Relation to EOS Program and Goals of USGCRP
Our Interdisciplinary Science Investigation covers modeling and data analysis efforts to improve understanding of coupling processes between atmospheric chemistry and climate. We address two major elements of the EOS Science Strategy -- (1) Clouds, Radiation, Water Vapor, and Precipitation and (2) Greenhouse Gases and Tropospheric Chemistry.
The project is strongly tied to the highest priority items in the USGCRP framework-Climate and Hydrologic Systems and Biogeochemical Dynamics. These two research areas are linked together in our investigation of the role of clouds in atmospheric processing of trace species. Our focus on the processes that control the vertical distribution of atmospheric constituents is vital to the USGCRP's "integrating priority" of "Focused Studies of Controlling Processes".
Science Background
Deep convection and stratosphere-troposphere exchange (STE) processes cause substantial changes in the vertical profiles of trace gases and aerosols which, in turn, have effects on the actinic flux and on the radiative forcing of climate. These transport processes develop on small spatial scales but are globally important and strongly influence the budgets of many species. However, these smaller-scale hydrodynamical effects and nonhydrostatic motions are typically not well represented in state-of-the-art GCMs. For example, considerable uncertainty is associated with parameterization of deep convection in GCMs. A variety of other models, submodels, and algorithms are available to evaluate convection and STE in a GCM and to further enhance the GCM.
Science Goal
The Goddard Earth Observing System Stretched-grid GCM (GEOS-SGCM) and the Goddard Cumulus Ensemble model will be used to investigate tropospheric convective mixing and STE effects and the ability of GCM parameterizations to accurately represent these effects at various horizontal resolutions. Development of the SGCM is underway under separate funding. Comparisons on a case-study basis between the cloud-resolving GCE model and GEOS-SGCM will allow evaluation of GCM convective parameterizations. Addition of chemical transport to both models, and a detailed spectral radiative scheme to the GCE model will allow estimation of the effects of mixing events on regional- and global-scale chemical budgets and radiative heating. The sensitivity of global chemical budgets and related climate characteristics to uncertainties in model description of convection and STE will be estimated.
Current Activities
A stretched-grid feature is being added to the Goddard Chemical Transport Model (GCTM) in preparation for eventual coupling with the GEOS SGCM. A fast chemical solver and associated chemical mechanisms are being prepared for coupling with the GCE and GCTM. Calculated photolysis rates using actinic flux from the DISORT code are being compared with measurements. Aircraft and satellite data sets for use in case study simulations are being identified, acquired, and reviewed.
Use of Satellite Data
Because CO is an excellent tracer of convective transport, the MAPS CO data will be very useful for the proposed simulations. Similarly, after EOS-AM launch, MOPITT CO will also be extremely valuable. TOMS total ozone data will be used in the calculation of photolysis rates, and TOMS-derived tropospheric ozone will be used in tropical case studies. When CERES and MODIS cloud products become available, we plan to use them in model verification.
Participation in Field Programs
Pickering and Stenchikov participated in the STERAO-A deep convection experiment in 1996. Pickering also took part in the GTE/TRACE-A mission in 1992 and is a participant in the 1997 SONEX mission. Dickerson is a key participant in AEROCE and INDOEX field missions. Our initial simulations with the stretched-grid GCTM will be conducted for periods during the TRACE-A and AEROCE field studies.
