Global retrieval of ATSR cloud parameters and evaluation (GRAPE): dataset assessment

Abstract. The Along-Track Scanning Radiometers (ATSRs) provide a long time-series of measurements suitable for the retrieval of cloud properties. This work evaluates the freely-available Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) dataset (version 3) created from the ATSR-2 (1995–2003) and Advanced ATSR (AATSR; 2002 onwards) records. Users are recommended to consider only retrievals flagged as high-quality, where there is a good consistency between the measurements and the retrieved state (corresponding to about 60% of converged retrievals over sea, and more than 80% over land). Cloud properties are found to be generally free of any significant spurious trends relating to satellite zenith angle. Estimates of the random error on retrieved cloud properties are suggested to be generally appropriate for optically-thick clouds, and up to a factor of two too small for optically-thin cases. The correspondence between ATSR-2 and AATSR cloud properties is high, but a relative calibration difference between the sensors of order 5–10% at 660 nm and 870 nm limits the potential of the current version of the dataset for trend analysis. As ATSR-2 is thought to have the better absolute calibration, the discussion focusses on this portion of the record. Cloud-top heights from GRAPE compare well to ground-based data at four sites, particularly for shallow clouds. Clouds forming in boundary-layer inversions are typically around 1 km too high in GRAPE due to poorly-resolved inversions in the modelled temperature profiles used. Global cloud fields are compared to satellite products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements, and a climatology of liquid water content derived from satellite microwave radiometers. In all cases the main reasons for differences are linked to differing sensitivity to, and treatment of, multi-layer cloud systems. The correlation coefficient between GRAPE and the two MODIS products considered is generally high (greater than 0.7 for most cloud properties), except for liquid and ice cloud effective radius, which also show biases between the datasets. For liquid clouds, part of the difference is linked to choice of wavelengths used in the retrieval. Total cloud cover is slightly lower in GRAPE (0.64) than the CALIOP dataset (0.66). GRAPE underestimates liquid cloud water path relative to microwave radiometers by up to 100 g m−2 near the Equator and overestimates by around 50 g m−2 in the storm tracks. Finally, potential future improvements to the algorithm are outlined.

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Global retrieval of ATSR cloud parameters and evaluation (GRAPE): dataset assessment

Atmospheric Chemistry and Physics ◽

10.5194/acp-11-3913-2011 ◽

2011 ◽

Vol 11 (8) ◽

pp. 3913-3936 ◽

Cited By ~ 32

Author(s):

A. M. Sayer ◽

C. A. Poulsen ◽

C. Arnold ◽

E. Campmany ◽

S. Dean ◽

...

Keyword(s):

Liquid Water Content ◽

Absolute Calibration ◽

Orthogonal Polarization ◽

Cloud Parameters ◽

Cloud Properties ◽

Long Time ◽

Shallow Clouds ◽

Moderate Resolution Imaging Spectroradiometer ◽

The Difference ◽

Microwave Radiometers

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The Retrieval of Marine Stratiform Cloud Properties from Multiple Observations in the 3.9-µm Window under Conditions of Varying Solar Illumination

Journal of Applied Meteorology ◽

10.1175/1520-0450-34.7.1512 ◽

1995 ◽

Vol 34 (7) ◽

pp. 1512-1524 ◽

Cited By ~ 12

Author(s):

Thomas J. Kleespies

Keyword(s):

Climate Modeling ◽

Thermal Structure ◽

Cloud Microphysics ◽

Time Interval ◽

Short Time Interval ◽

Cloud Parameters ◽

Cloud Properties ◽

Multiple Observations ◽

Simplifying Assumptions ◽

The Difference

Abstract Radiometric observations in the 3.9-µm region have been used by a number of investigators for the determination of cloud parameters or sea surface temperature at night. Only a few attempts have been made to perform quantitative assessments of cloud and surface properties during the daytime because of the inability to distinguish between the thermal and solar components of the satellite-sensed radiances. This paper presents a new method of separating the thermal and solar components of upwelling 3.9-µm radiances. Two collocated satellite observations are made under conditions where the solar illumination angle changes but the thermal structure of the cloud and atmosphere, as well as the cloud microphysics change very little. These conditions can easily be met by observing the same cloud from geosynchoronous orbit over a short time interval during the morning hours. When the radiances are differenced under these constraints, the thermal components cancel, and the difference in the radiances is simply the difference in the solar component. With a few simplifying assumptions, a cloud microphysical property, specifically effective radius, can be inferred. This parameter is of particular importance to both climate modeling and global change studies. The methodology developed in this paper is applied to data from the Visible-Infrared Spin Scan Radiometer Atmospheric Sounder onboard the GOES-7 spacecraft for a period in August 1992.

