Synergistic studies enhanced through data assimilation: combining multiple retrievals with a Mars Global Circulation Model

2021 ◽  
Author(s):  
James Holmes ◽  
Stephen Lewis ◽  
Manish Patel ◽  
Paul Streeter ◽  
Kylash Rajendran

<div> <p><span data-contrast="auto">The wealth of observations now available from multiple spacecraft in orbit around Mars and rovers/landers on the surface provides information on several aspects of the atmosphere, although they are restricted in space and time. Most of the observational datasets are largely complementary, so an efficient method to combine them in a physically consistent way will lead to more constrained studies of the evolution of the global martian atmosphere. Data assimilation is one such method, combining multiple retrievals with a Mars Global Circulation Model (GCM) while accounting for errors in both sources of information and producing an optimal representation of the evolving martian surface and atmosphere. Data assimilation is a powerful tool in that multiple parameters each observed independently by different instruments (e.g. water vapour, ozone, carbon monoxide, dust opacity, temperature) are all realistically constrained and physically consistent at the same time, and unobserved parameters can also be influenced by assimilated data (e.g. water vapour assimilation will impact on the water ice distribution). It also allows for study of atmospheric features that change significantly between observations and identifying processes that lead to the observed changes.</span><span data-ccp-props="{"335551550":6,"335551620":6}"> </span></p> </div> <div> <p><span data-contrast="auto">Data assimilation studies are prevalent on Earth and are becoming more mainstream for Mars, with several different Mars GCMs now capable of assimilating retrievals using different assimilation schemes. The Open University (OU) ExoMars modelling group Mars GCM has been combined with several retrieval datasets via data assimilation to study features of the ozone, carbon monoxide, water and dust cycles alongside dynamical features such as the polar vortices, surface warming during a global dust storm and planetary waves. OpenMARS (Open access to Mars Assimilated Remote Soundings), a publicly available global reanalysis dataset from 1999-2015, was also created using the OU assimilation system.</span><span data-ccp-props="{"335551550":6,"335551620":6}"> </span></p> </div> <div> <p><span data-contrast="auto">This talk will give a brief overview of the benefits and limitations of data assimilation for Mars, and will demonstrate how combining retrievals of different atmospheric parameters with a Mars GCM via data assimilation leads to a better constrained analysis of the martian atmosphere than is possible with retrievals or GCMs alone.</span><span data-ccp-props="{"335551550":6,"335551620":6}"> </span></p> </div>

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
P. Goswami ◽  
J. Baruah

Concentrations of atmospheric pollutants are strongly influenced by meteorological parameters like rainfall, relative humidity and wind advection. Thus accurate specifications of the meteorological fields, and their effects on pollutants, are critical requirements for successful modelling of air pollution. In terms of their applications, pollutant concentration models can be used in different ways; in one, short term high resolution forecasts are generated to predict and manage urban pollution. Another application of dynamical pollution models is to generate outlook for a given airbasin, such as over a large city. An important question is application-specific model configuration for the meteorological simulations. While a meso-scale model provides a high-resolution configuration, a global model allows better simulation of large-sale fields through its global environment. Our objective is to comparatively evaluate a meso-scale atmospheric model (MM5) and atmospheric global circulation model (AGCM) in simulating different species of pollutants over different airbasins. In this study we consider four locations: ITO (Central Delhi), Sirifort (South Delhi), Bandra (Mumbai) and Karve Road (Pune). The results show that both the model configurations provide comparable skills in simulation of monthly and annual loads, although the skill of the meso-scale model is somewhat higher, especially at shorter time scales.


2016 ◽  
Vol 829 (2) ◽  
pp. 115 ◽  
Author(s):  
João M. Mendonça ◽  
Simon L. Grimm ◽  
Luc Grosheintz ◽  
Kevin Heng

2018 ◽  
Vol 215 (3) ◽  
pp. 1523-1529
Author(s):  
Peter Olson ◽  
Maylis Landeau ◽  
Evan Reynolds

SUMMARY A fundamental assumption in palaeomagnetism is that the geomagnetic field closely approximates a geocentric axial dipole in time average. Here we use numerical dynamos driven by heterogeneous core–mantle boundary heat flux from a mantle global circulation model to demonstrate how mantle convection produces true dipole wander, rotation of the geomagnetic dipole on geologic timescales. Our heterogeneous mantle-driven dynamos show a dipole rotation about a near-equatorial axis in response to the transition in lower mantle heterogeneity from a highly asymmetric pattern at the time of supercontinent Pangea to a more symmetric pattern today. This predicted dipole rotation overlaps with a palaeomagnetically inferred rotation in the opposite direction and suggests that some events previously interpreted as true polar wander also include true dipole wander.


Radiocarbon ◽  
1990 ◽  
Vol 32 (1) ◽  
pp. 37-58 ◽  
Author(s):  
M R Manning ◽  
D C Lowe ◽  
W H Melhuish ◽  
R J Sparks ◽  
Gavin Wallace ◽  
...  

14C measured in trace gases in clean air helps to determine the sources of such gases, their long-range transport in the atmosphere, and their exchange with other carbon cycle reservoirs. In order to separate sources, transport and exchange, it is necessary to interpret measurements using models of these processes. We present atmospheric 14CO2 measurements made in New Zealand since 1954 and at various Pacific Ocean sites for shorter periods. We analyze these for latitudinal and seasonal variation, the latter being consistent with a seasonally varying exchange rate between the stratosphere and troposphere. The observed seasonal cycle does not agree with that predicted by a zonally averaged global circulation model. We discuss recent accelerator mass spectrometry measurements of atmospheric 14CH4 and the problems involved in determining the fossil fuel methane source. Current data imply a fossil carbon contribution of ca 25%, and the major sources of uncertainty in this number are the uncertainty in the nuclear power source of 14CH4, and in the measured value for δ14C in atmospheric methane.


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