BRIEF REPORT
10.1002/2014JA020006 Key Points:• New TIME-GCM 30 km lower boundary condition based on 3-hourly MERRA data • Introduces more day-to-day
variability in the model thermosphere • Improved ability to capture
thermo-spheric density variations observed by GOCE Correspondence to: K. Häusler, kathrin@ucar.edu Citation: Häusler, K., M. E. Hagan, A. J. G. Baumgaertner, A. Maute, G. Lu, E. Doornbos, S. Bruinsma, J. M. Forbes, and F. Gasperini (2014), Improved short-term variability in the thermosphere-ionosphere-mesosphere-electrodynamics general circulation model,
J. Geophys. Res. Space Physics, 119,
doi:10.1002/2014JA020006.
Received 20 MAR 2014 Accepted 15 JUL 2014
Accepted article online 17 JUL 2014
Improved short-term variability in the
thermosphere-ionosphere-mesosphere-electrodynamics
general circulation model
K. Häusler1,2, M. E. Hagan1, A. J. G. Baumgaertner1,3, A. Maute1, G. Lu1, E. Doornbos4,
S. Bruinsma5, J. M. Forbes3, and F. Gasperini3
1High Altitude Observatory, National Center for Atmospheric Research, Boulder, Colorado, USA,2Advanced Study Program, National Center for Atmospheric Research, Boulder, Colorado, USA,3Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, Colorado, USA,4Aerospace Engineering, Delft University of Technology, Delft, Netherlands,5Department of Terrestrial and Planetary Geodesy, CNES, Toulouse, France
Abstract
We report on a new source of tidal variability in the National Center for Atmospheric Research thermosphere-ionosphere-mesosphere-electrodynamics general circulation model (TIME-GCM). Lower boundary forcing of the TIME-GCM for a simulation of November–December 2009 based on 3-hourly Modern-Era Retrospective Analysis for Research and Application (MERRA) reanalysis data includes day-to-day variations in both diurnal and semidiurnal tides of tropospheric origin. Comparison with TIME-GCM results from a heretofore standard simulation that includes climatological tropospheric tides from the global-scale wave model reveal evidence of the impacts of MERRA forcing throughout the model domain, including measurable tidal variability in the TIME-GCM upper thermosphere. Additional comparisons with measurements made by the Gravity field and steady-state Ocean Circulation Explorer satellite show improved TIME-GCM capability to capture day-to-day variations in thermospheric density for the November–December 2009 period with the new MERRA lower boundary forcing.1. Introduction
Meteorological variations are proven to be important sources of variability in the mesosphere, thermo-sphere, and ionothermo-sphere, as evidenced in observational as well as numerical modeling results during the past decade. England [2012] recently reviewed the effects of tides of tropospheric origin on the upper atmo-sphere with particular attention to low-latitude ionospheric variability. Akmaev [2011] detailed achieve-ments in understanding ionospheric and thermospheric variability attributable to lower atmospheric sources, including sudden stratospheric warmings (SSW), using numerical models of the Earth’s atmo-sphere from the ground to the exoatmo-sphere. We refer the reader to the aforementioned reviews and references therein for details about the gains in our understanding of dynamical coupling into the thermosphere and related thermosphere-ionosphere interactions that occurred between 2002 and 2012.
More recent reports on the dynamical coupling between the lower and upper atmosphere provide addi-tional insight into the unresolved questions about the evolution and impacts of tides and planetary waves (PW) as they interact in the mesosphere, modulate the dynamo process at E region altitudes, and propagate into the upper atmosphere where they eventually dissipate. Much of the recent focus was on the behavior of the ionosphere and thermosphere during SSWs [e.g., Fang et al., 2012; Jin et al., 2012; Liu et al., 2013a; Pedatella and Liu, 2013b; Maute et al., 2014]. Lin et al. [2013] interpreted the ionospheric effects of the 2008–2010 SSWs observed by the FORMOSAT-3/COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) satellites in terms of changes in thermospheric tides. Motivated by observational evidence of the gravitationally excited lunar tides in the ionosphere during SSWs, including pronounced signatures in equatorial vertical plasma drifts [Fejer et al., 2011], the equatorial electrojet [Park et al., 2012], and the global ionospheric current system [Yamazaki et al., 2012], Forbes
and Zhang [2012] used a linear tidal model to demonstrate that the lunar tide may be amplified by
as much as factor of 3 over climatological values during an SSW event. Pedatella et al. [2012] demon-strated the essential role of the lunar tide during an SSW in a numerical experiment with an ionosphere-electrodynamics model.
