Mars' Annular Polar Vortex

2020 ◽  
Author(s):  
Emily Ball ◽  
Dann Mitchell ◽  
William Seviour ◽  
Geoffrey Vallis ◽  
Stephen Thomson
Keyword(s):  
Data Assimilation ◽  
Potential Vorticity ◽  
Local Minimum ◽  
Climate Model ◽  
Polar Vortex ◽  
Hadley Circulation ◽  
Martian Atmosphere ◽  
Barotropic Instability ◽  
Reanalysis Dataset ◽  
Radiation Scheme

<p><span>The Martian winter polar vortex </span><span>has recently been shown to be</span><span> annular in nature, with a local minimum in potential vorticity near the pole. This suggests barotropic instability, yet the vortex is remarkably persistent. It has been shown that its annular nature may be due to the release of latent heat from CO</span><span>2</span><span> condensation, CO<sub>2</sub> clouds, changes in dust distributions, and the strength of the Hadley circulation circulation, with many of these being interlinked</span><span>.</span><span> In this poster, we present </span><span>results </span><span>using the the Mars Analysis Correction Data Assimilation (MACDA) reanalysis dataset, which demonstrates clearly the annular vortex. Additionally</span><span>, we perform simulations of the Martian atmosphere and its response to varying topography and radiation scheme in the flexible Isca framework, a climate model capable of simulating the Martian basic state at varying levels of complexity. It is noted that the strength of the Martian polar vortex is significantly lower in Isca simulations than in the MACDA dataset. Through further simulations with Isca, we aim to investigate the effect of CO</span><span>2</span><span> condensation on the strength and shape of the Martian polar vortex.</span></p>

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
Keyword(s):  
Carbon Monoxide ◽  
Data Assimilation ◽  
Water Vapour ◽  
Circulation Model ◽  
Martian Atmosphere ◽  
Sources Of Information ◽  
Global Circulation Model ◽  
Martian Surface ◽  
Reanalysis Dataset ◽  
Global Circulation

<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>

scholarly journals Planetary waves in a coupled chemistry-climate model: analysis techniques and comparison with reanalysis data

2005 ◽  
Vol 5 (3) ◽  
pp. 2559-2598
Author(s):  
F. Mager ◽  
M. Dameris
Keyword(s):  
Large Scale ◽  
Vertical Structure ◽  
Climate Model ◽  
Polar Vortex ◽  
Reanalysis Data ◽  
Planetary Waves ◽  
Transient Waves ◽  
Reanalysis Dataset ◽  
Analysis Techniques ◽  
The Impact

Abstract. This paper presents several analysis techniques relating to large-scale atmospheric waves. Such analysis tools allow the extraction of planetary waves from reanalysis or model datasets, and can contribute to a detailed insight into the forcing, propagation, and vertical structure of planetary waves, and their dynamic impact on the atmosphere. The different tools presented here use time series of space Fourier coefficients in order to extract transient and stationary wave parts by zonal wavenumbers, and to quantify their dynamic effect in the form of sensible heat and momentum fluxes. In this work, they have been applied to model results from the coupled chemistry-climate model ECHAM4.L39(DLR)/CHEM (E39/C) (Hein et al., 2001) and to the ERA-15 reanalysis dataset from ECMWF. We show that E39/C qualitatively matches the variance distribution and vertical structure of transient waves from reanalysis data; quantitative differences can be traced back to the horizontal model resolution and the modelled zonal winds. The modelled polar vortex during Northern Hemisphere winter has previously been shown to be colder and more stable than observed (Hein et al., 2001; Schnadt et al., 2002; a possible explanation is that in the model experiment, a reduced heat flux by long transient waves at high latitudes disturbs and warms the polar vortex less than ERA-15 suggests, thereby leading to an overestimated stationary wavenumber 1 in E39/C. The results show that the tools used are well suited to investigate and estimate the impact of various dynamic processes related to large-scale waves.

scholarly journals The Diurnal Variation in Stratospheric Ozone from MACC Reanalysis, ERA-Interim, WACCM, and Earth Observation Data: Characteristics and Intercomparison

