An NWP Model Intercomparison of Surface Weather Parameters in the European Arctic during the Year of Polar Prediction Special Observing Period Northern Hemisphere 1

AbstractIncreased human activity in the Arctic calls for accurate and reliable weather predictions. This study presents an intercomparison of operational and/or high-resolution models in an attempt to establish a baseline for present-day Arctic short-range forecast capabilities for near-surface weather (pressure, wind speed, temperature, precipitation, and total cloud cover) during winter. One global model [the high-resolution version of the ECMWF Integrated Forecasting System (IFS-HRES)], and three high-resolution, limited-area models [Applications of Research to Operations at Mesoscale (AROME)-Arctic, Canadian Arctic Prediction System (CAPS), and AROME with Météo-France setup (MF-AROME)] are evaluated. As part of the model intercomparison, several aspects of the impact of observation errors and representativeness on the verification are discussed. The results show how the forecasts differ in their spatial details and how forecast accuracy varies with region, parameter, lead time, weather, and forecast system, and they confirm many findings from mid- or lower latitudes. While some weaknesses are unique or more pronounced in some of the systems, several common model deficiencies are found, such as forecasting temperature during cloud-free, calm weather; a cold bias in windy conditions; the distinction between freezing and melting conditions; underestimation of solid precipitation; less skillful wind speed forecasts over land than over ocean; and difficulties with small-scale spatial variability. The added value of high-resolution limited area models is most pronounced for wind speed and temperature in regions with complex terrain and coastlines. However, forecast errors grow faster in the high-resolution models. This study also shows that observation errors and representativeness can account for a substantial part of the difference between forecast and observations in standard verification.

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High Resolution Model Intercomparison Project (HighResMIP)

10.5194/gmd-2016-66 ◽

2016 ◽

Cited By ~ 5

Author(s):

R. J. Haarsma ◽

M. Roberts ◽

P. L. Vidale ◽

C. A. Senior ◽

A. Bellucci ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Computational Cost ◽

Horizontal Resolution ◽

Small Scale ◽

Model Intercomparison ◽

Resolution Model ◽

Intercomparison Project ◽

High Resolution Model ◽

The Impact

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest the possibility for significant changes in both large-scale aspects of circulation, as well as improvements in small-scale processes and extremes. However, such high resolution global simulations at climate time scales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centers and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other MIPs. Increases in High Performance Computing (HPC) resources, as well as the revised experimental design for CMIP6, now enables a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the possibility to extend to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulation. HighResMIP thereby focuses on one of the CMIP6 broad questions: “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

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High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

Geoscientific Model Development ◽

10.5194/gmd-9-4185-2016 ◽

2016 ◽

Vol 9 (11) ◽

pp. 4185-4208 ◽

Cited By ~ 220

Author(s):

Reindert J. Haarsma ◽

Malcolm J. Roberts ◽

Pier Luigi Vidale ◽

Catherine A. Senior ◽

Alessio Bellucci ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Computational Cost ◽

Horizontal Resolution ◽

Small Scale ◽

Model Intercomparison ◽

Resolution Model ◽

Intercomparison Project ◽

High Resolution Model ◽

The Impact

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

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Overlapping Interests: The Impact of Geographic Coordinate Assumptions on Limited-Area Atmospheric Model Simulations

Monthly Weather Review ◽

10.1175/mwr-d-12-00351.1 ◽

2013 ◽

Vol 141 (6) ◽

pp. 2120-2127 ◽

Cited By ~ 3

Author(s):

Andrew J. Monaghan ◽

Michael Barlage ◽

Jennifer Boehnert ◽

Cody L. Phillips ◽

Olga V. Wilhelmi

Keyword(s):

