Independent a priori information for reduced intercomparison errors between TROPOMI and TCCON retrievals of methane and carbon monoxide

2020 ◽  
Author(s):  
Johannes Lutzmann ◽  
Ralf Sussmann ◽  
Huilin Chen ◽  
Frank Hase ◽  
Rigel Kivi ◽  
...  
Keyword(s):  
A Priori ◽  
Polar Vortex ◽  
Total Carbon ◽  
Space Agency ◽  
Ongoing Work ◽  
The Status ◽  
Priori Information ◽  
The Moment ◽  
Stratospheric Intrusions

<p>Ground-based column measurements of trace gases by FTIR spectrometers within the Total Carbon Column Observing Network (TCCON) provide accurate ground reference for the validation of the nadir-viewing hyperspectral Tropospheric Monitoring Instrument (TROPOMI) on-board the ESA satellite Sentinel 5 Precursor (S-5P). In such intercomparisons of two independent remote soundings, errors can occur as the a priori profiles used in the respective retrievals are i) differing from each other, and ii) both different from the true atmospheric state at the moment of observation. In certain conditions of atmospheric dynamics, e.g. polar vortex subsidence or stratospheric intrusions, which strongly alter the shape of vertical concentration profiles, these intercomparison errors can become considerable (Ostler et al., 2014).</p><p>In our work funded by the German Space Agency DLR and performed as part of the ESA AO project TCCON4S5P, we search for potential sources of realistic common a priori profiles for S-5P and TCCON CH<sub>4</sub> and CO measurements which reduce these large errors. We examine the performance of a number of chemical transport models and data assimilation systems in reproducing dynamical effects and in minimizing intercomparison errors. In-situ profiles measured by AirCores are used as validation where they are available. We present the status and results of our ongoing work.</p><p>Reference:</p><p>Ostler, A., Sussmann, R., Rettinger, M., Deutscher, N. M., Dohe, S., Hase, F., Jones, N., Palm, M., and Sinnhuber, B.-M.: Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability, Atmos. Meas. Tech., 7, 4081–4101, doi:10.5194/amt-7-4081-2014, 2014. Ostler, A., Sussmann, R., Rettinger, M., Deutscher, N. M., Dohe, S., Hase, F., Jones, N., Palm, M., and Sinnhuber, B.-M.: Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability, Atmos. Meas. Tech., 7, 4081–4101, doi:10.5194/amt-7-4081-2014, 2014.</p>

scholarly journals Validation of first chemistry mode retrieval results from new limb-<i>imaging</i> FTS GLORIA with correlative MIPAS-STR observations

2014 ◽  
Vol 7 (12) ◽  
pp. 12691-12717 ◽  
Author(s):  
W. Woiwode ◽  
O. Suminska-Ebersoldt ◽  
H. Oelhaf ◽  
M. Höpfner ◽  
G. V. Belyaev ◽  
...  
Keyword(s):  
Polar Vortex ◽  
Ongoing Work ◽  
First Results ◽  
Research Aircraft ◽  
Order Of Magnitude ◽  
In Situ Observations ◽  
Field Deployment ◽  
Cross Track ◽  
Stratospheric Clouds

Abstract. We report first chemistry mode retrieval results from the new airborne limb-imaging infrared FTS (Fourier transform spectrometer) GLORIA and comparisons with observations by the conventional airborne limb-scanning infrared FTS MIPAS-STR. For GLORIA, the flights aboard the high-altitude research aircraft M55 Geophysica during the ESSenCe campaign (ESa Sounder Campaign 2011) were the very first in field deployment after several years of development. The simultaneous observations of GLORIA and MIPAS-STR during the flight on 16 December 2011 inside the polar vortex and under the conditions of optically partially transparent polar stratospheric clouds (PSCs) provided us the unique opportunity to compare the observations by two different infrared FTS generations directly. The retrieval results of temperature, HNO3, O3, H2O, CFC-11 and CFC-12 show reasonable agreement of GLORIA with MIPAS-STR and collocated in-situ observations. For the horizontally binned hyperspectral limb-images, the GLORIA sampling outnumbered the horizontal cross-track sampling of MIPAS-STR by up to one order of magnitude. Depending on the target parameter, typical vertical resolutions of 0.5 to 2.0 km were obtained for GLORIA and are typically by factors of 2 to 4 better compared to MIPAS-STR. While the improvement of the performance, characterisation and data processing of GLORIA are subject of ongoing work, the presented first results already demonstrate the considerable gain in sampling and vertical resolution achieved with GLORIA.