Project Structure
The following
diagram
demonstrates the interrelationships between model components. The phases of the project include (1) implementation of the stretched grid design in the GCTM, (2) implementation of a chemistry code in the GCTM, and (3) interactive calculations using the GCTM with the latest version fixed grid GEOS-GCM. Results of each of these steps have their own scientific value. Individual modules will be tested and applied to case studies of observed vertical mixing events. These steps will prepare us for integration of all modules into SGCM.Stretched grid GCM (SGCM): Global calculations with high local resolution
Low spatial resolution is the most important restriction in description of vertical atmospheric mixing caused by convection or frontal activity. Models with high resolution on the entire Earth require excessive computer resources. The nesting technique fails to describe correctly the interaction of the fine resolution region with the external coarse resolution domain over longer term calculations. Therefore based on the finite difference Goddard Earth Observing System (GEOS) General Circulation Model (GCM) we are developing a GCM with variable spatial resolution which can be focused on a specific region. It allows us to calculate regional mixing events with high spatial resolution and then look at the large-scale transport of trace gases accounting for their chemical transformations. Different numerical approaches to calculate global atmospheric circulation with variable resolution have been developed by Gravel and Staniforth (1992), Cote et al. (1993), Courtier and Geleyn (1988), and Deque and Piedelievre (1995).
The GEOS GCM was developed by the Data Assimilation Office (DAO) at the Goddard Laboratory for Atmospheres (GLA), in cooperation with the Climate and Radiation Branch, for use in the system being developed to analyze EOS data. The GEOS GCM has been documented by Takacs et al. (1994). The GEOS Data Assimilation System (DAS), currently using the GEOS-1 GCM in conjunction with an Optimal Interpolation analysis scheme, has been used to produce a multi-year global atmospheric data set for climate research (Schubert et al., 1993). The GEOS-1 GCM has also been used to produce multiple 10-year climate simulations for the Atmospheric Model Intercomparison Project (AMIP, Gates, 1992). The model was developed based on the "plug compatible" concept (Kalnay et al., 1989) and provided with a library of physical parameterizations. This structure simplifies model modifications and new version construction. The GEOS GCM uses the modified Sadourny (1975) finite difference scheme with advanced conservative characteristics (Burridge and Haseler, 1977). The time difference scheme in the version used here is based on leap-frog method in combination with "economical explicit" tendencies of (Brown and Campana, 1978). The vertical finite difference approximation is the same as Arakawa and Suarez (1983). The solar radiative transport scheme (Harshvardhan, 1987) is being modified to include explicit aerosol radiative effects (Ming-Dah Chou, personal communication concerning development of GEOS-2). The convection and clouds are parameterized using the Relaxed ArakawaSchubert scheme (Moorthi and Suarez, 1992). The planetary boundary layer is explicitly resolved and based on the MoninObuhov similarity theory. Turbulent mixing is calculated using the second order closure model of Helfand and Labraga (1988). Surface roughness lengths are defined by the vegetation type. The land surface vegetation model accounts for subgrid parameter variability (Koster and Suarez, 1992) and is based on the SiB model (Sellers et al., 1986). Transport of constituents is performed with a semi-Lagrangian scheme.
The stretched grid version of the GEOS GCM (SGCM) is being developed by Co-I Fox-Rabinovitz and Co-PI Stenchikov in cooperation with M. Suarez and L. Takacs of NASA/GSFC. The model is designed to concentrate the spatial resolution in a particular region of interest. The region of interest with a very high spatial resolution may be located any place on the globe, for example the Great Plains of the United States. The horizontal spatial resolution becomes coarser uniformly as a function of distance from the region of interest. This model needs one to two orders of magnitude less grid points compared with a uniform fine grid model.
SGCM is an ideal tool to calculate regional to global scale interactions. It can focus model resolution on the region of particular observed events and will be very useful to test the sensitivity of the GCM parameterizations to spatial resolution, as well as to estimate of input of specific events into the global chemical and radiative budgets. We will enhance the SGCM by incorporating gas-phase chemistry, aerosol transport and removal, as well as calculation of actinic fluxes. We will apply this model in simulations of observed STE and tropospheric mixing events, using a variety of different horizontal resolutions in the region of the event. The results will provide information about the quality of parameterizations and the importance of the small-scale tropospheric mixing and STE processes for global and regional chemical budgets and climate.
