediction system. At this early development stage and with the given coarse to medium resolutions, the model already features above-CMIP6-average skills (where CMIP6 denotes Coupled Model Intercomparison Project phase 6) in representing the climatology and competitive model throughput. Finally we identify remaining biases and suggest further improvements to be made to the model.

How Do We Optimally Sample Model Grids of Exoplanet Spectra?

The construction and implementation of atmospheric model grids is a popular tool in exoplanet characterization. These typically vary a number of parameters linearly, containing one model for every combination of parameter values. Here we investigate alternative methods of sampling parameters, including random sampling and Latin hypercube (LH) sampling, and how these compare to linearly sampled grids. We use a random forest to analyze the performance of these grids for two different models, as well as investigate the information content of the particular model grid from Goyal et al. (2019). We also use nested sampling to implement mock atmospheric retrievals on simulated James Webb Space Telescope transmission spectra by interpolating on linearly sampled model grids. Our results show that random or LH sampling outperforms linear sampling in parameter predictability for our higher-dimensional models, requiring fewer models in the grid, and thus allowing for more computationally intensive forward models to be used. We also found that using a traditional retrieval with interpolation on a linear grid can produce biased posterior distributions, especially for parameters with nonlinear effects on the spectrum. In particular, we advise caution when performing linear interpolation on the C/O ratio, cloud properties, and metallicity. Finally, we found that the information content analysis of the grid from Goyal et al. (2019) was able to highlight key areas of the spectra where the presence or absence of certain molecules can be detected, providing good indicators for parameters such as temperature and C/O ratio.

On the role of atmospheric simulations horizontal grid spacing for flood modeling

Our study focuses on the hydrologic implications of resolving and modeling atmospheric processes at different spatial scales. Here we use heavy precipitation events from an atmospheric model that was run at different horizontal grid spacings (i.e., 250 m, 500 m, 1 km, 2 km 4 km, and 12 km) and able to resolve different processes. Within an idealized simulation framework, these rainfall events are used as input to an operational distributed hydrologic model to evaluate the sensitivity of the hydrologic response to different forcing grid spacings. We consider the finest scale (i.e., 250 m) as reference, and compute event peak flows and volumes across a wide range of basin sizes. We find that the use of increasingly-coarser inputs leads to changes in the distribution of event peak flows and volumes, with the strongest sensitivity at the smallest catchment sizes. Our results show the compromise between computational cost and hydrologic performance, providing basic information for future endeavors geared towards regional downscaling.

Orographic resolution driving the improvements associated with horizontal resolution increase in the Northern Hemisphere winter mid-latitudes

Abstract. In recent years much attention has been devoted to the investigation of the impact of increasing the horizontal resolution of global climate models. In the present work, a set of atmosphere-only idealized sensitivity simulations with EC-Earth3 has been designed to disentangle the relative roles of increasing the resolution of the resolved orography and of the atmospheric grid. Focusing on the Northern Hemisphere winter, it is shown that if the grid is refined while keeping the resolved orography unchanged, model biases are reduced only on some specific occasions. Conversely, increasing the resolved (or mean) orography is found to clearly reduce several important systematic model errors, including synoptic transient eddies, the North Atlantic jet stream variability, and atmospheric blocking frequency and duration. From an analysis of the radiation budget it is concluded that the large changes in radiative fluxes caused by the resolution increase – something commonly observed in climate models – have a relevant impact on the atmospheric circulation, partially offsetting the benefits obtained from the increase in orographic resolution. These findings point to the necessity of always tuning climate models to fully exploit the benefits of high horizontal resolution.

On the applicability of urban canopy parametrization in building grey zone

AbstractWith increasing interest in urban meteorology and related services, the need to appropriately represent the urban environment in climate/weather models is rising. These regional weather/climate models typically use a km‐scale horizontal grid, which is insufficient to resolve the flow around buildings. Effects of the urban environment on the atmosphere above are represented through a bulk approach using the Urban Canopy Parametrization (UCP) schemes. Existing UCPs usually use the repeating canyon–roof representation that assumes homogeneous distribution of buildings within the grid box. It is commonly accepted that the assumption of homogeneity holds at km‐scale grid resolution but whether it also holds at sub‐km scale, where the regional models are increasingly approaching, is questionable. For this reason, among others, the resolution ranges from a few hundred metres to tens of metres (i.e. building‐resolving scales) is termed the building grey zone in the existing literature. This work shows that the assumption of homogeneity indeed does not hold at the building grey zone for the city‐state Singapore. To understand the possible influences of the use of UCPs at scales from the building grey zone to the conventional mesoscale, we use an urban‐grid method that allows us to estimate the parametrized fluxes from a typical UCP at varying resolutions over the urban landcover while keeping the same atmospheric model grid. Numerical results show that different urban‐grid resolutions yield variations in the near‐surface temperature and wind to a maximum of 0.5 K and 1 m·s−1. Their impact on the boundary‐layer parameters is found to be limited. Although these near‐surface variations are small, they are comparable to the near‐surface scaling variables and are thus physically significant.

