Validation of Atmospheric Profile Retrievals From the SNPP NOAA-Unique Combined Atmospheric Processing System. Part 1: Temperature and Moisture

Nalli, Nicholas R.; Gambacorta, Antonia; Liu, Quanhua; Barnet, Christopher D.; Tan, Changyi; Iturbide-Sanchez, Flavio; Reale, Anthony; Sun, Bomin; Wilson, Michael; Borg, Lori; Morris, Vernon R.

doi:10.1109/tgrs.2017.2744558

Cited by 56 publications

(52 citation statements)

References 40 publications

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“…To account for the IR vertical resolution, two different approaches to vertical averaging are applied to the IR sounder minus RO differences. The first analysis approach, used in previous IR sounder validation studies, applies an approximately 1 km slab layering to the difference profiles [ Susskind et al , ; Divakarla et al , ; Tobin et al , ; Nalli et al , ; M. L. Feltz et al , ; M. Feltz et al , ; Nalli et al , ]. A table in M. Feltz et al .…”

Section: Methodsmentioning

confidence: 99%

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Assessment of NOAA NUCAPS upper air temperature profiles using COSMIC GPS radio occultation and ARM radiosondes

et al. 2017

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The U.S. National Oceanic and Atmospheric Administration (NOAA) recently began operational processing to derive vertical temperature profiles from two new sensors, Cross‐Track Infrared Sounder and Advanced Technology Microwave Sounder, which were developed for the next generation of U.S. weather satellites. The NOAA‐Unique Combined Atmospheric Processing System (NUCAPS) has been developed by NOAA to routinely process data from future Joint Polar Satellite System operational satellites and the preparatory Suomi‐NPP satellite. This paper assesses the NUCAPS vertical temperature profile product from the upper troposphere into the middle stratosphere using radiosonde and GPS radio occultation (RO) data. Radiosonde data from the Department of Energy Atmospheric Radiation Measurement (ARM) program are=] compared to both the NUCAPS and GPS RO temperature products to evaluate bias and RMS errors. At all three fixed ARM sites for time periods investigated the NUCAPS temperature in the 100–40 hPa range is found to have an average bias to the radiosondes of less than 0.45 K and an RMS error of less than 1 K when temperature averaging kernels are applied. At a 95% confidence level, the radiosondes and RO were found to agree within 0.4 K at the North Slope of Alaska site and within 0.83 K at Southern Great Plains and Tropical Western Pacific. The GPS RO‐derived dry temperatures, obtained from the University Corporation for Atmospheric Research Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission, are used as a common reference for the intercomparison of NUCAPS temperature products to similar products produced by NASA from Atmospheric Infrared Sounder (AIRS) and by European Organisation for the Exploitation of Meteorological Satellites from MetOp‐B Infrared Atmospheric Sounding Interferometer (IASI). For seasonal and zonal scales, the NUCAPS agreement with AIRS and IASI is less than 0.5 K after application of averaging kernels.

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Section: Methodsmentioning

confidence: 99%

“…A recent study by Nalli et al . [] also makes an assessment of NUCAPS temperature and moisture products using radiosonde, ocean campaign data, and model data.…”

Section: Introductionmentioning

confidence: 99%

Assessment of NOAA NUCAPS upper air temperature profiles using COSMIC GPS radio occultation and ARM radiosondes

et al. 2017

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“…CLIMCAPS shares its AST heritage with the NOAA-Unique Combined Atmospheric Processing System (NUCAPS) that was operationally implemented as the AST version 5.9 retrieval algorithm [29] for the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp-A/B/C, CrIS on SNPP, as well as the Joint Polar Satellite System (JPSS) series [30] of which NOAA-20 is the first. Like NUCAPS, CLIMCAPS retrieves multiple atmospheric and diagnostic variables with which to characterize the atmospheric state [31][32][33]. These include profiles of temperature, water vapor, greenhouse and pollutant gases (O 3 , CO, CH 4 , SO 2 , HNO 3 , and N 2 O), cloud top pressure, cloud fraction, surface temperature and emissivity as well as an array of diagnostic metrics that characterizes scene complexity and retrieval quality.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)

2019

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The Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) retrieves multiple Essential Climate Variables (ECV) about the vertical atmosphere from hyperspectral infrared measurements made by the Atmospheric InfraRed Sounder (AIRS, 2002–present) and its successor, the Cross-track Infrared Sounder (CrIS, 2011–present). CLIMCAPS ECVs are profiles of temperature and water vapor, column amounts of greenhouse gases (CO2, CH4), ozone (O3) and precursor gases (CO, SO2) as well as cloud properties. AIRS (and CrIS) spectral measurements are highly correlated signals of many atmospheric state variables. CLIMCAPS inverts an AIRS (and CrIS) measurement into a set of discrete ECVs by employing a sequential Bayesian approach in which scene-dependent uncertainty is rigorously propagated. This not only linearizes the inversion problem but explicitly accounts for spectral interference from other state variables so that the correlation among ECVs (and their uncertainty) may be minimized. Here, we outline the CLIMCAPS retrieval methodology with specific focus given to its sequential scene-dependent uncertainty propagation system. We conclude by demonstrating continuity in two CLIMCAPS ECVs across AIRS and CrIS so that a long-term data record may be generated to study the feedback cycles characterizing our climate system.

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“…NOAA continually validates NUCAPS with in-situ measurements from field campaigns [18,19]. In AWIPS, forecasters have access to all NUCAPS retrievals, whether they are flagged successful or not.…”

Section: Figurementioning

confidence: 99%

“…In past HWTs, many of the case studies in written descriptions performed side-by-side comparisons of NUCAPS to model and/or radiosondes, which demonstrate real-world strengths and limitations to supplement quantitative validation studies on NUCAPS [18]. We provided additional training materials in the quick guides and addressed the limitations during the training.…”

Section: Questionnaire Designmentioning

confidence: 99%

Adapting Satellite Soundings for Operational Forecasting within the Hazardous Weather Testbed

et al. 2020

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In this paper, we describe how researchers and weather forecasters work together to make satellite sounding data sets more useful in severe weather forecasting applications through participation in National Oceanic and Atmospheric Administration (NOAA)’s Hazardous Weather Testbed (HWT) and JPSS Proving Ground and Risk Reduction (PGRR) program. The HWT provides a forum for collaboration to improve products ahead of widespread operational deployment. We found that the utilization of the NOAA-Unique Combined Atmospheric Processing System (NUCAPS) soundings was improved when the product developer and forecaster directly communicated to overcome misunderstandings and to refine user requirements. Here we share our adaptive strategy for (1) assessing when and where NUCAPS soundings improved operational forecasts by using real, convective case studies and (2) working to increase NUCAPS utilization by improving existing products through direct, face-to-face interaction. Our goal is to discuss the lessons we learned and to share both our successes and challenges working with the weather forecasting community in designing, refining, and promoting novel products. We foresee that our experience in the NUCAPS product development life cycle may be relevant to other communities who can then build on these strategies to transition their products from research to operations (and operations back to research) within the satellite meteorological community.

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Validation of Atmospheric Profile Retrievals From the SNPP NOAA-Unique Combined Atmospheric Processing System. Part 1: Temperature and Moisture

Cited by 56 publications

References 40 publications

Assessment of NOAA NUCAPS upper air temperature profiles using COSMIC GPS radio occultation and ARM radiosondes

Assessment of NOAA NUCAPS upper air temperature profiles using COSMIC GPS radio occultation and ARM radiosondes

Uncertainty Characterization and Propagation in the Community Long-Term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS)

Adapting Satellite Soundings for Operational Forecasting within the Hazardous Weather Testbed

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