scholarly journals The operational cloud retrieval algorithms from TROPOMI on board Sentinel-5 Precursor

2018 ◽  
Vol 11 (1) ◽  
pp. 409-427 ◽  
Author(s):  
Diego G. Loyola ◽  
Sebastián Gimeno García ◽  
Ronny Lutz ◽  
Athina Argyrouli ◽  
Fabian Romahn ◽  
...  
Keyword(s):  
Near Infrared ◽  
European Space Agency ◽  
Recognition Algorithm ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Space Agency ◽  
Retrieval Algorithms ◽  
Ozone Monitoring

Abstract. This paper presents the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency Sentinel-5 Precursor (S5P) mission scheduled for launch in 2017. Two algorithms working in tandem are used for retrieving cloud properties: OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). OCRA retrieves the cloud fraction using TROPOMI measurements in the ultraviolet (UV) and visible (VIS) spectral regions, and ROCINN retrieves the cloud top height (pressure) and optical thickness (albedo) using TROPOMI measurements in and around the oxygen A-band in the near infrared (NIR). Cloud parameters from TROPOMI/S5P will be used not only for enhancing the accuracy of trace gas retrievals but also for extending the satellite data record of cloud information derived from oxygen A-band measurements, a record initiated with the Global Ozone Monitoring Experiment (GOME) on board the second European Remote-Sensing Satellite (ERS-2) over 20 years ago. The OCRA and ROCINN algorithms are integrated in the S5P operational processor UPAS (Universal Processor for UV/VIS/NIR Atmospheric Spectrometers), and we present here UPAS cloud results using the Ozone Monitoring Instrument (OMI) and GOME-2 measurements. In addition, we examine anticipated challenges for the TROPOMI/S5P cloud retrieval algorithms, and we discuss the future validation needs for OCRA and ROCINN.

scholarly journals The operational cloud retrieval algorithms from TROPOMI on board Sentinel-5 Precursor

2017 ◽  
Author(s):  
Diego G. Loyola ◽  
Sebastián Gimeno García ◽  
Ronny Lutz ◽  
Fabian Romahn ◽  
Robert J. D. Spurr ◽  
...  
Keyword(s):  
European Space Agency ◽  
Recognition Algorithm ◽  
Trace Gas ◽  
Infrared Sensors ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Low Clouds ◽  
Space Agency ◽  
Retrieval Algorithms ◽  
Data Record

Abstract. This paper presents the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency Sentinel-5 Precursor (S5P) mission scheduled for launch in 2017. Two algorithms working in tandem are used for retrieving cloud properties: OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). OCRA retrieves the cloud fraction using TROPOMI measurements in the UV/VIS spectral regions and ROCINN retrieves the cloud top height (pressure) and optical thickness (albedo) using TROPOMI measurements in and around the oxygen A-band in the NIR. Cloud parameters from TROPOMI/S5P will be used not only for enhancing the accuracy of trace gas retrievals, but also for extending the satellite data record of cloud information derived from oxygen A-band measurements, a record initiated with GOME/ERS-2 over twenty years ago. Use of the oxygen A-band generates complementary cloud information (especially for low clouds), as compared to traditional thermal infrared sensors (as used in most meteorological satellites) that are less sensitive to low clouds due to reduced thermal contrast. The OCRA and ROCINN algorithms are integrated in the S5P operational processor UPAS (Universal Processor for UV/VIS/NIR Atmospheric Spectrometers), and we present here UPAS cloud results using OMI and GOME-2 measurements. In addition, we examine anticipated challenges for the TROPOMI/S5P cloud retrieval algorithms and we discuss the future validation needs for OCRA and ROCINN.

