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Jeff Forbes (CU), Xiaoli Zhang (CU), Sean Bruinsma (CNES), Jens Oberheide (Clemson U), Jason Leonard (CU) 1 Coupling to the Lower Atmosphere, an Observation-Based.

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Presentation on theme: "Jeff Forbes (CU), Xiaoli Zhang (CU), Sean Bruinsma (CNES), Jens Oberheide (Clemson U), Jason Leonard (CU) 1 Coupling to the Lower Atmosphere, an Observation-Based."— Presentation transcript:

1 Jeff Forbes (CU), Xiaoli Zhang (CU), Sean Bruinsma (CNES), Jens Oberheide (Clemson U), Jason Leonard (CU) 1 Coupling to the Lower Atmosphere, an Observation-Based Perspective Thermosphere density variability mainly due to: 1. Solar radiation forcing 2. Magnetospheric forcing 3. Meteorological influences from below The importance of 3. has only been realized very recently, and much of the variability is in the form of temporal and longitudinal variability imposed by tides propagating upwards from the lower atmosphere. The NADIR MURI has been instrumental in achieving the realization that satellite drag variability is linked to troposphere variability was well as to solar and magnetospheric variability.

2 Solar and Lunar Tidal Coupling 1.Atmospheric tides excited in the lower atmosphere grow exponentially with height until they reach the thermosphere where exponential growth is terminated due to molecular dissipation. 1.We have discovered that the waves with the longest vertical wavelengths can penetrate up to at least 400-500 km. 1. The TIMED satellite has provided observations that define the tidal spectrum entering the thermosphere at 110 km, and densities measured by the CHAMP and GRACE satellites provide information on those waves that penetrate to 300- 500 km – tidal theory can “fill in the gap” to some degree. 1.Solar tides generated by latent heating due to deep tropical convection carry the longitude and temporal variability of this source into the thermosphere. 1. The CHAMP and GRACE data enable investigation of lunar tide variability in the thermosphere for the first time, which is shown here to be significant. 1. The 2007-2010 solar minimum period has enabled separation of lower atmosphere variability from solar and geomagnetic variability in satellite drag.

3 Relative density variations about the zonal mean observed with (top) co- planar CHAMP at 332 km and (bottom) GRACE at 476 km in December 2008, for (left) evening and (right) morning. [Bruinsma and Forbes, 2010]. Tides Manifested as Longitude Structures

4 The longitude variability of diurnal temperature amplitude evolves with altitude due to: Filtering of vertically- propagating tides by molecular dissipation In-situ EUV source in the thermosphere In-situ source due to longitude-dependent ion drag How does the global wave spectrum evolve temporally and spatially in the thermosphere?

5 Methodology: A fitting scheme using “Hough Mode Extensions (HMEs)” is applied to TIMED/SABER and TIMED/TIDI measurements of temperatures and winds over 80-110 km and -50 o to +50 o latitude during 2002-2008. 1.SABER and TIDI are analyzed for diurnal and semidiurnal tidal components of various zonal (longitudinal) wavenumbers (i.e., SW2, SW1, SE2; DW1, DE3, etc.). 1.Each tidal component is fit with several HMEs; winds and temperatures are fit simultaneously; or, one parameter is fit and the other is used as validation. 1.Internal consistency of the HMEs yields the corresponding tidal density perturbations. 1.The HME methodology and the above internal consistency between winds, temperatures and densities has been tested using GCM output. 5. Validate using independent data sets, e.g., CHAMP data at 400 km. Methodology: Hough Mode Extensions as Basis Functions 5 Development of an Empirical Specification of Longitude-Dependent Tidal Structures

6 Sample HME: Eastward-Propagating Diurnal Tide with Zonal Wavenumber = 3 (DE3) 6

7 Sample Fit and Density Prediction SABER temperature at 110 km, September, UT = 0000, 2002- 2008 average Temperature at 110 km, UT = 0000, 2002-2008 average, based on fit to SABER temperatures and TIDI winds. Density perturbations at 110 km predicted by HMEs, DW2, DW1, D0, DE1, DE2, DE3, SW4, SW3, SW2, SW1, S0, SE1, SE2, SE3 7

8 Validation-CHAMP densities at 390 km vs. solar cycle CHAMP-DE3 HME-DE3 fitted to 2002- 2008 mean TIMED data; solar flux dependence from HMEs fitted to 2002- 2008 mean TIMED data; solar flux dependence from HMEs CHAMP-SE2 HME-SE2 8

9 Validation-CHAMP zonal winds at 400 km vs. solar cycle CHAMP DE3 zonal wind CHAMP DE3 zonal wind CHAMP HME Oberheide et al. (2009) 9

10 Sample Density Perturbations 10

11 Scatter in surface impact predictions due to presence of longitude-dependent tides Differences in impact latitude depend on longitude and local time of reentry. Current empirical models do not include these longitude-local time variations Illustration of impact trajectories for a single local time and for multiple longitudes superimposed on sample density perturbation distribution for a single longitude.

12 Scatter in satellite predicted orbital position due to presence of longitude-dependent tides

13 13 2007-2010 Averages Lunar Tidal Variations in Satellite Drag Lunar Tide from GRACE orbit has a period of 13.56 days Lunar Tide from CHAMP orbit has a period of 13.28 days

14 Conclusions from the MURI Effort 1.Atmospheric solar and lunar tides originating in the lower atmosphere add significant longitudinal, local time and temporal variability to the satellite drag and reentry environments. 1. These variations are not taken into account in existing empirical models, and are not adequately taken into account at the lower boundaries of physics-based models of the ionosphere-thermosphere system. 2.There exist distinct seasonal-latitudinal patterns and inter- annual consistency in the tidal amplitudes, and therefore the mean patterns are predictable, and can be included in existing empirical models, and/or at the lower thermosphere boundaries of physics-based models. 14

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