We present here the thermal structure of the upper atmosphere of Venus predicted by a full self-consistent Venus General Circulation Model (VGCM) developed at Laboratoire de MMeteorologie Dynamique (LMD) and… Click to show full abstract
We present here the thermal structure of the upper atmosphere of Venus predicted by a full self-consistent Venus General Circulation Model (VGCM) developed at Laboratoire de MMeteorologie Dynamique (LMD) and extended up to the thermosphere of the planet. Physical and photochemical processes relevant at those altitudes, plus a non-orographic GW parameterisation, have been added. All those improvements make the LMD-VGCM the only existing ground-to-thermosphere 3D model for Venus: a unique tool to investigate the atmosphere of Venus and to support the exploration of the planet by remote sounding. The aim of this paper is to present the model reference results, to describe the role of radiative, photochemical and dynamical effects in the observed thermal structure in the upper mesosphere/lower thermosphere of the planet. The predicted thermal structure shows a succession of warm and cold layers, as recently observed. A cooling trend with increasing latitudes is found during daytime at all altitudes, while at nighttime the trend is inverse above about 110 km, with an atmosphere up to 15 K warmer towards the pole. The latitudinal variation is even smaller at the terminator, in agreement with observations. Below about 110 km, a nighttime warm layer whose intensity decreases with increasing latitudes is predicted by our GCM. A comparison of model results with a selection of recent measurements shows an overall good agreement in terms of trends and order of magnitude. Significant data-model discrepancies may be also discerned. Among them, thermospheric temperatures are about 40-50 K colder and up to 30 K warmer than measured at terminator and at nighttime, respectively. The altitude layer of the predicted mesospheric local maximum (between 100 and 120 km) is also higher than observed. Possible interpretations are discussed and several sensitivity tests performed to understand the data-model discrepancies and to propose future model improvements.
               
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