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GMI Home > Projects
& Publications > Project Descriptions
Project Descriptions
This section describes the major projects completed since GMI’s inception.
The order is chronological with the most recent listed first. All output
may be obtained by anonymous ftp to dirac.gsfc.nasa.gov. The output directories
listed also contain ‘README’ and namelist files that give more
detailed information about the simulation.
Met fields: GEOS-4-Data Assimilation System,
2° lat x 2.5° lon x 42 levels (lid at 0.01 hPa)
Time Period: Feb. 2004-Dec. 2006
Aura4 Directory: /pub/gmidata2/output/gmic/aura4
There are 4 minor changes to the model compared to the version used for
Aura3: 1) H2 mixing ratio is set to 500 ppb everywhere, 2) a minor coding
error in the 'condense' subroutine was fixed, 3) the units for O3 produced
from shipping NOx emissions were corrected, and 4) an updated Pickering and
Allen lightning
parameterization was used. This run differs from Aura4 primarily by the emissions
used. Some of the new emissions include hourly NOx fossil fuel variation
(Harvard), seasonality of Chinese emissions (Streets), and a fix in the GFEDv2
boreal emissions for 2004-5. For a more complete description of this run,
read the Aura4 production run
summary. For a very detailed description
of the run, read the production
run details.
Met fields: GEOS-4-Data Assimilation System,
2° lat x 2.5° lon x 42 levels (lid at 0.01 hPa)
Time Period: Feb. 2004-Apr. 2007
Aura3 Directory: /pub/gmidata2/output/gmic/aura3
Aura2 Directory: /pub/gmidata2/output/gmic/aura2
This run was previously called ‘ap1.0HO2Aura2’. The met
fields used are a 3-hr time averaged DAS product. This simulation has
the new Pickering and Allen lightning parameterization with its original
NOx profile. It includes the HO2 heterogeneous uptake reaction that was
turned off in Aura2. Tropospheric aerosol inputs used are from 2004-2006
GOCART simulations. JPL06 reactions rates are used, however, photolysis
cross sections were not updated. The previous run of the Aura period, ‘Aura2’,
differs only in that it used the original GMI lightning parameterization
and the HO2 uptake reaction was turned off. Schoeberl et al. [2007] compare
tropospheric column O3 (TCO) from the aura2 run with an Aura OMI/MLS-derived
TCO product. For more information, read
the Aura3 production run summary. For a very detailed description
of the run, read the production
run details.
Combo Model – AURA Period - Forecasts
Met fields: Forecasts from GEOS-4-DAS first-look analyses,
2° lat x 2.5° lon x 42 levels (lid at 0.01 hPa)
Time Period: July 1, 2004-June 30, 2005
Directory: /pub/gmidata2/output/gmic/aura2for12h and ../aura2for24h
These simulations use the Aura2 version of the code (see above) with GEOS-4-DAS
instantaneous forecast met fields (6-hr updates) that were generated from
6-hr time-averaged DAS analyses. ‘for12h’ used 18-30 hr forecasts,
updating the forecast sequence every 12 hrs. ‘for24h’ used 12-36
hr forecasts, updating the forecast sequence every 24 hrs.
Met fields: GEOS-4-GCM,
2° lat x 2.5° lon x 42 levels (lid at 0.01 hPa)
Time Period: Jan. 1994-Dec. 1998 (years based on SSTs used in the GCM integration).
Directory: /pub/gmidata2/output/gmic/fvgcm/
This simulation uses the same model build as ’Aura3’, which
includes the new lightning parameterization and has HO2 uptake turned on. Met
fields have 3-hr updates. Inputs include Harvard 1980-1990 biomass burning
sources, ship emissions, fossil fuel and biofuel from Harvard (1995), and
source gas boundary conditions for 1994-8. Publications that used this or
a prior Combo-fvgcm integration include Schoeberl et al. [2006], Duncan et
al. [2007], and Strahan et al. [2007]. For more information,
read the FvgcmCombo production
run summary. For a very detailed description
of the run, read the production
run details.
Tropospheric Model – Hemispheric Transport of Air Pollution (HTAP) experiments
Met fields: GEOS-4-DAS,
2° lat x 2.5° lon x 42 levels (lid at 0.01 hPa)
Time Period: Jan. 1, 2001-Dec. 31, 2001.