scholarly journals The TROPOMI surface UV algorithm

2017 ◽  
Author(s):  
Anders V. Lindfors ◽  
Jukka Kujanpää ◽  
Niilo Kalakoski ◽  
Anu Heikkilä ◽  
Kaisa Lakkala ◽  
...  
Keyword(s):  
Dose Rate ◽  
Uv Radiation ◽  
Near Infrared ◽  
European Space Agency ◽  
Atmospheric Composition ◽  
Ozone Monitoring Instrument ◽  
Satellite Mission ◽  
Free Atmosphere ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) is the only payload of the Sentinel-5 Precursor (S5P), which is a polar orbiting satellite mission of the European Space Agency (ESA). TROPOMI is a nadir-viewing spectrometer measuring in the ultraviolet, visible, near-infrared and the shortwave infrared that provides near-global daily coverage. Among other things, TROPOMI measurements will be used for calculating the UV radiation reaching Earth's surface. Thus, the TROPOMI Surface UV product will contribute to the need of monitoring UV radiation by providing daily information on the prevailing UV conditions over the globe. The TROPOMI UV algorithm builds on the heritage of the OMI (Ozone Monitoring Instrument) and AC SAF (Satellite Application Facility for Atmospheric Composition and UV Radiation) algorithms. This paper provides a description of the algorithm that will be used for estimating surface UV radiation from TROPOMI observations. The TROPOMI Surface UV product includes the following UV quantities: the UV irradiance at 305, 310, 324, and 380 nm; the erythemally weighted UV; the vitamin-D weighted UV. Each of these are available as (i) daily dose or daily accumulated irradiance, (ii) overpass dose rate or irradiance, and (iii) local noon dose rate or irradiance. In addition, all quantities are available corresponding to actual cloud conditions and as clear-sky values, corresponding to otherwise the same conditions but assuming a cloud-free atmosphere. This yields 36 UV parameters altogether. The TROPOMI UV algorithm has been tested using input based on OMI and GOME-2 (Global Ozone Monitoring Experiment–2) satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.

scholarly journals The TROPOMI surface UV algorithm

2018 ◽  
Vol 11 (2) ◽  
pp. 997-1008 ◽  
Author(s):  
Anders V. Lindfors ◽  
Jukka Kujanpää ◽  
Niilo Kalakoski ◽  
Anu Heikkilä ◽  
Kaisa Lakkala ◽  
...  
Keyword(s):  
Dose Rate ◽  
Uv Radiation ◽  
Near Infrared ◽  
European Space Agency ◽  
Atmospheric Composition ◽  
Ozone Monitoring Instrument ◽  
Satellite Mission ◽  
Free Atmosphere ◽  
Monitoring Instrument ◽  
Ozone Monitoring

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) is the only payload of the Sentinel-5 Precursor (S5P), which is a polar-orbiting satellite mission of the European Space Agency (ESA). TROPOMI is a nadir-viewing spectrometer measuring in the ultraviolet, visible, near-infrared, and the shortwave infrared that provides near-global daily coverage. Among other things, TROPOMI measurements will be used for calculating the UV radiation reaching the Earth's surface. Thus, the TROPOMI surface UV product will contribute to the monitoring of UV radiation by providing daily information on the prevailing UV conditions over the globe. The TROPOMI UV algorithm builds on the heritage of the Ozone Monitoring Instrument (OMI) and the Satellite Application Facility for Atmospheric Composition and UV Radiation (AC SAF) algorithms. This paper provides a description of the algorithm that will be used for estimating surface UV radiation from TROPOMI observations. The TROPOMI surface UV product includes the following UV quantities: the UV irradiance at 305, 310, 324, and 380 nm; the erythemally weighted UV; and the vitamin-D weighted UV. Each of these are available as (i) daily dose or daily accumulated irradiance, (ii) overpass dose rate or irradiance, and (iii) local noon dose rate or irradiance. In addition, all quantities are available corresponding to actual cloud conditions and as clear-sky values, which otherwise correspond to the same conditions but assume a cloud-free atmosphere. This yields 36 UV parameters altogether. The TROPOMI UV algorithm has been tested using input based on OMI and the Global Ozone Monitoring Experiment-2 (GOME-2) satellite measurements. These preliminary results indicate that the algorithm is functioning according to expectations.

scholarly journals Ozone profile climatology for remote sensing retrieval algorithms

2019 ◽  
Vol 12 (9) ◽  
pp. 4745-4778 ◽  
Author(s):  
Kai Yang ◽  
Xiong Liu
Keyword(s):  
Remote Sensing ◽  
A Priori ◽  
Uv Spectra ◽  
Empirical Orthogonal Functions ◽  
Ozone Monitoring Instrument ◽  
Orthogonal Functions ◽  
Monitoring Instrument ◽  
Retrieval Algorithms ◽  
Ozone Monitoring ◽  
Priori Information