A systematic, science-driven approach for predicting subsurface properties

2020 ◽  
Vol 8 (1) ◽  
pp. T167-T181
Author(s):  
Kelly Kathleen Rose ◽  
Jennifer R. Bauer ◽  
MacKenzie Mark-Moser
Keyword(s):  
Language Processing ◽  
A Priori ◽  
Basin Scale ◽  
Porosity And Permeability ◽  
Priori Information ◽  
Efficient Exploration ◽  
Well Data ◽  
Ideal Framework ◽  
Discontinuous Data

As human exploration of the subsurface increases, there is a need for better data- and knowledge-driven methods to improve prediction of subsurface properties. Present subsurface predictions often rely upon disparate and limited a priori information. Even regions with concentrated subsurface exploration still face uncertainties that can obstruct safe and efficient exploration of the subsurface. Uncertainty may be reduced, even for areas with little or no subsurface measurements, using methodical, science-driven geologic knowledge and data. We have developed a hybrid spatiotemporal statistical-geologic approach, subsurface trend analysis (STA), that provides improved understanding of subsurface systems. The STA method assumes that the present-day subsurface is not random, but is a product of its history, which is a sum of its systematic processes. With even limited data and geologic knowledge, the STA method can be used to methodically improve prediction of subsurface properties. To demonstrate and validate the improved prediction potential of the STA method, it was applied in an analysis of the northern Gulf of Mexico. This evaluation was prepared using only existing, publicly available well data and geologic literature. Using the STA method, this information was used to predict subsurface trends for in situ pressure, in situ temperature, porosity, and permeability. The results of this STA-based analysis were validated against new reservoir data. STA-driven results were also contrasted with previous studies. Both indicated that STA predictions were an improvement over other methods. Overall, STA results can provide critical information to evaluate and reduce risks, identify and improve areas of scarce or discontinuous data, and provide inputs for multiscale modeling efforts, from reservoir scale to basin scale. Thereby, the STA method offers an ideal framework for guiding future science-based machine learning and natural language processing to optimize subsurface analyses and predictions.

scholarly journals Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability

2014 ◽  
Vol 7 (12) ◽  
pp. 4081-4101 ◽  
Author(s):  
A. Ostler ◽  
R. Sussmann ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
S. Dohe ◽  
...  
Keyword(s):  
Near Infrared ◽  
A Priori ◽  
Polar Vortex ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Seasonal Cycles ◽  
Stratospheric Intrusion ◽  
Smoothing Effects ◽  
Key Factor ◽  
Source Sink

Abstract. Dry-air column-averaged mole fractions of methane (XCH4) retrieved from ground-based solar Fourier transform infrared (FTIR) measurements provide valuable information for satellite validation, evaluation of chemical-transport models, and source-sink-inversions. In this context, Sussmann et al. (2013) have shown that midinfrared (MIR) soundings from the Network for the Detection of Atmospheric Composition Change (NDACC) can be combined with near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON) without the need to apply an overall intercalibration factor. However, in spite of efforts to reduce a priori impact, some residual seasonal biases were identified, and the reasons behind remained unclear. In extension to this previous work, which was based on multiannual quasi-coincident MIR and NIR measurements from the stations Garmisch (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong (34.41° S, 150.88° E, 30 m a.s.l.), we now investigate upgraded retrievals with longer temporal coverage and include three additional stations (Ny-Ålesund, 78.92° N, 11.93° E, 20 m a.s.l.; Karlsruhe, 49.08° N, 8.43° E, 110 m a.s.l.; Izaña, 28.31° N, 16.45° W, 2.370 m a.s.l.). Our intercomparison results (except for Ny-Ålesund) confirm that there is no overall bias between MIR and NIR XCH4 retrievals, and all MIR and NIR time series reveal a quasi-periodic seasonal bias for all stations, except for Izaña. We find that dynamical variability causes MIR–NIR differences of up to ~ 30 ppb (parts per billion) for Ny-Ålesund, ~ 20 ppb for Wollongong, ~ 18 ppb for Garmisch, and ~ 12 ppb for Karlsruhe. The mechanisms behind this variability are elaborated via two case studies, one dealing with stratospheric subsidence induced by the polar vortex at Ny-Ålesund and the other with a deep stratospheric intrusion event at Garmisch. Smoothing effects caused by the dynamical variability during these events are different for MIR and NIR retrievals depending on the altitude of the perturbation area. MIR retrievals appear to be more realistic in the case of stratospheric subsidence, while NIR retrievals are more accurate in the case of stratosphere–troposphere exchange (STE) in the upper troposphere/lower stratosphere (UTLS) region. About 35% of the FTIR measurement days at Garmisch are impacted by STE, and about 23% of the measurement days at Ny-Ålesund are influenced by polar vortex subsidence. The exclusion of data affected by these dynamical situations resulted in improved agreement of MIR and NIR seasonal cycles for Ny-Ålesund and Garmisch. We found that dynamical variability is a key factor in constraining the accuracy of MIR and NIR seasonal cycles. To mitigate this impact it is necessary to use more realistic a priori profiles that take these dynamical events into account (e.g., via improved models), and/or to improve the FTIR retrievals to achieve a more uniform sensitivity at all altitudes (possibly including profile retrievals for the TCCON data).

