scholarly journals Quality assessment of Second-generation Global Imager (SGLI)-observed cloud properties using SKYNET surface observation data

2021 ◽  
Author(s):  
Pradeep Khatri ◽  
Tadahiro Hayasaka ◽  
Hitoshi Irie ◽  
Husi Letu ◽  
Takashi Y. Nakajima ◽  
...  
Keyword(s):  
Second Generation ◽  
Global Climate ◽  
Observation Data ◽  
Cloud Particle ◽  
Ice Clouds ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission – Climate (GCOM-C) satellite launched on December 23, 2017, observes various geophysical parameters with the aim of a better understanding of the global climate system. As part of that aim, SGLI has great potential to unravel several uncertainties related to clouds by providing new cloud products along with several other atmospheric products related to cloud climatology, including aerosol products from polarization channels. However, a very little is known about the quality of the SGLI cloud products. This study uses data about clouds and global irradiances observed from the Earth’s surface using a sky radiometer and a pyranometer, respectively, to understand the quality of the two most fundamental cloud properties—cloud optical depth (COD) and cloud-particle effective radius (CER)—of both water and ice clouds. The SGLI-observed COD agrees well with values observed from the surface, although it agrees better for water clouds than for ice clouds, while the SGLI-observed CER exhibits poorer agreement than does the COD, with the SGLI values being generally higher than the sky radiometer values. These comparisons between the SGLI and sky radiometer cloud properties are found to differ for different cloud types of both the water and ice cloud phases and different solar and satellite viewing angles by agreeing better for relatively uniform and flat cloud type and for relatively low solar zenith angle. Analyses of SGLI-observed reflectance functions and values calculated by assuming plane-parallel cloud layers suggest that SGLI-retrieved cloud properties can have biases on the solar and satellite viewing angles, similar to other satellite sensors including the Moderate Resolution Imaging Spectroradiometer (MODIS). Furthermore, it is found that the SGLI-observed cloud properties reproduce global irradiances quite satisfactorily for both water and ice clouds by resembling several important features of the COD comparison, such as the better agreement for water clouds than for ice clouds and the tendency to underestimate (resp. overestimate) the COD in SGLI observations for optically thick (resp. thin) clouds.

scholarly journals Geostationary Enhanced Temporal Interpolation for CERES Flux Products

2013 ◽  
Vol 30 (6) ◽  
pp. 1072-1090 ◽  
Author(s):  
David R. Doelling ◽  
Norman G. Loeb ◽  
Dennis F. Keyes ◽  
Michele L. Nordeen ◽  
Daniel Morstad ◽  
...  
Keyword(s):  
Global Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Cloud Properties ◽  
Marine Stratus ◽  
Temporal Interpolation ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Observation Times

Abstract The Clouds and the Earth’s Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth’s top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1° latitude × 1° longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m−2 over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.

scholarly journals A study of some cloud microphysical parameters over Iraq using satellite data

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Murtadha A. Fadhil ◽  
Kais J. Al-Jumaily
Keyword(s):  
Optical Thickness ◽  
Heavy Precipitation ◽  
Liquid Water Path ◽  
Ice Clouds ◽  
Cloud Properties ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Using Data ◽  
Earth’S Climate ◽  
Two Parameters

Studying clouds is a top priority among many atmospheric scientists because clouds are one of the greatest unknown factors in predicting changes in the Earth’s climate. Clouds play an important role in maintaining the energy balance because they can reflect, absorb, and radiate energy. The aim of this research is to investigate the properties of clouds over Iraq using data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS)on board Aqua Satellite for water and ice clouds. The results showed that daily mean cloud top pressure patterns during spring months are higher than other months and cloud top temperature patterns reached their highest values during summer months. The results also indicated that the ice cloud effective particle radius is relatively large during summer while cloud optical thickness assume its largest values in winter months. It was found that the highest values of precipitation rate over Iraq occurred during March to mid-April. Correlation aanalysis between optical thickness and liquid water path over Iraq that these two parameters are positively correlated and the correlation for water cloud was better that that for ice clouds. Case studies of heavy precipitation events over Iraq showed that the maximum values of the most cloud properties variables were located ahead of the storm center. 

scholarly journals Impacts of Partly Cloudy Pixels on Shortwave Broadband Irradiance Computations

