Difference between revisions of "Obs Emiss Model Assimilation"
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<center><big>Observation, Emission, Model Assimilation</big></center> | <center><big>Observation, Emission, Model Assimilation</big></center> | ||
| − | == | + | ==ObsEmissModel== |
[[Image:071124_ObsEmissModel.PNG|300px]] | [[Image:071124_ObsEmissModel.PNG|300px]] | ||
| + | The 2007 Interim Report [http://htap.org], the available HTAP-relevant global models, observations and emissions were assessed. The HTAP community has made particular contributions toward the intercomparison of global models. | ||
| − | == | + | ==OEM_Links== |
[[Image:071124_OEM_Links.PNG|300px]] | [[Image:071124_OEM_Links.PNG|300px]] | ||
| + | The 2009 HTAP Assessment seeks to reconcile the models with observations and emissions. | ||
| − | == | + | ==OEM_LinkProc== |
[[Image:071124_OEM_LinkProc.PNG|300px]] | [[Image:071124_OEM_LinkProc.PNG|300px]] | ||
| + | This broader reconciliation will require the interaction of domain experts in all three areas, as well as the seamless flow of data among the participants. | ||
| + | A network that facilitates human-human as well as computer-computer interaction is desired. | ||
| − | == | + | ==OEM_Networking== |
[[Image:071124_OEM_Networking.PNG|300px]] | [[Image:071124_OEM_Networking.PNG|300px]] | ||
| + | The main goal of the HTAP network is to facilitate the human and data connectivity. Given the connectivity, we wish to enable the participants with shared tools and methods. | ||
| − | == | + | ==OMINO2_Avg== |
[[Image:071124_OMINO2_Avg.PNG|300px]] | [[Image:071124_OMINO2_Avg.PNG|300px]] | ||
| + | It is now possible to develop a chemical climatology (2004-7) of tropospheric NO2 based on routine daily satellite observations. The data show a highly patchy pattern over the Contiental US. | ||
| + | Such data can aid the understanding of NO2 sources, atmospheric dynamics and potential impacts on human health and welfare. | ||
| − | == | + | ==OMINO2_Mobile== |
[[Image:071124_OMINO2_Mobile.PNG|300px]] | [[Image:071124_OMINO2_Mobile.PNG|300px]] | ||
| + | Superposition of mobile emission sources on the climatotlogical OMI NO2 shows that most of the observed NO2 hotspots are indeed over metropolitan areas where automotive emissions of NOxare domiant. | ||
| − | == | + | ==OMINO2_Point== |
[[Image:071124_OMINO2_Point.PNG|300px]] | [[Image:071124_OMINO2_Point.PNG|300px]] | ||
| + | A broader elevated tropospheric NO2 is observed over the Ohio River valley, where a string of power plants are responsible for significant NOx emissions. | ||
| + | However, additional hotspots are also observed over known individual power plants in the western and southeastern US. | ||
| − | == | + | ==OMINO2_PointWest== |
[[Image:071124_OMINO2_PointWest.PNG|300px]] | [[Image:071124_OMINO2_PointWest.PNG|300px]] | ||
| + | In the Western US, individual power plants, most notable the Four Corners plant, are clearly discernable by impact on their surroundings | ||
| − | == | + | ==OMINO2_PointWestPoint== |
[[Image:071124_OMINO2_PointWestPoint.PNG|300px]] | [[Image:071124_OMINO2_PointWestPoint.PNG|300px]] | ||
| − | == | + | ==OMINO2_GASmokeAvg== |
[[Image:071124_OMINO2_GASmokeAvg.PNG|300px]] | [[Image:071124_OMINO2_GASmokeAvg.PNG|300px]] | ||
| + | Non-industrial sources of NOx are also detectable in the OMI NO2 climatology. The impact of the S. Georgia fire in May 2007 is clearly quantifyable. | ||
| − | == | + | ==OMINO2_GASmokeMobil== |
[[Image:071124_OMINO2_GASmokeMobil.PNG|300px]] | [[Image:071124_OMINO2_GASmokeMobil.PNG|300px]] | ||
| + | It is evident, that the fire emission can be spatially separated from the urban and power plant emissions. | ||
| − | == | + | ==OMINO2_IdahoSmoke== |
[[Image:071124_OMINO2_IdahoSmoke.PNG|300px]] | [[Image:071124_OMINO2_IdahoSmoke.PNG|300px]] | ||
| + | The regular biomass burning in the Northwestern US has also quantifiable impact on the tropospheric NO2. Such data can be evaluated to generate improved emission inventories for NOx. | ||
| − | == | + | The daily time resolution of the OMI NO2 data allows the quantification of the weekday-weekend effect. For example, in large metropolitan areas, the Friday NO2 exceeds the Sunday values by a factor of 1.2-1.4. This again can aid the development of higher time resolution emission inventories for NOx. |
| + | |||
| + | ==OMINO2_WeekdayWeekend== | ||
[[Image:071124_OMINO2_WeekdayWeekend.PNG|300px]] | [[Image:071124_OMINO2_WeekdayWeekend.PNG|300px]] | ||
| + | !!!Wrong Image!!! | ||
| + | ==OMINO2_OhioNewYork== | ||
| + | [[Image:071124_OMINO2_OhioNewYork.PNG|300px]] | ||
| + | However, there are also significant questions to be explored. | ||
| − | + | Why is the OMI NO2/EPA Emission ratio 40% higher over the Eastern megalopolis than over the Ohio River Valley? | |
| − | |||
| − | == | + | ==OMINO2_Emission_Model_Link== |
[[Image:071124_OMINO2_Emission_Model_Link.PNG|300px]] | [[Image:071124_OMINO2_Emission_Model_Link.PNG|300px]] | ||
| + | However, there are also significant questions to be explored. | ||
| − | == | + | Why is the OMI NO2/EPA Emission ratio 40% higher over the Eastern megalopolis than over the Ohio River Valley? |