Because of the ability to focus spatial resolution in any specific region, running the SGCM is ideal for regional chemistry/climate studies using observed data from regional field projects. The stretched grid approach automatically provides two-way interaction between the region of interest and external regions. It does not need the artificial boundary conditions as do nested grid methods. These features are especially important in the calculations of local mixing and STE effects on larger scale chemical and climate processes. Until now the SGCM has been developed on the basis of the plug compatible ARIES/GEOS Dynamical Core (Suarez and Takacs, 1995) and has used simplified diabatics (Held and Suarez, 1994). Numerical experiments have shown that dynamical processes are described correctly even for a large stretching factor. The numerical problems become more severe as this ratio increases. Numerical experiments have been conducted with the ratio of the maximum to minimum spatial resolution increasing up to a value of 32 (e.g., from 0.25x0.3 to 8x10). In the region of interest it provides even better spatial resolution then one of the best operational regional weather forecasting (ETA; Mesinger et al., 1995) models.
Figure descriptions
Fig. 1 and Fig. 2 demonstrate the stretched grids focused on different regions of interest (Great Plains region and INDOEX experiment region, respectively) and approximate land elevation. Because of graphic restrictions not all grid lines are shown. The finest resolution in the region of interest used in calculations was 25 km. The largest ratio of maximum to minimum grid spacing was 32.
Recent Publications
Fox-Rabinovitz, M. S., G. L. Stenchikov, M. J. Suarez, and L. L. Takacs, A finite difference GCM dynamical core with a variable resolution stretched grid, submitted to Monthly Weather Review, 1996.
Goddard Cumulus Ensemble (GCE) Model: Convective mixing and STE
Small-scale convection and cloudiness play an important role in the global atmospheric energetic and chemical balances. Chatfield and Crutzen (1984) hypothesized that deep convection is a major redistributor of trace gases from the boundary layer to the free troposphere, and Dickerson et al. (1987) presented observational evidence that such redistribution occurs. Pickering et al. (1990) showed that transport of ozone precursor gases to the middle and upper troposphere by deep continental convection substantially enhances ozone production in the cloud outflow especially with entrainment of urban plumes or fresh biomass burning plumes into convective cells (Pickering et al., 1992a; 1992b; 1996). In other conditions deep convection transports larger O3 and NOx mixing ratios downward to altitudes where O3 destruction is more rapid (Lelieveld and Crutzen, 1994; Pickering et al, 1993).
Existing cloud parameterizations in a GCM only account very crudely for cloud dynamics and microphysics, and the effects of clouds on the vertical transport of chemically- and optically-active pollutants and water vapor (Mote et al., 1994; Holton et al., 1995), which influence directly the atmospheric chemistry and radiative balance. To evaluate these effects of small-scale deep convective mixing on global chemical fields we use the NASA Goddard Cumulus Ensemble (GCE) Model (Tao and Simpson, 1993).
The GCE model is non-hydrostatic and explicitly calculates vertical convective transport in an ensemble of individual clouds and includes detailed calculations of cloud microphysics, yielding a regional representation of the effects of convection and STE. Model variables include horizontal and vertical velocities, potential temperature, mixing ratio of water vapor, cloud water, rain, cloud ice, snow, and hail/graupel. Cloudscale motions are assumed to be anelastically balanced by neglecting the local variation of air density with time. A Kesslertype twocategory liquid water (cloud water and rain) microphysical parameterization is currently used with a choice of two threecategory ice formulations. An improved fourclass, multiplemoment ice scheme (4ICE) has also been developed (Ferrier, 1994) and tested for several convective systems in different geographic locations (Ferrier et al., 1995). Solar and infrared radiative transfer processes have been included and their impact on cloud development and organization has been assessed (Tao et al., 1993, 1995). Microscale turbulent mixing processes are incorporated in the form of eddy diffusion which is computed using a turbulent kinetic energy equation. A version of the 2-D GCE model has been implemented on a DEC-ALPHA workstation in the Meteorology Department at the University of Maryland (Stenchikov et al, 1996).
