ASSIMILATION OF TEMPERATURES AND COLUMN DUST OPACITIES MEASURED BY EXOMARS TGO-ACS-TIRVIM DURING THE MY34 GLOBAL DUST STORM. R. M. B. Young, Department of Physics & National Space Science and Technology Center, United Arab Emirates University, Al Ain, United Arab Emirates (roland.young@uaeu.ac.ae), E. Millour, S. Guerlet, F. Forget, Laboratoire de Météorologie Dynamique, Jussieu, Paris, France, N. Ignatiev, A. V. Grigoriev, A. V. Shakun, A. Trokhimovskiy, O. Korablev, Space Research Institute (IKI), 84/32 Profsoyuznaya, 117997 Moscow, Russia, F. Montmessin, LATMOS/IPSL, UVSQ Université Paris-Saclay, UPMC Univ. Paris 06, CNRS, Guyancourt, France. members to assimilate atmospheric temperature profiles and column dust optical depth measurements retrieved from TIRVIM radiance spectra between Ls = 182.3 − 211.4◦ of MY34. ACS assimilation TuTD+CuC, MY34. Temperature (K) at p = 30.00 Pa, LMST 15h, 1 sol smoothing (acs091) 135 380 185 400 410 MY34 Ls (degree) 195 200 155 155 155 175 205 215 145 225 225 1516 55 165 380 205 390 400 410 190 assimilated as a function of (top) Local True Solar Time and latitude, and (bottom) MY34 Ls and Local True Solar Time. We use the Laboratoire de Météorologie Dynamique Mars Global Climate Model (LMD Mars GCM, Forget et al., 1999) and the Local Ensemble Transform Kalman Filter (LETKF, Hunt et al., 2007) with 36 ensemble 62.92 60 50 40 30 20 10 0 0.00 4 380 390 50 40 50 10 10 70 70 420 4 m2 kg 1) 86.04 60 50 40 30 20 10 0 0.00 Dust DSO (10 10 410 60 60 50 20 400 MY34 Sol number 50 60 60 40 50 5040 40 50 60 Dust DSO (10 50 40 20 60 40 50 20 10 10 10 30 90 30 20 40 10 10 10 60 Fig. 1. Number of atmospheric temperature retrievals 30 20 10 10 50 210 0 30 60 205 210 60 30 420 205 60 195 200 MY34 Ls (degree) MY34 Ls (degree) 195 200 190 50 190 410 MCS. Dust DSO at MCS wavelength 21.6Solmnumber (10 4 m2 s 1) at p = 30.00 Pa, LMST 15h MY34 185 70 185 400 10 10 60 0 390 20 30 30 0 380 10 200 40 50 4050 30 20 40 400 4 40 60 600 8 30 90 Latitude 12 30 50 Number of profiles / retrievals 800 210 30 0 90 1000 16 30 60 1200 205 10 60 420 20 240.3 225 210 195 180 165 150 135 140.6 m2 kg 1) 185 30 90 20 410 420 MY34 Ls (degree) 195 200 50 MY34 Sol number 400 Temperature (K) 19 185 0 40 390 0 210 165 175 185 215 5 185 155 155 155 Temperature (K) 145 30 380 8 of temperature 12 16 20 24 Number Local True Solar Timeprofiles (hour) (total = 312741) 420 205 234.1 225 210 195 180 165 150 135 130.1 ACS assimilation TuTD+CuC, MY34. Dust DSO at MCS wavelength 21.6Solmnumber (10 4 m2 kg 1) at p = 30.00 Pa, LMST 15h, 1 sol smoothing (acs091) MY34 Latitude 4 22 5 195 MCS. Temperature at pnumber = 30.00 Pa, LMST 15h MY34(K)Sol 60 0 225 155 165 175 190 30 90 200 60 155 390 185 60 400 30 Local True Solar Time (hour) Latitude Number of profiles / retrievals 0 30 165 145 175 Latitude (degree) 600 5 22 60 165 185 215 22 5 195 225 30 90 210 135 175 205 30 0 205 135 155 145 60 800 30 24 155 90 60 MY34 Ls (degree) 195 200 190 145 225 Latitude 60 90 90 185 90 175 Between March 2018 and December 2019 the ExoMars Trace Gas Orbiter Atmospheric Chemistry Suite Thermal Infrared channel (TIRVIM) made nadir observations of the Martian atmosphere, measuring atmospheric and surface temperatures as well as column-integrated opacities of dust and water ice over the full 24-hour range of local times. At the beginning of this period, a global dust storm (GDS) occurred during Mars Year 34 (Kass et al. 2019). To understand the meteorology of this dust storm, in particular those atmospheric properties that cannot be measured directly, such as wind, we make use of data assimilation to synthesise observations of Mars during this period a numerical simulation. Numberwith of temperature profiles (total = 312741) Fig. 2. Hovmöller diagrams at 30 Pa at 3 PM Local Mean Solar Time showing, from top to bottom: temperature analysis, MCS observations, dust density-scaled opacity analysis, MCS dust density-scaled opacity observations. The model forecasts the atmospheric state every three hours, mapping the temperature forecast to the observation locations and times by using the retrieval averaging kernel matrix and prior to ensure a like-for-like 1 100 15 3 4 1 2 60.0 40 40.0 25 20 20.0 10 25 30 5 60 35 40 102 42.6 80.0 4 20 101 103 3 2 1 5 80 0 2520 20 5 Dust DSO at 21.6 m (10 4 m2 kg 1) Pressure (Pa) 10 2 Pseudo-altitude above 610 Pa (km) 10 0.0 0.0 we assimilated temperature profiles to update the model temperature, and column dust opacities