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Penner, Joyce

Publications and source records attributed to Penner, Joyce.

Comparisons of global aerosol simulations from GOCART and GMI-UMich

Global aerosol mass and optical thickness (AOT) simulated by two aerosol models (GOCART and GMI-UMich) are evaluated and the strengths and shortcomings of the model approaches are investigated. These two offline CTM models are driven by the same meteorological fields (NASA GEOS-4), use the same dynamic transport algorithm, and have the same spatial resolution. However, they differ partially in emission, dry/wet deposition, and chemistry. The simulated aerosol masses are evaluated by the surface long-term measurements and short-term field campaigns (ACE-Asia and TRACE-P). AOT are calculated using modeled aerosol mass but externally mixed for GOCART and partially internally mixed for GMI-Mich. These AOT are evaluated using satellite observations from MODIS and MISR and ground measurements from AERONET. Our work demonstrates that there are significant differences in simulated aerosol mass and AOT by the two approaches. Further investigation will be performed to evaluate each mechanism which induces the differences quantitatively by implementing GOCART-like emission, deposition, and chemistry into GMI framework.

Bian, Huisheng↗

The Study of Biomass Emissions for Defining Radiative Forcing of Climate

Accurate quantification of the amounts of trace gases and particulate matter emitted from vegetation fires and other sources of biomass burning (agricultural waste and biofuels) on a regional and global basis is required by a number of users, including scientists studying a wide range of atmospheric processes, national governments who are required to report greenhouse gas emissions, and those interested in quantifying the sources of air pollution that affect human health at regional scales. Over the past decade, improvements in the ability to detect and map fires using a number of different satellite systems have been achieved, largely through efforts coordinated through working groups organized by the IGBP Data and Information System and Global Observation of Forest Cover (GOFC) projects. In addition, significant advances and improvement in or understanding of the emissions factors for biomass burning in different biomes has resulted through efforts by the Biomass Burning Experiment (BIBEX) organized through the International Global Atmospheric Chemistry project. A number of satellite-based fire data products have been generated, and a number of new products will shortly be available. These new data products will provide the basis for estimating emissions from biomass burning on a global basis. However, a number of issues remain concerning the availability of other data sets needed to generate these estimates. Recognizing these issues, the GOFC-Fire Satellite Validation Workshop (held in Lisbon, Portugal on 9-11 July 2001), recommended that a workshop focusing on Improving Global Estimates of Atmospheric Emissions from Biomass Burning be organized. This workshop was held from 17- 19 July 2002 on the campus of the University of Maryland, College Park, Maryland. This workshop served as the annual meeting of the GOFC/GOLD-Fire Program. The overall goals of the meeting were to review the information products generated from satellite imagery and other sources that are currently available for developing emission estimates from biomass burning, evaluate areas where improved or additional products would be beneficial, and recommend products for use by the atmospheric science community.

Penner, Joyce↗

Modeling the Absorbing Aerosol Index

We propose a scheme to model the absorbing aerosol index and improve the biomass carbon inventories by optimizing the difference between TOMS aerosol index (AI) and modeled AI with an inverse model. Two absorbing aerosol types are considered, including biomass carbon and mineral dust. A priori biomass carbon source was generated by Liousse et al [1996]. Mineral dust emission is parameterized according to surface wind and soil moisture using the method developed by Ginoux [2000]. In this initial study, the coupled CCM1 and GRANTOUR model was used to determine the aerosol spatial and temporal distribution. With modeled aerosol concentrations and optical properties, we calculate the radiance at the top of the atmosphere at 340 nm and 380 nm with a radiative transfer model. The contrast of radiance at these two wavelengths will be used to calculate AI. Then we compare the modeled AI with TOMS AI. This paper reports our initial modeling for AI and its comparison with TOMS Nimbus 7 AI. For our follow-on project we will model the global AI with aerosol spatial and temporal distribution recomputed from the IMPACT model and DAO GEOS-1 meteorology fields. Then we will build an inverse model, which applies a Bayesian inverse technique to optimize the agreement of between model and observational data. The inverse model will tune the biomass burning source strength to reduce the difference between modelled AI and TOMS AI. Further simulations with a posteriori biomass carbon sources from the inverse model will be carried out. Results will be compared to available observations such as surface concentration and aerosol optical depth.

Penner, Joyce↗