scholarly journals Ground-based infrared mapping of H2O2 on Mars near opposition

2019 ◽  
Vol 627 ◽  
pp. A60 ◽  
Author(s):  
T. Encrenaz ◽  
T. K. Greathouse ◽  
S. Aoki ◽  
F. Daerden ◽  
M. Giuranna ◽  
...  

We pursued our ground-based seasonal monitoring of hydrogen peroxide on Mars using thermal imaging spectroscopy, with two observations of the planet near opposition, in May 2016 (solar longitude Ls = 148.5°, diameter = 17 arcsec) and July 2018 (Ls = 209°, diameter = 23 arcsec). Data were recorded in the 1232–1242 cm−1 range (8.1 μm) with the Texas Echelon Cross Echelle Spectrograph (TEXES) mounted at the 3 m Infrared Telescope Facility (IRTF) at the Mauna Kea Observatories. As in the case of our previous analyses, maps of H2O2 were obtained using line depth ratios of weak transitions of H2O2 divided by a weak CO2 line. The H2O2 map of April 2016 shows a strong dichotomy between the northern and southern hemispheres, with a mean volume mixing ratio of 45 ppbv on the north side and less than 10 ppbv on the south side; this dichotomy was expected by the photochemical models developed in the LMD Mars Global Climate Model (LMD-MGCM) and with the recently developed Global Environmental Multiscale (GEM) model. The second measurement (July 2018) was taken in the middle of the MY 34 global dust storm. H2O2 was not detected with a disk-integrated 2σ upper limit of 10 ppbv, while both the LMD-MGCM and the LEM models predicted a value above 20 ppbv (also observed by TEXES in 2003) in the absence of dust storm. This depletion is probably the result of the high dust content in the atmosphere at the time of our observations, which led to a decrease in the water vapor column density, as observed by the PFS during the global dust storm. GCM simulations using the GEM model show that the H2O depletion leads to a drop in H2O2, due to the lack of HO2 radicals. Our result brings a new constraint on the photochemistry of H2O2 in the presence of a high dust content. In parallel, we reprocessed the whole TEXES dataset of H2O2 measurements using the latest version of the GEISA database (GEISA 2015). We recently found that there is a significant difference in the H2O2 line strengths between the 2003 and 2015 versions of GEISA. Therefore, all H2O2 volume mixing ratios up to 2014 from TEXES measurements must be reduced by a factor of 1.75. As a consequence, in four cases (Ls around 80°, 100°, 150°, and 209°) the H2O2 abundances show contradictory values between different Martian years. At Ls = 209° the cause seems to be the increased dust content associated with the global dust storm. The inter-annual variability in the three other cases remains unexplained at this time.

2021 ◽  
Vol 48 (7) ◽  
Author(s):  
Loïc Rossi ◽  
Margaux Vals ◽  
Franck Montmessin ◽  
François Forget ◽  
Ehouarn Millour ◽  
...  

Author(s):  
Fengjun Jin ◽  
Akio Kitoh ◽  
Pinhas Alpert

Water cycle components over the Mediterranean for both a current run (1979–2007) and a future run (2075–2099) are studied with the Japan Meteorological Agency’s 20 km grid global climate model. Results are compared with another study using the Coupled Model Intercomparison Project Phase 3 ensemble model (hereafter, the Mariotti model). Our results are surprisingly close to Mariotti’s. The projected mean annual change rates of precipitation ( P ) between the future and the current run for sea and land are −11 per cent and −10 per cent, respectively, which are not as high as Mariotti’s. Projected changes for evaporation ( E ) are +9.3 per cent and −3.6 per cent, compared with +7.2 per cent and −8.1 per cent in Mariotti’s study, respectively. However, no significant difference in the change in P – E over the sea body was found between these two studies. The increased E over the eastern Mediterranean was found to be higher than that in the western Mediterranean, but the P decrease was lower. The net moisture budget, P – E , shows that the eastern Mediterranean will become even drier than the western Mediterranean. The river model suggests decreasing water inflow to the Mediterranean of approximately 36 per cent (excluding the Nile).


2021 ◽  
Author(s):  
Francisco González-Galindo ◽  
Jean-Yves Chaufray ◽  
Franck Lefèvre ◽  
Franck Montmessin ◽  
Margaux Vals ◽  
...  