Other recent insights into the impacts of meteorological disturbances on the near-Earth space environment include revelations about interannual mesospheric and lower thermospheric tidal variability accompa-nied by variability in the ionosphere due to the effects of the El Ni ˜no-Southern Oscillation [Pedatella and
Liu, 2012, 2013a], a demonstration that sharp longitudinal gradients observed in equatorial vertical plasma
drifts cannot be uniquely attributable to tides and suggesting a plausible role for smaller-scale gravity waves [Fang et al., 2013], and a quantification that elucidated the comparative importance of in situ and tropo-spheric nonmigrating tidal sources in the thermosphere and ionosphere [Jones et al., 2013] along with the impacts of the latter on the zonal mean state of the ionosphere-thermosphere system [Jones et al., 2014]. Herein we explore the impacts of daily varying tropospheric tides on the thermosphere with the NCAR (National Center for Atmospheric Research) TIME-GCM (thermosphere-ionosphere-mesosphere-electrodynamics general circulation model) and a new lower boundary scheme based on 3-hourly Modern-Era Retrospective Analysis for Research and Application (MERRA) data [Rienecker et al., 2011]. This work complements the efforts of Liu et al. [2013b] who relaxed the TIME-GCM temperature and horizontal winds below the mesopause to the results from a whole atmosphere community climate model simulation that was constrained with MERRA data in order to explore day-to-day ionospheric variability due to lower atmosphere perturbations.
We compare and contrast the new TIME-GCM results with a complementary simulation based on the hereto-fore standard TIME-GCM lower boundary conditions (LBC). We further assess the capability of the new scheme by comparing TIME-GCM results with observations made by the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite.
2. TIME-GCM
The TIME-GCM is the latest in the series of three-dimensional time-dependent NCAR models developed to simulate the circulation, temperature, electrodynamics, and compositional structure of the upper atmo-sphere and ionoatmo-sphere. The TIME-GCM is a global grid point model that calculates neutral gas heating, dynamics, photoionization, electrodynamics, and the compositional structure of the middle and upper atmosphere and ionosphere from first principles for a given solar irradiance spectrum which varies with solar activity. Subgrid-scale gravity waves are necessary for realistic simulations of the mesopause region and are parameterized with a modified Lindzen- [1981] type scheme that is extended to include molecu-lar damping effects in the lower thermosphere. We refer the reader to Roble and Ridley [1994], Roble [1995, 1996] and references therein for a more complete description of the TIME-GCM.
For the November–December 2009 simulations discussed herein, we used the high-resolution version of the TIME-GCM, which has 2.5◦by 2.5◦in latitude and longitude and four grid points per scale height in the vertical direction. The high-resolution simulation is necessary in order to resolve upward propagating tides. We used the 10.7 cm solar radio flux (F10.7) values along with hemispheric power and cross-cap potential values based on Kp indices to represent solar radiative and auroral forcings during this solar minimum and geomagnetically quiescent period.
The TIME-GCM inherently accounts for atmospheric tides that are excited by the absorption of ultraviolet and extreme ultraviolet radiation in the middle and upper atmosphere, but we need to account for tidal components attributable to tropospheric absorption of infrared radiation and latent heat release associated with raindrop formation in deep convective tropical clouds. We include zonal and meridional wind, temper-ature, and geopotential height fields at the TIME-GCM lower boundary (i.e., 10 hPa; ≈ 30 km) to account for variations including tides and planetary waves excited in the troposphere.
Herein we report on two sets of TIME-GCM simulations. The first simulation includes the current stan-dard lower boundary condition based on monthly global-scale wave model (GSWM) tidal climatologies [Zhang et al., 2010a, 2010b] along with daily-averaged European Centre for Medium-Range Weather Fore-casts (ECMWF) reanalysis data on a 2.5◦by 2.5◦horizontal grid, to account for realistic day-to-day diurnal mean variations, including planetary wave activity. Notably, ECMWF is a 6-hourly data set, precluding its use as a reliable source of semidiurnal (i.e., 12 h) variations and necessitating our employ of the GSWM tidal climatologies.
