Seven years of global retrieval of cloud properties using space-borne data of GOME-1

Abstract. We present a global and regional multi-annual (June 1996–May 2003) analysis of cloud properties (spherical cloud albedo – CA, cloud optical thickness – COT and cloud top height – CTH) of optically thick (COT > 5) clouds, derived using measurements from the GOME instrument on board the ESA ERS-2 space platform. We focus on cloud top height, which is obtained from top-of-atmosphere backscattered solar light measurements in the O2 A-band using the Semi-Analytical CloUd Retrieval Algorithm SACURA. The physical framework relies on the asymptotic equations of radiative transfer. The dataset has been validated against independent ground- and satellite-based retrievals and is aimed to support trace-gases retrievals as well as to create a robust long-term climatology together with SCIAMACHY and GOME-2 ensuing retrievals. We observed the El Niño-Southern Oscillation anomaly in the 1997–1998 record through CTH values over the Pacific Ocean. The global average CTH as derived from GOME is 5.6 ± 3.2 km, for a corresponding average COT of 19.1 ± 13.9.

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Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

Atmospheric Measurement Techniques ◽

10.5194/amt-10-3215-2017 ◽

2017 ◽

Vol 10 (9) ◽

pp. 3215-3230 ◽

Cited By ~ 5

Author(s):

André Ehrlich ◽

Eike Bierwirth ◽

Larysa Istomina ◽

Manfred Wendisch

Keyword(s):

Remote Sensing ◽

Grain Size ◽

Sea Ice ◽

Optical Thickness ◽

Liquid Water ◽

Retrieval Algorithm ◽

Continuous Transition ◽

Cloud Properties ◽

Cloud Optical Thickness ◽

The Impact

Abstract. The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.

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Boosting long-term adaptation of hidden-Markov-models: incremental splitting of probability density functions

Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181) ◽

10.1109/icassp.1998.674459 ◽

2002 ◽

Author(s):

U. Bub ◽

H. Hoge

Keyword(s):

Probability Density ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Probability Density Functions ◽

Density Functions

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Trends and variability in stratospheric mixing: 1979–2005

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-7-6189-2007 ◽

2007 ◽

Vol 7 (3) ◽

pp. 6189-6228 ◽

Cited By ~ 1

Author(s):

H. Garny ◽

G. E. Bodeker ◽

M. Dameris

Keyword(s):

Solar Cycle ◽

Lyapunov Exponents ◽

Annual Cycle ◽

Degradation Products ◽

Southern Oscillation ◽

Trace Gases ◽

High Latitudes ◽

Quasi Biennial Oscillation ◽

Long Term Changes

Abstract. Changes in climate are likely to drive changes in stratospheric mixing with associated implications for changes in transport of ozone from tropical source regions to higher latitudes, transport of water vapour and source gas degradation products from the tropical tropopause layer into the mid-latitude lower stratosphere, and changes in the meridional distribution of long-lived trace gases. To diagnose long-term changes in stratospheric mixing, global monthly fields of Lyapunov exponents were calculated on the 450 K, 550 K, and 650 K isentropic surfaces by applying a trajectory model to wind fields from NCEP/NCAR reanalyses over the period 1979 to 2005. Potential underlying geophysical drivers of trends and variability in these mixing fields were investigated by applying a least squares regression model, which included basis functions for a mean annual cycle, seasonally dependent linear trends, the quasi-biennial oscillation (QBO), the solar cycle, and the El Niño Southern Oscillation (ENSO), to zonal mean time series of the Lyapunov exponents. Long-term positive trends in mixing are apparent over southern middle to high latitudes at 450 K through most of the year, while negative trends over southern high latitudes are apparent at 650 K from May to August. Wintertime negative trends in mixing over northern mid-latitudes are apparent at 550 K and 650 K. Over low latitudes, within 40° of the equator, the QBO exerts a strong influence on mixing at all three analysis levels. This QBO influence is strongly modulated by the annual cycle and shows a phase shift across the subtropical mixing barrier. Solar cycle and ENSO influences on mixing are generally not significant. The diagnosed long-term changes in mixing should aid the interpretation of trends in stratospheric trace gases.

