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G2a Atmosphere variability

Sean Bruinsma & Jia Yue

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The Atmosphere Variability Cluster concerns the analysis, modeling and prediction of variations in the thermosphere at all spatial and temporal scales, but particularly regarding the impact on satellite atmospheric drag.

Key questions:

What are the driver-response relationships, the temporal and spatial scales of the density and wind variability due to EUV/UV radiation and geomagnetic disturbances, radiative cooling, and, to a lesser degree, forcing due to disturbances propagating up from lower altitudes?
Which observations/proxies/indices are most representative of upper atmosphere heating due to solar EUV/UV emissions and geomagnetic activity?
What is the accuracy and precision of upper atmosphere density and wind models? The result of this activity will be a standard assessment procedure, which requires appropriate metrics as well as high-quality and high-resolution data over many years.
Which density and temperature datasets are available, or critically needed, to deal with items 1-3? Are the datasets coherent and appropriately edited?
How should atmospheric drag be computed in a consistent and standard manner?

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The Atmosphere Variability Cluster concerns the analysis, modeling and prediction of variations in the thermosphere at all spatial and temporal scales, but particularly regarding the impact on satellite atmospheric drag.

Key questions:

What are the driver-response relationships, the temporal and spatial scales of the density and wind variability due to EUV/UV radiation and geomagnetic disturbances, radiative cooling, and, to a lesser degree, forcing due to disturbances propagating up from lower altitudes?
Which observations/proxies/indices are most representative of upper atmosphere heating due to solar EUV/UV emissions and geomagnetic activity? New geomagnetic index Hpo(GFZ); EUV still a problem
What is the accuracy and precision of upper atmosphere density and wind models? The result of this activity will be a standard assessment procedure, which requires appropriate metrics as well as high-quality and high-resolution data over many years. Published metrics and procedures for density
Which density and temperature datasets are available, or critically needed, to deal with items 1-3? Are the datasets coherent and appropriately edited?
How should atmospheric drag be computed in a consistent and standard manner?

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The Atmosphere Variability Cluster concerns the analysis, modeling and prediction of variations in the thermosphere at all spatial and temporal scales, but particularly regarding the impact on satellite atmospheric drag.

Key questions:

What are the driver-response relationships, the temporal and spatial scales of the density and wind variability due to EUV/UV radiation and geomagnetic disturbances, radiative cooling, and, to a lesser degree, forcing due to disturbances propagating up from lower altitudes?
Which observations/proxies/indices are most representative of upper atmosphere heating due to solar EUV/UV emissions and geomagnetic activity?
What is the accuracy and precision of upper atmosphere density and wind models? The result of this activity will be a standard assessment procedure, which requires appropriate metrics as well as high-quality and high-resolution data over many years.
Which density and temperature datasets are available, or critically needed, to deal with items 1-3? Are the datasets coherent and appropriately edited?
How should atmospheric drag be computed in a consistent and standard manner?

Paper 1

Paper 2

Paper 3

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Title	Authors	Working abstract
Lower atmosphere impact on thermosphere density	Jia Yue, Nick Pedatella, Wandi Yu, Sean Bruinsma	Using two sets of WACCM-X runs with and without solar and geomagnetic disturbances but with lower atmosphere processes, we can quantify how much the lower atmosphere processes may contribute to the thermosphere density variability.
Description and comparison of 21st century thermosphere data	Sean Bruinsma, John Emmert, Christian Siemes, Kent Tobiska, Marty Mlynczak	The main upper atmosphere density datasets of this century as well as TIMED lower thermosphere data are reviewed, evaluated and compared. Total mass densities used in this study include all high-resolution CHAMP, GRACE and GOCE data, SwarmA, Stella, Starlette, global daily mean TLE densities, and the SET HASDM density database.
Drag Coefficient Modeling and its Impact on Density Estimation	Piyush Mehta, Christian Siemes, Gunther March, Nicholas Crisp, Logan Sheridan, Smriti Paul, ???

Papers for topical issue 1:

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“Description and comparison of 21st century thermosphere data”

Why do we need such an analysis? Example of data comparison at 250 km altitude:

In this example, the max mean difference is 26%

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The Atmosphere Variability Cluster concerns the analysis, modeling and prediction of variations in the thermosphere at all spatial and temporal scales, but particularly regarding the impact on satellite atmospheric drag.

Paper for topical issue 2: Neutrals and satellite drag pathways

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Drivers

(solar and geomagnetic)

Forecasts (day-year-cycle)

Satellite shape and characteristics

Upper atmosphere models

Orbit computation

Satellite drag computation and forecasting requires expertise in several domains

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The Atmosphere Variability Cluster concerns the analysis, modeling and prediction of variations in the thermosphere at all spatial and temporal scales, but particularly regarding the impact on satellite atmospheric drag.

Paper for topical issue 2:

Neutrals and satellite drag pathways	Sean Bruinsma, Thierry Dudok de Wit, Tim Fuller-Rowell, Stijn Lemmens, Katherine Garcia-Sage, Yuri Shprits, Jia Yue, Piyush Mehta, Fabian Schiemenz	Pathways for more accurate satellite aerodynamic drag calculation and prediction depend on atmosphere models, density data, assimilation, solar EUV and indices, geomagnetic indices, forecasting, Cd issues, uncertainty propagation, and operational limitations.

NB: no splinter this meeting – too soon for this group