scholarly journals Verification of the AIRS and MLS ozone algorithms based on retrieved daytime and nighttime ozone

2020 ◽  
Author(s):  
Wannan Wang ◽  
Tianhai Cheng ◽  
Ronald van der A ◽  
Jos de Laat ◽  
Jason E. Williams
Keyword(s):  
Spatial Scales ◽  
Retrieval Algorithm ◽  
Surface Emissivity ◽  
Atmospheric Infrared Sounder ◽  
Retrieval Method ◽  
Dry Land ◽  
Weather And Climate ◽  
Additional Support ◽  
Infrared Instruments ◽  
Total Column

Abstract. Ozone (O3) plays a significant role in weather and climate on regional to global spatial scales. Most studies on the variability in the total column of O3 (TCO) are typically analysed using daytime data. Based on knowledge of the chemistry and transport of O3, significant deviations between daytime and nighttime O3 are only expected either in the planetary boundary layer (PBL) or high in the stratosphere or mesosphere, having little effect on the TCO. Hence, we expect the daytime and nighttime TCO to be very similar. Comparing daytime and nighttime TCOs thus provides an approach to verify the retrieval algorithms of infrared instruments like the Atmospheric InfraRed Sounder (AIRS) and the Microwave Limb Sounder (MLS). Applying this verification on the AIRS and the MLS data we identified inconsistencies in observations of O3 from both satellite instruments. For AIRS, daytime-nighttime differences were found over oceans resembling cloud cover patterns, and over land, mostly over dry land areas, likely related to infrared surface emissivity. These differences point to issues with the representation of both processes in the AIRS retrieval algorithm. For MLS, a major issue was identified with the “ascending-descending” orbit flag, used to discriminate nighttime and daytime MLS measurements. Disregarding this issue, MLS day-night differences were significantly smaller than AIRS day-night differences, providing additional support for retrieval method origin of AIRS day-night TCO differences. MLS day-night differences are dominated by the upper stratospheric and mesospheric diurnal O3 cycle. These results provide useful information for improving infrared O3 products and at the same time will allow study the day-night differences of stratospheric and mesospheric O3.

scholarly journals Verification of the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS) ozone algorithms based on retrieved daytime and night-time ozone

2021 ◽  
Vol 14 (2) ◽  
pp. 1673-1687
Author(s):  
Wannan Wang ◽  
Tianhai Cheng ◽  
Ronald J. van der A ◽  
Jos de Laat ◽  
Jason E. Williams
Keyword(s):  
Spatial Scales ◽  
Retrieval Algorithm ◽  
Satellite Measurements ◽  
Night Time ◽  
Atmospheric Infrared Sounder ◽  
Dry Land ◽  
Novel Approach ◽  
Additional Support ◽  
Column Ozone

Abstract. Ozone (O3) plays a significant role in weather and climate on regional to global spatial scales. Most studies on the variability in the total column of O3 (TCO) are typically carried out using daytime data. Based on knowledge of the chemistry and transport of O3, significant deviations between daytime and night-time O3 are only expected either in the planetary boundary layer (PBL) or high in the stratosphere or mesosphere, with little effect on the TCO. Hence, we expect the daytime and night-time TCO to be very similar. However, a detailed evaluation of satellite measurements of daytime and night-time TCO is still lacking, despite the existence of long-term records of both. Thus, comparing daytime and night-time TCOs provides a novel approach to verifying the retrieval algorithms of instruments such as the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS). In addition, such a comparison also helps to assess the value of night-time TCO for scientific research. Applying this verification on the AIRS and the MLS data, we identified inconsistencies in observations of O3 from both satellite instruments. For AIRS, daytime–night-time differences were found over oceans resembling cloud cover patterns and over land, mostly over dry land areas, which is likely related to infrared surface emissivity. These differences point to issues with the representation of both processes in the AIRS retrieval algorithm. For MLS, a major issue was identified with the “ascending–descending” orbit flag, used to discriminate night-time and daytime MLS measurements. Disregarding this issue, MLS day–night differences were significantly smaller than AIRS day–night differences, providing additional support for the retrieval method origin of AIRS in stratospheric column ozone (SCO) day–night differences. MLS day–night differences are dominated by the upper-stratospheric and mesospheric diurnal O3 cycle. These results provide useful information for improving infrared O3 products.

scholarly journals Improved agreement of AIRS tropospheric carbon monoxide products with other EOS sensors using optimal estimation retrievals