The second simulation reported herein is characterized by a newly developed lower boundary condition based on 3-hourly MERRA data, which inherently includes realistic day-to-day variations in the diurnal and
Figure 1. Contours of (top) ECMWF/GSWM-09 and (bottom) MERRA
10 hPa 3-hourly temperatures versus longitude and time for 15–18 November 2009. Shown are averages between± 8.75◦geographic lat-itudes. The MERRA temperatures are interpolated to the2.5◦ × 2.5◦
TIME-GCM latitude-longitude grid. See text for details.
semidiurnal tidal fields as well as their diurnal means. MERRA covers the mod-ern era of remotely sensed data from 1979 through the present and uses the newest Goddard Earth Observing Sys-tem Data Assimilation SysSys-tem Version 5, which includes a special focus on the hydrological cycle in the atmospheric assimilation. (See http://gmao.gsfc.nasa. gov/research/merra/ for details.) We perturb TIME-GCM with MERRA data at pressure level 31, corresponding to 10 hPa or ≈ 30 km, after convert-ing the fields from their 1.25◦by 1.25◦ latitude-longitude MERRA framework to the 2.5◦by 2.5◦TIME-GCM structure by applying a bilinear remapping using the NCAR Command Language with the Earth System Modeling Framework soft-ware [NCAR Command Language, 2012;
Earth System Modeling Framework (ESMF) Joint Specification Team, 2012].
Figure 1 depicts the temporal and longi-tudinal evolution of ECMWF/GSWM-09 and MERRA equatorial temperatures at the TIME-GCM lower boundary for 15–18 November 2009 and exemplifies the vari-ability of the input fields. The illustrated temperatures are averages between ± 8.75◦geographic latitudes. While the salient features of both temperature fields are similar, there are also notable differences. Specifically, there is more small-scale structure and day-to-day vari-ability in the MERRA temperatures than there is in the ECMWF/GSWM-09 results. The differences between the two tem-perature fields can be as high as 4 K. The absence of small-scale structure in the ECMWF/GSWM-09 results is due to the averaging of the 6-hourly ECMWF data. In addition, there is no discernible difference between the illustrated MERRA temperatures and those on the original MERRA grid (not shown).
3. Results and Comparison With GOCE
Figure 2 illustrates TIME-GCM thermospheric densities at 270 km altitude and 0◦longitude during 15–24 November 2009 for the two different lower boundary conditions, the traditional ECMWF/GSWM-09 and the new MERRA forcing. Notably, the former specifications of day-to-day tropospheric tidal variability are smoothly varying, owing to the fact that GSWM-09 temperature, wind, and geopotential height perturba-tions are interpolated between the 15th day of each month. Both simulaperturba-tions are dominated by a strong diurnal variation in thermospheric density, which varies daily both in magnitude (up to 20%) and in latitude structure. The simulation with ECMWF/GSWM-09 LBC shows peak amplitudes between approximately 30◦N and 60◦N and approximately 30◦S and 75◦S near noon each day. These peak amplitudes move equatorward later in the day and are centered around the equator at dusk. Further, the TIME-GCM/ECMWF/GSWM-09 densities are systematically larger than the TIME-GCM/MERRA results at 270 km, and the latter exhibits more day-to-day variability than the former. TIME-GCM/MERRA peak densities always occur first in the southern
Figure 2. Contours of TIME-GCM thermospheric density (10−11kg/m3) at 270 km altitude and 0◦longitude during 15–24 November 2009 ver-sus hour from 00 UT on 15 November and geographic latitude with (top) ECMWF/GSWM-09 and (bottom) MERRA lower boundary forcing.
middle to high latitudes, and the den-sity is in general higher in the summer hemisphere than the winter hemisphere. Later in the day secondary peaks form in the Northern Hemisphere and around the equator but not as systematically as in the TIME-GCM/ECMWF/GSWM-09 simulation. These secondary peaks also exhibit significant day-to-day variability in amplitude and latitu-dinal structure. We return to the systematic difference between the TIME-GCM/ECMWF/GSWM-09 and TIME-GCM/MERRA densities in the discussion below.
Next we compare a subset of our TIME-GCM thermospheric density results with GOCE measurements. The GOCE satellite was launched on 17 March 2009 into a near Sun-synchronous dusk-dawn orbit and carried six accelerome-ters, which allow the neutral density and cross-track wind determination [after Doornbos et al., 2010] at approx-imately 270 km altitude. Figure 3 illustrates GOCE thermospheric den-sities from the ascending (≈ 18.2 local solar time (LST) in hours) and descend-ing (≈ 6.2 LST) portions of the orbit in November–December (day of year 305 to 364) 2009 along with complemen-tary TIME-GCM densities along the GOCE orbital track. We postprocess the sim-ulated hourly TIME-GCM data to make this comparison. First, we calculate the neutral density from the simulated constituents and then convert the model output from the pressure grid to an altitude-based grid with a vertical resolution of 5 km. Subsequently, we interpolate the TIME-GCM neutral densities in space and time to find the corresponding modeled densities along the GOCE orbit.