Directory: /pub/gmidata2/output/htap/full_chem
Eighteen simulations using the tropospheric model were integrated for the
HTAP study of source-receptor relationships for ozone and its precursors
(NOx, NMHC, CH4, and CO). The results were submitted to HTAP. This work was
supervised by Bryan Duncan.
Aerosol Model – Hemispheric Transport of Air Pollution (HTAP) experiments
Met fields: GEOS-4-DAS,
2° lat x 2.5° lon x 42 levels (lid at 0.01 hPa)
Time Period: Jan. 1, 2001-Dec. 31, 2001.
Directory: /pub/gmidata2/output/htap/aerosols
A modified version of the GMI aerosol model was used to integrate source-receptor
experiments for 4 regions: N. America, Europe, E. Asia, and S. Asia. Both baseline
(SR1) and perturbation runs (SR6) were submitted to HTAP (Hemispheric Transport
of Atmospheric Pollutants). These results are used in the HTAP
2007 Interim Report,
submitted in Dec. 2007. This work was supervised by Huisheng Bian.
Aerosol Model – Aerosol Sensitivity to Meteorology
Met fields: GEOS-1-Data Assimilation System (aka ‘DAO’),
GEOS-4-GCM (aka FVGCM), and NASA GISS II’ GCM
GEOS-1-DAS Resolution: 4° lat x 5° lon x 46 levels (lid at ~0.4 hPa)
GEOS-4-GCM Resolution: 4° lat x 5° lon x 42 levels (lid at ~0.01 hPa)
GISS II’ Resolution: 4° lat x 5° lon x 23 levels (lid at ~0.01
hPa)
Mechanism: Univ. of Michigan aerosol module
Time Period: DAS met fields Mar. 1997-Feb. 1998, other fields are from GCMs.
Source gases for 1995.
Directory: /pub/gmidata/gmia/MicroAerosolNov06/*_present_day
Current global aerosol models use different physical and chemical schemes
and parameters, different meteorological fields, and often different emission
sources. Since the physical and chemical parameterization schemes are often
tuned to obtain results that are consistent with observations, it is difficult
to assess the true uncertainty due to meteorology alone. Three meteorological
data sets are used to drive the same aerosol model. The differences and uncertainties
in aerosol simulations (for sulfate, organic carbon, black carbon, dust,
and sea salt) solely due to different meteorological fields are analyzed
and quantified. See Liu et al. [2007].
Aerosol Model – Preindustrial Aerosol Distributions
Met fields: GEOS-1-Data Assimilation System (aka ‘DAO’),
GEOS-4-GCM (aka FVGCM), and NASA GISS II’ GCM
GEOS-1-DAS Resolution: 4° lat x 5° lon x 46 levels (lid at ~0.4 hPa)
GEOS-4-GCM Resolution: 4° lat x 5° lon x 42 levels (lid at ~0.01 hPa)
GISS II’ Resolution: 4° lat x 5° lon x 23 levels (lid at ~0.01
hPa)
Mechanism: Univ. of Michigan aerosol module
Time Period: DAS met fields Mar. 1997-Feb. 1998, other fields are from GCMs.
Source gases for 1995.
Directory: /pub/gmidata/gmia/MicroAerosolNov06/*_preind
These simulations are analogous to the above simulations, but use estimates
of preindustrial levels of aerosol precursors in the aerosol calculation.
Tropospheric Model – IPCC AR4 model intercomparison study
Met fields: GEOS-1-Data Assimilation System (aka ‘DAO’),
GEOS-4-GCM (aka FVGCM), and NASA GISS II’ GCM
GEOS-1-DAS Resolution: 4° lat x 5° lon x 46 levels (lid at ~0.4 hPa)
GEOS-4-GCM Resolution: 4° lat x 5° lon x 42 levels (lid at ~0.01 hPa)
GISS II’ Resolution: 4° lat x 5° lon x 23 levels (lid at ~0.01
hPa)
Time Period: DAS met fields Mar. 1997-Feb. 1998, other fields are from GCMs.
Source gases for 1995.
Directory: /pub/gmidata/gmit-v1/IPCC_DEC_05/ccm3, ../dao, ../giss
These troposphere-only simulations (with synoz to represent stratospheric
ozone) were run with 3 sets of met fields using 4 different present day ( 1995)
and future (2030) emissions scenarios specified by the Accent AR4 photochemical
intercomparison. Analyses were performed outside of GMI and references can
be found in the IPCC-Accent publication list below.
