MODIS Global Cloud-Top Pressure and Amount Estimation: Algorithm Description and Results

2008 ◽  
Vol 47 (4) ◽  
pp. 1175-1198 ◽  
Author(s):  
W. Paul Menzel ◽  
Richard A. Frey ◽  
Hong Zhang ◽  
Donald P. Wylie ◽  
Chris C. Moeller ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Single Layer ◽  
Estimation Algorithm ◽  
Spectral Coverage ◽  
Earth Observing System ◽  
Cloud Properties ◽  
True Location ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Top Pressure ◽  
Layer Cloud

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System (EOS) Terra and Aqua platforms provides unique measurements for deriving global and regional cloud properties. MODIS has spectral coverage combined with spatial resolution in key atmospheric bands, which is not available on previous imagers and sounders. This increased spectral coverage/spatial resolution, along with improved onboard calibration, enhances the capability for global cloud property retrievals. MODIS operational cloud products are derived globally at spatial resolutions of 5 km (referred to as level-2 products) and are aggregated to a 1° equal-angle grid (referred to as level-3 product), available for daily, 8-day, and monthly time periods. The MODIS cloud algorithm produces cloud-top pressures that are found to be within 50 hPa of lidar determinations in single-layer cloud situations. In multilayer clouds, where the upper-layer cloud is semitransparent, the MODIS cloud pressure is representative of the radiative mean between the two cloud layers. In atmospheres prone to temperature inversions, the MODIS cloud algorithm places the cloud above the inversion and hence is as much as 200 hPa off its true location. The wealth of new information available from the MODIS operational cloud products offers the promise of improved cloud climatologies. This paper 1) describes the cloud-top pressure and amount algorithm that has evolved through collection 5 as experience has been gained with in-flight data from NASA Terra and Aqua platforms; 2) compares the MODIS cloud-top pressures, converted to cloud-top heights, with similar measurements from airborne and space-based lidars; and 3) introduces global maps of MODIS and High Resolution Infrared Sounder (HIRS) cloud-top products.

A New Method for Detection of Cirrus Overlapping Water Clouds and Determination of Their Optical Properties

2005 ◽  
Vol 62 (11) ◽  
pp. 3993-4009 ◽  
Author(s):  
Fu-Lung Chang ◽  
Zhanqing Li
Keyword(s):  
Optical Properties ◽  
Single Layer ◽  
Remote Sensing Data ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Cloud Properties ◽  
Water Cloud ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Layer Cloud

Abstract The frequent occurrence of high cirrus overlapping low water cloud poses a major challenge in retrieving their optical properties from spaceborne sensors. This paper presents a novel retrieval method that takes full advantage of the satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The main objectives are identification of overlapped high cirrus and low water clouds and determination of their individual optical depths, top heights, and emissivities. The overlapped high cloud top is determined from the MODIS CO2-slicing retrieval and the underlying low cloud top is determined from the neighboring MODIS pixels that are identified as single-layer low clouds. The algorithm applies a dual-layer cloud radiative transfer model using initial cloud properties derived from the MODIS CO2-slicing channels and the visible (0.65 μm) and infrared (11 μm) window channels. An automated iterative procedure follows by adjusting the high cirrus and low water cloud optical depths until computed radiances from the dual-layer model match with observed radiances from both the visible and infrared channels. The algorithm is valid for both single-layer and dual-layer clouds with the cirrus optical depth <∼4 (emissivity <∼0.85). For more than two-layer clouds, its validity depends on the thickness of the upper-layer cloud. A preliminary validation is conducted by comparing against ground-based active remote sensing data. Pixel-by-pixel retrievals and error analyses are presented. It is demonstrated that retrievals based on a single-layer assumption can result in systematic biases in the retrieved cloud top and optical properties for overlapped clouds. Such biases can be removed or lessened considerably by applying the new algorithm.

scholarly journals Marine liquid cloud geometric thickness retrieved from OCO-2's oxygen A-band spectrometer

2019 ◽  
Vol 12 (3) ◽  
pp. 1717-1737 ◽  
Author(s):  
Mark Richardson ◽  
Jussi Leinonen ◽  
Heather Q. Cronk ◽  
James McDuffie ◽  
Matthew D. Lebsock ◽  
...  
Keyword(s):  
Optical Depth ◽  
Single Layer ◽  
Cloud Droplet ◽  
Satellite Observation ◽  
Cloud Optical Depth ◽  
First Case ◽  
Phase Classification ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Top Pressure ◽  
Geometric Thickness

