scholarly journals Seasonal cycle of cloud cover analyzed using Meteosat images

1998 ◽  
Vol 16 (3) ◽  
pp. 331-341 ◽  
Author(s):  
J. Massons ◽  
D. Domingo ◽  
J. Lorente
Keyword(s):  
Spatial Resolution ◽  
Seasonal Cycle ◽  
Cloud Cover ◽  
High Spatial Resolution ◽  
Detection Method ◽  
Cloud Amount ◽  
Cloud Detection ◽  
Total Cloud Amount ◽  
Cloud Parameters ◽  
Cloud Properties

Abstract. A cloud-detection method was used to retrieve cloudy pixels from Meteosat images. High spatial resolution (one pixel), monthly averaged cloud-cover distribution was obtained for a 1-year period. The seasonal cycle of cloud amount was analyzed. Cloud parameters obtained include the total cloud amount and the percentage of occurrence of clouds at three altitudes. Hourly variations of cloud cover are also analyzed. Cloud properties determined are coherent with those obtained in previous studies.Key words. Cloud cover · Meteosat

scholarly journals Synergistic Use of MODIS and AIRS in a Variational Retrieval of Cloud Parameters

2004 ◽  
Vol 43 (11) ◽  
pp. 1619-1634 ◽  
Author(s):  
Jun Li ◽  
W. Paul Menzel ◽  
Wenjian Zhang ◽  
Fengying Sun ◽  
Timothy J. Schmit ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Cloud Amount ◽  
High Spectral Resolution ◽  
Test Bed ◽  
Computationally Efficient ◽  
Cloud Particle ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable global monitoring of the distribution of clouds. MODIS is able to provide a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size, and cloud optical thickness at high spatial resolution (1–5 km). The combined MODIS–AIRS system offers the opportunity for improved cloud products, better than from either system alone; this improvement is demonstrated in this paper with both simulated and real radiances. A one-dimensional variational (1DVAR) methodology is used to retrieve the CTP and ECA from AIRS longwave (650–790 cm−1 or 15.38–12.65 μm) cloudy radiance measurements (hereinafter referred to as MODIS–AIRS 1DVAR). The MODIS–AIRS 1DVAR cloud properties show significant improvement over the MODIS-alone cloud properties and slight improvement over AIRS-alone cloud properties in a simulation study, while MODIS–AIRS 1DVAR is much more computationally efficient than the AIRS-alone 1DVAR; comparisons with radiosonde observations show that CTPs improve by 10–40 hPa for MODIS–AIRS CTPs over those from MODIS alone. The 1DVAR approach is applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS and Geostationary Operational Environmental Satellite sounder cloud products. Data from ground-based instrumentation at the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in Oklahoma are used for validation; results show that MODIS–AIRS improves the MODIS CTP, especially in low-level clouds. The operational use of a high-spatial-resolution imager, along with information from a high-spectral-resolution sounder will be possible with instruments planned for the next-generation geostationary operational instruments.

scholarly journals Cloud climatologies from the InfraRed Sounders AIRS and IASI: Strengths, Weaknesses and Applications

2017 ◽  
Author(s):  
Claudia J. Stubenrauch ◽  
Artem G. Feofilov ◽  
Sofia E. Protopapadaki ◽  
Raymond Armante
Keyword(s):  
Cloud Amount ◽  
Co2 Concentration ◽  
Boreal Summer ◽  
Cloud Base ◽  
Cloud Detection ◽  
Ancillary Data ◽  
Total Cloud Amount ◽  
Low Level ◽  
Cloud Properties ◽  
High Level