scholarly journals Calibration of TCCON column-averaged CO<sub>2</sub>: the first aircraft campaign over European TCCON sites

2011 ◽  
Vol 11 (5) ◽  
pp. 14541-14582 ◽  
Author(s):  
J. Messerschmidt ◽  
M. C. Geibel ◽  
T. Blumenstock ◽  
H. Chen ◽  
N. M. Deutscher ◽  
...  
Keyword(s):  
Fourier Transform ◽  
A Priori ◽  
High Accuracy ◽  
Calibration Factor ◽  
Total Carbon ◽  
Fourier Transform Spectrometer ◽  
Calibration And Validation ◽  
Total Column ◽  
Better Than

Abstract. The Total Carbon Column Observing Network (TCCON) is a ground-based network of Fourier Transform Spectrometer (FTS) sites around the globe, where the column abundances of CO2, CH4, N2O, CO and O2 are measured. CO2 is constrained with a precision better than 0.25 %. To achieve a similarly high accuracy, calibration to World Meteorological Organization (WMO) standards is required. This paper introduces the first aircraft calibration campaign of five European TCCON sites and a mobile FTS instrument. A series of WMO standards in-situ profiles were obtained over European TCCON sites via aircraft and compared with retrievals of CO2 column amounts from the TCCON instruments. The results of the campaign show that the FTS measurements are consistently biased 1.0 % ± 0.2 % low with respect to WMO standards, in agreement with previous TCCON calibration campaigns. The standard a priori profile for the TCCON FTS retrievals is shown to not add a bias. The same calibration factor is generated using aircraft profiles as a priori and with the TCCON standard a priori. With a calibration to WMO standards, the highly precise TCCON CO2 measurements of total column concentrations provide a suitable database for the calibration and validation of nadir-viewing satellites.

scholarly journals Intercomparison of arctic XH<sub>2</sub>O observations from three ground-based Fourier transform infrared networks and application for satellite validation

2021 ◽  
Vol 14 (3) ◽  
pp. 1993-2011
Author(s):  
Qiansi Tu ◽  
Frank Hase ◽  
Thomas Blumenstock ◽  
Matthias Schneider ◽  
Andreas Schneider ◽  
...  
Keyword(s):  
Fourier Transform ◽  
A Priori ◽  
Fourier Transform Infrared ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Satellite Validation ◽  
Ftir Spectrometer ◽  
Priori Information ◽  
Good Agreement

