i
Algorithm Development of Temperature and Humidity Profile Retrievals for Long-Term HIRS Observations
-
2016
Source: Remote Sens. 8(4), 1-17
[PDF-3.56 MB]
Details:
-
Journal Title:Remote Sensing
-
Personal Author:
-
NOAA Program & Office:
-
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.
-
Source:Remote Sens. 8(4), 1-17
-
Document Type:
-
Funding:
-
Rights Information:CC BY
-
Compliance:Library
-
Main Document Checksum:urn:sha256:5a7bf97a66b91a33b9652342f198cea60f9752c40ca2a6d991e21d68beaaf5a5
-
File Type:
Supporting Files
-
No Additional Files
More +
Related Documents
-
Personal Author:Becker, Elizabeth ;Forney, Karin...2016 | Remote Sens. 8(2), 1-26Description:Species distribution models are now widely used in conservation and management to predict suitable habitat for protected marine species. The primary s...2016 | Remote Sens. 8(1), 1-20Description:Moderate Resolution Imaging Spectroradiometers (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) radiometers, flown onboard Terra/Aqua and...Personal Author:Obata, Kenta ;Miura, Tomoaki...2016 | Remote Sens. 8(1), 1-17Description:In this study, the Visible Infrared Imaging Radiometer Suite (VIIRS) Enhanced Vegetation Index (EVI) was spectrally cross-calibrated with the Moderate...Personal Author:Heidinger, Andrew ;Foster, Michael...2016 | Remote Sens. 8(6), 1-18Description:An important component of the AVHRR PATMOS-x climate date record (CDR)—or any satellite cloud climatology—is the performance of its cloud detectio...Personal Author:Liang, Xingming ;Ignatov, Alexander...2016 | Remote Sens. 8(3), 1-13Description:Clear-sky brightness temperatures (BT) in five bands of the Advanced Himawari Imager (AHI; flown onboard Himawari-8 satellite) centered at 3.9, 8.6, 1...Personal Author:Claverie, Martin ;Matthews, Jessica...2016 | Remote Sens. 8(3), 1-12Description:In-land surface models, which are used to evaluate the role of vegetation in the context of global climate change and variability, LAI and FAPAR play ...Personal Author:Ignatov, Alexander ;Zhou, Xinjia...2016 | Remote Sens. 8(4), 1-17Description:In response to its users’ needs, the National Oceanic and Atmospheric Administration (NOAA) initiated reanalysis (RAN) of the Advanced Very High Res...2016 | Remote Sens. 8(9), 1-17Description:In this study, six Arctic sea ice thickness products are compared: the AVHRR Polar Pathfinder-extended (APP-x), ICESat, CryoSat-2, SMOS, NASA IceBridg...Personal Author:Adler, Robert ;Sapiano, Mathew...2018 | Atmos., 9(4), 1-14Description:The new Version 2.3 of the Global Precipitation Climatology Project (GPCP) Monthly analysis is described in terms of changes made to improve the homog...Sensor Stability for SST (3S): Toward Improved Long-Term Characterization of AVHRR Thermal BandsCitePersonal Author:He, Kai ;Ignatov, Alexander...2016 | Remote Sens. 8(4), 1-21Description:Recently, the National Oceanic and Atmospheric Administration (NOAA) performed sea surface temperature (SST) reanalysis (RAN1) from seven AVHRR/3s onb...Personal Author:Shinoda, Toshiaki ;Han, Weiqing...2017 | Atmos., 8(9), 1-21Description:During the CINDY/DYNAMO field campaign, exceptionally large upper ocean responses to strong westerly wind events associated with the Madden–Julian o...Personal Author:Koner, Prabhat K. ;Harris, Andy2016 | Remote Sens. 8(9), 1-17Description:Global sea-surface temperatures (SST) from MODIS measured brightness temperatures generated using the regression methods, have been available to users...Personal Author:O’Donnell, John P. R. ;Schalles, John F.2016 | Remote Sens. 8(6), 1-22Description:We examined the influence of abiotic drivers on inter-annual and phenological patterns of aboveground biomass for Marsh Cordgrass, Spartina alterniflo...Personal Author:Heron, Scott ;Johnston, Lyza...2016 | Remote Sens. 8(1), 1-16Description:Satellite monitoring of thermal stress on coral reefs has become an essential component of reef management practice around the world. A recent develop...Personal Author:Caldwell, Jamie ;Heron, Scott...2016 | Remote Sens. 8(2), 1-15Description:Predicting wildlife disease risk is essential for effective monitoring and management, especially for geographically expansive ecosystems such as cora...
More +
You May Also Like
Personal Author:
Yu, Xiaolong ;
Lee, Zhongping
...
2019 | Remote Sensing of Environment 235 (2019) 111491
Description:
We propose a globally applicable algorithm (GAASPM) to seamlessly retrieve the concentration of suspended particulate matter (SPM) (CSPM) from remote ...
Checkout today's featured content at repository.library.noaa.gov