2019 ◽  
Vol 36 (3) ◽  
pp. 369-386 ◽  
Author(s):  
Seung-Hee Ham ◽  
Seiji Kato ◽  
Fred G. Rose
Keyword(s):  
Solar Zenith Angle ◽  
Cloud Fraction ◽  
Similar Magnitude ◽  
Cloud Optical Depth ◽  
Cloud Properties ◽  
Moderate Resolution ◽  
Satellite Sensors ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
First Time

AbstractBecause of the limitation of the spatial resolution of satellite sensors, satellite pixels identified as cloudy are often partly cloudy. For the first time, this study demonstrates the bias in shortwave (SW) broadband irradiances for partly cloudy pixels when the cloud optical depths are retrieved with an overcast and homogeneous assumption, and subsequently, the retrieved values are used for the irradiance computations. The sign of the SW irradiance bias is mainly a function of viewing geometry of the cloud retrieval. The bias in top-of-atmosphere (TOA) upward SW irradiances is positive for small viewing zenith angles (VZAs) <~60° and negative for large VZAs >~60°. For a given solar zenith angle and viewing geometry, the magnitude of the bias increases with the cloud optical depth and reaches a maximum at the cloud fraction between 0.2 and 0.8. The sign of the SW surface net irradiance bias is opposite of the sign of TOA upward irradiance bias, with a similar magnitude. As a result, the bias in absorbed SW irradiances by the atmosphere is smaller than the biases in both TOA and surface irradiances. The monthly mean biases in SW irradiances due to partly cloudy pixels are <1.5 W m−2 when cloud properties are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua.

scholarly journals Technical note: a new day- and night-time Meteosat Second Generation Cirrus Detection Algorithm MeCiDA

2007 ◽  
Vol 7 (4) ◽  
pp. 10933-10969
Author(s):  
W. Krebs ◽  
H. Mannstein ◽  
L. Bugliaro ◽  
B. Mayer
Keyword(s):  
Second Generation ◽  
Detection Efficiency ◽  
Detection Algorithm ◽  
Technical Note ◽  
High Temporal Resolution ◽  
Night Time ◽  
Ice Clouds ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. A new cirrus detection algorithm for the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG), MeCiDA, is presented. The algorithm uses the seven infrared channels of SEVIRI and thus provides a consistent scheme for cirrus detection at day and night. MeCiDA combines morphological and multi-spectral threshold tests and detects optically thick and thin ice clouds. The thresholds were determined by a comprehensive theoretical study using radiative transfer simulations for various atmospheric situations as well as by manually evaluating actual satellite observations. The retrieved cirrus masks have been validated by comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) Cirrus Reflection Flag. To study possible seasonal variations in the performance of the algorithm, one scene per month of the year 2004 was randomly selected and compared with the standard MODIS cirrus product. 81% of the pixels were classified identically by both algorithms. On average, MeCiDA detected 60% of the MODIS cirrus. A lower detection efficiency is to be expected for MeCiDA, as the spatial resolution of MODIS is considerably better and as we used only the thermal infrared channels in contrast to the MODIS algorithm which uses infrared and visible radiances. The advantage of MeCiDA compared to retrievals for polar orbiting instruments or previous geostationary satellites is that it allows to derive quantitative data every 15 min, 24 h a day. This high temporal resolution allows the study of diurnal variations and life cycle aspects. MeCiDA is fast enough for near real-time applications.

scholarly journals Limitations of Bispectral Infrared Cloud Phase Determination and Potential for Improvement

2008 ◽  
Vol 47 (11) ◽  
pp. 2895-2910 ◽  
Author(s):  
Shaima L. Nasiri ◽  
Brian H. Kahn
Keyword(s):  
Particle Size ◽  
A Priori ◽  
Atmospheric Temperature ◽  
Phase Determination ◽  
Cloud Particle ◽  
Ice Clouds ◽  
Cloud Height ◽  
Cloud Temperature ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Determining cloud thermodynamic phase using infrared satellite observations typically requires a priori assumptions about relationships between cloud phase and cloud temperature. In this study, limitations of an approach using two infrared channels with moderate spectral resolutions are demonstrated, as well as the potential for improvement using channels with higher spectral resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument uses a bispectral infrared cloud phase determination algorithm. MODIS observations during January 2005 show that approximately 23% of cloudy pixels are classified as mixed or unknown cloud phase; this increases to 78% when only cloud-top temperatures between 250 and 265 K are considered. Radiative transfer simulations show that the bispectral algorithm has limited ability to discriminate between water and ice clouds in this temperature range. There is also the potential for thin ice clouds at colder temperatures to be misclassified as water clouds. In addition, sensitivities to cloud particle size and cloud height can be larger than sensitivities to cloud phase. Simulations suggest that phase sensitivity may be higher with hyperspectral observations such as those from the Atmospheric Infrared Sounder (AIRS). The AIRS brightness temperature differences between channels at 8.1 and 10.4 μm show phase sensitivities of at least 0.5 K, regardless of cloud particle size, cloud-top temperature, or cloud height. They also demonstrate reduced sensitivity to atmospheric temperature and water vapor variability. The reduced sensitivity of AIRS radiances to these physical quantities shows that hyperspectral sounders will serve an important role in refining estimates of cloud phase.