We have applied the University of MD 2-D version of this model for a case study (Stenchikov et al., 1996) of a strong convective storm over the Great Plains in North Dakota on June 28-29, 1989, observed in detail during the North Dakota Thunderstorm Project (NDTP, Boe et al., 1992), and to investigate the convective amplification of tropospheric ozone production (Ellis et al., 1996). Below we describe the NDTP case study in more detail. The GCE model was used to describe processes in a cross section, perpendicular to the squall line and a reasonable distance from its ends. The squall line moved with a speed of the order of 50 km/hr in a direction perpendicular to the line, evolved into a major mesoscale convective complex (MCC), and lasted more than 2 days as indicated by satellite images. We chose a domain of ~1000 km in order to calculate the storm evolution and total vertical trace gas transport by convection into the extensive anvil for 12 hr and to decrease the lateral boundary condition effects. The numerical simulation was conducted with a spatial resolution of the order of ~1 km and a 31-node nonuniform vertical grid. The transport of CO, O3, and NOx, as well as water vapor and hydrometeors, was included.
Mixing across the tropopause due to intense convective events may significantly influence the atmospheric chemical balance. Stratosphere-troposphere exchange acts as an important natural source of O3 in the troposphere, and a source of H2O, HCs, CFCs, HCFCs and reactive nitrogen in the stratosphere. The redistribution of atmospheric trace gases produces secondary radiative, dynamical and climate effects, influencing lower stratospheric temperatures and the tropopause height. The model simulations well reproduced the unusual feature of the observed severe storm, an anvil formed well within the stratosphere. The simulation produced strong vertical mixing of atmospheric trace gases including H2O, CO, O3 and NOy; CO mixing ratios in the anvil matched the observations. Fig. 3 shows the spatial structure of the flow and distributions of the trace gases and hydrometeors at 8 hours into convective activity. The convective cell lifted much of the boundary layer CO into the giant anvil and a significant amount of ozone was transported by downdrafts behind the main convective cell into the troposphere (Fig. 3a). The streamlines on Fig. 3b show the classical structure of the flow in the convection. The concentration of the solid hydrometeors (ice, snow, and graupel) reached the observed value of 2 g/kg (Fig. 3c) in the central part of the anvil. If the chemistry and dynamics of this storm are typical of the roughly 100 MCCs occurring annually over the midlatitudes, then this mechanism plays an important role in CO, NOy, and O3 budgets and could be the dominant source of H2O in the lower stratosphere and upper troposphere over midlatitudes.
For the purposes of this project we will enhance the GCE model by incorporating chemistry, aerosol transport and removal, as well as calculation of actinic fluxes. We will calculate aerosol optical characteristics using Mie theory and will evaluate the aerosol effects on the radiative heating and actinic fluxes. An existing detailed spectral radiation scheme will be added to the GCE model. We plan to transport water vapor, aerosols, and species that are important for ozone photochemistry and sulfate production (e.g., NOx, NMHC, CO, O3, SO2, DMS, other S gases, etc.). We will apply this model in simulations of observed STE and tropospheric mixing events. The results will provide information about the quality of parameterizations and the importance of the small-scale tropospheric mixing and STE processes for global and regional chemical budgets and climate.
Figure description
Fig. 3 . Spatial structure of the trace gas and frozen hydrometeor transport as calculated by the model at 8 hours after beginning of the convection: (a) mixing ratios(ppbv) of CO (shaded) and ozone (isolines), (b) stream lines, © total solid hydrometeor (ice+snow+graupel) mixing ratio (g/kg).
Recent publications
Poulida, O., R. R. Dickerson, and A. Heymsfield, 1996: Troposphere-stratosphere exchange in a midlatitude mesoscale convective complex: Part 1. Observations, J. Geophys. Res., 101, 6823-6836.
Stenchikov, G., R. Dickerson, K. Pickering, W. Ellis Jr., B. Doddridge, S. Kondragunta, and O. Poulida, 1996: Stratosphere-troposphere exchange in a midlatitude mesoscale convective complex. 2. Numerical simulation, J. Geophys. Res., 101, 6837-6851.
