The September 2010 PIESA/Aerosol Experiments: Difference between revisions
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== Introduction == | == Introduction == | ||
This document is a summary of the GMAO Recovery Act Projects subtask ''Progress towards an Integrated Earth System Analysis''. | This document is a summary of the GMAO Recovery Act Projects subtask ''Progress towards an Integrated Earth System Analysis''. | ||
GMAO | GMAO staff, in collaboration with the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC, conducted simulations of aerosol distributions in the atmosphere using the [http://geos5.org/wiki/index.php?title=GEOS-5_System_Overview GEOS-5] modeling and data assimilation system coupled with the GOCART aerosol module. Realistic transport of simulated aerosols was achieved by ingesting [http://gmao.gsfc.nasa.gov/merra/ Modern Era Retrospective-analysis for Research and Applications] (MERRA) meteorological fields (referred to as ''replay'' technique). | ||
== System Configuration == | == System Configuration == | ||
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The QFED emissions are based on the ''top-down'' approach that uses the fact that the fire radiative power (FRP) at the top of the atmosphere is proportional to the rate of organic/vegetation mass that is burning. On the other hand, the emission of gasses and particulate matter released during burning is proportional to the consumed mass, hence the emissions rates are proportional to the measured FRP. | The QFED emissions are based on the ''top-down'' approach that uses the fact that the fire radiative power (FRP) at the top of the atmosphere is proportional to the rate of organic/vegetation mass that is burning. On the other hand, the emission of gasses and particulate matter released during burning is proportional to the consumed mass, hence the emissions rates are proportional to the measured FRP. | ||
The FRP needed to calculate the biomass burning emission was derived from the MODIS Thermal Anomalies/Fire products (MOD14, MYD14). The calibration of the QFED emissions was done individually for the MODIS/Terra and MODIS/Aqua data using the emissions factors from Andreae and Merlet [2001]. Our first step was to use global monthly mean GFED emissions to find individual global calibration factors for MODIS/Terra and MODIS/Aqua instruments. Using individual calibration factors has an advantage over using a single common factor for the two instruments, because one can account for the differences in the fire strengths at the local time of the satellite overpass, and ensures redundancy in case one of the satellites fails. The QFED fire emissions were used in the 'R_ddQFED' experiment. The benefits of this calibration is that globally the QFED fire emissions are comparable to the commonly used GFED emissions, however they are available daily at finer horizontal resolution of 0.25×0. | The FRP needed to calculate the biomass burning emission was derived from the MODIS Thermal Anomalies/Fire products (MOD14, MYD14). The calibration of the QFED emissions was done individually for the MODIS/Terra and MODIS/Aqua data using the emissions factors from Andreae and Merlet [2001]. Our first step was to use global monthly mean GFED emissions to find individual global calibration factors for MODIS/Terra and MODIS/Aqua instruments. Using individual calibration factors has an advantage over using a single common factor for the two instruments, because one can account for the differences in the fire strengths at the local time of the satellite overpass, and ensures redundancy in case one of the satellites fails. The QFED fire emissions were used in the '''R_ddQFED''' experiment. The benefits of this calibration is that globally the QFED fire emissions are comparable to the commonly used GFED emissions, however they are available daily at finer horizontal resolution of 0.25×0.3125 degrees. | ||
Our next objective was to produce more realistic fire emission magnitudes. As in-situ measurements of fire emissions are very limited, we relied instead on the fact that biomass burning can have significant contribution to the total aerosol loadings near active fires and downwind. Thus, one can use aerosol optical thickness (AOT) magnitude and relate it to the fire emission strength. | Our next objective was to produce more realistic fire emission magnitudes. As in-situ measurements of fire emissions are very limited, we relied instead on the fact that biomass burning can have significant contribution to the total aerosol loadings near active fires and downwind. Thus, one can use aerosol optical thickness (AOT) magnitude and relate it to the fire emission strength. | ||
Our approach was to find a global scale factor that minimizes the differences between the AOT retrieved by satellites and the modeled AOT which is equal to the sum of AOT due to biomass burning and AOT due to other type of aerosols. We constructed and performed two modeling runs - one with biomass burning (R_ddQFED) and another with no biomass burning (R_mmNOBB). From these two runs we calculated the contribution of the biomass burning to the total AOT and found the optimal value of the global scale factor that minimized the difference between the observed AOT and the modeled AOT. As a first approximation the same factor was used to scale the QFED emissions. The derived in this way globally scaled QFED emissions were used in the R_ddQFED_MISR experiment. | Our approach was to find a global scale factor that minimizes the differences between the AOT retrieved by satellites and the modeled AOT which is equal to the sum of AOT due to biomass burning and AOT due to other type of aerosols. We constructed and performed two modeling runs - one with biomass burning (R_ddQFED) and another with no biomass burning (R_mmNOBB). From these two runs we calculated the contribution of the biomass burning to the total AOT and found the optimal value of the global scale factor that minimized the difference between the observed AOT and the modeled AOT. As a first approximation the same factor was used to scale the QFED emissions. The derived in this way globally scaled QFED emissions were used in the '''R_ddQFED_MISR''' experiment. | ||
Our observational AOT dataset was based on a 3-hourly globally gridded (2×2 degrees) [http://www-misr.jpl.nasa.gov MISR] AOT spanning the 2003-2009 period. The decision to use MISR retrievals was primarily dictated by the robustness of the MISR aerosol retrievals algorithm over land. | |||
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== Overview of Experiments == | == Overview of Experiments == | ||
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===Comparison to MODIS=== | <!-- ===Comparison to MODIS=== --> | ||
===AERONET comparisons=== | <!-- ===AERONET comparisons=== --> | ||
== Data Availability == | == Data Availability == | ||
Selected modeling experiments have been made available online. The download options include: | |||
* [ftp://iesa@ftp.nccs.nasa.gov/aerosol/experiments FTP server] | |||
* [http://opendap.gsfc.nasa.gov:9090/dods/IESA/aerosols OPeNDAP server] | |||
* [http://portal.nccs.nasa.gov/cgi-lats4d/opendap.cgi?&path=/IESA/aerosols/ Download Tool] | |||
== Acknowledgments == | == Acknowledgments == | ||
The ''Progress towards an Integrated Earth System Analysis'' task was supported under the GMAO's activities as part of the American Recovery and Reinvestment Act (ARRA) of 2009. | |||
(Thank our sponsors, including ARRA) | <!-- (Thank our sponsors, including ARRA): We would like to thank the ARRA Project for the financial support and to our Atmospheric Chemistry and Dynamics Branch at NASA/GSFC colleagues for their help and collaborative efforts. --> | ||