MIPAS temperature from the stratosphere to the lower thermosphere: comparison of version vM21 with ACE-FTS, MLS, OSIRIS, SABER, SOFIE and lidar measurements

García‐Comas, M.; Funke, B.; Gardini, A.; López‐Puertas, M.; Jurado-Navarro, Á. Aythami; Clarmann, T. von; Stiller, G. P.; Kiefer, Michael; Boone, Christopher D.; Leblanc, Thierry; Marshall, B. T.; Schwartz, M.; Sheese, Patrick E.

doi:10.5194/amtd-7-6651-2014

Cited by 6 publications

(7 citation statements)

References 21 publications

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“…A detailed description of the new data version is given in García-Comas et al(2023).The noise error for individual profiles of the MIPAS temperature data version V8 T 661 is smaller than 1 K at altitudes below 60 km, 1-3 K at 60-70 km, 3-5 K at 70-90 km, 6-8 K at 90-100 km, 8-12 K at 100-105 km and 12-20 K at 105-115 km. These errors do not exhibit a significant dependence on latitude or season, although they slightly increase around the polar summer mesopause(Garcia-Comas et al, 2014). The systematic errors are generally smaller than 0.7 K below 55 km, 1 K at 60-80 km, 1-2 K at 80-90 km, 3 K at 95 km, 6-8 K at 100 km, 10-20 K at 105 km, and 20-30 K at 115 kmGarcia-Comas et al (2014).Here we use MIPAS data for the period 2008-2011 for both CO 2 and temperature.Data was filtered for quality followingLópez-Puertas et al (2017).…”

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confidence: 85%

“…As for the errors in this dataset, we do not expect them to change significantly from the previous version.For temperature, we used here the MIPAS temperature data version V8 T 661 retrieved from the CO 2 15 µm emission in the Upper Atmosphere (UA) mode(García-Comas et al, 2023). This is an upgrade version of the previous one, V5 T 611, which has been described in detail inGarcia-Comas et al (2014). The new version has been improved in several aspects.…”

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confidence: 99%

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A novel gravity wave transport parametrization for global chemistry climate models: description and validation

Guarino

Gardner

Feng

et al. 2023

Preprint

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The gravity wave drag parametrization of the Whole Atmosphere Community Climate Model (WACCM) has been modified to include the wave-driven atmospheric vertical mixing caused by propagating, non-breaking, gravity waves. The strength of this atmospheric mixing is represented in the model via the ‘effective wave diffusivity’ coefficient (Kwave). Using Kwave, a new total dynamical diffusivity (KDyn) is defined. KDyn represents the vertical mixing of the atmosphere by both breaking (dissipating) and vertically propagating (non-dissipating) gravity waves. Here we show that, when the new diffusivity is used, the downward fluxes of Fe and Na between 80 and 100 km largely increase. Larger meteoric ablation injection rates of these metals (within a factor 2 of measurements) can now be used in WACCM, which produce Na and Fe layers in good agreement with lidar observations. Mesospheric CO2 is also significantly impacted by the additional source of vertical mixing, with the largest CO2 concentration increase occurring between 80-90 km, where model-observation agreement improves. However, in regions where the model overestimates CO2 concentration, the new parametrization exacerbates the model bias. The summer mesopause in both hemispheres cools significantly, by up to 35 K, and shifts upward, partially correcting the WACCM low summer mesopause. Our results highlight the far-reaching implications and the necessity of representing vertically propagating, non-breaking, gravity waves in climate models. This method way of modelling gravity waves contributes to growing evidence that it is time to move away from dissipative-only gravity wave parametrizations.

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confidence: 85%

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confidence: 99%

A novel gravity wave transport parametrization for global chemistry climate models: description and validation

Guarino

Gardner

Feng

et al. 2023

Preprint

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“…According to the simulated spectra based on the forward model, the sensitivity of the emission line to the background temperature is studied. In order to analyze the spectral response to a small temperature disturbance, since the uncertainty of temperature is about 5 K during the night 14 , the input background temperature is disturbed by 5 K, and the simulation range is 80-120 km. As can be seen from figure 11 above, for strong lines (high spectral line intensity) 13098.85 1 cm − and 13100.82 1 cm − , the temperature response is better between tangent height 90 km and 105 km, indicating that this altitude range is more sensitive to temperature.…”

Section: Background Atmospheric Temperaturementioning

confidence: 99%

Forward model for O2 a-band night glow limb radiance in the mesophere and lower thermosphere

Wang,

Luo,

et al. 2023

First International Conference on Spatial Atmospheric Marine Environmental Optics (SAME 2023)