Ellis, W. G., Jr., A. M. Thompson, S. Kondragunta, K. E. Pickering, G. Stenchikov, R. R. Dickerson, and W.-K. Tao, 1996: Potential ozone production following convective transport based on future emission scenarios. Atm. Environment, 30, 667-672.
The Goddard chemistry and transport model: Transport of trace species
Transport by large and small scale processes plays a large role in determining the distribution of trace gases. The effect of transport and chemistry on the global distribution of chemical species will be investigated using the Goddard chemistry and transport model (GCTM). The GCTM is used to solve the constituent continuity equation. The constituent continuity equation describes the effect of large-scale (advection) and small scale (moist convection, turbulence, and chemistry) processes on the distribution of trace gases.
Large-scale transport by the wind is solved using a multidimensional and semi-Lagrangian extension of the piecewise parabolic method (PPM) (Lin and Rood, 1996). This algorithm maintains the conservation and monotonic properties of the traditional upstream-biased Eulerian PPM algorithm while avoiding the constraints of the Courant-Friedrichs-Lewy (CFL) stability condition. Large-scale transport may be calculated using winds from a GCM or data assimilation system.
Deep convective mixing associated with moist convection is capable of moving trace gases from the planetary boundary layer (PBL) to upper troposphere in a few hours. Because it occurs on small spatial scales, its effect must be parameterized. The GCTM is one of the first to include a parameterization of deep convective mixing. Deep convective mixing in the GCTM is calculated using convective mass fluxes from the Relaxed Arakawa-Schubert (RAS) algorithm (Moorthi and Suarez, 1992) that is used to parameterize moist convection in the Goddard Earth Observing System Atmospheric General Circulation Model (GEOS AGCM) (Takacs et al., 1994).
Turbulent mixing is an efficient transport mechanism in the PBL. Turbulent mixing in the GCTM is parameterized by mixing a fraction (a ) of material in the lowest model layer uniformly through the PBL each time step. The PBL depth is obtained from the GEOS AGCM. The algorithm results in a well-mixed PBL for a equal to one and an unmixed PBL for a equal to zero.
Chemical transformations also affect trace gas concentrations. Past calculations with the GCTM have used parameterized chemistry; however, an efficient version of Gear's predictor corrector method (SMVGEAR) (Jacobson and Turco, 1994) is currently being added to the GCTM in order to study processes where a more realistic representation of chemistry is needed.
Calculations with the GCTM
We investigated the distributions of Rn-222 (Allen et al., 1996a) and carbon monoxide (CO) (Allen et al., 1996b) using a twenty layer, 2° in latitude by 2.5° in longitude version of the GCTM. The GCTM was driven in an off-line fashion by assimilated data from the Goddard Earth Observing System data assimilation system (GEOS-1 DAS) [Schubert et al., 1995]. The main components of this system are the GEOS-1 AGCM and an analysis scheme that is used to blend AGCM output with atmospheric observations. The GEOS-1 DAS fields used to solve the continuity equation are the horizontal wind, surface pressure, temperature, PBL depth, convective mass flux, and convective detrainment. These calculations are unique because convective mass fluxes from the driving model were archived and used to calculate deep convective mixing in the GCTM. The GEOS-1 DAS data set is unique because the analysis system used to produce it was held constant throughout the assimilation period. The Rn-222 and CO calculations were a test of how well the GCTM simulates pollutant export and ventilation of the boundary layer when driven by GEOS-1 DAS data. Model-calculated and measured concentrations of Rn-222 at Bermuda [Hutter et al., 1995] and CO at Mace Head, Ireland [Doddridge et al., 1994] are shown in Figures 4a and 4b. The excellent agreement between model-calculated and measured values provides compelling evidence that the location of atmospheric waves is well captured by the GEOS-1 DAS and that export of pollutants and ventilation of the midlatitude PBL is well simulated.