Abstract. In this paper, we compare column-averaged dry-air mole fractions of water vapor (XH2O) retrievals from the COllaborative Carbon Column Observing Network (COCCON) with retrievals from two co-located high-resolution Fourier transform infrared (FTIR) spectrometers as references at two boreal sites, Kiruna, Sweden, and Sodankylä, Finland, from 6 March 2017 to 20 September 2019. In the framework of the Network for the Detection of Atmospheric Composition Change (NDACC), an FTIR spectrometer is operated at Kiruna. The H2O product derived from these observations has been generated with the MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) processor. In Sodankylä, a Total Carbon Column Observing Network (TCCON) spectrometer is operated, and the official XH2O data as provided by TCCON are used for this study. The datasets are in good overall agreement, with COCCON data showing a wet bias of (49.20±58.61) ppm ((3.33±3.37) %, R2=0.9992) compared with MUSICA NDACC and (56.32±45.63) ppm ((3.44±1.77) %, R2=0.9997) compared with TCCON. Furthermore, the a priori H2O volume mixing ratio (VMR) profiles (MAP) used as a priori information in the TCCON retrievals (also adopted for COCCON retrievals) are evaluated with respect to radiosonde (Vaisala RS41) profiles at Sodankylä. The MAP and radiosonde profiles show similar shapes and a good linear correlation of integrated XH2O, indicating that MAP is a reasonable approximation of the true atmospheric state and an appropriate choice for the scaling retrieval methods as applied by COCCON and TCCON. COCCON shows a reduced dry bias (−14.96 %) in comparison with TCCON (−19.08 %) with respect to radiosonde XH2O. Finally, we investigate the quality of satellite data at high latitudes. For this purpose, the COCCON XH2O is compared with retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) generated with the MUSICA processor (MUSICA IASI) and with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). Both paired datasets generally show good agreement and similar correlations at the two sites. COCCON measures 4.64 % less XH2O at Kiruna and 3.36 % less at Sodankylä with respect to MUSICA IASI, whereas COCCON measures 9.71 % more XH2O at Kiruna and 7.75 % more at Sodankylä compared with TROPOMI. Our study supports the assumption that COCCON also delivers a well-characterized XH2O data product. This emphasizes that this approach might complement the TCCON network with respect to satellite validation efforts. This is the first published study where COCCON XH2O has been compared with MUSICA NDACC and TCCON retrievals and has been used for MUSICA IASI and TROPOMI validation.

scholarly journals A simple empirical model estimating atmospheric CO<sub>2</sub> background concentrations

2012 ◽  
Vol 5 (6) ◽  
pp. 1349-1357 ◽  
Author(s):  
M. Reuter ◽  
M. Buchwitz ◽  
O. Schneising ◽  
F. Hase ◽  
J. Heymann ◽  
...  
Keyword(s):  
A Priori ◽  
Total Carbon ◽  
A Priori Information ◽  
Background Concentrations ◽  
Simulation Experiments ◽  
Real Time Processing ◽  
Potential Applications ◽  
Scanning Imaging ◽  
Priori Information ◽  
Simple Empirical Model

Abstract. A simple empirical CO2 model (SECM) is presented to estimate column-average dry-air mole fractions of atmospheric CO2 (XCO2) as well as mixing ratio profiles. SECM is based on a simple equation depending on 17 empirical parameters, latitude, and date. The empirical parameters have been determined by least squares fitting to NOAA's (National Oceanic and Atmospheric Administration) assimilation system CarbonTracker version 2010 (CT2010). Comparisons with TCCON (total carbon column observing network) FTS (Fourier transform spectrometer) measurements show that SECM XCO2 agrees quite well with reality. The synthetic XCO2 values have a standard error of 1.39 ppm and systematic station-to-station biases of 0.46 ppm. Typical column averaging kernels of the TCCON FTS, a SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY), and two GOSAT (Greenhouse gases Observing SATellite) XCO2 retrieval algorithms have been used to assess the smoothing error introduced by using SECM profiles instead of CT2010 profiles as a priori. The additional smoothing error amounts to 0.17 ppm for a typical SCIAMACHY averaging kernel and is most times much smaller for the other instruments (e.g. 0.05 ppm for a typical TCCON FTS averaging kernel). Therefore, SECM is well suited to provide a priori information for state-of-the-art ground-based (FTS) and satellite-based (GOSAT, SCIAMACHY) XCO2 retrievals. Other potential applications are: (i) near real-time processing systems (that cannot make use of models like CT2010 operated in delayed mode), (ii) "CO2 proxy" methods for XCH4 retrievals (as correction for the XCO2 background), and (iii) observing system simulation experiments especially for future satellite missions.