2010 ◽  
Vol 10 (19) ◽  
pp. 9521-9533 ◽  
Author(s):  
J. X. Warner ◽  
Z. Wei ◽  
L. L. Strow ◽  
C. D. Barnet ◽  
L. C. Sparling ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Degrees Of Freedom ◽  
Lower Troposphere ◽  
Optimal Estimation ◽  
Primary Objective ◽  
Retrieval Algorithm ◽  
Atmospheric Infrared Sounder ◽  
Error Covariance ◽  
Transport Experiment ◽  
Total Column

Abstract. We present in this paper an alternative retrieval algorithm for the Atmospheric Infrared Sounder (AIRS) tropospheric Carbon Monoxide (CO) products using the Optimal Estimation (OE) technique, which is different from the AIRS operational algorithm. The primary objective for this study was to compare AIRS CO, as well as the other retrieval properties such as the Averaging Kernels (AKs), the Degrees of Freedom for Signal (DOFS), and the error covariance matrix, against the Tropospheric Emission Spectrometer (TES) and the Measurement of Pollution in the Troposphere (MOPITT) CO, which were also derived using the OE technique. We also demonstrate that AIRS OE CO results are much more realistic than AIRS V5 operational CO, especially in the lower troposphere and in the Southern Hemisphere (SH). These products are validated with in situ profiles obtained by the Differential Absorption Carbon Monoxide Measurements (DACOM), which took place as part of NASA's Intercontinental Chemical Transport Experiment (INTEX-B) field mission that was conducted over the northern Pacific in Spring 2006. To demonstrate the differences existing in the current operational products we first show a detailed direct comparison between AIRS V5 and TES operational V3 CO for the global datasets from December 2005 to July 2008. We then present global CO comparisons between AIRS OE, TES V3, and MOPITT V4 at selected pressure levels as well as for the total column amounts. We conclude that the tropospheric CO retrievals from AIRS OE and TES V3 agree to within 5–10 ppbv or 5% on average globally and throughout the free troposphere. The agreements in total column CO amounts between AIRS OE and MOPITT V4 have improved significantly compared to AIRS V5 with global relative RMS differences now being 12.7%.

scholarly journals Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B

2014 ◽  
Vol 7 (3) ◽  
pp. 3021-3073 ◽  
Author(s):  
M. Grossi ◽  
P. Valks ◽  
D. Loyola ◽  
B. Aberle ◽  
S. Slijkhuis ◽  
...  
Keyword(s):  
Water Vapour ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Data Sets ◽  
Vertical Column ◽  
Data Set ◽  
Vertical Column Density ◽  
Data Processor ◽  
Climate Analysis ◽  
Total Column

Abstract. The knowledge of the total column water vapour (TCWV) global distribution is fundamental for climate analysis and weather monitoring. In this work, we present the retrieval algorithm used to derive the operational TCWV from the GOME-2 sensors and perform an extensive inter-comparison and validation in order to estimate their absolute accuracy and long-term stability. We use the recently reprocessed data sets retrieved by the GOME-2 instruments aboard EUMETSAT's MetOp-A and MetOp-B satellites and generated by DLR in the framework of the O3M-SAF using the GOME Data Processor (GDP) version 4.7. The retrieval algorithm is based on a classical Differential Optical Absorption Spectroscopy (DOAS) method and combines H2O/O2 retrieval for the computation of the trace gas vertical column density. We introduce a further enhancement in the quality of the H2O column by optimizing the cloud screening and developing an empirical correction in order to eliminate the instrument scan angle dependencies. We evaluate the overall consistency between about 8 months measurements from the newer GOME-2 instrument on the MetOp-B platform with the GOME-2/MetOp-A data in the overlap period. Furthermore, we compare GOME-2 results with independent TCWV data from ECMWF and with SSMIS satellite measurements during the full period January 2007–August 2013 and we perform a validation against the combined SSM/I + MERIS satellite data set developed in the framework of the ESA DUE GlobVapour project. We find global mean biases as small as ± 0.03 g cm−2 between GOME-2A and all other data sets. The combined SSM/I-MERIS sample is typically drier than the GOME-2 retrievals (−0.005 g cm−2), while on average GOME-2 data overestimate the SSMIS measurements by only 0.028 g cm−2. However, the size of some of these biases are seasonally dependent. Monthly average differences can be as large as 0.1 g cm−2, based on the analysis against SSMIS measurements, but are not as evident in the validation with the ECMWF and the SSM/I + MERIS data. Studying two exemplary months, we estimate regional differences and identify a very good agreement between GOME-2 total columns and all three independent data sets, especially for land areas, although some discrepancies over ocean and over land areas with high humidity and a relatively large surface albedo are also present.

scholarly journals Measurement of Small-Slope Free-Form Optical Surfaces with the Modified Phase Retrieval

