Difference between revisions of "Multi-mission Observation Operator (M2O2)"
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− | == | + | == Contact information == |
− | + | *PI : Meemong Lee / Jet Propulsion Laboratory | |
− | *PI | + | |
*Co-Is : Kevin Bowman & Richard Weidner / Jet Propulsion Laboratory, Chris Lynnes /Goddard Space Flight Center, Daven Henze / University of Colorado, Boulder | *Co-Is : Kevin Bowman & Richard Weidner / Jet Propulsion Laboratory, Chris Lynnes /Goddard Space Flight Center, Daven Henze / University of Colorado, Boulder | ||
− | + | == Overview == | |
− | + | ||
The goal of the M2O2 is to create a streamlined interface mechanism between the atmospheric chemistry model developers and the atmospheric sounding mission data providers by infusing mission-generic observation integration technologies developed under the Advanced Information System Technology (AIST) program. The M2O2 addresses a major challenge in utilizing the space-based observations within the atmospheric chemistry modeling and assimilation community, which involves linking between the model analysis and the observed atmospheric state in the level 2 mission data products (L2 data). The state-of-the-practice is to develop an observation operator for each atmospheric component of an atmospheric sounding mission, which often involves laborious data preparation. A wide range of observation operators with its own ad-hoc way of handling L2 data greatly hinders integration of observations from multiple missions. A generic observation operator that provides the link between the model analysis and mission observations requires an automated “assimilation-purpose” data preparation service and representation coordinate transformation. | The goal of the M2O2 is to create a streamlined interface mechanism between the atmospheric chemistry model developers and the atmospheric sounding mission data providers by infusing mission-generic observation integration technologies developed under the Advanced Information System Technology (AIST) program. The M2O2 addresses a major challenge in utilizing the space-based observations within the atmospheric chemistry modeling and assimilation community, which involves linking between the model analysis and the observed atmospheric state in the level 2 mission data products (L2 data). The state-of-the-practice is to develop an observation operator for each atmospheric component of an atmospheric sounding mission, which often involves laborious data preparation. A wide range of observation operators with its own ad-hoc way of handling L2 data greatly hinders integration of observations from multiple missions. A generic observation operator that provides the link between the model analysis and mission observations requires an automated “assimilation-purpose” data preparation service and representation coordinate transformation. | ||
The scope of the M2O2 is limited to the “adjoint”-based global assimilations of three | The scope of the M2O2 is limited to the “adjoint”-based global assimilations of three | ||
− | types of space-based observations, O<sub>3</sub>, CH4, and CO<sub>2</sub> (xCO<sub>2</sub>) in 3D variational assimilation (3Dvar) and 4D variational assimilation (4D-var) processes. The 3D-var method updates the forecast by integrating the observations where the cost is computed for each assimilation time step over the entire atmospheric layers. The 4D-var method updates the initial condition by optimizing the cost integrated over the assimilation period and over the atmospheric layers. The global assimilation processes employs [[ | + | types of space-based observations, O<sub>3</sub>, CH4, and CO<sub>2</sub> (xCO<sub>2</sub>) in 3D variational assimilation (3Dvar) and 4D variational assimilation (4D-var) processes. The 3D-var method updates the forecast by integrating the observations where the cost is computed for each assimilation time step over the entire atmospheric layers. The 4D-var method updates the initial condition by optimizing the cost integrated over the assimilation period and over the atmospheric layers. The global assimilation processes employs [[GEOS-Chem v9-01-01]] as the forward model and [[GEOS-Chem Adjoint v33]] as the adjoint model. |
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− | ---- | + | The technical objectives of M2O2 include : |
+ | #Derive assimilation-ready data products (L2# data) from level-2 mission data products. | ||
+ | #Create a ‘data-to-data’ web-service with configurable requests and mission-sensitive L2# data products. | ||
+ | #Develop a mission-generic assimilation software library that can be easily integrated to atmospheric chemistry transport model (CTM) systems. | ||
− | + | ==Delivery Schedule== | |
