2.1. GOCART Model
 Aerosol simulations in the GOCART model include major tropospheric aerosol types of sulfate, dust, OC, BC, and sea salt. The model uses assimilated meteorological fields from the Goddard Earth Observing System Data Assimilation System (GEOS DAS), containing winds, temperature, pressure, specific and relative humidity, cloud mass flux, cloud fraction, precipitation, boundary layer depth, surface winds, and surface wetness. Physical processes in the model are emission, advection, convection, boundary layer mixing, wet deposition (rainout and washout), dry deposition, and settling. Chemical processes include gas and aqueous phase reactions that convert sulfate precursors (dimethylsulfide and SO2) to sulfate. A dust source parameterization has been constructed in the GOCART model, where locations of the dust sources are determined at the topographic depression areas with bare soil surfaces, while the dust uplifting probability is defined according to the degree of depression. The model simulation of dust aerosol has been found to be consistent with surface, lidar, and satellite observations [Ginoux et al., 2001]. The biomass burning emissions of BC and OC are based on the burned biomass inventory which is estimated using the satellite observations of fire counts and aerosol index [Duncan et al., 2003]. The new biomass burning emissions have since significantly improved the modeled seasonal variations of biomass burning and have made interannual biomass burning simulation possible [Chin et al., 2002]. Detailed description of the model has been presented elsewhere [Chin et al., 2000a, 2000b; Ginoux et al., 2001; Chin and Ginoux, 2002].
 Emissions in our forecast mode were basically the same as described by Chin et al. . Anthropogenic emissions of SO2 were taken from the Emission Database for Global Atmospheric Research [Olivier et al., 1996], and those of BC and OC were from a global data set [Cooke et al., 1999]. We used the climatological biomass burning emissions of BC, OC, and SO2 for March, April, and May, and only considered the continuously erupting volcanic emissions. Sea salt emissions with 4 size bins (0.1–10 μm) were calculated as a function of surface wind speed [Gong et al., 1997; Monahan et al., 1986]. Following Ginoux et al. , emission rates of 7 dust size groups (0.1–6 μm) were calculated as
where Ep is the emission rate for size group p, Sd is the probability source function, which is the probability of sediments accumulated at the topographic depression regions with bare surface, fp is the fraction of size group p within the soil, u is the surface wind speed, and ut is the threshold velocity of wind erosion determined by particle size and surface wetness. Note that while the anthropogenic emission rates were kept constant in the model, dust and sea-salt emissions had very strong temporal variations, depending on surface and meteorological conditions especially wind speed. Figure 1 shows the emissions for April 2001 for sulfur (SO2 and DMS), carbonaceous aerosols (BC + OC), dust, and sea salt in our forecast mode. Updated emissions from sporadically erupting volcanoes, biomass burning, and anthropogenic sources are incorporated in the analysis mode as the information has become available after the field operation. Dust source function Sd in the analysis mode is also modified based on the information from the ACE-Asia measurements (see section 3). These updated emissions (not shown) are currently being used in our postmission analysis mode.
Figure 1. Emissions of aerosols and precursor gases in April 2001 used in the GOCART forecast mode: (a) sulfur (DMS + SO2), (b) carbonaceous (BC + OC), (c) dust, and (d) sea salt.
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 The aerosol optical thickness was determined from the mass concentrations, size distributions, refractive indices, and hygroscopic properties of individual type of aerosols. We assumed lognormal size distributions for sulfate, OC, and BC aerosols with effective dry radii of 0.16, 0.09, and 0.04 μm, respectively, and lognormal size distributions for each discrete dust and sea salt size groups. The wavelength-dependent refractive indices are based on the Global Aerosol Data Set (GADS) [Köpke et al., 1997]. With the exception of dust, aerosols are considered to have different degrees of hygroscopic growth rate with ambient moisture. The hygroscopic growth factors are based on the GADS data and others [d'Almeida, 1991]. For example, at ambient relative humidity (RH) of 80%, the radius of wet sulfate, OC, BC, and sea-salt aerosols are a factor of 1.6, 1.5, 1.2, and 2 larger than their dry size. We assume that dust particle sizes do not change with RH, since dust aerosols contain little hygroscopic material and their radiative properties are relatively insensitive to changes in RH [Li-Jones et al., 1998]. All aerosol particles are treated as external mixtures due to the difficulties and high uncertainties in describing the degree of internal mixing (details of aerosol optical parameters and the calculation of optical thickness in the GOCART model have been provided by Chin et al. ).
2.2. GEOS DAS Meteorological Products
 The meteorological data used to run the GOCART model are generated by the GEOS DAS, which is developed and run operationally by the NASA Goddard Data Assimilation Office (DAO). The GEOS DAS version 3 (GEOS-3) products were used in the model during the 2001 ACE-Asia field experiment. The GEOS-3 system is run by the DAO in two assimilation modes: the First Look assimilation and the Late Look assimilation. The First Look runs 4 times/day, about 8–15 hours behind real time, analyzing meteorological input data from conventional and satellite observations available at the time. The input data include upper air winds, geopotential heights, pressure, total precipitable water, sea-surface winds, sea-surface temperature, and sea-surface ice. The Late Look system configuration is similar to that for the First Look but it runs 2 to 3 weeks behind real time, allowing a more complete set of input observations to be integrated into the assimilation system. The First Look system also produces 5-day (0–120-hour) forecast products twice a day initialized at 0 and 12 hours Universal Time (UT). The forecast products are generated from the same general circulation model used in the assimilation, except that there is no observation data input to the system. The forecast system is initialized by the First Look assimilation output and runs 5 days forward. Table 1 lists the GEOS-3 prognostic and diagnostic fields used in our aerosol forecast and simulations.