Micromachines ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Xinxue Ma ◽  
Jianli Wang ◽  
Bin Wang ◽  
Xinyue Liu
Keyword(s):  
Wave Front ◽  
Phase Retrieval ◽  
Computation Time ◽  
Experimental Arrangement ◽  
Free Form ◽  
Retrieval Algorithm ◽  
Retrieval Method ◽  
Optical Surfaces ◽  
Image Capturing ◽  
Phase Retrieval Algorithm

In this paper, we demonstrate the use of the modified phase retrieval as a method for application in the measurement of small-slope free-form optical surfaces. This technique is a solution for the measurement of small-slope free-form optical surfaces, based on the modified phase retrieval algorithm, whose essence is that only two defocused images are needed to estimate the wave front with an accuracy similar to that of the traditional phase retrieval but with less image capturing and computation time. An experimental arrangement used to measure the small-slope free-form optical surfaces using the modified phase retrieval is described. The results of these experiments demonstrate that the modified phase retrieval method can achieve measurements comparable to those of the standard interferometer.

scholarly journals Extinction coefficients retrieved in deep tropical ice clouds from lidar observations using a CALIPSO-like algorithm compared to in-situ measurements from the Cloud Integrated Nephelometer during CRYSTAL-FACE

2006 ◽  
Vol 6 (5) ◽  
pp. 10649-10672 ◽  
Author(s):  
V. Noel ◽  
D. M. Winker ◽  
T. J. Garrett ◽  
M. McGill
Keyword(s):  
Spatial Scales ◽  
Deep Convection ◽  
Retrieval Algorithm ◽  
Crystal Face ◽  
Ice Clouds ◽  
Extinction Coefficients ◽  
Convective Systems ◽  
Lidar Ratio ◽  
Deep Convective Systems

Abstract. This paper presents a comparison of lidar ratios and volume extinction coefficients in tropical ice clouds, retrieved using observations from two instruments: the 532-nm Cloud Physics Lidar (CPL), and the in-situ Cloud Integrating Nephelometer (CIN) probe. Both instruments were mounted on airborne platforms during the CRYSTAL-FACE campaign and took measurements up to 17 km. Coincident observations from two cases of ice clouds located on top of deep convective systems are compared. First, lidar ratios are retrieved from CPL observations of attenuated backscatter, using a retrieval algorithm for opaque cloud similar to one used in the soon-to-be launched CALIPSO mission, and compared to results from the regular CPL algorithm. These lidar ratios are used to retrieve extinction coefficient profiles, which are compared to actual observations from the CIN in-situ probe, putting the emphasis on their vertical variability. When observations coincide, retrievals from both instruments are very similar. Differences are generally variations around the average profiles, and general trends on larger spatial scales are usually well reproduced. The two instruments agree well, with an average difference of less than 11% on optical depth retrievals. Results suggest the CALIPSO Deep Convection algorithm can be trusted to deliver realistic estimates of the lidar ratio, leading to good retrievals of extinction coefficients.

scholarly journals Retrievals of Tropospheric Ozone Profiles from the Synergic Observation of AIRS and OMI: Methodology and Validation

2018 ◽  
Author(s):  
Dejian Fu ◽  
Susan S. Kulawik ◽  
Kazuyuki Miyazaki ◽  
Kevin W. Bowman ◽  
John R. Worden ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Measurement Uncertainty ◽  
Tropospheric Ozone ◽  
Retrieval Algorithm ◽  
Vertical Resolution ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Global Coverage ◽  
Ozone Monitoring ◽  
Wide Swath

Abstract. The Tropospheric Emission Spectrometer (TES) on the A-Train Aura satellite was designed to profile tropospheric ozone and its precursors, taking measurements from 2004 to 2018. Starting in 2008, TES global sampling of tropospheric ozone was gradually reduced in latitude with global coverage stopping in 2011. To extend the record of TES, this work presents a multispectral approach that will provide O3 data products with vertical resolution and measurement uncertainty similar to TES by combining the single-footprint thermal infrared (TIR) hyperspectral radiances from the Aqua Atmospheric Infrared Sounder (AIRS) instrument and the ultraviolet (UV) channels from the Aura Ozone Monitoring Instrument (OMI). The joint AIR+OMI O3 retrievals are processed through the MUlti-SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) retrieval algorithm. Comparisons of collocated joint AIRS+OMI and TES to ozonesonde measurements show that both systems have similar errors, with mean and standard deviation of the differences well within the estimated measurement uncertainty. AIRS+OMI and TES have slightly different biases (within 5 parts per billion) versus the sondes. Both AIRS and OMI have wide swath widths (~ 1,650 km for AIRS; ~ 2,600 km for OMI) across satellite ground tracks. Consequently, the joint AIRS+OMI measurements have the potential to maintain TES vertical sensitivity while increasing coverage by two orders of magnitude, thus providing an unprecedented new dataset to quantify the evolution of tropospheric ozone.