scholarly journals Calibration of TCCON column-averaged CO<sub>2</sub>: the first aircraft campaign over European TCCON sites

2011 ◽  
Vol 11 (21) ◽  
pp. 10765-10777 ◽  
Author(s):  
J. Messerschmidt ◽  
M. C. Geibel ◽  
T. Blumenstock ◽  
H. Chen ◽  
N. M. Deutscher ◽  
...  
Keyword(s):  
Fourier Transform ◽  
A Priori ◽  
High Accuracy ◽  
Calibration Factor ◽  
Total Carbon ◽  
Fourier Transform Spectrometer ◽  
Calibration And Validation ◽  
Total Column ◽  
Better Than

Abstract. The Total Carbon Column Observing Network (TCCON) is a ground-based network of Fourier Transform Spectrometer (FTS) sites around the globe, where the column abundances of CO2, CH4, N2O, CO and O2 are measured. CO2 is constrained with a precision better than 0.25% (1-σ). To achieve a similarly high accuracy, calibration to World Meteorological Organization (WMO) standards is required. This paper introduces the first aircraft calibration campaign of five European TCCON sites and a mobile FTS instrument. A series of WMO standards in-situ profiles were obtained over European TCCON sites via aircraft and compared with retrievals of CO2 column amounts from the TCCON instruments. The results of the campaign show that the FTS measurements are consistently biased 1.1% ± 0.2% low with respect to WMO standards, in agreement with previous TCCON calibration campaigns. The standard a priori profile for the TCCON FTS retrievals is shown to not add a bias. The same calibration factor is generated using aircraft profiles as a priori and with the TCCON standard a priori. With a calibration to WMO standards, the highly precise TCCON CO2 measurements of total column concentrations provide a suitable database for the calibration and validation of nadir-viewing satellites.

scholarly journals On the consistency of methane isotopologue retrievals using TCCON and multiple spectroscopic databases

2020 ◽  
Author(s):  
Edward Malina ◽  
Ben Veihelmann ◽  
Dietrich G. Feist ◽  
Isamu Morino
Keyword(s):  
Atlantic Ocean ◽  
Water Vapour ◽  
Spectral Range ◽  
Cross Sections ◽  
A Priori ◽  
Total Carbon ◽  
A Priori Information ◽  
Ascension Island ◽  
Spectroscopic Database ◽  
Priori Information

Abstract. In this study we perform retrievals of the two main methane isotopologues 12CH4 and 13CH4 using measurements from the Total Carbon Column Observing Network (TCCON) from two sites, namely Ascension Island in the Atlantic Ocean and Tsukuba, Japan. Using the TCCON GGG2014 retrieval environment retrievals are performed using four separate spectroscopic databases and a set of spectral fit windows. Databases used include the TCCON spectroscopic database; the HITRAN2016 database; the GEISA2015 database; and the ESA SEOM-IAS database. We assess the retrievals using standard TCCON methane windows, and specific windows (in the 4190–4340 cm-1 range) based on the sensitivity of the instruments TROPOMI present on Copernicus Sentinel-5P (S5P) and the future Sentinel 5 (S5) mission present on MetOp-SG. We assess the biases in retrieving methane isotopologues using these different spectral windows and different spectroscopic databases. The sensitivity of these retrievals (across windows and databases) to errors in the a priori information, specifically pressure, temperature, methane and water vapour are also assessed. We find significant biases between retrievals calculated using differing spectroscopic databases and windows for both methane isotopologues, with up to a 3 % bias between 12CH4 retrievals and 20 % bias in 13CH4 retrievals. Retrievals using the 4190–4340 cm-1 spectral range show the results with the least variation between spectroscopic databases, and we therefore recommend that this band should be used in future TCCON methane retrievals. Results obtained with the SEOM-IAS database show the lowest fit residuals. Uncertainty on 13CH4 retrievals are relatively high (0.1–2 ppb, combination of systematic and random). The sensitivity to a priori assumptions are shown to be significant for both 12CH4 and 13CH4. Uncertainty in the pressure cross sections is shown to be the most significant, with variations across all spectroscopic databases and spectral windows.

scholarly journals A Drift Indication of Unearthing in Face Detection and Feature Extraction