Abstract. New ozone (O3) profile climatologies are created from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) O3 record between 2005 and 2016, within the period of Aura Microwave Limb Sounder (MLS) and Aura Ozone Monitoring Instrument (OMI) assimilation. These two climatologies consist of monthly mean O3 profiles and the corresponding covariances dependent on the local solar time, longitude (15∘), and latitude (10∘), which are parameterized by tropopause pressure and total O3 column. They are validated through comparisons, which show good agreements with previous O3 profile climatologies. Compared to a monthly zonal mean climatology, both tropopause- and column-dependent climatologies provide improved a priori information for profile and total O3 retrievals from remote sensing measurements. Furthermore, parameterization of the O3 profile with total column O3 usually reduces the natural variability of the resulting climatological profile in the upper stratosphere further than the tropopause parameterization, which usually performs better in the upper troposphere and lower stratosphere (UTLS). Therefore tropopause-dependent climatology is more appropriate for profile O3 retrieval for complementing the vertical resolution of backscattered ultraviolet (UV) spectra, while the column-dependent climatology is more suited for use in total O3 retrieval algorithms, with an advantage of complete profile specification without requiring ancillary information. Compared to previous column-dependent climatologies, the new MERRA-2 column-dependent climatology better captures the diurnal, seasonal, and spatial variations and dynamical changes in O3 profiles with higher resolutions in O3, latitude, longitude, and season. The new MERRA-2 climatologies contain the first quantitative characterization of O3 profile covariances, which facilitate a new approach to improve O3 profiles using the most probable patterns of profile adjustments represented by the empirical orthogonal functions (EOFs) of the covariance matrices. The MERRA-2 daytime column-dependent climatology is used in the combo O3 and SO2 algorithm for retrieval from the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) satellite, the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on the Suomi National Polar Partnership (SNPP), and the Ozone Monitoring Instrument (OMI) on the Aura spacecraft.

scholarly journals Sensitivity of Dobson and Brewer Umkehr ozone profile retrievals to ozone cross-sections and stray light effects

2011 ◽  
Vol 4 (9) ◽  
pp. 1841-1853 ◽  
Author(s):  
I. Petropavlovskikh ◽  
R. Evans ◽  
G. McConville ◽  
S. Oltmans ◽  
D. Quincy ◽  
...  
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
European Space Agency ◽  
Stray Light ◽  
Ozone Monitoring Instrument ◽  
Section Data ◽  
Space Agency ◽  
Ozone Profile ◽  
The World ◽  
Ozone Monitoring

Abstract. Remote sounding methods are used to derive ozone profile and column information from various ground-based and satellite measurements. Vertical ozone profiles measured in Dobson units (DU) are currently retrieved based on laboratory measurements of the ozone absorption cross-section spectrum between 270 and 400 nm published in 1985 by Bass and Paur (BP). Recently, the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) proposed using the set of ozone cross-section measurements made at the Daumont laboratory in 1992 (BDM) for revising the Aura Ozone Monitoring Instrument (OMI) and Global Ozone Monitoring Experiment (GOME) satellite ozone profiles and total ozone column retrievals. Dobson Umkehr zenith sky data have been collected by NOAA ground-based stations at Boulder, CO (BDR) and Mauna Loa Observatory, HI (MLO) since the 1980s. The UMK04 algorithm is based on the BP ozone cross-section data. It is currently used for all Dobson Umkehr data processing submitted to the World Ozone and Ultraviolet radiation Data Centre (WOUDC) under the Global Atmosphere Watch (GAW) program of the World Meteorological Organization (WMO). Ozone profiles are also retrieved from measurements by the Mark IV Brewers operated by the NOAA-EPA Brewer Spectrophotometer UV and Ozone Network (NEUBrew) using a modified UMK04 algorithm (O3BUmkehr v.2.6, Martin Stanek). This paper describes the sensitivity of the Umkehr retrievals with respect to the proposed ozone cross-section changes. It is found that the ozone cross-section choice only minimally (within the retrieval accuracy) affects the Dobson and the Brewer Umkehr retrievals. On the other hand, significantly larger errors were found in the MLO and Boulder Umkehr ozone data (−8 and +5% bias in stratosphere and troposphere respectively) when the out-of-band (OOB) stray light contribution to the Umkehr measurement is not taken into account (correction is currently not included in the UMK04). The vertical distribution of OOB effect in the retrieved profile can be related to the local ozone climatology, instrument degradation, and optical characteristics of the instrument. Nonetheless, recurring OOB errors do not contribute to the long-term ozone trends.