Model-calculated mid-troposphere CO concentrations during April and October are compared to MAPS measurements in Figures 5a and 5b [Connors et al., 1996]. Model-calculated concentrations are within a standard deviation of measured concentrations at nearly all latitudes during both seasons, although the shapes of the distributions vary significantly due to several factors including errors in the specification of sources and the tendency of the deep convective mixing algorithm in the GCTM to move material from the PBL to the upper troposphere directly resulting in an underestimation of concentrations in the midtroposphere.
Future plans
The SMVGEAR algorithm is currently being added to the GCTM. The addition of this algorithm will allow the GCTM to be used to study processes where chemical transformations are important. In addition, the GCTM is currently being modified so that it can be run in an on-line mode within the GEOS AGCM. This will allow the GCTM to be used to study radiatively active trace gases. The GCTM is also being modified to accept as input dynamical fields from the 70 layer GEOS-2 and 46 layer STRATAN data assimilation systems.
Finally, a stretched grid version of the GCTM is under development. A stretched grid version of the GCTM is ideal for studying the effect of small scale processes on the large-scale distribution of trace gases. This model will be capable of being run on-line within the GEOS Stretched Grid GCM (GEOS SGCM) or off-line. The off-line version is useful because it is less expensive to run and can be used before development of the GEOS SGCM is completed.
Figure descriptions
Fig. 4. a) Surface layer Rn-222 (pCi/SCM) at Bermuda during January 1992. Data (X's) includes periods when local contamination is unlikely. b) Time series of CO (ppbv) for August 1991 through January 1993 at Mace Head, Ireland. Measurements are shown with asterisks. In both plots, model output (solid lines) is sampled every six hours.
Fig. 5. MAPS CO (the shaded range shows mean (solid line) +/- 1 sigma) and 500 hPa model-calculated CO (dashed line). MAPS data are composite for April 9-19, 1994, and September 30 to October 11, 1994.. Model fields are 1989-1993 means for April and October. Units are ppbv.
Recent Publications
Allen, D. J., R. B. Rood, A. M. Thompson, and R. D. Hudson, Three-dimensional Rn-222 calculations using assimilated meteorological data and a convective mixing algorithm, J. Geophys. Res., 101, 6871-6881, 1996a.
Allen, D. J., P. Kasibhatla, A. M. Thompson, R. B. Rood, B. G. Doddridge, K. E. Pickering, R. D. Hudson, and S.-J. Lin, Transport-induced interannual variability of carbon monoxide determined using a chemistry and transport model, J. Geophys. Res., 101, 28655-28669, 1996b.
Chemical Models: Calculation of chemical species mixing ratios and production/loss rates
We plan to implement a chemical solver in the Goddard Chemistry and Transport Model (GCTM) and in the Goddard Cumulus Ensemble (GCE) model. There will be two chemical mechanisms and a numerical chemical solver available to the project. The Jacobson routines (Jacobson, 1994; Jacobson and Turco, 1994; Jacobson, 1995) include a fast chemistry solver (SMVGEAR II) for gas-phase and aqueous-phase reactions. SMVGEAR II is a sparse-matrix, vectorized Gear Code that rapidly solves stiff first order ordinary differential equations over large grid domains. The chemistry solver is a three-dimensional model, for which the grid location and size are changeable and the horizontal grid cell resolution is expandable and contractible. SMVGEAR II is structured such that species and reactions can easily be removed to simplify the chemistry.
The Jacobson chemical scheme provides options of gas-phase chemical mechanisms appropriate for polluted boundary layer, clean free tropospheric, or stratospheric regimes. There are a total of 246 kinetic reactions and 45 photolytic reactions. The chemistry model can be run in either of three modes: box, column, or global. We are currently running the Jacobson mechanisms and solver on our workstations at the University of Maryland.
The second gas-phase chemical mechanism, which is appropriate for free tropospheric conditions, is that of A. M. Thompson of NASA Goddard. This scheme (Thompson and Cicerone, 1982; Pickering et al., 1990) contains standard CO/NOx/CH4/O3 reactions, as well as oxidation reactions for ethane, ethene, propane, propene, toluene, and acetylene. Isoprene oxidation is included as an option. We plan to implement the Thompson scheme with the Jacobson solver. This approach will allow chemical calculations that are compatible with the results obtained in the previous work described below.
