scholarly journals Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach

2016 ◽  
Vol 9 (3) ◽  
pp. 1135-1152 ◽  
Author(s):  
Hans Martin Schulz ◽  
Boris Thies ◽  
Shih-Chieh Chang ◽  
Jörg Bendix
Keyword(s):  
Optical Thickness ◽  
Cloud Forest ◽  
New Technique ◽  
Remotely Sensed Data ◽  
Detection Scheme ◽  
Cloud Properties ◽  
Cloud Optical Thickness ◽  
Frequency Map ◽  
Fog Detection

Abstract. The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of  ≈ 40, classification errors significantly increase.

scholarly journals Detection of ground fog in mountainous areas from MODIS day-time data using a statistical approach

2015 ◽  
Vol 8 (11) ◽  
pp. 12155-12201
Author(s):  
H. M. Schulz ◽  
B. Thies ◽  
S.-C. Chang ◽  
J. Bendix
Keyword(s):  
Optical Thickness ◽  
Cloud Forest ◽  
New Technique ◽  
Time Data ◽  
Remotely Sensed Data ◽  
Detection Scheme ◽  
Cloud Properties ◽  
Cloud Optical Thickness ◽  
Frequency Map ◽  
Fog Detection

Abstract. The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data can not be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog from MODIS data in mountainous terrain is presented. Due to the sharpening of input data using MODIS bands 1 and 2 the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.

scholarly journals Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O<sub>2</sub>-O<sub>2</sub>, MODIS and Suomi-NPP VIIRS

2020 ◽  
Author(s):  
Steven Compernolle ◽  
Athina Argyrouli ◽  
Ronny Lutz ◽  
Maarten Sneep ◽  
Jean-Christopher Lambert ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Atmospheric Composition ◽  
Cloud Data ◽  
Geographical Patterns ◽  
Cloud Properties ◽  
Accurate Knowledge ◽  
Cloud Height ◽  
Cloud Optical Thickness ◽  
High Clouds

Abstract. Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data derived from Copernicus Sentinel-5 Precursor (S5P) TROPOMI radiance measurements: cloud top height and cloud optical thickness (retrieved with the S5P OCRA/ROCINN_CAL algorithm), cloud height (S5P OCRA/ROCINN_CRB and S5P FRESCO) and radiometric cloud fraction (all three algorithms). The analysis combines: (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS and OMI O2-O2), and (iii) ground-based validation with respect to correlative observations (2018-04-30 to 2020-02-27) from the CLOUDNET network of ceilometers, lidars and radars. Peculiar geographical patterns were identified, and will be mitigated in future releases of the cloud data products. Zonal mean latitudinal variation of S5P cloud properties are similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud top height and cloud optical thickness, and with CLOUDNET cloud top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud top height is below the cloud top height of VIIRS and of CLOUDNET, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the CLOUDNET cloud mean height for the low clouds, but match on an average better with the CLOUDNET cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the CLOUDNET observations.

scholarly journals Sensitivity of liquid cloud optical thickness and effective radius retrievals to cloud bow and glory conditions using two SEVIRI imagers

2019 ◽  
Vol 12 (5) ◽  
pp. 2863-2879 ◽  
Author(s):  
Nikos Benas ◽  
Jan Fokke Meirink ◽  
Martin Stengel ◽  
Piet Stammes
Keyword(s):  
Size Distribution ◽  
Optical Thickness ◽  
Droplet Size Distribution ◽  
Effective Radius ◽  
High Temporal Resolution ◽  
Climate Data ◽  
Cloud Properties ◽  
Data Record ◽  
Stratocumulus Clouds ◽  
Cloud Optical Thickness