scholarly journals Retrieving tropospheric nitrogen dioxide from the Ozone Monitoring Instrument: effects of aerosols, surface reflectance anisotropy, and vertical profile of nitrogen dioxide

2014 ◽  
Vol 14 (3) ◽  
pp. 1441-1461 ◽  
Author(s):  
J.-T. Lin ◽  
R. V. Martin ◽  
K. F. Boersma ◽  
M. Sneep ◽  
P. Stammes ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Vertical Profile ◽  
Measurement Errors ◽  
Surface Reflectance ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Reflectance Anisotropy ◽  
Cloud Properties ◽  
Optical Effects ◽  
Ozone Monitoring

Abstract. Retrievals of tropospheric nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) are subject to errors in the treatments of aerosols, surface reflectance anisotropy, and vertical profile of NO2. Here we quantify the influences over China via an improved retrieval process. We explicitly account for aerosol optical effects (simulated by nested GEOS-Chem at 0.667° long. × 0.5° lat. and constrained by aerosol measurements), surface reflectance anisotropy, and high-resolution vertical profiles of NO2 (simulated by GEOS-Chem). Prior to the NO2 retrieval, we derive the cloud information using consistent ancillary assumptions. We compare our retrieval to the widely used DOMINO v2 product, using MAX-DOAS measurements at three urban/suburban sites in East China as reference and focusing the analysis on the 127 OMI pixels (in 30 days) closest to the MAX-DOAS sites. We find that our retrieval reduces the interference of aerosols on the retrieved cloud properties, thus enhancing the number of valid OMI pixels by about 25%. Compared to DOMINO v2, our retrieval better captures the day-to-day variability in MAX-DOAS NO2 data (R2 = 0.96 versus 0.72), due to pixel-specific radiative transfer calculations rather than the use of a look-up table, explicit inclusion of aerosols, and consideration of surface reflectance anisotropy. Our retrieved NO2 columns are 54% of the MAX-DOAS data on average, reflecting the inevitable spatial inconsistency between the two types of measurement, errors in MAX-DOAS data, and uncertainties in our OMI retrieval related to aerosols and vertical profile of NO2. Sensitivity tests show that excluding aerosol optical effects can either increase or decrease the retrieved NO2 for individual OMI pixels with an average increase by 14%. Excluding aerosols also complexly affects the retrievals of cloud fraction and particularly cloud pressure. Employing various surface albedo data sets slightly affects the retrieved NO2 on average (within 10%). The retrieved NO2 columns increase when the NO2 profiles are taken from MAX-DOAS retrievals (by 19% on average) or TM4 simulations (by 13%) instead of GEOS-Chem simulations. Our findings are also relevant to retrievals of other pollutants (e.g., sulfur dioxide, ormaldehyde, glyoxal) from UV–visible backscatter satellite instruments.

scholarly journals Retrieving tropospheric nitrogen dioxide over China from the Ozone Monitoring Instrument: effects of aerosols, surface reflectance anisotropy and vertical profile of nitrogen dioxide

2013 ◽  
Vol 13 (8) ◽  
pp. 21203-21257 ◽  
Author(s):  
J.-T. Lin ◽  
R. V. Martin ◽  
K. F. Boersma ◽  
M. Sneep ◽  
P. Stammes ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Vertical Profile ◽  
Absolute Difference ◽  
Surface Reflectance ◽  
Ozone Monitoring Instrument ◽  
Mean Absolute Difference ◽  
Monitoring Instrument ◽  
Reflectance Anisotropy ◽  
Cloud Properties ◽  
Ozone Monitoring