Land Use ◽

High Resolution ◽

Input Data ◽

Atmospheric Model ◽

Earth Model ◽

Limited Area ◽

Near Surface ◽

Geographic Coordinate System ◽

Earth Models ◽

The Impact

Abstract There is growing use of limited-area models (LAMs) for high-resolution (<10 km) applications, for which consistent mapping of input terrestrial and meteorological datasets is critical for accurate simulations. The geographic coordinate systems of most input datasets are based on spheroid-shaped (i.e., elliptical) Earth models, while LAMs generally assume a perfectly sphere-shaped Earth. This distinction is often neglected during preprocessing, when input data are remapped to LAM domains, leading to geolocation discrepancies that can exceed 20 km at midlatitudes. A variety of terrestrial (topography and land use) input dataset configurations is employed to explore the impact of Earth model assumptions on a series of 1-km LAM simulations over Colorado. For the same terrestrial datasets, the ~20-km geolocation discrepancy between spheroidal-versus-spherical Earth models over the domain leads to simulated differences in near-surface and midtropospheric air temperature, humidity, and wind speed that are larger and more widespread than those due to using different topography and land use datasets altogether but not changing the Earth model. Simulated differences are caused by the shift of static fields with respect to boundary conditions, and altered Coriolis forcing and topographic gradients. The sensitivity of high-resolution LAM simulations to Earth model assumptions emphasizes the importance for users to ensure terrestrial and meteorological input data are consistently mapped during preprocessing (i.e., datasets share a common geographic coordinate system before remapping to the LAM domain). Concurrently, the modeling community should update preprocessing systems to make sure input data are correctly mapped for all global and limited-area simulation domains.

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Impact of assimilation of radiosonde and UAV observations on numerical weather prediction analyses and forecasts in the Arctic and Antarctic

10.5194/egusphere-egu2020-21750 ◽

2020 ◽

Author(s):

Timo Vihma ◽

Tuomas Naakka ◽

Qizhen Sun ◽

Tiina Nygård ◽

Michael Tjernström ◽

...

Keyword(s):

Wind Speed ◽

Numerical Weather Prediction ◽

Weather Prediction ◽

The Arctic ◽

Observation Site ◽

Near Surface ◽

Numerical Weather ◽

Background Fields ◽

The Impact

Weather forecasting in the Arctic and Antarctic is a challenge above all due to rarity of observations to be assimilated in numerical weather prediction (NWP) models. As observations are expensive and logistically challenging, it is important to evaluate the benefit that additional observations could bring to NWP.Considering the Arctic, in this study the effects of the spatial coverage of the network on numerical weather prediction were evaluated by comparing radiosonde observations from land station taken from Integrated Global Radiosonde Archive (IGRA) and radiosonde observations from expeditions in the Arctic Ocean with operational analyses and background fields (12&#8208;hr forecasts) of the European Centre for Medium Range Weather Forecasts (ECMWF). The focus was on 850 hPa level temperature for the period January 2016 &#8211; September 2018. Comparison of the analyses and background fields showed that radiosoundings had a remarkable impact on improving operational analyses but the impact had a large geographical variation. In particular, radiosonde observations from islands (Jan Mayen and Bear Island) in the northern North Atlantic and from Arctic expeditions substantially improved analyses suggesting that those observations were critical for the quality of analyses and forecasts. Comparison of two cases with and without assimilation of radiosonde sounding data from expeditions of Icebreaker Oden in 2016 and 2018 in the central Artic Ocean showed that satellite observations were not able to compensate for the large spatial gap in the radiosounding network. In the areas where the network is reasonably dense, the density of the sounding network was not the most critical factor for the quality of background fields. Instead, the quality of background field was more related to how radiosonde observations were utilized in the assimilation and to the quality of those observations.Considering the Antarctic, we applied radiosonde sounding and Unmanned Aerial Vehicles (UAV) observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting (Polar WRF) model. Our experiments revealed small or moderate impacts of radiosonde and UAV data assimilation. In any case, the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature, wind speed, and humidity at the observation site for most of the time. Further, the impact on the results of 5-day long Polar WRF experiments was often felt over distances of at least 300 km from the observation site. All experiments succeeded in capturing the main features of the evolution of near-surface variables, but the effects of data assimilation varied between different cases. Due to the limited vertical extent of the UAV observations, the impact of their assimilation was limited to the lowermost 1-2 km layer, and assimilation of radiosonde data was more beneficial for modelled sea level pressure and near-surface wind speed. Considering the perspectives for technological advance, atmospheric soundings applying UAV have a large potential to supplement conventional radiosonde sounding observations.The differences in the results obtained for the Arctic and Antarctic are discussed.

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The impact of shallow stratification on air-sea CO2 flux in the summer Arctic Ocean

10.5194/egusphere-egu21-715 ◽

2021 ◽

Author(s):

Yuanxu Dong ◽

Dorothee Bakker ◽

Thomas Bell ◽

Peter Liss ◽

Ian Brown ◽

...

