scholarly journals Retrieval of Water Vapour Profiles from GLORIA Nadir Observations

2021 ◽  
Vol 13 (18) ◽  
pp. 3675
Author(s):  
Nils König ◽  
Gerald Wetzel ◽  
Michael Höpfner ◽  
Felix Friedl-Vallon ◽  
Sören Johansson ◽  
...  
Keyword(s):  
Water Vapour ◽  
Degrees Of Freedom ◽  
Infrared Imaging ◽  
A Priori ◽  
Reanalysis Data ◽  
Radiometric Calibration ◽  
Imaging Spectrometer ◽  
The North ◽  
Priori Information ◽  
Radiosonde Ascent

We present the first analysis of water vapour profiles derived from nadir measurements by the infrared imaging Fourier transform spectrometer GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere). The measurements were performed on 27 September 2017, during the WISE (Wave driven ISentropic Exchange) campaign aboard the HALO aircraft over the North Atlantic in an area between 37°–50°N and 20°–28°W. From each nadir recording of the 2-D imaging spectrometer, the spectral radiances of all non-cloudy pixels have been averaged after application of a newly developed cloud filter. From these mid-infrared nadir spectra, vertical profiles of H2O have been retrieved with a vertical resolution corresponding to five degrees of freedom below the aircraft. Uncertainties in radiometric calibration, temperature and spectroscopy have been identified as dominating error sources. Comparing retrievals resulting from two different a priori assumptions (constant exponential vs. ERA 5 reanalysis data) revealed parts of the flight where the observations clearly show inconsistencies with the ERA 5 water vapour fields. Further, a water vapour inversion at around 6 km altitude could be identified in the nadir retrievals and confirmed by a nearby radiosonde ascent. An intercomparison of multiple water vapour profiles from GLORIA in nadir and limb observational modes, IASI (Infrared Atmospheric Sounding Interferometer) satellite data from two different retrieval processors, and radiosonde measurements shows a broad consistency between the profiles. The comparison shows how fine vertical structures are represented by nadir sounders as well as the influence of a priori information on the retrievals.

scholarly journals IASI-METOP and MIPAS-ENVISAT data fusion

2010 ◽  
Vol 10 (1) ◽  
pp. 183-211 ◽  
Author(s):  
S. Ceccherini ◽  
U. Cortesi ◽  
S. Del Bianco ◽  
P. Raspollini ◽  
B. Carli
Keyword(s):  
Data Fusion ◽  
Degrees Of Freedom ◽  
Solution Method ◽  
Information Gain ◽  
A Priori ◽  
A Priori Information ◽  
Priori Information ◽  
Single Instrument ◽  
Fusion Products ◽  
Temporal Coverage

Abstract. The combination of data obtained with different sensors (data fusion) is a powerful technique that can provide target products of the best quality in terms of precision and accuracy, as well as spatial and temporal coverage and resolution. In this paper the results are presented of the data fusion of measurements of ozone vertical profile performed by two space-borne interferometers (IASI on METOP and MIPAS on ENVISAT) using the new measurement-space-solution method. With this method both the loss of information due to interpolation and the propagation of possible biases (caused by a priori information) are avoided. The data fusion products are characterized by means of retrieval errors, information gain, averaging kernels and number of degrees of freedom. The analysis is performed both on simulated and real measurements and the results demonstrate and quantify the improvement of data fusion products with respect to measurements of a single instrument.

scholarly journals In-Flight Radiometric Calibration Of The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

1988 ◽  
Author(s):  
James E. Conel ◽  
Robert O. Green ◽  
Ronald E. Alley ◽  
Carol J. Bruezte ◽  
Veronique Carrere ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Radiometric Calibration ◽  
Imaging Spectrometer

scholarly journals Unconstrained, robust Kalman filtering for GNSS troposphere tomography

2013 ◽  
Vol 6 (5) ◽  
pp. 9133-9162 ◽  
Author(s):  
W. Rohm ◽  
K. Zhang ◽  
J. Bosy
Keyword(s):  
Water Vapour ◽  
Kalman Filtering ◽  
Weather Prediction ◽  
A Priori ◽  
Real Data ◽  
Reference Station ◽  
A Priori Information ◽  
Dependent Observations ◽  
Integrated Water Vapour ◽  
Priori Information