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Aerosol retrieval based on 10 years of passive remote sensing satellite measurements over the Arctic – validation and trend analysis

10.5194/egusphere-egu2020-15037 ◽

2020 ◽

Author(s):

Soheila Jafariserajehlou ◽

Marco Vountas ◽

Larysa Istomina ◽

John P. Burrows

Keyword(s):

Remote Sensing ◽

Trend Analysis ◽

Optical Thickness ◽

Arctic Region ◽

The Arctic ◽

Retrieval Algorithm ◽

Identification Algorithm ◽

Aerosol Retrieval ◽

Along Track

The Aerosol Optical Thickness (AOT) retrieval over the Arctic region is a challenging task due to uncertainties and difficulties in its prerequisites, mainly (i) cloud masking methods and (ii) modeling the underlying snow/ice surface. In the past this led to a large data gap over the Arctic which hampered our understanding of the direct/indirect aerosol effect on Arctic and global climate change. For the purpose of improving our knowledge, we present, for the first time, long-term AOT maps of snow and ice covered areas based on satellite remote sensing.In this study, a previously developed aerosol retrieval algorithm over snow/ice, (Istomina et al., 2012; in IUP, University of Bremen) is used to retrieve AOT for a period of 10 years, 2002-2012, over the Arctic and to analyze its spatial and temporal changes. This algorithm is based on a multi-angle approach and uses pre-computed look-up tables to retrieve AOT.The algorithm has been improved with respect to cloud masking (based on clear snow spectral shape) using the ASCIA cloud identification algorithm (Jafariserajehlou et al., 2019). The modified AOT retrieval algorithm is applied to observations from Advanced Along-Track Scanning Radiometer (AATSR) on European Space Agency&#8217;s (ESA) measurements. The retrieved dataset provides long-term AOT at a spatial resolution of 1 km2 over snow/ice covered surface in the extended Arctic region (60&#176;- 90&#176;) during polar day. The results show that Arctic haze events appearing every late-winter and early spring are very well captured in AATSR derived AOTs. To validate the retrieved AOTs, results are compared with ground-based AERONET data. The comparisons revealed partially excellent agreement but also limits of the retrieval algorithm are discussed. In addition, some preliminary results of a trend analysis of the long-term record will be presented. It is foreseen to use the results in the trans-regional research project (AC)&#179; investigating Arctic amplification.References[1] Istomina, L.: Retrieval of aerosol optical thickness over snow and ice surfaces in the Arctic using Advanced Along Track Scanning Radiometer, PhD thesis, University of Bremen, Bremen, Germany, 2012.[2] Jafariserajehlou, S. and Mei, L. and Vountas, M. and Rozanov, V. and Burrows, J. P. and Hollmann, R., A cloud identification algorithm over the Arctic for use with AATSR/SLSTR measurements, Atmos. Meas. Tech., 12, 1059-1076, doi:10.5194/amt-12-1059-2019, 2019.&#160;

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Model Selection in Atmospheric Remote Sensing with an Application to Aerosol Retrieval from DSCOVR/EPIC, Part 1: Theory

Remote Sensing ◽

10.3390/rs12223724 ◽

2020 ◽

Vol 12 (22) ◽

pp. 3724

Author(s):

Sruthy Sasi ◽

Vijay Natraj ◽

Víctor Molina García ◽

Dmitry S. Efremenko ◽

Diego Loyola ◽

...

Keyword(s):

Model Selection ◽

Optical Thickness ◽

Marginal Likelihood ◽

Likelihood Estimation ◽

Retrieval Algorithm ◽

Aerosol Layer ◽

Aerosol Model ◽

Microphysical Properties ◽

Cloud Properties ◽

Atmospheric Remote Sensing

The retrieval of aerosol and cloud properties such as their optical thickness and/or layer/top height requires the selection of a model that describes their microphysical properties. We demonstrate that, if there is not enough information for an appropriate microphysical model selection, the solution’s accuracy can be improved if the model uncertainty is taken into account and appropriately quantified. For this purpose, we design a retrieval algorithm accounting for the uncertainty in model selection. The algorithm is based on (i) the computation of each model solution using the iteratively regularized Gauss–Newton method, (ii) the linearization of the forward model around the solution, and (iii) the maximum marginal likelihood estimation and the generalized cross-validation to estimate the optimal model. The algorithm is applied to the retrieval of aerosol optical thickness and aerosol layer height from synthetic measurements corresponding to the Earth Polychromatic Imaging Camera (EPIC) instrument onboard the Deep Space Climate Observatory (DSCOVR) satellite. Our numerical simulations show that the heuristic approach based on the thesolution minimizing the residual, which is frequently used in literature, is completely unrealistic when both the aerosol model and surface albedo are unknown.