Table 1. GEOS-3 Products Used in the GOCART Model
|PS||surface pressure (hPa)||2-D||3||inst|
|SLP||sea level pressure (hPa)||2-D||3||inst|
|SURFTYPE||surface types (water, land, ice, etc.)||2-D||3||inst|
|GWET||soil moisture (% of field capacity)||2-D||3||inst|
|TROPP||tropopause pressure (hPa)||2-D||3||inst|
|UWND||zonal wind (m s−1)||3-D||6||inst|
|VWND||meridional wind (m s−1)||3-D||6||inst|
|SPHU||specific humidity (g kg−1)||3-D||6||inst|
|PREACC||total precipitation (mm day−1)||2-D||3||avg|
|PRECON||convective precipitation (mm day−1)||2-D||3||avg|
|HFLUX||sensible heat flux (W m−2)||2-D||3||avg|
|TGROUND||ground temperature (SST over water) (K)||2-D||3||avg|
|RADSWG||net downward shortwave flux at ground (W m−2)||2-D||3||avg|
|ALBEDO||surface albedo (0–1)||2-D||3||avg|
|USTAR||friction velocity (m s−1)||2-D||3||avg|
|Z0||surface roughness (m)||2-D||3||avg|
|PBL||planetary boundary layer depth (hPa)||2-D||3||avg|
|U10M||zonal wind at 10 meters (m s−1)||2-D||3||avg|
|V10M||meridional wind at 10 meters (m s−1)||2-D||3||avg|
|TAUCLD||cloud optical depth||3-D||6||avg|
|CLDRAS||convective cloud fraction||3-D||6||avg|
|MOISTQ||specific humidity tendency, moist (g kg−1 day−1)||3-D||6||avg|
|DQLS||specific humidity tendency, stratform (g kg−1 day−1)||3-D||6||avg|
|KH||eddy diffusivity coefficient, scalars (m2 s−1)||3-D||6||avg|
|CLDMAS||cloud mass flux (kg m−2 s−1)||3-D||6||avg|
|DTRAIN||detrainment cloud mass flux (kg m−2 s−1)||3-D||6||avg|
2.3. Aerosol Forecast
 During the ACE-Asia period, we used the GEOS-3 First Look assimilation products to initialize the GOCART model, and the First Look 0 UT forecast products to generate aerosol forecast products. The DAO provided the forecast products at 2° × 2.5° horizontal resolution, while the assimilated products were at 1° × 1°. We regridded the 1° × 1° assimilated GEOS-3 data to 2° × 2.5° grid in order to obtain a consistent resolution and reduce the computational time. The vertical resolution in the original GEOS-3 data contains 48 sigma layers, with 22 layers above 30 mb. We aggregated the top 22 layers into 4 to reduce the total number of layers to 30 in our tropospheric simulations. The model layer thickness increases gradually from surface to the model top. Below 3 km, the vertical resolution varies from 24 m to 900 m. Above 3 km, the vertical resolution changes from 1 km to about 1.5 km near the tropopause. The GOCART model products were in the same spatial resolution as the meteorological data (i.e., 2° × 2.5°, or about 200 km in midlatitudes, and 30 vertical layers), and were saved every 3 hours. Table 2 lists our 24–96-hour forecast products provided for the field operations.
Table 2. GOCART Model Forecast Products
|Forecast Product||Forecast Frequency, Hours|
|Latitude-longitude distributions:|| |
| optical thickness of individual and total aerosols||3|
| column burden (g m−2) of individual aerosol species||3|
|Latitudinal cross section at 125°E, 135°E, and 140°E:|| |
| total Aerosol extinction (km−1)||3|
| individual aerosol concentration (g m−3)||3|
|Longitudinal cross section at 30°N and 40°N:|| |
| total Aerosol extinction (km−1)||3|
| individual aerosol concentration (g m−3)||3|
|Meteorological variables (GEOS DAS):|| |
| low-level (700–1000 mb), midlevel (400–700 mb), and high-level (above 400 mb) cloud cover||3|
| total precipitation (mm day−1)||3|
| wind speed and direction at 0.1 km and 4 km||6|
|Global distributions:|| |
| optical thickness for individual and total aerosols||3|
| concentration of sulfate and dust at 0.1, 4, and 6 km||3|
 Our daily forecast procedure involved processing the GEOS-3 data, running the GOCART forecast model, generating figures and animation, providing results on the Website as well as to the Joint Office of Science Support (JOSS) field catalog for easy access in the operation field, and, finally, briefing the science team in the Operations Center for flight planning. The daily operational procedure is illustrated in Figure 2.