Abstract. The mesoscale variability of water vapour (WV) in the troposphere is a highly complex phenomenon and modeling and monitoring the WV distribution is a very important but challenging task. Any observation technique that can reliably provide WV distribution is essential for both monitoring and predicting weather. GNSS tomography technique is a powerful tool that builds upon the critical ground-based GNSS infrastructure – Continuous Operating Reference Station (CORS) networks and can be used to sense the amount of WV. Previous research suggests that 3-D WV field from GNSS tomography has an uncertainty of 1 hPa. However all the models used in GNSS tomography heavily rely on a priori information and constraints from non-GNSS measurements. In this study, 3-D GNSS tomography models are investigated based on an unconstrained approach with limited a priori information. A case study is designed and the results show that unconstrained solutions are feasible by using a robust Kalman filtering technique and effective removal of linearly dependent observations and parameters. Discrepancies between reference wet refractivity data derived from the Australian Numerical Weather Prediction (NWP) model (i.e. ACCESS) and the GNSS tomography model using both simulated and real data are 4.2 ppm (mm km−1) and 6.5 ppm (mm km−1), respectively, which are essentially in the same order of accuracy. Therefore the accuracy of the integrated values should not be worse than 0.06 m in terms of zenith wet delay and the integrated water vapour is a fifth of this value which is roughly 10 mm.

scholarly journals Radiometric Intercomparison between Suomi-NPP VIIRS and Aqua MODIS Reflective Solar Bands Using Simultaneous Nadir Overpass in the Low Latitudes

2013 ◽  
Vol 30 (12) ◽  
pp. 2720-2736 ◽  
Author(s):  
Sirish Uprety ◽  
Changyong Cao ◽  
Xiaoxiong Xiong ◽  
Slawomir Blonski ◽  
Aisheng Wu ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Atmospheric Transmission ◽  
Imaging Spectrometer ◽  
The North ◽  
Swir Band ◽  
Low Latitudes ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Shortwave Infrared ◽  
The Impact

Abstract On-orbit radiometric performance of the Suomi National Polar-Orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) is studied using the extended simultaneous nadir overpass (SNO-x) approach. Unlike the traditional SNO analysis of data in the high latitudes, this study extends the analysis to the low latitudes—in particular, over desert and ocean sites with relatively stable and homogeneous radiometric properties—for intersatellite comparisons. This approach utilizes a pixel-by-pixel match with an efficient geospatial matching algorithm to map VIIRS data into the Moderate Resolution Imaging Spectroradiometer (MODIS). VIIRS moderate-resolution bands M-1 through M-8 are compared with Aqua MODIS equivalent bands to quantify radiometric bias over the North African desert and over the ocean. Biases exist between VIIRS and MODIS in several bands, primarily because of spectral differences as well as possible calibration uncertainties, residual cloud contamination, and bidirectional reflectance distribution function (BRDF). The impact of spectral differences on bias is quantified by using the Moderate Resolution Atmospheric Transmission (MODTRAN) and hyperspectral measurements from the Earth Observing-1 (EO-1) Hyperion and the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). After accounting for spectral differences and bias uncertainties, the VIIRS radiometric bias over desert agrees with MODIS measurements within 2% except for the VIIRS shortwave infrared (SWIR) band M-8, which indicates a nearly 3% bias. Over ocean, VIIRS agrees with MODIS within 2% by the end of January 2013 with uncertainty less than 1%. Furthermore, VIIRS bias relative to MODIS is also computed at the Antarctica Dome C site for validation and the result agrees well within 1% with the bias estimated using SNO-x over desert.

scholarly journals Imager-to-radiometer inflight cross calibration: RSP radiometric comparison with airborne and satellite sensors

2015 ◽  
Vol 8 (10) ◽  
pp. 10361-10386
Author(s):  
J. McCorkel ◽  
B. Cairns ◽  
A. Wasilewski
Keyword(s):  
Infrared Imaging ◽  
Spectral Response ◽  
Landsat 8 ◽  
Radiometric Calibration ◽  
Imaging Spectrometer ◽  
Airborne Measurements ◽  
Satellite Sensors ◽  
Cross Calibration ◽  
Spectrometer Data ◽  
Spectral Channels

Abstract. This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP) that takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

scholarly journals Atmospheric composition and thermodynamic retrievals from the ARIES airborne FTS system – Part 1: Technical aspects and simulated capability