Keyword(s):

Surface Water ◽

Wind Speed ◽

Sea Ice ◽

Surface Temperature ◽

Arctic Ocean ◽

The Arctic ◽

Near Surface ◽

Ice Melt ◽

The Arctic Ocean ◽

The Impact

Air-sea carbon dioxide (CO2) flux is often indirectly estimated by the bulk method using the in-situ air-sea difference in CO2 fugacity and a wind speed dependent parameterisation of the gas transfer velocity (K). In the summer, sea-ice melt in the Arctic Ocean generates strong shallow stratification with significant gradients in temperature, salinity, dissolved inorganic carbon (DIC) and alkalinity (TA), and thus a near-surface CO2 fugacity &#160;(fCO2w) gradient. This gradient can cause an error in bulk air-sea CO2 flux estimates when the fCO2w is measured by the ship&#8217;s underway system at ~5 m depth. Direct air-sea CO2 flux measurement by eddy covariance (EC) is free from the impact of shallow stratification because the EC CO2 flux does not rely on a fCO2w measurement. In this study, we use summertime EC flux measurements from the Arctic Ocean to back-calculate the sea surface fCO2w and temperature and compare them with the underway measurements. We show that the EC air-sea CO2 flux agrees well with the bulk flux in areas less likely to be influenced by ice melt (salinity > 32). However, in regions with salinity less than 32, the underway fCO2w is higher than the EC estimate of surface fCO2w and thus the bulk estimate of ocean CO2 uptake is underestimated. The fCO2w difference can be partly explained by the surface to sub-surface temperature difference. The EC estimate of surface temperature is lower than the sub-surface water temperature and this difference is wind speed-dependent. Upper-ocean salinity gradients from CTD profiles suggest likely difference in DIC and TA concentrations between the surface and sub-surface water. These DIC and TA gradients likely explain much of the near-surface fCO2w gradient. Accelerating summertime loss of sea ice results in additional meltwater, which enhances near-surface stratification and increases the uncertainty of bulk air-sea CO2 flux estimates in polar regions.

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Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in the EC-Earth global climate model

Geoscientific Model Development ◽

10.5194/gmd-10-1383-2017 ◽

2017 ◽

Vol 10 (3) ◽

pp. 1383-1402 ◽

Cited By ~ 35

Author(s):

Paolo Davini ◽

Jost von Hardenberg ◽

Susanna Corti ◽

Hannah M. Christensen ◽

Stephan Juricke ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Climate Model ◽

Global Climate ◽

Rainfall Variability ◽

Global Climate Model ◽

Small Scale ◽

Low Resolution ◽

The Impact ◽

Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate – specifically the Madden–Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

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Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

Geoscientific Model Development ◽

10.5194/gmd-10-2031-2017 ◽

2017 ◽

Vol 10 (5) ◽

pp. 2031-2055 ◽

Cited By ~ 14

Author(s):

Thomas Schwitalla ◽

Hans-Stefan Bauer ◽

Volker Wulfmeyer ◽

Kirsten Warrach-Sagi

Keyword(s):

High Resolution ◽

Land Surface ◽

Large Scale ◽

Temperature Fields ◽

Surface Model ◽

Limited Area ◽

Data Set ◽

Latitude Belt ◽

Simulated Precipitation ◽

The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

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Numerical simulations of June 7, 2020 convective precipitation over Slovakia using deterministic, probabilistic, and convection-permitting approaches

Időjárás ◽

10.28974/idojaras.2021.4.3 ◽

2021 ◽

Vol 125 (4) ◽

pp. 571-607

Author(s):

André Simon ◽

Martin Belluš ◽

Katarína Čatlošová ◽

Mária Derková ◽

Martin Dian ◽

...

Keyword(s):

Satellite Imagery ◽

Weather Prediction ◽

Severe Weather ◽

Precipitation Forecast ◽

Convective Precipitation ◽

Small Scale ◽

Limited Area ◽

Systematic Effect ◽

The Impact

The paper presented is dedicated to the evaluation of the influence of various improvements to the numerical weather prediction (NWP) systems exploited at the Slovak Hydrometeorological Institute (SHMÚ). The impact was illustrated in a case study with multicell thunderstorms and the results were confronted with the reference analyses from the INCA nowcasting system, regional radar reflectivity data, and METEOSAT satellite imagery. The convective cells evolution was diagnosed in non-hydrostatic dynamics experiments to study weak mesoscale vortices and updrafts. The growth of simulated clouds and evolution of the temperature at their top were compared with the brightness temperature analyzed from satellite imagery. The results obtained indicated the potential for modeling and diagnostics of small-scale structures within the convective cloudiness, which could be related to severe weather. Furthermore, the non-hydrostatic dynamics experiments related to the stability and performance improvement of the time scheme led to the formulation of a new approach to linear operator definition for semi-implicit scheme (in text referred as NHHY). We demonstrate that the execution efficiency has improved by more than 20%. The exploitation of several high resolution measurement types in data assimilation contributed to more precise position of predicted patterns and precipitation representation in the case study. The non-hydrostatic dynamics provided more detailed structures. On the other hand, the potential of a single deterministic forecast of prefrontal heavy precipitation was not as high as provided by the ensemble system. The prediction of a regional ensemble system A-LAEF (ALARO Limited Area Ensemble Forecast) enhanced the localization of precipitation patterns. Though, this was rather due to the simulation of uncertainty in the initial conditions and also because of the stochastic perturbation of physics tendencies. The various physical parameterization setups of A-LAEF members did not exhibit a systematic effect on precipitation forecast in the evaluated case. Moreover, the ensemble system allowed an estimation of uncertainty in a rapidly developing severe weather case, which was high even at very short range.

