There is a need to be able to estimate the relative humidity in the Planetary Boundary Layer (PBL) since relative humidity can affect aerosol retrieval. Satellite retrievals of Relative Humidity are extremely complicated since they need to resolve 1km vertical resolution for temperature and water vapor. The AIRS hyperspectral sensor may be able to retrieve relative humidity with 20% RMSE but low correlations with R2 – 0.4. The alternative is to explore meteorological forecasts (i.e. Rapid Refresh) to see if we can use them in the processing stream for aerosols. While the state of delay zero is assimilated, the following forecasts for large enough delay can be used to provide PBL integrated RH that can be used in modified aerosol retrieval models to modify aerosol models and/or provide useful diagnostic flags during the retrieval. We find that even for 18 hr. forecasts, the RMSE errors are < 15% which is significantly better that AIRS sensor retrievals.
","abstract_html":"<p>There is a need to be able to estimate the relative humidity in the Planetary Boundary Layer (PBL) since relative humidity can affect aerosol retrieval. Satellite retrievals of Relative Humidity are extremely complicated since they need to resolve 1km vertical resolution for temperature and water vapor. The AIRS hyperspectral sensor may be able to retrieve relative humidity with 20% RMSE but low correlations with R<sup>2</sup> – 0.4. The alternative is to explore meteorological forecasts (i.e. Rapid Refresh) to see if we can use them in the processing stream for aerosols. While the state of delay zero is assimilated, the following forecasts for large enough delay can be used to provide PBL integrated RH that can be used in modified aerosol retrieval models to modify aerosol models and/or provide useful diagnostic flags during the retrieval. We find that even for 18 hr. forecasts, the RMSE errors are < 15% which is significantly better that AIRS sensor retrievals.</p>","abstract_has_math":false,"creators":["Daniel, David"],"institution":null,"degree_name":"Master of Engineering (M.E.)","degree_level":"Thesis","degree_discipline":"Engineering","degree_department":null,"school":null,"contributors":["Barry Gross"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-01-01T08:00:00Z","date_published":"2013-01-01T08:00:00Z","updated_at":"2026-07-24T01:57:14Z","subjects":["Atmospheric","NOAA","Rapid Refresh","AIRS Mission","aerosol retrieval","Electrical and Computer Engineering","Electrical and Electronics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://academicworks.cuny.edu/cc_etds_theses/644","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Barry Gross"]},{"key":"dc:creator","label":"Author","values":["Daniel, David"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-10-14T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Engineering (M.E.)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Atmospheric","NOAA","Rapid Refresh","AIRS Mission","aerosol retrieval","Electrical and Computer Engineering","Electrical and Electronics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://academicworks.cuny.edu/cc_etds_theses/644"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["There is a need to be able to estimate the relative humidity in the Planetary Boundary Layer (PBL) since relative humidity can affect aerosol retrieval. Satellite retrievals of Relative Humidity are extremely complicated since they need to resolve 1km vertical resolution for temperature and water vapor. The AIRS hyperspectral sensor may be able to retrieve relative humidity with 20% RMSE but low correlations with R2 – 0.4. The alternative is to explore meteorological forecasts (i.e. Rapid Refresh) to see if we can use them in the processing stream for aerosols. While the state of delay zero is assimilated, the following forecasts for large enough delay can be used to provide PBL integrated RH that can be used in modified aerosol retrieval models to modify aerosol models and/or provide useful diagnostic flags during the retrieval. We find that even for 18 hr. forecasts, the RMSE errors are < 15% which is significantly better that AIRS sensor retrievals.
"]},{"key":"dc:title","label":"Title","values":["ASSESSING PERFORMANCE OF NCEP RAPID REFRESH MODEL TO PREDICT BOUNDARY LAYER PROPERTIES"]}]}],"canonical_facts":{"dc:contributor":["Barry Gross"],"dc:creator":["Daniel, David"],"dc:date.available":["2016-10-14T07:00:00Z"],"dc:description.abstract":["There is a need to be able to estimate the relative humidity in the Planetary Boundary Layer (PBL) since relative humidity can affect aerosol retrieval. Satellite retrievals of Relative Humidity are extremely complicated since they need to resolve 1km vertical resolution for temperature and water vapor. The AIRS hyperspectral sensor may be able to retrieve relative humidity with 20% RMSE but low correlations with R2 – 0.4. The alternative is to explore meteorological forecasts (i.e. Rapid Refresh) to see if we can use them in the processing stream for aerosols. While the state of delay zero is assimilated, the following forecasts for large enough delay can be used to provide PBL integrated RH that can be used in modified aerosol retrieval models to modify aerosol models and/or provide useful diagnostic flags during the retrieval. We find that even for 18 hr. forecasts, the RMSE errors are < 15% which is significantly better that AIRS sensor retrievals.
"],"dc:identifier":["https://academicworks.cuny.edu/cc_etds_theses/644"],"dc:subject":["Atmospheric","NOAA","Rapid Refresh","AIRS Mission","aerosol retrieval","Electrical and Computer Engineering","Electrical and Electronics"],"dc:title":["ASSESSING PERFORMANCE OF NCEP RAPID REFRESH MODEL TO PREDICT BOUNDARY LAYER PROPERTIES"],"thesis:degree_discipline":["Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Engineering (M.E.)"]},"updated_at":"2026-07-24T01:57:14Z"}