Effects of grid spacing on high-frequency precipitation variance in coupled high-resolution global ocean–atmosphere models

High-frequency precipitation variance is calculated in 12 different free-running (non-data-assimilative) coupled high resolution atmosphere–ocean model simulations, an assimilative coupled atmosphere–ocean weather forecast model, and an assimilative reanalysis. The results are compared with results from satellite estimates of precipitation and rain gauge observations. An analysis of irregular sub-daily fluctuations, which was applied by Covey et al. (Geophys Res Lett 45:12514–12522, 2018. https://doi.org/10.1029/2018GL078926) to satellite products and low-resolution climate models, is applied here to rain gauges and higher-resolution models. In contrast to lower-resolution climate simulations, which Covey et al. (2018) found to be lacking with respect to variance in irregular sub-daily fluctuations, the highest-resolution simulations examined here display an irregular sub-daily fluctuation variance that lies closer to that found in satellite products. Most of the simulations used here cannot be analyzed via the Covey et al. (2018) technique, because they do not output precipitation at sub-daily intervals. Thus the remainder of the paper focuses on frequency power spectral density of precipitation and on cumulative distribution functions over time scales (2–100 days) that are still relatively “high-frequency” in the context of climate modeling. Refined atmospheric or oceanic model grid spacing is generally found to increase high-frequency precipitation variance in simulations, approaching the values derived from observations. Mesoscale-eddy-rich ocean simulations significantly increase precipitation variance only when the atmosphere grid spacing is sufficiently fine (< 0.5°). Despite the improvements noted above, all of the simulations examined here suffer from the “drizzle effect”, in which precipitation is not temporally intermittent to the extent found in observations.

Evaluating the Nature and Extent of Changes to Climate Sensitivity Between FGOALS‐g2 and FGOALS‐g3

AbstractEquilibrium climate sensitivity (ECS) and its related feedbacks are important metrics that can be used to measure the global mean surface temperature change in future climate projections, and the cloud feedback (CF) is considered to be the main contributor to ECS uncertainties. However, the use of different CF methods significantly affects the CF amplitudes, and the sign of the CF may also change. Combining the radiative kernel approach with a simplified CF method, the differences in the ECS and associated feedbacks between two versions of the Flexible Global Ocean–Atmosphere–Land System model (i.e., FGOALS‐g2 and FGOALS‐g3) were analyzed. Results show that the ECS of FGOALS‐g3 is smaller than that of FGOALS‐g2 (2.8 vs. 3.3 K). The main feedback processes that contribute to the ECS change in FGOALS‐g3 are the weaker surface albedo feedback and stronger negative shortwave CF. The reduced surface albedo feedback in FGOALS‐g3 can be attributed mainly to the differences in the simulations of sea ice area, surface temperature, and the Atlantic Meridional Overturning Circulation, as well as their interactions, compared with FGOALS‐g2. The enhanced negative shortwave CF in FGOALS‐g3 is directly related to the strengthened feedback of cloud area fraction and liquid water path. Furthermore, these changes can be traced back to the different atmospheric moist processes, parameter tuning, ocean grid, and external forcings used in FGOALS‐g3, as these all affect the mean climate state of the model.

Automated detection and classification of synoptic-scale fronts from atmospheric data grids

Abstract. Automatic determination of fronts from atmospheric data is an important task for weather prediction as well as for research of synoptic-scale phenomena. In this paper we introduce a deep neural network to detect and classify fronts from multi-level ERA5 reanalysis data. Model training and prediction is evaluated using two different regions covering Europe and North America with data from two weather services. We apply label deformation within our loss function, which removes the need for skeleton operations or other complicated post-processing steps as used in other work, to create the final output. We obtain good prediction scores with a critical success index higher than 66.9 % and an object detection rate of more than 77.3 %. Frontal climatologies of our network are highly correlated (greater than 77.2 %) to climatologies created from weather service data. Comparison with a well-established baseline method based on thermodynamic criteria shows a better performance of our network classification. Evaluated cross sections further show that the surface front data of the weather services as well as our network classification are physically plausible. Finally, we investigate the link between fronts and extreme precipitation events to showcase possible applications of the proposed method. This demonstrates the usefulness of our new method for scientific investigations.

Comparative high-resolution spectroscopy of M dwarfs: Exploring non-LTE effects

Context.M dwarfs are key targets for high-resolution spectroscopy and model atmosphere analyses because of the high incidence of these stars in the solar neighbourhood and their importance as exoplanetary hosts. Several methodological challenges make such analyses difficult, leading to significant discrepancies in the published results.Aims.The aim of our work is to compare M dwarf parameters derived by recent high-resolution near-infrared studies with each other and with fundamental stellar parameters. We also assess to what extent deviations from local thermodynamic equilibrium (LTE) for iron and potassium influence the outcome of these studies.Methods.We carry out line formation calculations based on a modern model atmosphere grid appropriate for M dwarfs along with a synthetic spectrum synthesis code that treats formation of atomic and molecular lines in cool-star atmospheres including departures from LTE. We use near-infrared spectra collected with the CRIRES instrument at the ESO VLT as reference observational data.Results.We find that the effective temperatures obtained with spectroscopic techniques in different studies mostly agree to better than 100 K and are mostly consistent with the fundamental temperatures derived from interferometric radii and bolometric fluxes. At the same time, much worse agreement in the surface gravities and metallicities is evident. Significant discrepancies in the latter parameters appear when results of the studies based on the optical and near-infrared observations are intercompared. We demonstrate that non-LTE effects are negligible for Fe Iin M-dwarf atmospheres but are important for K I, which has a number of strong lines in the near-infrared spectra of these stars. These effects, leading to potassium abundance and metallicity corrections on the order of 0.2 dex, may be responsible for some of the discrepancies in the published analyses. Differences in the temperature–pressure structures of the atmospheric models may be another factor contributing to the deviations between the spectroscopic studies, in particular at low metallicities and high effective temperatures.Conclusions.High-resolution spectroscopic studies of M dwarfs are yet to reach the level of consistency and reproducibility typical of similar investigations of FGK stars. Attention should be given to details of the line formation physics as well as input atomic and molecular data. Collecting high-quality spectra with a wide wavelength coverage of M dwarfs with known fundamental parameters is an essential step in benchmarking spectroscopic parameter determination of low-mass stars.