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Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland

Atmospheric Measurement Techniques ◽

10.5194/amt-9-3193-2016 ◽

2016 ◽

Vol 9 (7) ◽

pp. 3193-3203 ◽

Cited By ~ 2

Author(s):

Moa K. Sporre ◽

Ewan J. O'Connor ◽

Nina Håkansson ◽

Anke Thoss ◽

Erik Swietlicki ◽

...

Keyword(s):

Infrared Imaging ◽

Microwave Radiometer ◽

Single Layer ◽

Radar Data ◽

Liquid Water Path ◽

Cloud Parameters ◽

Cloud Properties ◽

Moderate Resolution Imaging Spectroradiometer ◽

Biogenic Aerosols ◽

Cloud Mask

Abstract. Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the satellites Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, satellites overestimated CTH by 326 m (14 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 169 m (5.8 %). MODIS collection 6 overestimated LWP by on average 13 g m−2 (11 %). Interestingly, LWP for MODIS collection 5.1 is slightly overestimated by Aqua (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the reflectance bands of the MODIS instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high-latitude location.

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CORRECTION FOR THE CIRRUS CLOUD TOP HEIGHT OF MODIS BASED ON CALIPSO IN BEIJING-TIANJIN-HEBEI REGION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-w9-203-2019 ◽

2019 ◽

Vol XLII-3/W9 ◽

pp. 203-210

Author(s):

B. Y. Yang ◽

J. Liu ◽

X. Jia

Keyword(s):

Remote Sensing ◽

Satellite Observation ◽

Orthogonal Polarization ◽

Cirrus Cloud ◽

Weather System ◽

Cloud Optical Depth ◽

Lower Cloud ◽

Moderate Resolution ◽

Moderate Resolution Imaging Spectroradiometer ◽

The Difference

Abstract. Cirrus plays an important role in atmospheric radiation. It affects weather system and climate change. Satellite remote sensing is an important kind of observation for cloud. As a passive remote sensing instrument, large bias was found for thin cirrus cloud top height retrieval from MODIS (Moderate Resolution Imaging Spectroradiometer). Comparatively, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) aboard CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation) which is an active remote sensing instrument can acquire more accurate characteristics of thin cirrus cloud. In this study, CALIPSO cirrus cloud top height data was used to correct MODIS cirrus cloud top height. The data analysis area was selected in Beijing-Tianjin-Hebei region and data came from 2013 to 2017. Linear fitting method was selected based on cross-validation method between MODIS and CALIPSO data. The results shows that the difference between MODIS and CALIPSO changes from −3~2 km to −2.0~2.5 km, and the maximum difference changes from about −0.8 km to about 0.2 km. In the context of different vertical levels and cloud optical depth, MODIS cirrus cloud top height is improved after correcting, which is more obvious at lower cloud top height and optical thinner cirrus.

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Evaluation of Model-Predicted Top-of-Atmosphere Radiation and Cloud Parameters over Africa with Observations from GERB and SEVIRI

Journal of Climate ◽

10.1175/2011jcli3856.1 ◽

2011 ◽

Vol 24 (15) ◽

pp. 4015-4036 ◽

Cited By ~ 10

Author(s):

Wouter Greuell ◽

Erik van Meijgaard ◽

Nicolas Clerbaux ◽

Jan Fokke Meirink

Keyword(s):

