Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations
A project for deriving temperature and humidity profiles from High-resolution Infrared Radiation Sounder (HIRS) observations is underway to build a long-term dataset for climate applications. The retrieval algorithm development of the project includes a neural network retrieval scheme, a two-tiered...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-03-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/8/4/280 |
| _version_ | 1818320285713039360 |
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| author | Lei Shi Jessica L. Matthews Shu-peng Ho Qiong Yang John J. Bates |
| author_facet | Lei Shi Jessica L. Matthews Shu-peng Ho Qiong Yang John J. Bates |
| author_sort | Lei Shi |
| collection | DOAJ |
| description | A project for deriving temperature and humidity profiles from High-resolution Infrared Radiation Sounder (HIRS) observations is underway to build a long-term dataset for climate applications. The retrieval algorithm development of the project includes a neural network retrieval scheme, a two-tiered cloud screening method, and a calibration using radiosonde and Global Positioning System Radio Occultation (GPS RO) measurements. As atmospheric profiles over high surface elevations can differ significantly from those over low elevations, different neural networks are developed for three classifications of surface elevations. The significant impact from the increase of carbon dioxide in the last several decades on HIRS temperature sounding channel measurements is accounted for in the retrieval scheme. The cloud screening method added one more step from the HIRS-only approach by incorporating the Advanced Very High Resolution Radiometer (AVHRR) observations to assess the likelihood of cloudiness in HIRS pixels. Calibrating the retrievals with radiosonde and GPS RO reduces biases in retrieved temperature and humidity. Except for the lowest pressure level which exhibits larger variability, the mean biases are within ±0.3 °C for temperature and within ±0.2 g/kg for specific humidity at standard pressure levels, globally. Overall, the HIRS temperature and specific humidity retrievals closely align with radiosonde and GPS RO observations in providing measurements of the global atmosphere to support other relevant climate dataset development. |
| first_indexed | 2024-12-13T10:22:35Z |
| format | Article |
| id | doaj.art-f0cbfb1640df4674904d6760d44a5fdb |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-13T10:22:35Z |
| publishDate | 2016-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-f0cbfb1640df4674904d6760d44a5fdb2022-12-21T23:51:09ZengMDPI AGRemote Sensing2072-42922016-03-018428010.3390/rs8040280rs8040280Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS ObservationsLei Shi0Jessica L. Matthews1Shu-peng Ho2Qiong Yang3John J. Bates4NOAA’s National Centers for Environmental Information (NCEI), 151 Patton Avenue, Asheville, NC 28801, USANOAA’s National Centers for Environmental Information (NCEI), 151 Patton Avenue, Asheville, NC 28801, USACOSMIC Project Office, University Corporation for Atmospheric Research, Boulder, CO 80307, USAJoint Institute for the Study of the Atmosphere and Ocean, Seattle, WA 98105, USANOAA’s National Centers for Environmental Information (NCEI), 151 Patton Avenue, Asheville, NC 28801, USAA project for deriving temperature and humidity profiles from High-resolution Infrared Radiation Sounder (HIRS) observations is underway to build a long-term dataset for climate applications. The retrieval algorithm development of the project includes a neural network retrieval scheme, a two-tiered cloud screening method, and a calibration using radiosonde and Global Positioning System Radio Occultation (GPS RO) measurements. As atmospheric profiles over high surface elevations can differ significantly from those over low elevations, different neural networks are developed for three classifications of surface elevations. The significant impact from the increase of carbon dioxide in the last several decades on HIRS temperature sounding channel measurements is accounted for in the retrieval scheme. The cloud screening method added one more step from the HIRS-only approach by incorporating the Advanced Very High Resolution Radiometer (AVHRR) observations to assess the likelihood of cloudiness in HIRS pixels. Calibrating the retrievals with radiosonde and GPS RO reduces biases in retrieved temperature and humidity. Except for the lowest pressure level which exhibits larger variability, the mean biases are within ±0.3 °C for temperature and within ±0.2 g/kg for specific humidity at standard pressure levels, globally. Overall, the HIRS temperature and specific humidity retrievals closely align with radiosonde and GPS RO observations in providing measurements of the global atmosphere to support other relevant climate dataset development.http://www.mdpi.com/2072-4292/8/4/280temperaturehumidityHIRSretrieval algorithms and methodssatellite observation |
| spellingShingle | Lei Shi Jessica L. Matthews Shu-peng Ho Qiong Yang John J. Bates Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations Remote Sensing temperature humidity HIRS retrieval algorithms and methods satellite observation |
| title | Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations |
| title_full | Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations |
| title_fullStr | Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations |
| title_full_unstemmed | Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations |
| title_short | Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations |
| title_sort | algorithm development of temperature and humidity profile retrievals for long term hirs observations |
| topic | temperature humidity HIRS retrieval algorithms and methods satellite observation |
| url | http://www.mdpi.com/2072-4292/8/4/280 |
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