Abstract. Retrievals of cloud properties from geostationary satellite sensors offer extensive spatial and temporal coverage and resolution. The high temporal resolution allows the observation of diurnally resolved cloud properties. However, retrievals are sensitive to varying illumination and viewing geometries, including cloud glory and cloud bow conditions, which can lead to irregularities in the diurnal data record. In this study, these conditions and their effects on liquid cloud optical thickness and effective radius retrievals are analyzed using the Cloud Physical Properties (CPP) algorithm. This analysis is based on the use of Spinning Enhanced Visible and Infrared Imager (SEVIRI) reflectances and products from Meteosat-8 and Meteosat-10, which are located over the Indian and Atlantic Ocean, respectively, and cover an extensive common area under different viewing angles. Comparisons of the retrievals from two full days, over ocean and land, and using different spectral combinations of visible and shortwave-infrared channels, are performed, to assess the importance of these factors in the retrieval process. The sensitivity of the cloud-bow- and cloud-glory-related irregularities to the width of the assumed droplet size distribution is analyzed by using different values of the effective variance of the size distribution. The results suggest for marine stratocumulus clouds an effective variance of around 0.05, which implies a narrower size distribution than typically assumed in satellite-based retrievals. For the case with continental clouds a broader size distribution (effective variance around 0.15) is obtained. This highlights the importance of appropriate size distribution assumptions and provides a way to improve the quality of cloud products in future climate data record releases.

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

2017 ◽  
Vol 10 (9) ◽  
pp. 3215-3230 ◽  
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.

scholarly journals Comparing ERA-Interim clouds with satellite observations using a simplified satellite simulator

2018 ◽  
Author(s):  
Martin Stengel ◽  
Cornelia Schlundt ◽  
Stefan Stapelberg ◽  
Oliver Sus ◽  
Salomon Eliasson ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Reanalysis Data ◽  
Cloud Fraction ◽  
Satellite Observations ◽  
Vertical Position ◽  
Polar Regions ◽  
Cloud Properties ◽  
Low Clouds ◽  
Low Cloud ◽  
Cloud Optical Thickness

Abstract. An evaluation of the ERA-Interim clouds using satellite observations is presented. To facilitate such an evaluation in a proper way, a simplified satellite simulator has been developed and applied to six-hourly ERA-Interim reanalysis data covering the period 1982 to 2014. The simulator converts modelled cloud fields, for example those of the ERA-Interim reanalysis, to simulated cloud fields by accounting for specific characteristics of passive imaging satellite sensors such as the Advanced Very High Resolution Radiometer (AVHRR), which form the basis of many long-term observational datasets of cloud properties. It is attempted to keep the simulated cloud fields close to the original modelled cloud fields to allow a quality assessment of the latter based on comparisons of the simulated clouds fields with the observations. Applying the simulator to ERA-Interim data, this study firstly focuses on spatial distribution and frequency of clouds (total cloud fraction) and on their vertical position, using cloud top pressure to express the cloud fraction of high, mid-level and low clouds. Furthermore, the cloud-top thermodynamic phase is investigated. All comparisons incorporate knowledge of systematic uncertainties in the satellite observations and are further stratified by accounting for the limited sensitivity of the observations to clouds with very low cloud optical thickness (COT). The comparisons show that ERA-Interim has generally too low cloud fraction – nearly everywhere on the globe except in the polar regions. This underestimation is caused by a lack of mid-level and/or low clouds – for which the comparisons only show a minor sensitivity to cloud optical thickness thresholds applied. The amount of ERA-Interim high clouds, being higher than in the observations, agrees to the observations within their estimated uncertainties. Removing the optically very thin clouds (COT 

scholarly journals Sensitivity of liquid cloud optical thickness and effective radius retrievals to cloud bow and glory conditions using two SEVIRI imagers

2019 ◽  
Author(s):  
Nikos Benas ◽  
Jan Fokke Meirink ◽  
Martin Stengel ◽  
Piet Stammes
Keyword(s):  
Size Distribution ◽  
Optical Thickness ◽  
Droplet Size Distribution ◽  
Effective Radius ◽  
High Temporal Resolution ◽  
Climate Data ◽  
Cloud Properties ◽  
Data Record ◽  
Stratocumulus Clouds ◽  
Cloud Optical Thickness