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 625
Author(s):  
Ansgar Schanz ◽  
Klemens Hocke ◽  
Niklaus Kämpfer ◽  
Simon Chabrillat ◽  
Antje Inness ◽  
...  
Keyword(s):  
Diurnal Variation ◽  
Climate Model ◽  
Stratospheric Ozone ◽  
Polar Vortex ◽  
Model Systems ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Observation Data ◽  
High Latitudes ◽  
Free Running

In this study, we compare the diurnal variation in stratospheric ozone of the MACC (Monitoring Atmospheric Composition and Climate) reanalysis, ECMWF Reanalysis Interim (ERA-Interim), and the free-running WACCM (Whole Atmosphere Community Climate Model). The diurnal variation of stratospheric ozone results from photochemical and dynamical processes depending on altitude, latitude, and season. MACC reanalysis and WACCM use similar chemistry modules and calculate a similar diurnal cycle in ozone when it is caused by a photochemical variation. The results of the two model systems are confirmed by observations of the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) experiment and three selected sites of the Network for Detection of Atmospheric Composition Change (NDACC) at Mauna Loa, Hawaii (tropics), Bern, Switzerland (midlatitudes), and Ny-Ålesund, Svalbard (high latitudes). On the other hand, the ozone product of ERA-Interim shows considerably less diurnal variation due to photochemical variations. The global maxima of diurnal variation occur at high latitudes in summer, e.g., near the Arctic NDACC site at Ny-Ålesund, Svalbard. The local OZORAM radiometer observes this effect in good agreement with MACC reanalysis and WACCM. The sensed diurnal variation at Ny-Ålesund is up to 8% (0.4 ppmv) due to photochemical variations in summer and negligible during the dynamically dominated winter. However, when dynamics play a major role for the diurnal ozone variation as in the lower stratosphere (100–20 hPa), the reanalysis models ERA-Interim and MACC which assimilate data from radiosondes and satellites outperform the free-running WACCM. Such a domain is the Antarctic polar winter where a surprising novel feature of diurnal variation is indicated by MACC reanalysis and ERA-Interim at the edge of the polar vortex. This effect accounts for up to 8% (0.4 ppmv) in both model systems. In summary, MACC reanalysis provides a global description of the diurnal variation of stratospheric ozone caused by dynamics and photochemical variations. This is of high interest for ozone trend analysis and other research which is based on merged satellite data or measurements at different local time.

Downscaling of precipitation on a lake basin: evaluation of rule and decision tree induction algorithms

2012 ◽  
Vol 43 (3) ◽  
pp. 215-230 ◽  
Author(s):  
Manish Kumar Goyal ◽  
C. S. P. Ojha
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Lake Basin ◽  
Monthly Precipitation ◽  
M5 Model Tree ◽  
Reanalysis Dataset ◽  
Model Tree ◽  
Basin Scale ◽  
M5 Model

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.

scholarly journals Dynamic Downscaling of the Impact of Climate Change on the Ocean Circulation in the Galápagos Archipelago

2013 ◽  
Vol 2013 ◽  
pp. 1-18 ◽  
Author(s):  
Yanyun Liu ◽  
Lian Xie ◽  
John M. Morrison ◽  
Daniel Kamykowski
Keyword(s):  
Climate Change ◽  
Ocean Circulation ◽  
Global Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Ocean Model ◽  
Reanalysis Dataset ◽  
Equatorial Undercurrent ◽  
Galapagos Archipelago ◽  
The Impact

The regional impact of global climate change on the ocean circulation around the Galápagos Archipelago is studied using the Hybrid Coordinate Ocean Model (HYCOM) configured for a four-level nested domain system. The modeling system is validated and calibrated using daily atmospheric forcing derived from the NCEP/NCAR reanalysis dataset from 1951 to 2007. The potential impact of future anthropogenic global warming (AGW) in the Galápagos region is examined using the calibrated HYCOM with forcing derived from the IPCC-AR4 climate model. Results show that although the oceanic variability in the entire Galápagos region is significantly affected by global climate change, the degree of such effects is inhomogeneous across the region. The upwelling region to the west of the Isabella Island shows relatively slower warming trends compared to the eastern Galápagos region. Diagnostic analysis suggests that the variability in the western Galápagos upwelling region is affected mainly by equatorial undercurrent (EUC) and Panama currents, while the central/east Galápagos is predominantly affected by both Peru and EUC currents. The inhomogeneous responses in different regions of the Galápagos Archipelago to future AGW can be explained by the incoherent changes of the various current systems in the Galápagos region as a result of global climate change.