2013 ◽  
Vol 6 (6) ◽  
pp. 10833-10887 ◽  
Author(s):  
S. M. Illingworth ◽  
G. Allen ◽  
S. Newman ◽  
A. Vance ◽  
F. Marenco ◽  
...  
Keyword(s):  
Evaluation System ◽  
Degrees Of Freedom ◽  
Retrieval System ◽  
A Priori ◽  
Atmospheric Composition ◽  
Trace Gas ◽  
Technical Aspects ◽  
System Part ◽  
Priori Information ◽  
The Uk

Abstract. In this study we present an assessment of the retrieval capability of the Airborne Research Interferometer Evaluation System (ARIES); an airborne remote sensing Fourier Transform Spectrometer (FTS) operated on the UK Facility for Airborne Atmospheric Measurement (FAAM) aircraft. Simulated optimally-estimated-retrievals of partial column trace gas concentrations, and thermodynamic vertical profiles throughout the troposphere and planetary boundary layer have been performed here for simulated infrared spectra representative of the ARIES system. We also describe the operational and technical aspects of the pre-processing necessary for routine retrieval from the FAAM platform and the selection and construction of a priori information. As exemplars of the capability of the ARIES retrieval system, simulated retrievals of temperature, water vapour (H2O), carbon monoxide (CO), ozone (O3), and methane (CH4), and their corresponding sources of error and potential vertical sensitivity, are discussed for ARIES scenes across typical global environments. The maximum Degrees of Freedom for Signal (DOFS) for the retrievals, assuming a flight altitude of 7 km, were: 3.99, 2.97, 0.85, 0.96, and 1.45 for temperature, H2O, CO, O3, and CH4, respectively for the a priori constraints specified. Retrievals of temperature display significant vertical sensitivity (DOFS in the range 2.6 to 4.0 across the altitude range) as well as excellent simulated accuracy, with the vertical sensitivity for H2O also extending to lower altitudes (DOFS ranging from 1.6 to 3.0). It was found that the maximum sensitivity for CO, O3, and CH4 was approximately 1–2 km below the simulated altitudes in all scenarios. Comparisons of retrieved and simulated-truth partial atmospheric columns are used to assess the capability of the ARIES measurement system. Maximum mean biases (and bias standard deviations) in partial columns (i.e. below aircraft total columns) were found to be: +0.06 (±0.02 at 1σ) %, +3.95 (±3.11)%, +3.74 (±2.97)%, −8.26 (±4.64)% and +3.01 (±2.61)% for temperature, H2O, CO, O3, and CH4 respectively, illustrating that the retrieval system performs well compared to an optimal scheme. The maximum total a posteriori retrieval errors across the partial columns were also calculated, and were found to be 0.20%, 22.57%, 18.22%, 17.61%, and 16.42% for temperature, H2O, CO, O3, and CH4 respectively.

scholarly journals Spectral and Radiometric Calibration of the Next Generation Airborne Visible Infrared Spectrometer (AVIRIS-NG)

2019 ◽  
Vol 11 (18) ◽  
pp. 2129 ◽  
Author(s):  
John W. Chapman ◽  
David R. Thompson ◽  
Mark C. Helmlinger ◽  
Brian D. Bue ◽  
Robert O. Green ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Image Data ◽  
Radiometric Calibration ◽  
Next Generation ◽  
Imaging Spectrometer ◽  
In Situ Data ◽  
Novel Approach ◽  
Infrared Spectrometer ◽  
Calibration Techniques ◽  
Spectrometer Data

We describe advanced spectral and radiometric calibration techniques developed for NASA’s Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). By employing both statistically rigorous analysis and utilizing in situ data to inform calibration procedures and parameter estimation, we can dramatically reduce undesirable artifacts and minimize uncertainties of calibration parameters notoriously difficult to characterize in the laboratory. We describe a novel approach for destriping imaging spectrometer data through minimizing a Markov Random Field model. We then detail statistical methodology for bad pixel correction of the instrument, followed by the laboratory and field protocols involved in the corrections and evaluate their effectiveness on historical data. Finally, we review the geometric processing procedure used in production of the radiometrically calibrated image data.

scholarly journals Atmospheric composition and thermodynamic retrievals from the ARIES airborne FTS system – Part 1: Technical aspects and simulated capability