Stratospheric Model – 'Hindcast,' 1975-2004
Met fields: Finite Volume GCM (FVGCM), 2° lat x 2.5°
lon x 33 levels (lid at ~0.01 hPa)
Time Period: Source gas boundary conditions from 1975-2004.
Directory: /pub/gmidata/gmis/hind/cold and ../warm
The credibility of a model used to assess future ozone trends can be evaluated
by the model’s ability to ‘hindcast’ ozone over the period
of existing measurements. We wish to bracket some of the range of possible
model results by doing simulations representing a perpetually warm and a
perpetually cold Arctic winter. Two years of FVGCM met fields were chosen
based on their Arctic lower stratospheric temperatures. The hindcast simulations
include variations due to chlorine and bromine sources, solar UV cycle, and
volcanic aerosols.
Publications using results from the hindcast simulations are Waugh et al.
[2007] and Douglass et al. [2006].
Stratospheric Model – Sensitivity of Antarctic ozone recovery to meteorology
Met fields: Finite Volume GCM (FVGCM) and Finite Volume
DAS (FVDAS), 4° lat x 5° lon x 28 levels (lid at ~0.4 hPa)
Time Period: FVDAS represents July 1, 1999-June 30, 2000. WMO source gas boundary
conditions represent the period 1995-2030.
Directory: /pub/gmidata/LLNL/GMI-S/FVCCM and ../FVDAS
This experiment was designed to investigate the uncertainty due to meteorology
in the prediction of ozone recovery. We chose meteorological input from a
general circulation model and from a data assimilation system because they
are know to have significant differences in their residual circulation. Source
gas boundary conditions came from the WMO scenario ‘MA2’, which
includes changing surface concentrations for 16 halocarbons, including CFCs,
HCFCs, and halons. Methane and nitrous oxide boundary conditions increase
by ~25% and ~11%, respectively, over the simulation period.
Age of air in the GCM was known to be much more realistic than in the DAS,
however both meteorological fields were known to have some realistic transport
characteristics. Simulations with these wind fields were also performed with
the Goddard Chemistry and Transport Model and the results were graded with
some of the original GMI objective grading criteria [Douglass et al., 1999].
Both simulations scored higher than any previous GMI simulations. The age
of air differences indicated significant differences in residual circulations
[Schoeberl et al., 2003].
Each GMI CTM simulation was integrated by repeating one year of meteorological
input from the FVGCM and the FVDAS to simulate 1995-2030. Both met fields
had a colder than average Arctic winter. Analyses of chemistry, transport,
and polar processes in these simulations are reported in Douglass et al.
[2004], Considine et al. [2004], and Strahan and Douglass [2004]. We found
that ozone trends in the Antarctic were dominated by chlorine changes rather
than transport differences (chemistry rules, transport drools).
Stratospheric Model – Sensitivity of Lower Stratospheric Chemistry and
Transport to Meteorology
Met fields: GEOS-1-Data Assimilation System (aka ‘DAO’),
NCAR Middle Atmosphere Community Climate Model Version 2 (MACCM2), and NASA
GISS II’ GCM
GEOS-1-DAS Resolution: 4° lat x 5° lon x 46 levels (lid at ~0.4 hPa)
MACCM2 Resolution: 4° lat x 5° lon x 52 levels (lid at ~0.01 hPa)
GISS II’ Resolution: 4° lat x 5° lon x 23 levels (lid at ~0.01
hPa)
Time Period: DAS met fields Mar. 1997-Feb. 1998, other fields are from GCMs.
Source gases for 1995.
Directory: /pub/gmidata/LLNL/GMI_tracer_runs (tracer experiments only)
This is the ‘original’ GMI study. Three sets of 1-yr met fields
(GEOS-1-DAS, NCAR MACCM2, and GISS II’) were used to simulate a perturbed
and a baseline stratosphere. Temperature and transport diagnostics were developed
and used to evaluate the credibility of the stratosphere in CTM simulations
with these met fields [Douglass et al., 1999]. The MACCM2 winds were identified
as being the most realistic in the northern hemisphere lower stratosphere.
Kinnison et al. [2001] used GMI-MACCM2 simulation to study the effects of
exhaust injected into the lower stratosphere from a supersonic aircraft fleet
on stratospheric ozone.
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