Abstract. The cloud retrieval scheme developed at the Laboratoire de Météorologie Dynamique (LMD) can now be easily adapted to any Infrared (IR) sounder: the CIRS (Clouds from IR Sounders) retrieval applies improved radiative transfer, as well as an original method accounting for atmospheric spectral transmissivity changes associated with CO2 concentration. The latter is essential when considering long-term time series of cloud properties. For the 13-year and 8-year global climatologies of cloud properties from observations of the Atmospheric IR Sounder (AIRS) and of the IR Atmospheric Interferometer (IASI), respectively, we used the latest ancillary data (atmospheric profiles, surface emissivities and atmospheric spectral transmissivities). The A-Train active instruments, lidar and radar of the CALIPSO and CloudSat missions, provide a unique opportunity to evaluate the retrieved AIRS cloud properties such as cloud amount and height as well as to explore the vertical structure of different cloud types. CIRS cloud detection agreement with CALIPSO-CloudSat is about 84%–85% over ocean, 79%–82% over land and 70%–73% over ice / snow, depending on atmospheric ancillary data. Global cloud amount has been estimated to 67%–70%. CIRS cloud height coincides with the middle between the cloud top and the apparent cloud base (real base for optically thin clouds or height at which the cloud reaches opacity) independent of cloud emissivity, which is about 1 km below cloud top for low-level clouds and about 1.5 km to 2.5 km below cloud top for high-level clouds, slightly increasing because the apparent vertical cloud extent is slightly larger for large cloud emissivity. IR sounders are in particular advantageous for the retrieval of upper tropospheric cloud properties, with a reliable cirrus identification down to an IR optical depth of 0.1, day and night. Total cloud amount consists of about 40% high-level clouds and about 40% low-level clouds and 20% mid-level clouds, the latter two only detected when not hidden by upper clouds. Upper tropospheric clouds are most abundant in the tropics, where high opaque clouds make out 7.5%, thick cirrus 27.5% and thin cirrus about 21.5% of all clouds. The asymmetry in upper tropospheric cloud amount between Northern and Southern hemisphere with annual mean of 5% has a pronounced seasonal cycle with a maximum of 25% in boreal summer, which can be linked to the shift of the ITCZ peak latitude. Comparing tropical geographical change patterns of high opaque clouds with that of thin cirrus as a function of changing tropical mean surface temperature indicates that their response to climate change may be quite different, with potential consequences on the atmospheric circulation.

scholarly journals Total and partial cloud amount detection during summermonths 2005 at Westerland (Sylt, Germany)

2008 ◽  
Vol 8 (4) ◽  
pp. 13479-13505 ◽  
Author(s):  
N. H. Schade ◽  
A. Macke ◽  
H. Sandmann ◽  
C. Stick
Keyword(s):  
Cloud Cover ◽  
Cloud Amount ◽  
Cirrus Clouds ◽  
Total Cloud Amount ◽  
The North ◽  
Seaside Resort ◽  
The North Sea ◽  
Sky Imager ◽  
Downward Radiation ◽  
High Clouds

Abstract. The detection of cloudiness is investigated by means of partial and total cloud amount estimations from pyrgeometer radiation measurements and all-sky imager observations. The measurements have been performed in Westerland, a seaside resort on the North Sea island of Sylt, Germany, during summer 2005. An improvement to previous studies on this subject results from the fact that for the first time partial cloud amount (PCA), defined as total cloud amounts without high clouds, calculations from longwave downward radiation (LDR) according to the APCADA-Algorithm (Dürr and Philipona, 2004) are validated against both human observations from the German Weather Service DWD at the nearby airport of Sylt and digital all-sky imaging. Differences between the resulting total cloud amounts (TCA's), defined as total cloud amount for all-cloud situations, derived from the camera images and from human observations are within ±1 octa in 72% and within ±2 octa in 85% of the cases. Compared to human observations PCA measurements according to APCADA underestimate the observed cloud cover in 47% of all cases and the differences are within ±1 octa in 60% and ±2 octa in 74% of all cases. Since high cirrus clouds can not be derived from LDR, separate comparisons for all cases without high clouds have been performed showing an agreement within ±1(2) octa in 73(90)% for PCA and also for camera derived TCA. For this coastal mid-latitude site under investigation we find similar though slightly smaller agreements to human observations as reported in Dürr and Philipona (2004). Though limited to day-time the cloud cover retrievals from the sky imager are not much affected by cirrus clouds and provide a more reliable cloud climatology for all-cloud conditions than APCADA.

International Satellite Cloud Climatology Project: Extending the Record

2021 ◽  
pp. 1-62
Author(s):  
William B. Rossow ◽  
Kenneth R. Knapp ◽  
Alisa H Young
Keyword(s):  
Product Design ◽  
Cloud Amount ◽  
Cloud Microphysics ◽  
Temperature Threshold ◽  
Ancillary Data ◽  
Total Cloud Amount ◽  
High Cloud ◽  
Enso Events ◽  
Cloud Properties ◽  
Low Cloud