Satellite Data ◽

Climate Model ◽

Longwave Radiation ◽

Radiation Budget ◽

Trade Wind ◽

Water Path ◽

Cloud Parameters ◽

Cloud Properties ◽

Condensed Water ◽

Moderate Resolution Imaging Spectroradiometer

Abstract This study compared the Regional Atmospheric Climate Model version 2 (RACMO) with satellite data by simultaneously looking at cloud properties and top-of-atmosphere (TOA) fluxes. This study used cloud properties retrieved from Spinning Enhanced Visible and Infrared Imager (SEVIRI) data and TOA shortwave and longwave outgoing radiative fluxes measured by one of the Geostationary Earth Radiation Budget (GERB) sensors. Both SEVIRI and GERB resolve the diurnal cycle extremely well with 96 images per day. To test the physical parameterizations of the model, RACMO was run for a domain-enclosing Africa and part of the surrounding oceans. Simulations for July 2006, forced at the lateral boundaries by ERA-Interim reanalyses, show generally accurate positioning of the various cloud regimes but also some important model–observation differences, which the authors tried to reduce by altering model parameterizations. These differences are as follows: 1) TOA albedo differences in clear-sky regions like the Sahara and southern Africa. These differences were considerably reduced by prescribing the surface albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. 2) A considerable overestimation of outgoing longwave radiation within the continental ITCZ caused by the fact that modeled cirrus clouds are far too thin. 3) Underestimation by the model of cloud cover, condensed water path and albedo of the stratocumulus fields off the coast of Angola. The authors reduced these underestimations by suppressing the amount of turbulent mixing above the boundary layer, by prescribing droplet radii derived from SEVIRI data, and by assuming in-cloud horizontal homogeneity for the radiation calculations. 4) Overestimation by the model of the albedo of the trade wind cumulus fields over the Atlantic Ocean. This study argues that this overestimation is likely caused by a model overestimation of condensed water path. In general, the analyses demonstrate the power of the simultaneous evaluation of the TOA fluxes and cloud properties.

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Examination of POLDER/PARASOL and MODIS/Aqua Cloud Fractions and Properties Representativeness

Journal of Climate ◽

10.1175/2011jcli3857.1 ◽

2011 ◽

Vol 24 (16) ◽

pp. 4435-4450 ◽

Cited By ~ 18

Author(s):

Shan Zeng ◽

Frédéric Parol ◽

Jérôme Riedi ◽

Céline Cornet ◽

François Thieuleux

Keyword(s):

Cloud Cover ◽

Temporal Variations ◽

Cloud Fraction ◽

Atmospheric Sciences ◽

Cloud Parameters ◽

Cloud Properties ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Level 2

Abstract The Polarization and Anisotropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL) and Aqua are two satellites on sun-synchronous orbits in the A-Train constellation. Aboard these two platforms, the Polarization and Directionality of Earth Reflectances (POLDER) and Moderate Resolution Imaging Spectroradiometer (MODIS) provide quasi simultaneous and coincident observations of cloud properties. The similar orbits but different detecting characteristics of these two sensors call for a comparison between the derived datasets to identify and quantify potential uncertainties in retrieved cloud properties. To focus on the differences due to different sensor spatial resolution and coverage, while minimizing sampling and weighting issues, the authors have recomputed monthly statistics directly from the respective official level-2 products. The authors have developed a joint dataset that contains both POLDER and MODIS level-2 cloud products collocated on a common sinusoidal grid. The authors have then computed and analyzed monthly statistics of cloud fractions corresponding either to the total cloud cover or to the “retrieved” cloud fraction for which cloud optical properties are derived. These simple yet crucial cloud statistics need to be clearly understood to allow further comparison work of the other cloud parameters. From this study, it is demonstrated that on average POLDER and MODIS datasets capture correctly the main characteristics of global cloud cover and provide similar spatial distributions and temporal variations. However, each sensor has its own advantages and weaknesses in discriminating between clear and cloudy skies in particular situations. Also it is shown that significant differences exist between the MODIS total cloud fraction (day mean) and the “retrieved” cloud fraction (combined mean). This study found a global negative difference of about 10% between POLDER and MODIS day-mean cloud fraction. On the contrary, a global positive difference of about 10% exists between POLDER and MODIS combined-mean cloud fraction. These statistical biases show both global and regional distributions that can be driven by sensors characteristics, environmental factors, and also carry potential information on cloud cover structure. These results provide information on the quality of cloud cover derived from POLDER and MODIS and should be taken into account for the use of other cloud products.

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

Journal of Applied Meteorology ◽

10.1175/jam2166.1 ◽

2004 ◽

Vol 43 (11) ◽

pp. 1619-1634 ◽

Cited By ~ 36

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.