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Climate SPHINX: evaluating the impact of resolution and stochastic physics parameterisations in climate simulations

10.5194/gmd-2016-115 ◽

2016 ◽

Cited By ~ 5

Author(s):

Paolo Davini ◽

Jost von Hardenberg ◽

Susanna Corti ◽

Hannah M. Christensen ◽

Stephan Juricke ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Rainfall Variability ◽

Pilot Project ◽

Small Scale ◽

Low Resolution ◽

Climate Simulations ◽

Advanced Computing ◽

The Impact ◽

Stochastic Physics

Abstract. The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 km up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979–2008) and a climate change projection (2039–2068), together with coupled transient runs (1850–2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PBytes of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Center (LRZ) in Garching, Germany. About 140 TBytes of post-processed data are stored on the CINECA supercomputing center archives and are freely accessible to the community thanks to an EUDAT Data Pilot project. This paper presents the technical and scientific setup of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given: an improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increases is observed. It is also shown that including stochastic parameterisation in the low resolution runs helps to improve some aspects of the tropical climate – specifically the Madden-Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

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Nitrification of the lowermost stratosphere during the exceptionally cold Arctic winter 2015–2016

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-13681-2019 ◽

2019 ◽

Vol 19 (21) ◽

pp. 13681-13699 ◽

Cited By ~ 1

Author(s):

Marleen Braun ◽

Jens-Uwe Grooß ◽

Wolfgang Woiwode ◽

Sören Johansson ◽

Michael Höpfner ◽

...

Keyword(s):

Nitric Acid ◽

Cross Sections ◽

Large Scale ◽

Potential Temperature ◽

Lagrangian Model ◽

The Arctic ◽

Small Scale ◽

Mixing Ratios ◽

Fine Structures ◽

The Impact

Abstract. The Arctic winter 2015–2016 was characterized by exceptionally low stratospheric temperatures, favouring the formation of polar stratospheric clouds (PSCs) from mid-December until the end of February down to low stratospheric altitudes. Observations by GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) on HALO (High Altitude and LOng range research aircraft) during the PGS (POLSTRACC–GW-LCYCLE II–SALSA) campaign from December 2015 to March 2016 allow the investigation of the influence of denitrification on the lowermost stratosphere (LMS) with a high spatial resolution. Two-dimensional vertical cross sections of nitric acid (HNO3) along the flight track and tracer–tracer correlations derived from the GLORIA observations document detailed pictures of wide-spread nitrification of the Arctic LMS during the course of an entire winter. GLORIA observations show large-scale structures and local fine structures with enhanced absolute HNO3 volume mixing ratios reaching up to 11 ppbv at altitudes of 13 km in January and nitrified filaments persisting until the middle of March. Narrow coherent structures tilted with altitude of enhanced HNO3, observed in mid-January, are interpreted as regions recently nitrified by sublimating HNO3-containing particles. Overall, extensive nitrification of the LMS between 5.0 and 7.0 ppbv at potential temperature levels between 350 and 380 K is estimated. The GLORIA observations are compared with CLaMS (Chemical Lagrangian Model of the Stratosphere) simulations. The fundamental structures observed by GLORIA are well reproduced, but differences in the fine structures are diagnosed. Further, CLaMS predominantly underestimates the spatial extent of HNO3 maxima derived from the GLORIA observations as well as the overall nitrification of the LMS. Sensitivity simulations with CLaMS including (i) enhanced sedimentation rates in case of ice supersaturation (to resemble ice nucleation on nitric acid trihydrate (NAT)), (ii) a global temperature offset, (iii) modified growth rates (to resemble aspherical particles with larger surfaces) and (iv) temperature fluctuations (to resemble the impact of small-scale mountain waves) slightly improved the agreement with the GLORIA observations of individual flights. However, no parameter could be isolated which resulted in a general improvement for all flights. Still, the sensitivity simulations suggest that details of particle microphysics play a significant role for simulated LMS nitrification in January, while air subsidence, transport and mixing become increasingly important for the simulated HNO3 distributions towards the end of the winter.

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