The In situ Global Ocean Observing System for Climate (and Other Needs)

2015 ◽  
Vol 49 (2) ◽  
pp. 112-121
Author(s):  
Stephen R. Piotrowicz ◽  
David M. Legler
Keyword(s):  
Weather Forecasting ◽  
Spatial Scales ◽  
The Arctic ◽  
Global Ocean ◽  
Observation System ◽  
Ocean Management ◽  
Accuracy And Precision ◽  
Weather And Climate ◽  
Ocean Observing

AbstractThe Global Ocean Observing System (GOOS) is the international observation system that ensures long-term sustained ocean observations. The ocean equivalent of the atmospheric observing system supporting weather forecasting, GOOS, was originally developed to provide data for weather and climate applications. Today, GOOS data are used for all aspects of ocean management as well as weather and climate research and forecasting. National Oceanic and Atmospheric Administration (NOAA), through the Climate Observation Division of the Office of Oceanic and Atmospheric Research/Climate Program Office, is a major supporter of the climate component of GOOS. This paper describes the eight elements of GOOS, and the Arctic Observing Network, to which the Climate Observation Division is a major contributor. In addition, the paper addresses the evolution of the observing system as rapidly evolving new capabilities in sensors, platforms, and telecommunications allow observations at unprecedented temporal and spatial scales with the accuracy and precision required to address questions of climate variability and change.

scholarly journals Two-Step Phase Retrieval Algorithm Using Single-Intensity Measurement

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Cheng Zhang ◽  
Meiqin Wang ◽  
Qianwen Chen ◽  
Dong Wang ◽  
Sui Wei
Keyword(s):  
Phase Retrieval ◽  
Fourier Spectrum ◽  
Retrieval Algorithm ◽  
Improved Method ◽  
Retrieval Method ◽  
Intensity Measurements ◽  
Successful Recovery ◽  
Reconstruction Quality ◽  
Low Probability ◽  
Phase Retrieval Algorithm

Aiming at the problem that the single-intensity phase retrieval method has poor reconstruction quality and low probability of successful recovery, an improved method is proposed in this paper. Our method divides the phase retrieval into two steps: firstly, the GS algorithm is used to recover the amplitude in the spatial domain from the single-spread Fourier spectrum, and then the classical GS algorithm using two intensity measurements (one is recorded and the other is estimated from the first step) measurements is used to recover the phase. Finally, the effectiveness of the proposed method is verified by numerical experiments.

Surface Emissivity Impact on Temperature and Moisture Soundings from Hyperspectral Infrared Radiance Measurements

2011 ◽  
Vol 50 (6) ◽  
pp. 1225-1235 ◽  
Author(s):  
Zhigang Yao ◽  
Jun Li ◽  
Jinlong Li ◽  
Hong Zhang
Keyword(s):  
Land Surface ◽  
Prediction Models ◽  
Weather Prediction ◽  
Atmospheric Temperature ◽  
Retrieval Algorithm ◽  
Surface Emissivity ◽  
Angle Dependence ◽  
Infrared Radiance ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact

AbstractAn accurate land surface emissivity (LSE) is critical for the retrieval of atmospheric temperature and moisture profiles along with land surface temperature from hyperspectral infrared (IR) sounder radiances; it is also critical to assimilating IR radiances in numerical weather prediction models over land. To investigate the impact of different LSE datasets on Atmospheric Infrared Sounder (AIRS) sounding retrievals, experiments are conducted by using a one-dimensional variational (1DVAR) retrieval algorithm. Sounding retrievals using constant LSE, the LSE dataset from the Infrared Atmospheric Sounding Interferometer (IASI), and the baseline fit dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) are performed. AIRS observations over northern Africa on 1–7 January and 1–7 July 2007 are used in the experiments. From the limited regional comparisons presented here, it is revealed that the LSE from the IASI obtained the best agreement between the retrieval results and the ECMWF reanalysis, whereas the constant LSE gets the worst results when the emissivities are fixed in the retrieval process. The results also confirm that the simultaneous retrieval of atmospheric profile and surface parameters could reduce the dependence of soundings on the LSE choice and finally improve sounding accuracy when the emissivities are adjusted in the iterative retrieval. In addition, emissivity angle dependence is investigated with AIRS radiance measurements. The retrieved emissivity spectra from AIRS over the ocean reveal weak angle dependence, which is consistent with that from an ocean emissivity model. This result demonstrates the reliability of the 1DVAR simultaneous algorithm for emissivity retrieval from hyperspectral IR radiance measurements.

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