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Linear trends in cloud top height from passive observations in the oxygen A-band

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-5679-2014 ◽

2014 ◽

Vol 14 (11) ◽

pp. 5679-5692 ◽

Cited By ~ 22

Author(s):

L. Lelli ◽

A. A. Kokhanovsky ◽

V. V. Rozanov ◽

M. Vountas ◽

J. P. Burrows

Keyword(s):

Southern Oscillation ◽

Global Scale ◽

Retrieval Algorithm ◽

Linear Change ◽

Strongly Coupled ◽

Latitude Belt ◽

Global Trend ◽

Asymptotic Equations ◽

Increasing Trend ◽

Least Squares Techniques

Abstract. Measurements by the hyperspectral spectrometers GOME, SCIAMACHY and GOME-2 are used to determine the rate of linear change (and trends) in cloud top height (CTH) in the period between June 1996 and May 2012. The retrievals are obtained from Top-Of-Atmosphere (TOA) backscattered solar light in the oxygen A-band using the Semi-Analytical CloUd Retrieval Algorithm SACURA. The physical framework relies on the asymptotic equations of radiative transfer, valid for optically thick clouds. Using linear least-squares techniques, a global trend of −1.78 ± 2.14 m yr−1 in deseasonalized CTH has been found, in the latitude belt within ±60°, with diverging tendencies over land (+0.27 ± 3.2 m yr−1) and ocean (−2.51 ± 2.8 m yr−1). The El Niño–Southern Oscillation (ENSO), strongly coupled to CTH, forces clouds to lower altitudes. The global ENSO-corrected trend in CTH amounts to −0.49 ± 2.22 m yr−1. At a global scale, no explicit regional pattern of statistically significant trends (at 95% confidence level, estimated with bootstrap technique) have been found, which would be representative of typical natural synoptical features. One exception is North Africa, which exhibits the strongest upward trend in CTH sustained by an increasing trend in water vapour.

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Trends in cloud top height from passive observations in the oxygen A-band

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-31409-2013 ◽

2013 ◽

Vol 13 (12) ◽

pp. 31409-31444

Author(s):

L. Lelli ◽

A. A. Kokhanovsky ◽

V. V. Rozanov ◽

M. Vountas ◽

J. P. Burrows

Keyword(s):

Southern Oscillation ◽

Global Scale ◽

Retrieval Algorithm ◽

Linear Change ◽

Strongly Coupled ◽

Latitude Belt ◽

Global Trend ◽

Asymptotic Equations ◽

Increasing Trend ◽

Least Squares Techniques

Abstract. Measurements by the hyperspectral spectrometers GOME, SCIAMACHY, and GOME-2 are used to determine the rate of linear change (and trends) in cloud top height (CTH) in the period between June 1996 and May 2012. The retrievals are obtained from Top-Of-Atmosphere (TOA) backscattered solar light in the oxygen A-band using the Semi-Analytical CloUd Retrieval Algorithm SACURA. The physical framework relies on the asymptotic equations of radiative transfer, valid for optically thick clouds. Using linear least-squares techniques, a global trend of −1.78 ± 2.14 m yr−1 in deseasonalised CTH has been found, in the latitude belt within ±60°, with diverging tendencies over land (+0.27 ± 3.2 m yr−1) and ocean (−2.51 ± 2.8 m yr−1). The El Niño-Southern Oscillation (ENSO), strongly coupled to CTH, forces clouds to lower altitudes. The global ENSO-corrected trend in CTH amounts to −0.49 ± 2.22 m yr−1. At a~global scale, no explicit regional pattern of statistically significant trends (at 95 % confidence level, estimated with bootstrap technique) have been found, which would be representative of typical natural synoptical features. One exception is North Africa, which exhibits the strongest upward trend in CTH sustained by an increasing trend in water vapor.