2019 ◽  
Vol 9 (1) ◽  
pp. 6288-6293
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Face Detection ◽  
Large Range ◽  
A Priori ◽  
A Priori Information ◽  
Extraction Techniques ◽  
The Face ◽  
Priori Information ◽  
The Moment

Nowadays analysis of research on face recognition has explored to extracting auxiliary data from varied biometric techniques like fingerprints, face, iris, palm, voice etc. Research on face recognition, face detection and feature extraction has a long history, and even may be derived back to the nineteenth century. However, the first face detection in the main reckons on a priori information of bound folks and might not free itself from human intervention. Until the looks of highspeed, superior computers, the face detection methodology makes a big burst through. Face detection has been a quick growing, difficult and fascinating space in real time applications. Facial detection and feature extraction becomes an interesting research topic. A large range of face detection and feature extraction algorithms are developed in last decades. In this paper a shot is created to review a good vary of strategies used for face recognition comprehensively. This paper contributes a huge survey of varied face detection and feature extraction techniques. At the moment, there are loads of face detection and feature extraction techniques and algorithms found and developed round the world

scholarly journals Multi-station intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability

2014 ◽  
Vol 7 (7) ◽  
pp. 6743-6790
Author(s):  
A. Ostler ◽  
R. Sussmann ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
S. Dohe ◽  
...  
Keyword(s):  
Near Infrared ◽  
A Priori ◽  
Polar Vortex ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Seasonal Cycles ◽  
Stratospheric Intrusion ◽  
Smoothing Effects ◽  
Key Factor ◽  
Source Sink

Abstract. Dry-air column-averaged mole fractions of methane (XCH4) retrieved from ground-based solar Fourier transform infrared (FTIR) measurements provide valuable information for satellite validation, evaluation of chemistry-transport models, and source-sink-inversions. In this context, Sussmann et al. (2013) have shown that mid-infrared (MIR) soundings from the Network for the Detection of Atmospheric Composition Change (NDACC) can be combined with near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON) without the need to apply an overall intercalibration factor. However, in spite of efforts to reduce a priori impact, some residual seasonal biases were identified, and the reasons behind remained unclear. In extension to this previous work, which was based on multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong (34.41° S, 150.88° E, 30 m a.s.l.), we now investigate upgraded retrievals with longer temporal coverage and include three additional stations (Ny-Ålesund, 78.92° N, 11.93° E, 20 m a.s.l.; Karlsruhe, 49.08° N, 8.43° E, 110 m a.s.l.; Izaña, 28.31° N, 16.45° W, 2.370 m a.s.l.). Our intercomparison results (except for Ny-Ålesund) confirm that there is no overall bias between MIR and NIR XCH4 retrievals, and all MIR and NIR time series reveal a quasi-periodic seasonal bias for all stations, except for Izaña. We find that dynamical variability causes MIR–NIR differences of up to ~ 30 ppb for Ny-Ålesund, ~ 20 ppb for Wollongong, ~ 18 ppb for Garmisch, and ~ 12 ppb for Karlsruhe. The mechanisms behind this variability are elaborated via two case studies, one dealing with stratospheric subsidence induced by the polar vortex at Ny-Ålesund and the other with a deep stratospheric intrusion event at Garmisch. Smoothing effects caused by the dynamical variability during these events are different for MIR and NIR retrievals depending on the altitude of the perturbation area. MIR retrievals appear to be more realistic in the case of stratospheric subsidence, while NIR retrievals are more accurate in the case of stratosphere-troposphere exchange (STE) in the upper troposphere/lower stratosphere (UTLS) region. About 35% of the FTIR measurement days at Garmisch are impacted by STE, and about 23% of the measurement days at Ny-Ålesund are influenced by polar vortex subsidence. The exclusion of data affected by these dynamical situations resulted in improved agreement of MIR and NIR seasonal cycles for Ny-Ålesund and Garmisch. We found that dynamical variability is a key factor in constraining the accuracy of MIR and NIR seasonal cycles. The only way to avoid this problem is to use more realistic a priori profiles that take these dynamical events into account (e.g. via improved models), and/or to improve the FTIR retrievals to achieve a more uniform sensitivity at all altitudes (possibly including profile retrievals for the TCCON data).

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