AbstractISCCP continues to quantify the global distribution and diurnal-to-interannual variations of cloud properties in a revised version. This paper summarizes assessments of the previous version, describes refinements of the analysis and enhanced features of the product design, discusses the few notable changes in the results, and illustrates the long-term variations of global mean cloud properties and differing high cloud changes associated with ENSO. The new product design includes a global, pixel-level product on a 0.1°?grid, all other gridded products at 1.0°-equivalent equal-area, separate-satellite products with ancillary data for regional studies, more detailed, embedded quality information, and all gridded products in netCDF format. All the data products including all input data), expanded documentation, the processing code and an Operations Guide are available online. Notable changes are: (1) a lowered ice-liquid temperature threshold, (2) a treatment of the radiative effects of aerosols and surface temperature inversions, (3) refined specification of the assumed cloud microphysics, and (4) interpolation of the main daytime cloud information overnight. The changes very slightly increase the global monthly mean cloud amount with a little more high and a little less middle and low cloud. Over the whole period, total cloud amount slowly decreases caused by decreases in cumulus/altocumulus; consequently, average cloud top temperature and optical thickness have increased. The diurnal and seasonal cloud variations are very similar to earlier versions. Analysis of the whole record shows that high cloud variations, but not low clouds, exhibit different patterns in different ENSO events.

scholarly journals Change Detection in Multitemporal High Spatial Resolution Remote-Sensing Images Based on Saliency Detection and Spatial Intuitionistic Fuzzy C-Means Clustering

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Liang Huang ◽  
Qiuzhi Peng ◽  
Xueqin Yu
Keyword(s):  
Remote Sensing ◽  
Change Detection ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Detection Method ◽  
Saliency Detection ◽  
Detection Accuracy ◽  
Remote Sensing Images ◽  
Saliency Maps ◽  
Multitemporal Remote Sensing

In order to improve the change detection accuracy of multitemporal high spatial resolution remote-sensing (HSRRS) images, a change detection method of multitemporal remote-sensing images based on saliency detection and spatial intuitionistic fuzzy C-means (SIFCM) clustering is proposed. Firstly, the cluster-based saliency cue method is used to obtain the saliency maps of two temporal remote-sensing images; then, the saliency difference is obtained by subtracting the saliency maps of two temporal remote-sensing images; finally, the SIFCM clustering algorithm is used to classify the saliency difference image to obtain the change regions and unchange regions. Two data sets of multitemporal high spatial resolution remote-sensing images are selected as the experimental data. The detection accuracy of the proposed method is 96.17% and 97.89%. The results show that the proposed method is a feasible and better performance multitemporal remote-sensing image change detection method.

scholarly journals Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

2017 ◽  
Vol 17 (9) ◽  
pp. 5789-5807 ◽  
Author(s):  
John C. Kealy ◽  
Franco Marenco ◽  
John H. Marsham ◽  
Luis Garcia-Carreras ◽  
Pete N. Francis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Second Generation ◽  
High Surface ◽  
Cloud Amount ◽  
Limiting Factors ◽  
Cloud Detection ◽  
Airborne Remote Sensing ◽  
Horizontal Extent ◽  
Cloud Properties ◽  
Cloud Mask

Abstract. Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km  ×  3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.

scholarly journals Total and partial cloud amount detection during summer 2005 at Westerland (Sylt, Germany)

2009 ◽  
Vol 9 (4) ◽  
pp. 1143-1150 ◽  
Author(s):  
N. H. Schade ◽  
A. Macke ◽  
H. Sandmann ◽  
C. Stick
Keyword(s):  
Cloud Cover ◽  
Cloud Amount ◽  
Cirrus Clouds ◽  
Total Cloud Amount ◽  
The North ◽  
Seaside Resort ◽  
The North Sea ◽  
Sky Imager ◽  
Downward Radiation ◽  
High Clouds

Abstract. The detection of cloudiness is investigated by means of partial and total cloud amount estimations from pyrgeometer radiation measurements and visible all-sky imager observations. The measurements have been performed in Westerland, a seaside resort on the North Sea island of Sylt, Germany, during summer 2005. An improvement to previous studies on this subject resulting in the first time partial cloud amounts (PCAs), defined as cloud amounts without high clouds calculated from longwave downward radiation (LDR) according to the APCADA algorithm (Dürr and Philipona, 2004), are validated against both human observations from the National Meteorological Servive DWD at the nearby airport of Sylt and digital all-sky imaging. The aim is to establish the APCADA scheme at a coastal midlatitude site for longterm observations of cloud cover and to quantify errors resulting from the different methods of detecting cloudiness. Differences between the resulting total cloud amounts (TCAs), defined as cloud amount for all-cloud situations, derived from the camera images and from human observations are within ±1 octa in 72% and within ±2 octa in 85% of the cases. Compared to human observations, PCA measurements, according to APCADA, underestimate the observed cloud cover in 47% of all cases and the differences are within ±1 octa in 60% and ±2 octa in 74% of all cases. Since high cirrus clouds can not be derived from LDR, separate comparisons for all cases without high clouds have been performed showing an agreement within ±1(2) octa in 73(90)% for PCA and also for camera-derived TCA. For this coastal mid-latitude site under investigation, we find similar though slightly smaller agreements to human observations as reported by Dürr and Philipona (2004). Though limited to daytime, the cloud cover retrievals from the sky imager are not really affected by cirrus clouds and provide a more reliable cloud climatology for all-cloud conditions than APCADA.