scholarly journals Retrieval of cloud properties from spectral zenith radiances observed by sky radiometers

2019 ◽  
Vol 12 (11) ◽  
pp. 6037-6047 ◽  
Author(s):  
Pradeep Khatri ◽  
Hironobu Iwabuchi ◽  
Tadahiro Hayasaka ◽  
Hitoshi Irie ◽  
Tamio Takamura ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Estimation Algorithm ◽  
Calibration Procedure ◽  
Evaluation Study ◽  
Vapor Concentration ◽  
Observation Data ◽  
Ancillary Data ◽  
Cloud Particle ◽  
Cloud Optical Depth ◽  
Cloud Properties

Abstract. An optimal estimation algorithm to retrieve the cloud optical depth (COD) and cloud particle effective radius (CER) from spectral zenith radiances observed by narrow field-of-view (FOV) ground-based sky radiometers was developed. To further address the filter degradation problem while analyzing long-term observation data, an on-site calibration procedure is proposed, which has good accuracy compared with the standard calibration transfer method. An error evaluation study conducted by assuming errors in observed transmittances and ancillary data for water vapor concentration and surface albedo suggests that the errors in input data affect retrieved CER more than COD. Except for some narrow domains that fall within a COD of < 15, the retrieval errors are small for both COD and CER. The retrieved cloud properties reproduce the broadband radiances observed by a narrow FOV radiometer more precisely than broadband irradiances observed by a wide-FOV pyranometer, justifying the quality of the retrieved product (at least of COD) and indicating the important effect of the instrument FOV in cloud remote sensing. Furthermore, CODs (CERs) from sky radiometer and satellite observations show good (poor) agreement.

Assessment of Arctic Cloud Cover Anomalies in Atmospheric Reanalysis Products Using Satellite Data

2016 ◽  
Vol 29 (17) ◽  
pp. 6065-6083 ◽  
Author(s):  
Yinghui Liu ◽  
Jeffrey R. Key
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Global Climate ◽  
Correlation Coefficients ◽  
Cloud Amount ◽  
Satellite Observation ◽  
Skill Score ◽  
Global Climate Models ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Cloud cover is one of the largest uncertainties in model predictions of the future Arctic climate. Previous studies have shown that cloud amounts in global climate models and atmospheric reanalyses vary widely and may have large biases. However, many climate studies are based on anomalies rather than absolute values, for which biases are less important. This study examines the performance of five atmospheric reanalysis products—ERA-Interim, MERRA, MERRA-2, NCEP R1, and NCEP R2—in depicting monthly mean Arctic cloud amount anomalies against Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations from 2000 to 2014 and against Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations from 2006 to 2014. All five reanalysis products exhibit biases in the mean cloud amount, especially in winter. The Gerrity skill score (GSS) and correlation analysis are used to quantify their performance in terms of interannual variations. Results show that ERA-Interim, MERRA, MERRA-2, and NCEP R2 perform similarly, with annual mean GSSs of 0.36/0.22, 0.31/0.24, 0.32/0.23, and 0.32/0.23 and annual mean correlation coefficients of 0.50/0.51, 0.43/0.54, 0.44/0.53, and 0.50/0.52 against MODIS/CALIPSO, indicating that the reanalysis datasets do exhibit some capability for depicting the monthly mean cloud amount anomalies. There are no significant differences in the overall performance of reanalysis products. They all perform best in July, August, and September and worst in November, December, and January. All reanalysis datasets have better performance over land than over ocean. This study identifies the magnitudes of errors in Arctic mean cloud amounts and anomalies and provides a useful tool for evaluating future improvements in the cloud schemes of reanalysis products.