Abstract. Retrievals of cloud properties from geostationary satellite sensors offer extensive spatial and temporal coverage and resolution. The high temporal resolution allows the detection of diurnally resolved cloud properties. However, retrievals are sensitive to varying illumination and viewing geometries, including cloud glory and cloud bow conditions, which can lead to irregularities in the diurnal data record. In this study, these conditions and their effects on liquid cloud optical thickness and effective radius retrievals were analyzed using the Cloud Physical Properties (CPP) algorithm. This analysis was based on the use of SEVIRI reflectances and products from Meteosat-8 and -10, which are located over the Indian and Atlantic Ocean, respectively, and cover an extensive common area under different viewing angles. Comparisons of the retrievals over different underlying surfaces (ocean/land) and using different spectral combinations of visible and shortwave-infrared channels were also performed, to assess the importance of these factors in the retrieval process. The sensitivity of the cloud bow and glory related irregularities to the width of the assumed droplet size distribution was analyzed by using different values of the effective variance of the size distribution. The results suggest for marine stratocumulus clouds an effective variance of around 0.05, which implies a narrower size distribution than typically assumed in satellite-based retrievals. For a case with continental clouds a broader size distribution (effective variance around 0.15) was obtained. This highlights the importance of appropriate size distribution assumptions and provides a way to improve the quality of cloud products in future climate data record releases.

scholarly journals Validation of the Sentinel-5 Precursor TROPOMI cloud data with Cloudnet, Aura OMI O<sub>2</sub>–O<sub>2</sub>, MODIS, and Suomi-NPP VIIRS

2021 ◽  
Vol 14 (3) ◽  
pp. 2451-2476
Author(s):  
Steven Compernolle ◽  
Athina Argyrouli ◽  
Ronny Lutz ◽  
Maarten Sneep ◽  
Jean-Christopher Lambert ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Recognition Algorithm ◽  
Atmospheric Composition ◽  
Oxygen Absorption ◽  
Absorption Bands ◽  
Cloud Data ◽  
Geographical Patterns ◽  
Cloud Properties ◽  
Cloud Height ◽  
Cloud Optical Thickness

Abstract. Accurate knowledge of cloud properties is essential to the measurement of atmospheric composition from space. In this work we assess the quality of the cloud data from three Copernicus Sentinel-5 Precursor (S5P) TROPOMI cloud products: (i) S5P OCRA/ROCINN_CAL (Optical Cloud Recognition Algorithm/Retrieval of Cloud Information using Neural Networks;Clouds-As-Layers), (ii) S5P OCRA/ROCINN_CRB (Clouds-as-Reflecting Boundaries), and (iii) S5P FRESCO-S (Fast Retrieval Scheme for Clouds from Oxygen absorption bands – Sentinel). Target properties of this work are cloud-top height and cloud optical thickness (OCRA/ROCINN_CAL), cloud height (OCRA/ROCINN_CRB and FRESCO-S), and radiometric cloud fraction (all three algorithms). The analysis combines (i) the examination of cloud maps for artificial geographical patterns, (ii) the comparison to other satellite cloud data (MODIS, NPP-VIIRS, and OMI O2–O2), and (iii) ground-based validation with respect to correlative observations (30 April 2018 to 27 February 2020) from the Cloudnet network of ceilometers, lidars, and radars. Zonal mean latitudinal variation of S5P cloud properties is similar to that of other satellite data. S5P OCRA/ROCINN_CAL agrees well with NPP VIIRS cloud-top height and cloud optical thickness and with Cloudnet cloud-top height, especially for the low (mostly liquid) clouds. For the high clouds, S5P OCRA/ROCINN_CAL cloud-top height is below the cloud-top height of VIIRS and of Cloudnet, while its cloud optical thickness is higher than that of VIIRS. S5P OCRA/ROCINN_CRB and S5P FRESCO cloud height are well below the Cloudnet cloud mean height for the low clouds but match on average better with the Cloudnet cloud mean height for the higher clouds. As opposed to S5P OCRA/ROCINN_CRB and S5P FRESCO, S5P OCRA/ROCINN_CAL is well able to match the lowest CTH mode of the Cloudnet observations. Peculiar geographical patterns are identified in the cloud products and will be mitigated in future releases of the cloud data products.

scholarly journals Exploring the differences in cloud properties observed by the Terra and Aqua MODIS sensors

2009 ◽  
Vol 9 (1) ◽  
pp. 1489-1520
Author(s):  
N. Meskhidze ◽  
L. A. Remer ◽  
S. Platnick ◽  
R. Negrón Juárez ◽  
A. M. Lichtenberger ◽  
...  
Keyword(s):  
Diurnal Variation ◽  
Optical Thickness ◽  
Deep Convection ◽  
Cloud Fraction ◽  
Trade Wind ◽  
Clear Correlation ◽  
Remotely Sensed Data ◽  
Diurnal Variability ◽  
Cloud Properties ◽  
Different Parts