We conducted a series of simulations of deep convective events with the Goddard Cumulus Ensemble (GCE) model (Tao and Simpson, 1993), using the model winds to transport trace gases. Subsequently, we used the Thompson NASA Goddard tropospheric chemistry models in estimating the perturbations to ozone production in the free troposphere caused by deep convection. Once boundary layer NOx is diluted in the free troposphere, O3 production proceeds more efficiently (Liu et al., 1987). Results from analyses by Pickering et al. (1990; 1992b,c; 1993), summarized by Pickering et al. (1994), are depicted in Figure 6. The convective enhancement factor for ozone production in cloud outflow in these case studies ranged from slightly less than 1.0 for a low NOx tropical marine environment to a factor of >50 for a case of fresh biomass burning pollution lofted into a pristine free troposphere. We used the box model version of the NASA Goddard mechanism to compute ozone production during 8 days of transport downwind of major convective systems over Brazil during the biomass burning season (Pickering et al., 1996). These results are demonstrated in Figure 7.
Figure Descriptions
Fig. 6. Summary of ozone production convective enhancement factors (CEF) for cloud outflow regions of simulated case-study convective events (Pickering et al., 1994). CEF is computed as the ratio of the column rate of O3 production in cloud-processed air to that in undisturbed air, as calculated with the NASA Goddard 1-D tropospheric chemistry model.
Fig. 7. Cumulative net ozone production computed with NASA Goddard tropospheric chemistry box model downstream of September 26-27, 1992, Brazilian convective systems during TRACE-A is noted at 24-hour intervals (denoted by crosses) along a characteristic forward trajectory. First value for each day is cumulative production using highest 9-minute average cloud outflow mixing ratios at 11.3 km as initial conditions; second value is cumulative production using highest 9-minute average cloud outflow data at 9.5 km. Asterisks show locations of measurements; increments in measured ozone mixing ratios obtained by comparing TRACE-A DC-8 flights 6 and 7 and by comparing Natal, Brazil ozonesonde profiles from September 28 and 30, 1992.
Recent Publications
Pickering, K. E., et al., Convective transport of biomass burning emissions over Brazil during TRACE-A, J. Geophys. Res., 101, 23,993-24,012, 1996.
Radiative Models: Radiative Heating and Photochemistry
Radiative effects are important for two main aspects of our study: (1) for calculation of radiative energetical effects that may be forcing factors for climate and (2) for calculations of actinic flux that are necessary for photochemical modeling. We plan to include these features in the GCE model, such that longer-term calculations accounting for aerosol and optically active trace gases can be performed. Actinic flux off-line calculations will also be added to the SGCM. For heating rate calculations in longer-term simulations with the GCE model, we will employ the radiative scheme used in the Goddard Earth Observing System (GEOS-2) GCM (Chou, 1992; Chou and Suarez, 1994; Takacs et al., 1994). This scheme contains 21 spectral intervals and has been modified to account for aerosols and optically active trace gases. We have calculated volcanic aerosol forcing using this model and compared results with Morcrett scheme calculations. The two-stream and delta-Eddington approximations, which work well for calculation of energetic radiation fluxes, may produce up to a 30% error in calculation of actinic fluxes (Ruggaber et al., 1993; 1994), because of insufficient azimuthal angle approximation of the light intensities. Therefore in our calculations we use the discrete ordinate model with 16 ordinates (DISORT, Stamnes et al., 1988), which gives 1-2% accuracy ( Kondragunta et al., 1995). With this model we have calculated photochemical ozone production for the July 15, 1995 East Coast episode, when the observed ozone concentration was very high and exceeded federal air quality standards. We used the routinely observed aerosol size distributions (Kaufman et al., 1994) with the same refractive index for ammonium sulfate Ri = 1.45-0.005i as used in the retrieval procedure, and calculated aerosol spectral extinction and phase function using the Mie package (Wiscombe, 1980). The calculated NO2 photolysis rates correspond very well to the observed ones.