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Evaluating the Consistency and Continuity of Pixel-Scale Cloud Property Data Records From Aqua and SNPP

10.5194/amt-2021-391 ◽

2021 ◽

Author(s):

Qing Yue ◽

Eric J. Fetzer ◽

Likun Wang ◽

Brian H. Kahn ◽

Nadia Smith ◽

...

Keyword(s):

Global Environmental Change ◽

Retrieval Algorithm ◽

Cloud Data ◽

Cloud Properties ◽

Global Environmental ◽

Property Data ◽

Atmospheric Profile ◽

Cloud Top Pressure ◽

Pixel Scale

Abstract. The Aqua, SNPP, and JPSS satellites carry a combination of hyperspectral infrared sounders (AIRS, CrIS) and high-spatial-resolution narrowband imagers (MODIS, VIIRS). They provide an opportunity to acquire high-quality long-term cloud data records and are a key component of the existing Program of Record of cloud observations. By matching observations from sounders and imagers across different platforms at pixel scale, this study evaluates the self-consistency and continuity of cloud retrievals from Aqua and SNPP by multiple algorithms, including the AIRS Version-7 retrieval algorithm and the Community Long-term Infrared Microwave Combined Atmospheric Product System (CLIMCAPS) Version-2 for sounders, and the Standard Aqua-MODIS Collection-6.1 and the NASA MODIS-VIIRS continuity cloud products for imagers. Metrics describing detailed statistical distributions at sounder field of view (FOV) and the joint histograms of cloud properties are evaluated. These products are found highly consistent despite their retrieval from different sensors using different algorithms. Differences between the two sounder cloud products are mainly due to cloud clearing and treatment of clouds in scenes with unsuccessful atmospheric profile retrievals. The sounder subpixel cloud heterogeneity evaluated using the standard deviation of imager retrievals at sounder FOV shows good agreement between the standard and continuity products from different satellites. However, impact of algorithm and instrument differences between MODIS and VIIRS is revealed in cloud top pressure retrievals and in the imager cloud distribution skewness. Our study presents a unique aspect to examine NASA’s progress toward building a continuous cloud data record with sufficient quality to investigate clouds’ role in global environmental change.

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Trends and variability in stratospheric mixing: 1979–2005

Atmospheric Chemistry and Physics ◽

10.5194/acp-7-5611-2007 ◽

2007 ◽

Vol 7 (21) ◽

pp. 5611-5624 ◽

Cited By ~ 21

Author(s):

H. Garny ◽

G. E. Bodeker ◽

M. Dameris

Keyword(s):

Solar Cycle ◽

Lyapunov Exponents ◽

Annual Cycle ◽

Degradation Products ◽

Southern Oscillation ◽

Trace Gases ◽

High Latitudes ◽

Quasi Biennial Oscillation ◽

Long Term Changes

Abstract. Changes in climate are likely to drive changes in stratospheric mixing with associated implications for changes in transport of ozone from tropical source regions to higher latitudes, transport of water vapour and source gas degradation products from the tropical tropopause layer into the mid-latitude lower stratosphere, and changes in the meridional distribution of long-lived trace gases. To diagnose long-term changes in stratospheric mixing, global monthly fields of Lyapunov exponents were calculated on the 450 K, 550 K, and 650 K isentropic surfaces by applying a trajectory model to wind fields from NCEP/NCAR reanalyses over the period 1979 to 2005. Potential underlying geophysical drivers of trends and variability in these mixing fields were investigated by applying a least squares regression model, which included basis functions for a mean annual cycle, seasonally dependent linear trends, the quasi-biennial oscillation (QBO), the solar cycle, and the El Niño Southern Oscillation (ENSO), to zonal mean time series of the Lyapunov exponents. Long-term positive trends in mixing are apparent over southern middle to high latitudes at 450 K through most of the year, while negative trends over southern high latitudes are apparent at 650 K from May to August. Wintertime negative trends in mixing over northern mid-latitudes are apparent at 550 K and 650 K. Over low latitudes, within 40° of the equator, the QBO exerts a strong influence on mixing at all three analysis levels. This QBO influence is strongly modulated by the annual cycle and shows a phase shift across the subtropical mixing barrier. Solar cycle and ENSO influences on mixing are generally not significant. The diagnosed long-term changes in mixing should aid the interpretation of trends in stratospheric trace gases.

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