scholarly journals Characterising optical array particle imaging probes: implications for small-ice-crystal observations

2021 ◽  
Vol 14 (3) ◽  
pp. 1917-1939
Author(s):  
Sebastian O'Shea ◽  
Jonathan Crosier ◽  
James Dorsey ◽  
Louis Gallagher ◽  
Waldemar Schledewitz ◽  
...  
Keyword(s):  
Field Experiments ◽  
Field Measurements ◽  
Sample Volume ◽  
Ice Crystal ◽  
Cloud Particle ◽  
Ice Clouds ◽  
Cloud Properties ◽  
Imaging Probes ◽  
New Methodologies ◽  
Particle Imaging

Abstract. The cloud particle concentration, size, and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory, and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that remove the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data-processing protocols, either removing or significantly reducing the concentration of small ice crystals (< 200 µm) in certain conditions. This work suggests that the observational evidence for a ubiquitous mode of small ice particles in ice clouds is likely due to a systematic instrument bias. Size distribution parameterisations based on OAP measurements need to be revisited using these improved methodologies.

scholarly journals A critical look at spatial scale choices in satellite-based aerosol indirect effect studies

2010 ◽  
Vol 10 (23) ◽  
pp. 11459-11470 ◽  
Author(s):  
B. S. Grandey ◽  
P. Stier
Keyword(s):  
Radiative Forcing ◽  
Spatial Scales ◽  
Cloud Droplet ◽  
Spatial Variations ◽  
Opposite Pattern ◽  
Cloud Properties ◽  
Methodological Errors ◽  
Albedo Effect ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Analysing satellite datasets over large regions may introduce spurious relationships between aerosol and cloud properties due to spatial variations in aerosol type, cloud regime and synoptic regime climatologies. Using MODerate resolution Imaging Spectroradiometer data, we calculate relationships between aerosol optical depth τa derived liquid cloud droplet effective number concentration Ne and liquid cloud droplet effective radius re at different spatial scales. Generally, positive values of dlnNedlnτa are found for ocean regions, whilst negative values occur for many land regions. The spatial distribution of dlnredlnτa shows approximately the opposite pattern, with generally postive values for land regions and negative values for ocean regions. We find that for region sizes larger than 4° × 4°, spurious spatial variations in retrieved cloud and aerosol properties can introduce widespread significant errors to calculations of dlnNedlnτa and dlnredlnτa. For regions on the scale of 60° × 60°, these methodological errors may lead to an overestimate in global cloud albedo effect radiative forcing of order 80% relative to that calculated for regions on the scale of 1° × 1°.

scholarly journals Comparison of PARASOL Observations with Polarized Reflectances Simulated Using Different Ice Habit Mixtures

2013 ◽  
Vol 52 (1) ◽  
pp. 186-196 ◽  
Author(s):  
Benjamin H. Cole ◽  
Ping Yang ◽  
Bryan A. Baum ◽  
Jerome Riedi ◽  
Laurent C.-Labonnote ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Atmospheric Sciences ◽  
Reflection Data ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Polarized Reflectance

AbstractInsufficient knowledge of the habit distribution and the degree of surface roughness of ice crystals within ice clouds is a source of uncertainty in the forward light scattering and radiative transfer simulations of ice clouds used in downstream applications. The Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 ice microphysical model presumes a mixture of various ice crystal shapes with smooth facets, except for the compact aggregate of columns for which a severely rough condition is assumed. When compared with Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) polarized reflection data, simulations of polarized reflectance using smooth particles show a poor fit to the measurements, whereas very rough-faceted particles provide an improved fit to the polarized reflectance. In this study a new microphysical model based on a mixture of nine different ice crystal habits with severely roughened facets is developed. Simulated polarized reflectance using the new ice habit distribution is calculated using a vector adding–doubling radiative transfer model, and the simulations closely agree with the polarized reflectance observed by PARASOL. The new general habit mixture is also tested using a spherical albedo differences analysis, and surface roughening is found to improve the consistency of multiangular observations. These results are consistent with previous studies that have used polarized reflection data. It is suggested that an ice model incorporating an ensemble of different habits with severely roughened surfaces would potentially be an adequate choice for global ice cloud retrievals.

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