<p>The thermal escape of hydrogen from Mars is recognized as one of the major drivers of the long-term climatic evolution of the planet. Recent works have shown that, contrary to what was previously believed, water is not trapped in the lower atmosphere of Mars. Instead, it can be transported to the middle/upper atmosphere, producing layers of supersaturated water (Fedorova et al., 2018, 2021). Upper atmospheric water can then be converted to hydrogen by photolysis or chemical reactions with ions, boosting the rate of hydrogen escape (Chaffin et al., 2017; Stone et al., 2020). Strong seasonal variations in the escape rate, and significant increases of both the water abundance in the mesosphere and the hydrogen escape rate during dust storms, evidence the strong coupling between the hydrogen escape and the water cycle (Chaffin et al., 2014; Fedorova et al., 2018, 2020). A global model able to simulate all the processes related to water, from the ice sublimation to the transport to the upper atmosphere and its atmospheric escape, is needed in order to help interpreting the observations. This model can also be used to explore also the water cycle and hydrogen escape on past Mars conditions characterized by different orbital parameters, allowing for a better estimation of the accumulated escape rate.</p> <p>Previous simulations with the LMD-Mars Global Climate Model (LMD-MGCM), and their comparison with observational results by SPICAM/Mars Express showed that the simulated escape rate was underestimated, in particular during the second half of the Martian year (Chaufray et al., 2021). However, those simulations did not take into account the microphysical processes producing water supersaturation, and thus underestimated the role of water transport in the escape rate. In addition, the model did not include the photochemistry of water-derived ions, which can play an important role in converting water into hydrogen (Stone et al., 2020).</p> <p>New simulations with an improved version of the LMD-MGCM have been produced that overcome those previous limitations. The water cloud microphysics has now been fully considered in the simulations, using the model by Navarro et al. (2014). The photochemical model has been updated to include water-derived ions (H2O+, H3O+, OH+). Also, the deuterium fractionation model has been improved (Rossi et al., 2021), and deuterated species have been included in the photochemical model. While this last modification is not expected to modify the hydrogen escape rate, the inclusion of deuterated species can provide important diagnostics on the hydrogen escape and its accumulation over Mars history.</p> <p>In this presentation we will show the results of the improved version of the LMD-MGCM, comparing with available observations. The focus will be on the predicted hydrogen escape rate, and how it is affected by the inclusion of different physical processes. We find that including the possibility of water supersaturation increases the Hydrogen escape rate in more than one order of magnitude at most seasons, taking the simulated rate to better agreement with SPICAM observations during the second half of the year. This confirms previous observational results indicating the importance of water supersaturation (Fedorova et al. 2020). We also find that the inclusion of water-derived ions in the photochemistry also increases the escape rate, in particular during the first part of the year. We will also compare the predicted water abundance in the mesosphere with Mars Express and ExoMars TGO observations, and the abundances of water-derived ions with NGIMS/MAVEN measurements.</p> <p>References:</p> <p>Chaffin, M. et al., Unexpected variability of Martian hydrogen escape, Geophysical Research Letters, Volume 41, pp. 314-320 (2014)</p> <p>Chaffin, M. et al., Elevated atmospheric escape of atomic hydrogen from Mars induced by high-altitude water, Nature Geoscience, 10, pp. 174-178 (2017)</p> <p>Fedorova, A. et al., Water vapor in the middle atmosphere of Mars during the 2007 global dust storm, Icarus, 300, pp. 440-457 (2018)</p> <p>Fedorova, A. et al., Stormy water on Mars: The distribution and saturation of atmospheric water during the dusty season, Science, 367, pp. 297-300 (2020)</p> <p>Fedorova, A. et al., Multi-Annual Monitoring of the Water Vapor Vertical Distribution on Mars by SPICAM on Mars Express, Journal of Geophysical Research: Planets, 126, e06616 (2021)</p> <p>Navarro, T. et al., Global climate modeling of the Martian water cycle with improved microphysics and radiatively active water ice clouds, Journal of Geophysical Research: Planets, 119, pp. 1479-1495 (2014)</p> <p>Rossi, L. et al., The Effect of the Martian 2018 Global Dust Storm on HDO as Predicted by a Mars Global Climate Model, Geophysical Research Letters, 48, e90962 (2021)</p> <p>Stone, S. et al., Hydrogen escape from Mars is driven by seasonal and dust storm transport of water,Science, 370, pp. 824-831 (2020)</p>


1996 ◽  
Author(s):  
Larry Bergman ◽  
J. Gary ◽  
Burt Edelson ◽  
Neil Helm ◽  
Judith Cohen ◽  
...  

2010 ◽  
Vol 10 (14) ◽  
pp. 6527-6536 ◽  
Author(s):  
M. A. Brunke ◽  
S. P. de Szoeke ◽  
P. Zuidema ◽  
X. Zeng

Abstract. Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003–2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that CloudSat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP~h9) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP~h2) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Zmax>−15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h~LWP1/2). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20° S, 85° W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20° S, 75° W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface.


2009 ◽  
Vol 29 (1) ◽  
pp. 94-101 ◽  
Author(s):  
Heiko Goelzer ◽  
Anders Levermann ◽  
Stefan Rahmstorf

2012 ◽  
Vol 43 (3) ◽  
pp. 215-230 ◽  
Author(s):  
Manish Kumar Goyal ◽  
C. S. P. Ojha

We investigate the performance of existing state-of-the-art rule induction and tree algorithms, namely Single Conjunctive Rule Learner, Decision Table, M5 Model Tree, Decision Stump and REPTree. Downscaling models are developed using these algorithms to obtain projections of mean monthly precipitation to lake-basin scale in an arid region in India. The effectiveness of these algorithms is evaluated through application to downscale the predictand for the Lake Pichola region in Rajasthan state in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (1) the National Centre for Environmental Prediction (NCEP) reanalysis dataset for the period 1948–2000 and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001–2100. M5 Model Tree algorithm was found to yield better performance among all other learning techniques explored in the present study. The precipitation is projected to increase in future for A2 and A1B scenarios, whereas it is least for B1 and COMMIT scenarios using predictors.


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