Although the illustrated modeled densities are on average (0.2–0.4) ×10−11kg/m3larger than the
mea-surements (Figure 3), there is some general agreement between the results, especially for the dawn data. TIME-GCM captures the overall temporal variation in the dawn (descending) data during the 2 months along with most of the day-to-day variations in the observed peaks over the Northern Hemisphere tropics. There is less agreement in the dusk sector, particularly in late November and early December when GOCE observed a sharp decline in density which persists for a couple of weeks (days 336–352), while TIME-GCM densities weaken slowly over the same period. During this time period the biggest difference between the model and the measurements amounts to 1 × 10−11kg/m3. Dusk model-measurement comparisons at the beginning
of November 2009 are far more favorable. Notably, there is clear evidence of a 3 to 6 day periodicity in the GOCE data during the month of November. Bispectral analysis and subsequent least squares fits [after Wu et
al., 1995] to the combined GOCE ascending and descending orbit data between the equator and 30◦N dur-ing November reveal 7% density amplitude variations attributable to a 5.5 day modulation along with 3% variations due to a 3.5 day modulation. Spectral analysis of the daily Ap values also shows peaks at approx-imately 3.5 and 5.5 days. Thus geomagnetic activity, as parameterized by Ap, seems responsible for the observed neutral density variation in the GOCE data. The white line in each plot in Figure 3 depicts the daily
Apindex and demonstrates that the observed periodicity is well correlated with the geomagnetic activ-ity showing peak densities shortly after peak Ap values. The correlation between neutral densactiv-ity variabilactiv-ity
Figure 3. Contours of thermospheric density (10−11kg/m3) at 270 km during November–December 2009 as measured by (top row) GOCE and (bottom row) modeled by TIME-GCM along the (left) ascending and (right) descending portions of the satellite orbit as a function of day of year from 1 November and geographic latitude. The ascending portion of the orbit corresponds to 18.2 LST, the descending portion to 6.2 LST. The white line in each plot represents the daily averagedApindex (nT).
and geomagnetic activity will be the subject of a detailed follow-up study (F. Gasperini et al., manuscript in preparation, 2014).
TIME-GCM densities along the GOCE orbit (Figure 3) exhibit significantly less variability than the full model results (Figure 2). This is largely attributable to the fact that the full model results contain all of the variations in the diurnal cycle, while the results along the GOCE track represent latitude and day-to-day variability at specific local times. There are also signatures of the 5.5 day and 3.5 day modulation in the TIME-GCM/MERRA density data along the GOCE orbit, but they are only about half as big as the observed variations. The wave amplitudes increase slightly (i.e., by a percentage point) if the 30 day analysis period is shifted forward in time by 10 days.
The increase in TIME-GCM short-term tidal variability associated with MERRA lower boundary forcing is exemplified by the migrating diurnal (DW1), eastward propagating wave number 3 diurnal (DE3), and east-ward propagating wave number 2 semidiurnal (SE2) thermospheric temperature tidal amplitudes illustrated in Figure 4. These results contrast the mid-November to mid-December 2009 amplitudes obtained when TIME-GCM is forced with the new versus the traditional lower boundary conditions. The illustrated differ-ences are solely attributable to the contrasts between 30 km MERRA and ECMWF/GSWM-09 inputs, because solar and geomagnetic forcings were identical in the two simulations. The DW1 is primarily excited by in situ absorption of extreme ultraviolet radiation in the upper thermosphere and is the dominant thermo-spheric tidal component. Thus, we anticipate the similarity in the magnitude of the TIME-GCM MERRA and ECMWF/GSWM-09 DW1 amplitudes, but note that the former exhibit more day-to-day variability than the latter. The differences between the DE3 and SE2 simulation results are striking with MERRA forcing produc-ing respective peak temperature amplitudes up to 8 K and 30 K larger than the amplitudes associated with the ECMWF/GSWM-09 forcing. Despite differences, there is consistent evidence of a quasi 3 day modula-tion of the DE3 amplitude in both simulamodula-tions at 350 km altitude. Averaging the DE3 amplitudes for both
Figure 4. Contours of (left) TIME-GCM 350 km DW1, (middle) DE3, and (right) SE2 thermospheric temperature amplitudes (K) as a function of day of year between
15 November and 14 December 2009 and geographic latitude with (top) ECMWF/GSWM-09 and (bottom) MERRA lower boundary forcing.