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rotational structure of O2 A-band airglow 5 . At the same time, the change of A-band airglow can be used to study gravity By means of satellite load, the atmospheric temperature in the range of 60-110 km can be obtained by analyzing the band is about 94 km 4 , and during the day, the peak value of airglow is about 85 km. airglow in MLT region cannot reach the ground and can only be observed by spaceborne. At night, the peak value of A-O2 molecules widely existing when transmitted through the atmosphere. Due to this self-absorption effect, the O2 A-band in the atmosphere, and most of O2 molecules are in the ground state, the A-band airglow is absorbed by the ground state is also the studied most in O2 A-band, so A-band usually refers to this (0-0) band. Since O2 is a substance widely existing intensity 3 , and the intensity of (0-0) band is at least one order of magnitude higher than other bands. Therefore, this band composed of different vibration bands, among which O2 A (0-0) band centered at 762 nm has the largest radiation In 1954, Chamberlain et al. firstly observed the airglow radiation of O2 A-band at the same time 2 . O2 A-band airglow is target of passive remote sensing.region. It provides a tracer object for the detection of space atmospheric environment and can be used as the observation phenomena and dynamic processes in this area is still lacking. Airglow is one of the important optical phenomena in this Due to the limited and rare detection targets and new detection technologies, the actual observation of complex optical density in this area is too thin, and the interaction between neutral air molecules and electromagnetic waves is very weak.The regional structure of MLT depends on the interaction of dynamics, radiation and photochemical processes 1 . The The mesosphere and lower atmosphere (MLT) refers to the region in the atmosphere with an altitude of 60 km to 110 km.

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“…The WACCM temperatures were bias-corrected using MIPAS version 5 middle and upper atmosphere measurements, which cover an altitude range of 18-102 km, but are performed less frequently (García-Comas et al, 2014 variables. The a priori of the latter is a zero profile, while the regularisation is of Tikhonov type.…”

Section: A Priori Temperature and Trace Gas Distributionsmentioning

confidence: 99%

IMK/IAA MIPAS temperature retrieval version 8: nominal measurements

Kiefer¹,

Clarmann²,

Funke³

et al. 2020

Preprint

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Abstract. A new global set of atmospheric temperature profiles is retrieved from recalibrated radiance spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Changes with respect to previous data versions include a new radiometric calibration considering the time-dependency of the detector non-linearity, and a more robust frequency calibration scheme. Temperature is retrieved using a smoothing constraint, while tangent altitude pointing information is constrained using optimal estimation. ECMWF ERA-Interim is used as temperature a priori below 43 km. Above, a priori data is based on data from the Whole Atmosphere Community Climate Model Version 4 (WACCM4). Bias-corrected fields from specified dynamics runs, sampled at the MIPAS times and locations, are used, blended with ERA-Interim between 43 and 53 km. Horizontal variability of temperature is considered by scaling an a priori 3D temperature field in the orbit plane in a way that the horizontal structure is provided by the a priori while the vertical structure comes from the measurements. Additional microwindows with better sensitivity at higher altitudes are used. The background continuum is jointly fitted with the target parameters up to 58 km altitude. The radiance offset correction is strongly regularized towards an empirically determined vertical offset profile. In order to avoid the propagation of uncertainties of O3 and H2O a priori assumptions, the abundances of these species are retrieved jointly with temperature. The retrieval is based on HITRAN 2016 spectroscopic data, with a few amendments. Temperature-adjusted climatologies of vibrational populations of CO2 states emitting in the 15 micron region are used in the radiative transfer modelling in order to account for non-local thermodynamic equilibrium. Numerical integration in the radiative transfer model is now performed at higher accuracy. The random component of the temperature uncertainty typically varies between 0.4 and 0.8 K, with occasional excursions up to 1.3 K above 60 km altitude. The leading sources of the random component of the temperature error are measurement noise, gain calibration uncertainty, spectral shift, and uncertain CO2 mixing ratios. The systematic error is caused by uncertainties in spectroscopic data and line shape uncertainties. It ranges from 0.2 K at 24 km altitude for northern midlatitude nighttime conditions to 2.3 K at 12 km for tropical nighttime conditions. The estimated total uncertainty amounts to values between 0.5 K at 24 km and northern polar winter conditions to 2.3 K at 12 km and northern midlatitude day conditions. The vertical resolution varies around 3 km for altitudes below 50 km. The long-term drift encountered in the previous temperature product has been largely reduced. The consistency between high spectral resolution results from 2002–2004 and the reduced spectral resolution results from 2005–2012 has been largely improved. As expected, most pronounced temperature differences between version 8 and previous data versions are found in elevated stratopause situations. The fact that the phase of temperature waves seen by MIPAS is not locked to the wave phase found in ECMWF analyses demonstrates that our retrieval provides independent information and does not merely reproduce the prior information.

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MIPAS temperature from the stratosphere to the lower thermosphere: comparison of version vM21 with ACE-FTS, MLS, OSIRIS, SABER, SOFIE and lidar measurements

Cited by 6 publications

References 21 publications

A novel gravity wave transport parametrization for global chemistry climate models: description and validation

A novel gravity wave transport parametrization for global chemistry climate models: description and validation

Forward model for O2 a-band night glow limb radiance in the mesophere and lower thermosphere

IMK/IAA MIPAS temperature retrieval version 8: nominal measurements

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