Satellites See the World’s Atmosphere

Ackerman, S. A.; Platnick, Steven; Bhartia, P. K.; Duncan, B. N.; L’Ecuyer, Tristan; Heidinger, A. K.; Skofronick-Jackson, Gail; Loeb, Norman G.; Schmit, Timothy J.; Smith, Nadia

doi:10.1175/amsmonographs-d-18-0009.1

Cited by 42 publications

(37 citation statements)

References 441 publications

(390 reference statements)

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“…Historically, inversion methods are designed to retrieve state variables for weather applications [14][15][16][17][18][19][20][21][22][23] that can tolerate a degree of scene-dependent uncertainty and correlation because the high rate of change in weather systems greatly exceeds product uncertainty. It is when one considers climate applications that depend on the quantification of a low rate of change and subtle correlations among ECVs over large space-time scales that product uncertainty must be carefully treated and fully characterized.…”

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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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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“…CALIPSO (https://www-calipso.larc.nasa.gov/), developed jointly by the United States and France, was successfully launched on 28 April 2006 to fill in the gaps in observations of aerosol and cloud properties and their global distribution. The main instrument carried on the satellite is the cloud aerosol Lidar CALIOP with cross-polarization, which is the lowest dual-wavelength (532 and 1064 nm) polarization Lidar [34]. We used the CALIPSO aerosol products (cal_lid_l2_05kmapro-standard-v4-10 and cal_lid_l2_vfm-standard-v4-10) to analyze the transport distance and the range of influence of the dust in the 2017 dust events.…”

Section: Calipsomentioning

confidence: 99%

Can MERRA-2 Reanalysis Data Reproduce the Three-Dimensional Evolution Characteristics of a Typical Dust Process in East Asia? A Case Study of the Dust Event in May 2017

et al. 2020

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This study used the MERRA-2 reanalysis dataset and ground-based and satellite observational data to comprehensively analyze a typical dust storm event in east Asia on 2–7 May 2017 which engulfed most of China as well as ocean and Japan, and explore the accuracy and comprehensiveness of the MERRA-2 dataset in the analysis of dust processes. The results of comparison show that the description of the spatiotemporal distribution and evolution of the dust aerosols in the dust event using the MERRA-2 data is consistent with the data of AERONET, National Urban Air Quality Real-time Publishing Platform and Hamawari-8. Gobi Deserts was the most influential source area of this dust event with the highest emissions reaching 1.9 × 106 μg/m3. The vertical motion of the atmosphere can lift dust from the source area above 500 hPa. There were low-pressure troughs at 500 and 850 hPa and the winds behind and in front of the trough led to the high-altitude, long-distance transport of dust. Dust gradually affected the northwest China, north China, northeast China, and even the ocean and Japan on 2–7 May. This study demonstrates that although there is some uncertainty about the source of dust emission in the MERRA-2 model, the data accurately simulated the evolution of the dust event and analyze it comprehensively, while the accuracy of simulating the long-term evolution of dust requires further evaluation.

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“…The fine spectral resolution allows for the retrieval of accurate and detailed vertical temperature and moisture profiles, trace gas concentrations, and cloud and surface parameters. 9,[12][13][14] Broad-band sounders and imagers, on the other hand, are not capable of capturing this level of detail in vertical structure because their sensitivity to spectral differences in IR radiation is much lower, as illustrated by the example of the broad spectral response functions (SRFs) in Fig. 1.…”

Section: Instrumentsmentioning

confidence: 99%

Low earth orbit sounder retrieval products at geostationary earth orbit spatial and temporal scales

Anheuser

Weisz

Menzel

2020

J. Appl. Rem. Sens.

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Infrared (IR) sounders, onboard satellites in low Earth orbit, are high spectral resolution interferometers capable of providing very accurate IR radiance measurements using thousands of channels. Though their temporal resolution is a relatively low 12 h, these data can be used to produce high vertical resolution temperature and humidity profiles. Imagers, often aboard satellites in geostationary Earth orbit, are radiometers providing high spatial and temporal resolution radiance measurements across a more limited number of bands, typically ∼10 to ∼20. Their data are used for monitoring Earth's weather and climate. A data fusion method (developed and previously demonstrated at University of Wisconsin-Madison) is utilized to construct high vertical resolution, sounder-like temperature and humidity retrievals at imager high spatial and temporal resolution. Using the Crosstrack Infrared Sounder (CrIS) and Advanced Baseline Imager (ABI) data, comparison of concurrent and ∼50-min time-series fusion to radiosondes launched from February 2017 to March 2019 over the Department of Energy Atmospheric Radiation Measurement Southern Great Plains Site shows that the improved spatial and temporal resolution does not come at the expense of accuracy as compared with the sounder retrieval at native resolution. © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Satellites See the World’s Atmosphere

Cited by 42 publications

References 441 publications

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

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

Can MERRA-2 Reanalysis Data Reproduce the Three-Dimensional Evolution Characteristics of a Typical Dust Process in East Asia? A Case Study of the Dust Event in May 2017

Low earth orbit sounder retrieval products at geostationary earth orbit spatial and temporal scales

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