Abstract. Retrievals of tropospheric nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) are subject to errors in the treatments of aerosols, surface reflectance anisotropy, and vertical profile of NO2. Here we quantify the influences over China via an improved retrieval process. We explicitly account for aerosol optical effects (simulated by nested GEOS-Chem at 0.667° lon × 0.5° lat and constrained by aerosol measurements), surface reflectance anisotropy, and high-resolution vertical profiles of NO2 (simulated by GEOS-Chem). Prior to the NO2 retrieval, we derive the cloud information using consistent ancillary assumptions. We compare our retrieval to the widely used DOMINO v2 product, using as reference MAX-DOAS measurements at three urban/suburban sites in East China and focusing the analysis on the 127 OMI pixels (in 30 days) closest to the MAX-DOAS sites. We find that our retrieval reduces the interference of aerosols on the retrieved cloud properties, thus enhancing the number of valid OMI pixels by about 25%. Compared to DOMINO v2, our retrieval improves the correlation with the MAX-DOAS data in the day-to-day variability of NO2 (R2 = 0.96 vs. 0.72). Our retrieved NO2 columns are about 50% of the MAX-DOAS data on average. This reflects the inevitable spatial inconsistency between the two types of measurement, uncertainties in MAX-DOAS data, and residual uncertainties in our OMI retrievals related to aerosols and vertical profile of NO2. Through a series of tests, we find that excluding aerosol scattering/absorption can either increase or decrease the retrieved NO2, with a mean absolute difference by about 20%. Concentrating aerosols at the boundary layer top enhances the retrieved NO2 by 8% on average with a mean absolute difference by 23%. The aerosol perturbations also affect nonlinearly the retrieved cloud fraction and particularly cloud pressure. Employing various surface albedo datasets alters the retrieved NO2 by 0–7% on average. The retrieved NO2 columns increase when the NO2 profiles are taken from MAX-DOAS retrievals (by 20% on average) or TM4 simulations (by 10%) instead of GEOS-Chem simulations. Our findings are also relevant to retrievals of other pollutants (e.g., sulfur dioxide, formaldehyde, glyoxal) from UV-vis backscatter satellite instruments.

scholarly journals OCRA radiometric cloud fractions for GOME-2 on MetOp-A/B

2015 ◽  
Vol 8 (12) ◽  
pp. 13471-13524 ◽  
Author(s):  
R. Lutz ◽  
D. Loyola ◽  
S. Gimeno García ◽  
F. Romahn
Keyword(s):  
A Priori ◽  
Recognition Algorithm ◽  
Cloud Fraction ◽  
Polarization Measurement ◽  
Point Of View ◽  
Computational Time ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Monitoring ◽  
Priori Information

Abstract. This paper describes an approach for cloud parameter retrieval (radiometric cloud fraction estimation) using the polarization measurements of the Global Ozone Monitoring Experiment-2 (GOME-2) on-board the MetOp-A/B satellites. The core component of the Optical Cloud Recognition Algorithm (OCRA) is the calculation of monthly cloud-free reflectances for a global grid (resolution of 0.2° in longitude and 0.2° in latitude) and to derive radiometric cloud fractions. These cloud fractions will serve as a priori information for the retrieval of cloud top height (CTH), cloud top pressure (CTP), cloud top albedo (CTA) and cloud optical thickness (COT) with the Retrieval Of Cloud Information using Neural Networks (ROCINN) algorithm. This approach is already being implemented operationally for the GOME/ERS-2 and SCIAMACHY/ENVISAT sensors and here we present version 3.0 of the OCRA algorithm applied to the GOME-2 sensors. Based on more than six years of GOME-2A data (February 2007–June 2013), reflectances are calculated for ≈ 35 000 orbits. For each measurement a degradation correction as well as a viewing angle dependent and latitude dependent correction is applied. In addition, an empirical correction scheme is introduced in order to remove the effect of oceanic sun glint. A comparison of the GOME-2A/B OCRA cloud fractions with co-located AVHRR geometrical cloud fractions shows a general good agreement with a mean difference of −0.15±0.20. From operational point of view, an advantage of the OCRA algorithm is its extremely fast computational time and its straightforward transferability to similar sensors like OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument) on Sentinel 5 Precursor, as well as Sentinel 4 and Sentinel 5. In conclusion, it is shown that a robust, accurate and fast radiometric cloud fraction estimation for GOME-2 can be achieved with OCRA by using the polarization measurement devices (PMDs).

scholarly journals OCRA radiometric cloud fractions for GOME-2 on MetOp-A/B

2016 ◽  
Vol 9 (5) ◽  
pp. 2357-2379 ◽  
Author(s):  
Ronny Lutz ◽  
Diego Loyola ◽  
Sebastián Gimeno García ◽  
Fabian Romahn
Keyword(s):  
A Priori ◽  
Recognition Algorithm ◽  
Cloud Fraction ◽  
Polarization Measurement ◽  
Point Of View ◽  
Computational Time ◽  
Ozone Monitoring Instrument ◽  
Monitoring Instrument ◽  
Ozone Monitoring ◽  
Priori Information