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Cloud thermodynamic phase inferred from merged POLDER and MODIS data

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-7-14103-2007 ◽

2007 ◽

Vol 7 (5) ◽

pp. 14103-14137 ◽

Cited By ~ 9

Author(s):

J. Riedi ◽

B. Marchant ◽

S. Platnick ◽

B. Baum ◽

F. Thieuleux ◽

...

Keyword(s):

Satellite Data ◽

General Circulation ◽

Hydrological Cycle ◽

General Circulation Models ◽

Liquid Water Content ◽

Microphysical Properties ◽

Cloud Properties ◽

Moderate Resolution Imaging Spectroradiometer ◽

Thermodynamic Phase ◽

Insight Into

Abstract. The global spatial and diurnal distribution of cloud properties is a key issue for understanding the hydrological cycle, and critical for advancing efforts to improve numerical weather models and general circulation models. Satellite data provides the best way of gaining insight into global cloud properties. In particular, the determination of cloud thermodynamic phase is a critical first step in the process of inferring cloud optical and microphysical properties from satellite measurements. It is important that cloud phase be derived together with an estimate of the confidence of this determination, so that this information can be included with subsequent retrievals (optical thickness, effective particle radius, and ice/liquid water content). In this study, we combine three different and well documented approaches for inferring cloud phase into a single algorithm. The algorithm is applied to data obtained by the MODIS (MODerate resolution Imaging Spectroradiometer) and POLDER3 (Polarization and Directionality of the Earth Reflectance) instruments. It is shown that this synergistic algorithm can be used routinely to derive cloud phase along with an index that helps to discriminate ambiguous phase from confident phase cases. The resulting product provides a semi-continuous confidence index ranging from confident liquid to confident ice instead of the usual discrete classification of liquid phase, ice phase, mixed phase (potential combination of ice and liquid particles), or simply unknown phase clouds. This approach is expected to be useful for cloud assimilation and modeling efforts while providing more insight into the global cloud properties derived from satellite data.

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Analysis of Near-Cloud Changes in Atmospheric Aerosols Using Satellite Observations and Global Model Simulations

Remote Sensing ◽

10.3390/rs13061151 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1151

Author(s):

Tamás Várnai ◽

Alexander Marshak

Keyword(s):

Atmospheric Aerosols ◽

Large Scale ◽

Climate Models ◽

Orthogonal Polarization ◽

Atmospheric Models ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

The Difference ◽

Modern Era

This paper examines cloud-related variations of atmospheric aerosols that occur in partly cloudy regions containing low-altitude clouds. The goal is to better understand aerosol behaviors and to help better represent the radiative effects of aerosols on climate. For this, the paper presents a statistical analysis of a multi-month global dataset that combines data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite instruments with data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) global reanalysis. Among other findings, the results reveal that near-cloud enhancements in lidar backscatter (closely related to aerosol optical depth) are larger (1) over land than ocean by 35%, (2) near optically thicker clouds by substantial amounts, (3) for sea salt than for other aerosol types, with the difference from dust reaching 50%. Finally, the study found that mean lidar backscatter is higher near clouds not because of large-scale variations in meteorological conditions, but because of local processes associated with individual clouds. The results help improve our understanding of aerosol-cloud-radiation interactions and our ability to represent them in climate models and other atmospheric models.

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Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland

10.5194/amt-2016-26 ◽

2016 ◽

Author(s):

Moa K. Sporre ◽

Ewan J. O’Connor ◽

Nina Håkansson ◽

Anke Thoss ◽

Erik Swietlicki ◽

...

Keyword(s):

Infrared Imaging ◽

Microwave Radiometer ◽

Single Layer ◽

Radar Data ◽

Liquid Water Path ◽

Cloud Parameters ◽

Cloud Properties ◽

Moderate Resolution Imaging Spectroradiometer ◽

Biogenic Aerosols ◽

Cloud Mask

Abstract. Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the satellites Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement program (ARM) mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from an a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single layer clouds, satellites overestimated CTH by 340 m (16 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 320 m (9 %). MODIS collection 6 overestimated LWP by on average 13 g m−2 (11 %), interestingly, LWP for MODIS collection 5.1 is slightly overestimated by Aqua (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the reflectance bands of the MODIS instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high latitude location.

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