scholarly journals Trends in Global Cloud Cover in Two Decades of HIRS Observations

2005 ◽  
Vol 18 (15) ◽  
pp. 3021-3031 ◽  
Author(s):  
Donald Wylie ◽  
Darren L. Jackson ◽  
W. Paul Menzel ◽  
John J. Bates
Keyword(s):  
Cloud Cover ◽  
Cloud Amount ◽  
Cloud Detection ◽  
Total Cloud Cover ◽  
Infrared Observation ◽  
Upper Troposphere ◽  
Polar Orbiting Satellite ◽  
The Tropics ◽  
High Clouds ◽  
Infrared Radiometer

Abstract The frequency of cloud detection and the frequency with which these clouds are found in the upper troposphere have been extracted from NOAA High Resolution Infrared Radiometer Sounder (HIRS) polar-orbiting satellite data from 1979 to 2001. The HIRS/2 sensor was flown on nine satellites from the Television Infrared Observation Satellite-Next Generation (TIROS-N) through NOAA-14, forming a 22-yr record. Carbon dioxide slicing was used to infer cloud amount and height. Trends in cloud cover and high-cloud frequency were found to be small in these data. High clouds show a small but statistically significant increase in the Tropics and the Northern Hemisphere. The HIRS analysis contrasts with the International Satellite Cloud Climatology Project (ISCCP), which shows a decrease in both total cloud cover and high clouds during most of this period.

scholarly journals Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements

2018 ◽  
Author(s):  
Fanny Jeanneret ◽  
Giovanni Martucci ◽  
Simon Pinnock ◽  
Alexis Berne
Keyword(s):  
Cloud Cover ◽  
Swiss Alps ◽  
Shortwave Radiation ◽  
Cloud Detection ◽  
Cloud Data ◽  
Mountainous Regions ◽  
Cloud Properties ◽  
Synoptic Observations ◽  
The Cost ◽  
Cloud Mask

Abstract. The validation of long term cloud datasets retrieved from satellites is challenging due to their worldwide coverage going back as far as the 1980s, among others. A trustworthy reference cannot be found easily at every location and every time. Mountainous regions represent especially a problem since ground-based measurements are sparser. Moreover, as retrievals from passive satellite radiometers are difficult in winter due to the presence of snow on the ground, it is particularly important to develop new ways to evaluate and to correct satellite datasets over elevated areas. In winter for ground levels above 1000 m (a.s.l.) in Switzerland, the cloud occurrence of the newly-released cloud property datasets of the ESA Climate Change Initiative Cloud_cci project (AVHRR-PM and MODIS-Aqua series) is 132 % to 217 % that of SYNOP observations, corresponding to between 24 % and 54 % of false cloud detections. Furthermore, the overestimations increase with the altitude of the sites and are associated with particular retrieved cloud properties. In this study, a novel post-processing approach is proposed to reduce the amount of false cloud detections in the satellite datasets. A combination of ground-based downwelling longwave and shortwave radiation and temperature measurements is used to obtain a mask for the cloud cover above 41 locations in Switzerland. An agreement of 85 % is obtained when the cloud cover is compared to surface synoptic observations (90 % within ±1 okta difference). The obtained cloud mask has been co-located with the satellite observations and a decision tree is trained to automatically detect the overestimations in the satellite's cloud masks. Cross-validated results show that 62 ± 13 % of these overestimations can be identified by the model, reducing the systematic error in the satellite datasets to 4.3 ± 2.8 %, at the cost of an increase of 7 ± 2 % of missed clouds. Using this model, it is hence possible to significantly improve the cloud detection reliability in elevated areas in the Cloud_cci's AVHRR-PM and MODIS-Aqua products.

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