| + | |||
| + | ==OMINO2_NudgingExample== | ||
[[Image:071124_OMINO2_NudgingExample.PNG|300px]] | [[Image:071124_OMINO2_NudgingExample.PNG|300px]] | ||
| + | However, there are also significant questions to be explored. | ||
| + | |||
| + | Why is the OMI NO2/EPA Emission ratio 40% higher over the Eastern megalopolis than over the Ohio River Valley? | ||
| − | == | + | ==OMINO2_TropoStratoSeparation== |
[[Image:071124_OMINO2_TropoStratoSeparation.PNG|300px]] | [[Image:071124_OMINO2_TropoStratoSeparation.PNG|300px]] | ||
| + | Also, why does the Stratospheric NO2 from OMI exhibit ‘NO2 holes’ over the major Easter cities in some of the months? | ||
| + | Is the Total NO2 column split properly between the troposphere and stratosphere? | ||
| − | == | + | ==OMINO2_GlobalOMIModelMap== |
[[Image:071124_OMINO2_GlobalOMIModelMap.PNG|300px]] | [[Image:071124_OMINO2_GlobalOMIModelMap.PNG|300px]] | ||
| + | The available OMI NO2 data and the results of NO2 models will allow a global-scale comparison. | ||
| + | This new opportunity will permit the global-scale reconciliation of the models-emissions and observations. | ||
| − | == | + | ==OMINO2_SurfOMIModelTime== |
[[Image:071124_OMINO2_SurfOMIModelTime.PNG|300px]] | [[Image:071124_OMINO2_SurfOMIModelTime.PNG|300px]] | ||
| + | Model Observation comparison: Temporal pattern | ||
Revision as of 21:13, November 24, 2007
ObsEmissModel
The 2007 Interim Report [1], the available HTAP-relevant global models, observations and emissions were assessed. The HTAP community has made particular contributions toward the intercomparison of global models.
OEM_Links
The 2009 HTAP Assessment seeks to reconcile the models with observations and emissions.
OEM_LinkProc
This broader reconciliation will require the interaction of domain experts in all three areas, as well as the seamless flow of data among the participants.
A network that facilitates human-human as well as computer-computer interaction is desired.
OEM_Networking
The main goal of the HTAP network is to facilitate the human and data connectivity. Given the connectivity, we wish to enable the participants with shared tools and methods.
OMINO2_Avg
It is now possible to develop a chemical climatology (2004-7) of tropospheric NO2 based on routine daily satellite observations. The data show a highly patchy pattern over the Contiental US.
Such data can aid the understanding of NO2 sources, atmospheric dynamics and potential impacts on human health and welfare.
OMINO2_Mobile
Superposition of mobile emission sources on the climatotlogical OMI NO2 shows that most of the observed NO2 hotspots are indeed over metropolitan areas where automotive emissions of NOxare domiant.
OMINO2_Point
A broader elevated tropospheric NO2 is observed over the Ohio River valley, where a string of power plants are responsible for significant NOx emissions.
However, additional hotspots are also observed over known individual power plants in the western and southeastern US.
OMINO2_PointWest
In the Western US, individual power plants, most notable the Four Corners plant, are clearly discernable by impact on their surroundings
OMINO2_PointWestPoint
OMINO2_GASmokeAvg
Non-industrial sources of NOx are also detectable in the OMI NO2 climatology. The impact of the S. Georgia fire in May 2007 is clearly quantifyable.
OMINO2_GASmokeMobil
It is evident, that the fire emission can be spatially separated from the urban and power plant emissions.
OMINO2_IdahoSmoke
The regular biomass burning in the Northwestern US has also quantifiable impact on the tropospheric NO2. Such data can be evaluated to generate improved emission inventories for NOx.
The daily time resolution of the OMI NO2 data allows the quantification of the weekday-weekend effect. For example, in large metropolitan areas, the Friday NO2 exceeds the Sunday values by a factor of 1.2-1.4. This again can aid the development of higher time resolution emission inventories for NOx.
OMINO2_WeekdayWeekend
!!!Wrong Image!!!
OMINO2_OhioNewYork
However, there are also significant questions to be explored.
Why is the OMI NO2/EPA Emission ratio 40% higher over the Eastern megalopolis than over the Ohio River Valley?
OMINO2_Emission_Model_Link
However, there are also significant questions to be explored.
Why is the OMI NO2/EPA Emission ratio 40% higher over the Eastern megalopolis than over the Ohio River Valley?
OMINO2_NudgingExample
However, there are also significant questions to be explored.
Why is the OMI NO2/EPA Emission ratio 40% higher over the Eastern megalopolis than over the Ohio River Valley?
OMINO2_TropoStratoSeparation
Also, why does the Stratospheric NO2 from OMI exhibit ‘NO2 holes’ over the major Easter cities in some of the months?
Is the Total NO2 column split properly between the troposphere and stratosphere?
OMINO2_GlobalOMIModelMap
The available OMI NO2 data and the results of NO2 models will allow a global-scale comparison.
This new opportunity will permit the global-scale reconciliation of the models-emissions and observations.
OMINO2_SurfOMIModelTime
Model Observation comparison: Temporal pattern