to update the dust column and hence the dust profiles. In run TuTDCuD we did the same as TuT-CuD but also updated the dust profiles (first) based on the Kalman gain for temperature. TuTD-CuC surface pressure at Curiosity location Mean error = 10.2 Pa, RMS error = 11.7 Pa 4 2 5 7075 80 0 90 95985 80 60 6570 40.0 20 20.0 0 0.0 0.0 0 30 60 90 Latitude MCS dust DSO at 21.6 m, 03+/-1h LMST, MY34 sol = 416.00-420.00 10 2 100 42 4 2 2 10 20 101 80 60 60.0 40 40.0 20 20.0 40 30 102 2 4 0 103 90 60 30 0 30 Latitude 60 0.0 0.0 90 Fig. 3. Vertical section through the dust density-scaled opacity field at 3 AM local time at 21.6 µm, averaged over MY34 sols 416–420, at the peak of the Global Dust Storm. Top is the TuTD-CuD analysis, middle is the GCM ensemble, and bottom are the MCS observations. The assimilation period began about 5 Ls before the onset of the GDS, and ended shortly after its peak (just before a long gap in the observations). We ran four configurations of the assimilation and model. In run TuTD we assimilated temperature profiles and used them to update the model temperature, as well as dust profiles under certain conditions, by using the Kalman gain for temperature (Navarro et al., 2017). In run TuT-CuD 381 382 383 384 12 18 Local True Solar Time (hrs) 24 40 0 40 80 6 TuTD-CuC surface pressure at Curiosity location Mean error = 7.1 Pa, RMS error = 14.6 Pa 900 53.1 80.0 Pseudo-altitude above 610 Pa (km) 1 750 0 30 2 Pressure (Pa) 10 60 65 40 Surface pressure (Pa) 5 90 0 20 1 60.0 800 80 206.5 207.0 MY34 Ls (degree) 207.5 208.0 208.5 850 800 750 700 416 417 418 419 420 12 18 Local True Solar Time (hrs) 24 Surface pressure diurnal with diurnal mean removed MY34cycle Sol number 80 Residual pressure (Pa) 15 103 50 253045 54 10 102 3 15 60 Dust DSO at 21.6 m (10 4 m2 kg 1) 101 1 187.0 Surface pressure diurnal with diurnal mean removed MY34cycle Sol number Residual pressure (Pa) 100 98.3 80.0 Dust DSO at 21.6 m (10 4 m2 kg 1) 1 80 Pseudo-altitude above 610 Pa (km) Pressure (Pa) 10 2 40 35 10 186.5 850 700 380 90 60 30 0 30 60 90 GCM MY34 (acs089), 03h LMST, MY34 sols 416.00-420.00, Ls = 206.44-208.93 Latitude MY34 Ls (degree) 185.5 186.0 185.0 900 Surface pressure (Pa) comparison between forecast and observations (Rodgers & Connor, 2003). The observations used are shown in Fig.TuTD-CuC 1. (acs091), 03h LMST, MY34 sols 416.00-420.00, Ls = 206.44-208.93 40 0 40 80 0 6 Fig. 4. Time series and diurnal cycle of surface pres- sure at the Curiosity rover location. Time series are corrected for surface elevation using the pressure scale height based on the temperature at 1 km altitude, and the diurnal cycle is averaged over the corresponding 4-sol period and has the running diurnal mean removed. From top to bottom: Time series and diurnal cycle for analysis TuTD-CuD before the onset of the GDS, (sols 380–384); time series and diurnal cycle for analysis TuTD-CuD at the peak of the GDS (sols 416–420). In all three cases we used the Kalman gain from the temperature assimilation to update the surface pressure and horizontal velocities. Finally, we ran an ensemble of GCM simulations constrained by column dust optical depth maps based on MCS dust observations (Montabone et al., 2020), the so-called “MY34 dust scenario”. We verified our analyses against in-sample TIRVIM measurements and independent MCS temperature and dust profiles. Figure 2 shows the TuTD-CuD analysis compared with independent MCS temperature and dust retrievals at 30 Pa. Our reanalysis matched the MCS vertical dust distribution at the peak of the storm particularly well during night-time (Fig. 3). By reconstructing the atmospheric wind field via the assimilation process, we found that at the peak of the storm a strong asymmetry develops in the mid-latitude jets, and the diurnal and semi-diurnal tides change significantly. Finally, we verified the surface pressure analysis against independent Curiosity observations; the diurnal cycle at the Curios- ity location (corrected for the surface elevation in the model) is shown in Fig. 4. The work summarised in this abstract is currently under review (Young et al., 2022). References F. Forget et al. (1999), JGR, 104, 24155–24175. B. R. Hunt et al. (2007), Physica D, 230, 112. D. M. Kass et al. (2019), GRL, 46, e2019GL083931. L. Montabone et al. (2020), JGR, 125, e2019JE006111. T. Navarro et al. (2017) , ESS, 4, 690. C. D. Rodgers & B. J. Connor (2003), JGR, 108, 4116. R. M. B. Young et al. (2022), submitted.