An ensemble Kalman filter data assimilation system for the martian atmosphere: Implementation and simulation experiments

Icarus ◽  
2010 ◽  
Vol 209 (2) ◽  
pp. 470-481 ◽  
Author(s):  
Matthew J. Hoffman ◽  
Steven J. Greybush ◽  
R. John Wilson ◽  
Gyorgyi Gyarmati ◽  
Ross N. Hoffman ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Martian Atmosphere ◽  
Simulation Experiments ◽  
Data Assimilation System ◽  
Assimilation System

scholarly journals Evolution of Antarctic ozone in September–December predicted by CCMVal-2 model simulations for the 21st century

2013 ◽  
Vol 13 (8) ◽  
pp. 4413-4427 ◽  
Author(s):  
J. M. Siddaway ◽  
S. V. Petelina ◽  
D. J. Karoly ◽  
A. R. Klekociuk ◽  
R. J. Dargaville
Keyword(s):  
21St Century ◽  
Climate Model ◽  
Polar Vortex ◽  
Early Summer ◽  
Slow Increase ◽  
Large Variability ◽  
Model Simulations ◽  
Antarctic Ozone ◽  
Decadal Rate ◽  
The Antarctic

Abstract. Chemistry-Climate Model Validation phase 2 (CCMVal-2) model simulations are used to analyze Antarctic ozone increases in 2000–2100 during local spring and early summer, both vertically integrated and at several pressure levels in the lower stratosphere. Multi-model median trends of monthly zonal mean total ozone column (TOC), ozone volume mixing ratio (VMR), wind speed and temperature poleward of 60° S are investigated. Median values are used to account for large variability in models, and the associated uncertainty is calculated using a bootstrapping technique. According to the trend derived from the twelve CCMVal-2 models selected, Antarctic TOC will not return to a 1965 baseline, an average of 1960–1969 values, by the end of the 21st century in September–November, but will return in ~2080 in December. The speed of December ozone depletion before 2000 was slower compared to spring months, and thus the decadal rate of December TOC increase after 2000 is also slower. Projected trends in December ozone VMR at 20–100 hPa show a much slower rate of ozone recovery, particularly at 50–70 hPa, than for spring months. Trends in temperature and winds at 20–150 hPa are also analyzed in order to attribute the projected slow increase of December ozone and to investigate future changes in the Antarctic atmosphere in general, including some aspects of the polar vortex breakup.

scholarly journals Impact of an observational time window on coupled data assimilation: simulation with a simple climate model

2017 ◽  
Vol 24 (4) ◽  
pp. 681-694 ◽  
Author(s):  
Yuxin Zhao ◽  
Xiong Deng ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Chang Liu ◽  
...  
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Climate Model ◽  
Time Window ◽  
Coupled Model ◽  
Circulation Model ◽  
Scale Interactions ◽  
Climate Signals ◽  
Coupled Data Assimilation ◽  
Climate Analysis

Abstract. Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.

scholarly journals How much should we believe correlations between Arctic cyclones and sea ice extent?

2017 ◽  
Author(s):  
Jamie G. L. Rae ◽  
Alexander D. Todd ◽  
Edward W. Blockley ◽  
Jeff K. Ridley
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
Reanalysis Dataset ◽  
Sea Ice Extent ◽  
Sea Level Pressure ◽  
Temporal Sampling ◽  
Time Period ◽  
Arctic Sea ◽  
Short Time

Abstract. This paper presents an analysis of Arctic summer cyclones in a climate model and in a reanalysis dataset. A cyclone identification and tracking algorithm is run for output from model simulations at two resolutions, and for the reanalysis, using two different tracking variables (mean sea-level pressure and 850 hPa vorticity) for identification of the cyclones. Correlations between characteristics of the cyclones and September Arctic sea ice extent are investigated, and the influence of the tracking variable, the spatial resolution of the model, and spatial and temporal sampling, on the correlations is explored. We conclude that the correlations obtained depend on all of these factors, and that care should be taken when interpreting the results of such analyses, especially when the focus is on one reanalysis, or output from one model, analysed with a single tracking variable for a short time period.

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