simulations between ± 30◦geographic latitude to capture all peak amplitudes and subsequently perform-ing a fast Fourier transform analysis for this time period, we find a 30% (28%) 3.5 day wave modulation of the MERRA (ECMWF/GSWM-09) DE3 amplitude. Relatedly, comparable analyses of the DE3 amplitudes at 35 km near the TIME-GCM lower boundary suggest that the quasi 3 day planetary wave modulation of DE3 ampli-tude (20%) is inherent in the MERRA lower boundary forcing. However, there is no clear evidence of a quasi 3 day planetary wave modulation of DE3 amplitude at 35 km for ECMWF/GSWM-09. Although the PW activ-ity is similar for both LBCs in general, they differ in detail. For example, we find reduced power in the quasi 3 day planetary wave (e.g., by a factor of 3 at 90◦W) in the periodogram for the ECMWF/GSWM-09 LBC com-pared to the MERRA LBC which might explain the lack of a clear quasi 3 day planetary wave modulation of DE3 for the TIME-GCM/ECMWF/GSWM-09 simulation at 35 km (not shown).
The attribution of the comparative importance of planetary wave variability in the TIME-GCM tropospheric sources, and the evolution and impacts of these waves in the model middle and upper atmosphere, is the subject of a future investigation. It will also include a comprehensive analysis of GOCE data as well as tem-perature measurements made between 20 km and 100 km from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite.
4. Discussion and Conclusions
We introduce a new TIME-GCM lower boundary scheme based on 3-hourly MERRA temperatures, hori-zontal winds, and geopotential heights, which self-consistently account for day-to-day tidal and planetary wave variability. TIME-GCM total thermospheric densities associated with the MERRA forcing are compara-tively smaller and more variable than the densities obtained when the model lower boundary is specified by ECMWF daily means and GSWM-09 climatological tides. These results provide additional evidence of the effects of tides on the mean state of the thermosphere [Akmaev and Shved, 1980; Forbes et al., 1993;
Yamazaki and Richmond, 2013; Siskind et al., 2014; Jones et al., 2014]. Specifically, the comparatively larger
the corresponding TIME-GCM/ECMWF/GSWM-09 components. The compositional mixing effect associated with this transport leads to the comparatively smaller TIME-GCM/MERRA thermospheric densities illustrated in Figure 2, which are dominated by atomic oxygen.
Comparisons between TIME-GCM/MERRA and GOCE thermospheric densities during the geomagneti-cally quiescent November–December 2009 period are encouraging in that the model captures many of the salient features in the satellite observations (Figure 3). Further, model-measurement comparisons are needed to evaluate the short-term variability throughout the atmosphere. In particular, the large non-migrating tidal components in TIME-GCM/MERRA thermospheric temperatures warrant further study. We plan to extend our simulation in time to make accurate comparisons with thermospheric tidal tem-perature diagnostics from combined Challenging Minisatellite Payload (CHAMP) and Gravity Recovery And Climate Experiment (GRACE) satellite observations that require TIME-GCM postprocessing to deter-mine temperatures along the CHAMP and GRACE orbital tracks and subsequent tidal analysis of the ascending and descending portions of their orbits [after Forbes and Zhang, 2012]. Relatedly, we plan to assess short-term tidal variability in the model middle atmosphere and lower thermosphere by postpro-cessing the TIME-GCM/MERRA results for comparison with TIMED/SABER temperature measurements [after Zhang et al., 2006].
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Acknowledgments
TIME-GCM results are archived on the National Center for Atmospheric Research High Performance Storage System and are available on request. MERRA data used in the present study are available through the Goddard Earth Sciences Data and Information Services Center (http://disc.sci.gsfc. nasa.gov/mdisc/data-holdings/merra/ merra_products_nonjs.shtml). ECMWF data were obtained from the ECMWF TOGA 2.5 degree Global Surface and Upper Air Analyses (http://rda.ucar. edu/datasets/ds111.2/), whileApdata were downloaded from http://spidr. ngdc.noaa.gov. GSWM-09 results are available from http://www.hao.ucar. edu/modeling/gswm/gswm.html. The GOCE observations are avail-able through https://earth.esa.int/ web/guest/-/goce-data-access-7219. This work was supported by the U.S. Participating Investigator (USPI) Program under NASA grant NNX12AD26G. The production of GOCE thermosphere density data products is supported by the ESA Support To Science Element pro-gram. K.H. is supported by the Advanced Study Program Postdoctoral Fellowship of the National Center for Atmospheric Research. The National Center for Atmospheric Research is sponsored by the National Science Foundation. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation.
Alan Rodger thanks the reviewers for their assistance in evaluating this paper.
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