Abstract. This paper describes an approach for cloud parameter retrieval (radiometric cloud-fraction estimation) using the polarization measurements of the Global Ozone Monitoring Experiment-2 (GOME-2) onboard the MetOp-A/B satellites. The core component of the Optical Cloud Recognition Algorithm (OCRA) is the calculation of monthly cloud-free reflectances for a global grid (resolution of 0.2° in longitude and 0.2° in latitude) to derive radiometric cloud fractions. These cloud fractions will serve as a priori information for the retrieval of cloud-top height (CTH), cloud-top pressure (CTP), cloud-top albedo (CTA) and cloud optical thickness (COT) with the Retrieval Of Cloud Information using Neural Networks (ROCINN) algorithm. This approach is already being implemented operationally for the GOME/ERS-2 and SCIAMACHY/ENVISAT sensors and here we present version 3.0 of the OCRA algorithm applied to the GOME-2 sensors. Based on more than five years of GOME-2A data (April 2008 to June 2013), reflectances are calculated for  ≈  35 000 orbits. For each measurement a degradation correction as well as a viewing-angle-dependent and latitude-dependent correction is applied. In addition, an empirical correction scheme is introduced in order to remove the effect of oceanic sun glint. A comparison of the GOME-2A/B OCRA cloud fractions with colocated AVHRR (Advanced Very High Resolution Radiometer) geometrical cloud fractions shows a general good agreement with a mean difference of −0.15 ± 0.20. From an operational point of view, an advantage of the OCRA algorithm is its very fast computational time and its straightforward transferability to similar sensors like OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument) on Sentinel 5 Precursor, as well as Sentinel 4 and Sentinel 5. In conclusion, it is shown that a robust, accurate and fast radiometric cloud-fraction estimation for GOME-2 can be achieved with OCRA using polarization measurement devices (PMDs).

scholarly journals Ozone Profile Climatology for Remote Sensing Retrieval Algorithms

2019 ◽  
Author(s):  
Kai Yang ◽  
Xiong Liu
Keyword(s):  
Remote Sensing ◽  
A Priori ◽  
Uv Spectra ◽  
Empirical Orthogonal Functions ◽  
Ozone Monitoring Instrument ◽  
Orthogonal Functions ◽  
Monitoring Instrument ◽  
Retrieval Algorithms ◽  
Ozone Monitoring ◽  
Priori Information

Abstract. New ozone (O3) profile climatologies are created from the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) O3 record between 2005 and 2016, within the period of Aura Microwave Limb Sounder (MLS) and Aura Ozone Monitoring Instrument (OMI) assimilation. These two climatologies consist of local solar time, longitudinal (15°), and latitudinal (10°) dependent monthly mean O3 profiles and the corresponding covariances, which are parameterized respectively by tropopause pressure and total O3 column. They are validated through comparisons, which show good agreements with previous O3 profile climatologies. Compared to a monthly zonal mean climatology, both tropopause- and column-dependent climatologies provide improved a priori information for profile and total O3 retrievals from remote sensing measurements. Furthermore, parameterization of O3 profile with total column usually reduces the natural variability of the resulting climatological profile in the upper stratosphere further than the tropopause parameterization, which usually performs better in the upper troposphere and lower stratosphere (UTLS). Therefore tropopause-dependent climatology is more appropriate for profile O3 retrieval for complementing the vertical resolution of backscattered ultraviolet (UV) spectra, while the column-dependent climatology is more suited for use in total O3 retrieval algorithms, with an advantage of complete profile specification without requiring ancillary information. Compared to previous column-dependent climatologies, the new MERRA-2 column-dependent climatology better capture the diurnal, seasonal, and spatial variations and dynamical changes of O3 profiles with higher resolutions in O3, latitude, longitude, and season. The new MERRA-2 climatologies contain first quantitative characterization of O3 profile covariances, which facilitate a new approach to improve O3 profiles using the most probable patterns of profile adjustments represented by the empirical orthogonal functions (EOFs) of the covraniance matrices. The MERRA-2 daytime column-dependent climatology is used in the combo O3 and SO2 algorithm for retrieval from the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, the Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) on the Suomi National Polar Partnership (SNPP), and the Ozone Monitoring Instrument (OMI) on the Aura spacecraft.

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