2014 ◽  
Vol 7 (4) ◽  
pp. 1133-1150 ◽  
Author(s):  
S. M. Illingworth ◽  
G. Allen ◽  
S. Newman ◽  
A. Vance ◽  
F. Marenco ◽  
...  
Keyword(s):  
Evaluation System ◽  
Degrees Of Freedom ◽  
Retrieval System ◽  
A Priori ◽  
Atmospheric Composition ◽  
A Posteriori ◽  
Technical Aspects ◽  
System Part ◽  
Priori Information ◽  
The Uk

Abstract. In this study we present an assessment of the retrieval capability of the Airborne Research Interferometer Evaluation System (ARIES): an airborne remote-sensing Fourier transform spectrometer (FTS) operated on the UK Facility for Airborne Atmospheric Measurement (FAAM) aircraft. Simulated maximum a posteriori retrievals of partial column trace gas concentrations, and thermodynamic vertical profiles throughout the troposphere and planetary boundary layer have been performed here for simulated infrared spectra representative of the ARIES system operating in the nadir-viewing geometry. We also describe the operational and technical aspects of the pre-processing necessary for routine retrieval from the FAAM platform and the selection and construction of a priori information. As exemplars of the capability of the ARIES retrieval system, simulated retrievals of temperature, water vapour (H2O), carbon monoxide (CO), ozone (O3), and methane (CH4), and their corresponding sources of error and potential vertical sensitivity, are discussed for ARIES scenes across typical global environments. The maximum Degrees of Freedom for Signal (DOFS) for the retrievals, assuming a flight altitude of 7 km, were 3.99, 2.97, 0.85, 0.96, and 1.45 for temperature, H2O, CO, O3, and CH4, respectively, for the a priori constraints specified. Retrievals of temperature display significant vertical sensitivity (DOFS in the range 2.6 to 4.0 across the altitude range) as well as excellent simulated accuracy, with the vertical sensitivity for H2O also extending to lower altitudes (DOFS ranging from 1.6 to 3.0). It was found that the maximum sensitivity for CO, O3, and CH4 was approximately 1–2 km below the simulated altitudes in all scenarios. Comparisons of retrieved and simulated-truth partial atmospheric columns are used to assess the capability of the ARIES measurement system. Maximum mean biases (and bias standard deviations) in partial columns (i.e. below aircraft total columns) were found to be +0.06 (±0.02 at 1σ)%, +3.95 (±3.11)%, +3.74 (±2.97)%, −8.26 (±4.64)%, and +3.01 (±2.61)% for temperature, H2O, CO, O3, and CH4, respectively, illustrating that the retrieval system performs well compared to an optimal scheme. The maximum total a posteriori retrieval errors across the partial columns were also calculated, and were found to be 0.20, 22.57, 18.22, 17.61, and 16.42% for temperature, H2O, CO, O3, and CH4, respectively.

scholarly journals Elimination of hidden a priori information from remotely sensed profile data

2007 ◽  
Vol 7 (2) ◽  
pp. 397-408 ◽  
Author(s):  
T. von Clarmann ◽  
U. Grabowski
Keyword(s):  
Degrees Of Freedom ◽  
A Priori ◽  
Michelson Interferometer ◽  
State Variables ◽  
A Priori Information ◽  
Loss Of Information ◽  
Remote Measurements ◽  
Priori Information ◽  
Representation Scheme ◽  
Additional Loss

Abstract. Profiles of atmospheric state variables retrieved from remote measurements often contain a priori information which causes complication in the statistical use of data and in the comparison with other measured or modeled data. For such applications it often is desirable to remove the a priori information from the data product. If the retrieval involves an ill-posed inversion problem, formal removal of the a priori information requires resampling of the data on a coarser grid, which in some sense, however, is a prior constraint in itself. The fact that the trace of the averaging kernel matrix of a retrieval is equivalent to the number of degrees of freedom of the retrieval is used to define an appropriate information-centered representation of the data where each data point represents one degree of freedom. Since regridding implies further degradation of the data and thus causes additional loss of information, a re-regularization scheme has been developed which allows resampling without additional loss of information. For a typical ClONO2 profile retrieved from spectra as measured by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the constrained retrieval has 9.7 degrees of freedom. After application of the proposed transformation to a coarser information-centered altitude grid, there are exactly 9 degrees of freedom left, and the averaging kernel on the coarse grid is unity. Pure resampling on the information-centered grid without re-regularization would reduce the degrees of freedom to 7.1 (6.7) for a staircase (triangular) representation scheme.

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