− | M2O2 task plans to deliver L2#-based assimilation service to GEOSChem-Adjoint community that can perform 3D-var and 4D-var assimilations of level-2 data products from MLS, TES, ACOS, and AIRS. The delivery will be carried out in two phases, beta-site phase and final phase. The beta-site phase delivery includes M2O2 software library, assimilation application, and run results on | + | M2O2 task plans to deliver L2#-based assimilation service to GEOSChem-Adjoint community that can perform 3D-var and 4D-var assimilations of level-2 data products from MLS, TES, ACOS, and AIRS. The delivery will be carried out in two phases, beta-site phase and final phase. The beta-site phase delivery includes M2O2 software library, assimilation application, and run results on <tt>prospero.colorado.edu</tt> at <tt>/data/meemong/M2O2</tt> folder. During the beta-site phase, the technology readiness level (TRL) will be assessed for operational readiness and a final delivery will be developed including a user guide (downloadable via GEOSChem-wiki). |
*2012/12.15 ... MLS-O<sub>3</sub> L2# data & assimilation server beta site | *2012/12.15 ... MLS-O<sub>3</sub> L2# data & assimilation server beta site |
Revision as of 21:37, 21 November 2012
Contact information
- PI : Meemong Lee / Jet Propulsion Laboratory
- Co-Is : Kevin Bowman & Richard Weidner / Jet Propulsion Laboratory, Chris Lynnes /Goddard Space Flight Center, Daven Henze / University of Colorado, Boulder
Overview
The goal of the M2O2 is to create a streamlined interface mechanism between the atmospheric chemistry model developers and the atmospheric sounding mission data providers by infusing mission-generic observation integration technologies developed under the Advanced Information System Technology (AIST) program. The M2O2 addresses a major challenge in utilizing the space-based observations within the atmospheric chemistry modeling and assimilation community, which involves linking between the model analysis and the observed atmospheric state in the level 2 mission data products (L2 data). The state-of-the-practice is to develop an observation operator for each atmospheric component of an atmospheric sounding mission, which often involves laborious data preparation. A wide range of observation operators with its own ad-hoc way of handling L2 data greatly hinders integration of observations from multiple missions. A generic observation operator that provides the link between the model analysis and mission observations requires an automated “assimilation-purpose” data preparation service and representation coordinate transformation.
The scope of the M2O2 is limited to the “adjoint”-based global assimilations of three types of space-based observations, O3, CH4, and CO2 (xCO2) in 3D variational assimilation (3Dvar) and 4D variational assimilation (4D-var) processes. The 3D-var method updates the forecast by integrating the observations where the cost is computed for each assimilation time step over the entire atmospheric layers. The 4D-var method updates the initial condition by optimizing the cost integrated over the assimilation period and over the atmospheric layers. The global assimilation processes employs GEOS-Chem v9-01-01 as the forward model and GEOS-Chem Adjoint v33 as the adjoint model.
The technical objectives of M2O2 include :
- Derive assimilation-ready data products (L2# data) from level-2 mission data products.
- Create a ‘data-to-data’ web-service with configurable requests and mission-sensitive L2# data products.
- Develop a mission-generic assimilation software library that can be easily integrated to atmospheric chemistry transport model (CTM) systems.
Delivery Schedule
M2O2 task plans to deliver L2#-based assimilation service to GEOSChem-Adjoint community that can perform 3D-var and 4D-var assimilations of level-2 data products from MLS, TES, ACOS, and AIRS. The delivery will be carried out in two phases, beta-site phase and final phase. The beta-site phase delivery includes M2O2 software library, assimilation application, and run results on prospero.colorado.edu at /data/meemong/M2O2 folder. During the beta-site phase, the technology readiness level (TRL) will be assessed for operational readiness and a final delivery will be developed including a user guide (downloadable via GEOSChem-wiki).
- 2012/12.15 ... MLS-O3 L2# data & assimilation server beta site
- 2013/01.15 ... MLS-O3 L2# data & assimilation server final (M2O2-v1.0)
- 2013/03.15 ... ACOS-XCO2 L2# data & assimilation server beta site
- 2013/04.15 ... ACOS-XCO2 L2# data & assimilation server final (M2O2-v1.1)
- 2013/07.15 ... ACOS-CH4 L2# data & assimilation server beta site
- 2013/08.15 ... ACOS-CH4 L2# data & assimilation server final (M2O2-v1.2)
- 2013/10.15 ... AIRS-CO2 L2# data & assimilation server beta site
- 2014/01.15 ... AIRS-CO2L2# data & assimilation server final (M2O2-v1.3)
- 2014/03.15 ... Multi-mission assimilation server final (M2O2-v2.0)