Abstract. The aerosol-cloud interaction in different parts of the globe is examined here using multi-year statistics of remotely sensed data from two MODIS sensors aboard NASA's Terra (morning) and Aqua (afternoon) satellites. Simultaneous retrievals of aerosol loadings and cloud properties by the MODIS sensor allowed us to explore intra-diurnal variation of liquid cloud fraction (CF) and optical thickness (COT) for clean, moderately polluted and heavily polluted clouds in different seasons. Data analysis for six-years of MODIS retrievals revealed strong temporal and spatial patterns in intra-diurnal variation of cloud fraction and optical thickness over different parts of the global oceans and the land. For the vast areas of stratocumulus cloud regions, the data shows that the presence of aerosols can more than double afternoon reduction of CF and COT pointing to the possible predominance of semi-direct over the indirect effects of aerosols in stratocumulus clouds. A positive relationship between AOD and morning-to-afternoon variation of trade wind cumulus cloud cover was also found over the northern Indian Ocean, though no clear correlation between the concentration of Indo-Asian haze and intra-diurnal variation of COT was established. Over the Amazon region during wet conditions, aerosols are associated with an enhanced convective process in which morning shallow warm clouds are organized into afternoon deep convection with greater ice cloud coverage. Analysis presented here demonstrates that the new technique for exploring intra-diurnal variability in cloud properties by using the differences in data products from the two daily MODIS overpasses is capable of capturing some of the major features of morning-to-afternoon variations in cloud properties and can be used for improved understanding of aerosol radiative effects.

scholarly journals Exploring the differences in cloud properties observed by the Terra and Aqua MODIS Sensors

2009 ◽  
Vol 9 (10) ◽  
pp. 3461-3475 ◽  
Author(s):  
N. Meskhidze ◽  
L. A. Remer ◽  
S. Platnick ◽  
R. Negrón Juárez ◽  
A. M. Lichtenberger ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Deep Convection ◽  
Cloud Fraction ◽  
Trade Wind ◽  
Remotely Sensed Data ◽  
Ice Cloud ◽  
Cloud Properties ◽  
Different Seasons ◽  
Convective Process ◽  
Different Parts

Abstract. The aerosol-cloud interaction in different parts of the globe is examined here using multi-year statistics of remotely sensed data from two MODIS sensors aboard NASA's Terra (morning) and Aqua (afternoon) satellites. Simultaneous retrievals of aerosol loadings and cloud properties by the MODIS sensor allowed us to explore morning-to-afternoon variation of liquid cloud fraction (CF) and optical thickness (COT) for clean, moderately polluted and heavily polluted clouds in different seasons. Data analysis for seven-years of MODIS retrievals revealed strong temporal and spatial patterns in morning-to-afternoon variation of cloud fraction and optical thickness over different parts of the global oceans and the land. For the vast areas of stratocumulus cloud regions, the data shows that the days with elevated aerosol abundance were also associated with enhanced afternoon reduction of CF and COT pointing to the possible reduction of the indirect climate forcing. A positive correlation between aerosol optical depth and morning-to-afternoon variation of trade wind cumulus cloud cover was also found over the northern Indian Ocean, though no clear relationship between the concentration of Indo-Asian haze and morning-to-afternoon variation of COT was established. Over the Amazon region during wet conditions, aerosols are associated with an enhanced convective process in which morning shallow warm clouds are organized into afternoon deep convection with greater ice cloud coverage. Analysis presented here demonstrates that the new technique for exploring morning-to-afternoon variability in cloud properties by using the differences in data products from the two daily MODIS overpasses is capable of capturing some of the major features of diurnal variations in cloud properties and can be used for better understanding of aerosol radiative effects.

scholarly journals A Novel Rules Based Approach for Estimating Software Birthmark

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shah Nazir ◽  
Sara Shahzad ◽  
Sher Afzal Khan ◽  
Norma Binti Alias ◽  
Sajid Anwar
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Rule ◽  
New Technique ◽  
License Agreement ◽  
Rule Based ◽  
Software Birthmark ◽  
A New Technique

Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark.

Sign in / Sign up

Export Citation Format

Share Document