Figure description
Fig. 8. Comparison of calculated and measured NO2 photolysis rate j(NO2) for a wide range of aerosol optical depths tau 0.0<tau<2.0 at =0.38m. The root mean square error is 3.2410-4 and the correlation coefficient is 0.99.
Fig. 9. Vertical profiles of j(NO2). Aircraft measurements (Kelly et al., 1995) at 58 solar zenith angle are marked by dots. Calculated curves (a-e) correspond to 58 solar zenith angle, and optical depths =0. (a), =0.5 (b), =1.0 ©, =1.5 (d), =2.0 (e). Curves (f-j) are for 0 solar zenith angle, and aerosol optical depth =0 (f), =0.5 (g), =1.0 (h), =1.5 (i), =2.0(j).
Fig. 10. UAM-V model simulations of increase in ozone mixing ratio (ppbv) in the boundary layer on July 14, 1995 caused by aerosol. In calculations we used the observed aerosol size distribution for July 15, 1995 scaled to get =2.0 for =0.38m. The aerosol was distributed from the surface to 360 m. The emissions were taken from 1990 emission inventory projected to episodic days in July, 1995. Wind fields are generated by RAMS. The photolysis rates were calculated for the standard mid-latitude summer atmosphere.
Recent publication
Dickerson, R. R., S. Kondragunta, G. Stenchikov, B. Doddridge, W. F. Ryan, B. Holben, The impact of aerosols on photochemical smog production, to be submitted to Science, 1997.
References
Allen, D. J., et al., Three-dimensional Rn-222 calculations using assimilated meteorological data and a convective mixing algorithm, J. Geophys. Res., 101, 6871-6881, 1996a.
Allen, D. J., et al., Transport-induced interannual variability of carbon monoxide determined using a chemistry and transport model, J. Geophys. Res., 101, 28655-28669, 1996b.
Arakawa, A., and M. J. Suarez, Vertical differencing of the primitive equations in sigma coordinates, Mon. Wea. Rev., 111, 3445, 1983.
Brown, J. and K. Campana, An economical time-differencing system for numerical weather prediction, Mon. Wea. Rev., 106, 1125-1136, 1978.
Burridge, D. M. and J. Haseler, A model for medium range weather forecastingadiabatic formulation, Tech. Rep. No. 4, European Centre for Medium Range Weather Forecasts, Bracknell, Berks, U. K., 46 pp., 1977.
Chatfield, R. B. and P. J. Crutzen, 1984: Sulfur dioxide in remote oceanic air: Cloud transport of reactive precursors, J. Geophys. Res., 89, 7111-7132.
Chou, M. D.,and Max J. Suarez, 1994: An efficient thermal infrared radiation parameterization for use in general circulation models, NASA Technical Memorandum 104606, Vol. 3, Technical Report Series on Global Modeling and Data Assimilation, (Goddard Space Flight Center, Greenbelt, Maryland), 85 pp.
Chou, M. D., 1992: A solar radiation model for use in climate studies, J. Atmos. Sci., 49, 762-772.
Connors, V., et al., Global distributions of biomass burning and carbon monoxide in the middle troposphere during early April and October 1994, in Proceedings of the Chapman Conference on Biomass Burning and Global Change, MIT Press, Cambridge, Mass., in press, 1996.
Cote, J., M. Roch, A. Staniforth, and L. Fillion, A variable resolution semi-lagrangian finate-element global model of the shallow-water equations, Mon. Wea. Rev., 121, 231-243, 1993.
Courtier, P. and J. Geleyn, A global numerical weather prediction model with variable resolution: Application to the shallow-water equations, Q. J. R. Meteorol. Soc., 114, 1321-1346, 1988.
Deque, M. and J. Piedelievre, High resolution climate simulation over Europe, Climate Dynamics, 11, 321-339, 1995.
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