Abstract. This paper introduces the OCO2CLD-LIDAR-AUX product, which uses the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar and the Orbiting Carbon Observatory-2 (OCO-2) hyperspectral A-band spectrometer. CALIPSO provides a prior cloud top pressure (Ptop) for an OCO-2-based retrieval of cloud optical depth, Ptop and cloud geometric thickness expressed in hPa. Measurements are of single-layer liquid clouds over oceans from September 2014 to December 2016 when collocated data are available. Retrieval performance is best for solar zenith angles <45∘ and when the cloud phase classification, which also uses OCO-2's weak CO2 band, is more confident. The highest quality optical depth retrievals agree with those from the Moderate Resolution Imaging Spectroradiometer (MODIS) with discrepancies smaller than the MODIS-reported uncertainty. Retrieved thicknesses are consistent with a substantially subadiabatic structure over marine stratocumulus regions, in which extinction is weighted towards the cloud top. Cloud top pressure in these clouds shows a 4 hPa bias compared with CALIPSO which we attribute mainly to the assumed vertical structure of cloud extinction after showing little sensitivity to the presence of CALIPSO-identified aerosol layers or assumed cloud droplet effective radius. This is the first case of success in obtaining internal cloud structure from hyperspectral A-band measurements and exploits otherwise unused OCO-2 data. This retrieval approach should provide additional constraints on satellite-based estimates of cloud droplet number concentration from visible imagery, which rely on parameterization of the cloud thickness.

scholarly journals Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

2010 ◽  
Vol 49 (11) ◽  
pp. 2315-2333 ◽  
Author(s):  
Galina Wind ◽  
Steven Platnick ◽  
Michael D. King ◽  
Paul A. Hubanks ◽  
Michael J. Pavolonis ◽  
...  
Keyword(s):  
Water Vapor ◽  
Near Infrared ◽  
Single Layer ◽  
Precipitable Water ◽  
Detection Algorithm ◽  
Cloud Detection ◽  
Water Vapor Absorption ◽  
Cloud Properties ◽  
Cloud Models ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System (EOS) Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that present difficulties for retrieving cloud effective radius using single-layer plane-parallel cloud models. The algorithm uses the MODIS 0.94-μm water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94-μm methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases.

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

2016 ◽  
Vol 9 (7) ◽  
pp. 3193-3203 ◽  
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.

scholarly journals Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators

2012 ◽  
Vol 25 (13) ◽  
pp. 4699-4720 ◽  
Author(s):  
Robert Pincus ◽  
Steven Platnick ◽  
Steven A. Ackerman ◽  
Richard S. Hemler ◽  
Robert J. Patrick Hofmann
Keyword(s):  
Optical Thickness ◽  
Model Error ◽  
Diagnostic Tools ◽  
Limited Information ◽  
Global Models ◽  
Cloud Properties ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Top Pressure

Abstract The properties of clouds that may be observed by satellite instruments, such as optical thickness and cloud-top pressure, are only loosely related to the way clouds are represented in models of the atmosphere. One way to bridge this gap is through “instrument simulators,” diagnostic tools that map the model representation to synthetic observations so that differences can be interpreted as model error. But simulators may themselves be restricted by limited information or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Satellite Cloud Climatology Project (ISCCP), two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail datasets developed for comparison with global models using ISCCP and MODIS simulators. In nature MODIS observes less midlevel cloudiness than ISCCP, consistent with the different methods used to determine cloud-top pressure; aspects of this difference are reproduced by the simulators. Differences in observed distributions of optical thickness, however, are not captured. The largest differences can be traced to different approaches to partly cloudy pixels, which MODIS excludes and ISCCP treats as homogeneous. These cover roughly 15% of the planet and account for most of the optically thinnest clouds. Instrument simulators cannot reproduce these differences because there is no way to synthesize partly cloudy pixels. Nonetheless, MODIS and ISCCP observations are consistent for all but the optically thinnest clouds, and models can be robustly evaluated using instrument simulators by integrating over the robust subset of observations.

scholarly journals CERES Synoptic Product: Methodology and Validation of Surface Radiant Flux

2015 ◽  
Vol 32 (6) ◽  
pp. 1121-1143 ◽  
Author(s):  
David A. Rutan ◽  
Seiji Kato ◽  
David R. Doelling ◽  
Fred G. Rose ◽  
Le Trang Nguyen ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Diurnal Cycle ◽  
Radiant Energy ◽  
Energy System ◽  
Surface Fluxes ◽  
Radiant Flux ◽  
Earth Observing System ◽  
Cloud Properties ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Surface Observations

AbstractThe Clouds and the Earth’s Radiant Energy System Synoptic (SYN1deg), edition 3, product provides climate-quality global 3-hourly 1° × 1°gridded top of atmosphere, in-atmosphere, and surface radiant fluxes. The in-atmosphere surface fluxes are computed hourly using a radiative transfer code based upon inputs from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), 3-hourly geostationary (GEO) data, and meteorological assimilation data from the Goddard Earth Observing System. The GEO visible and infrared imager calibration is tied to MODIS to ensure uniform MODIS-like cloud properties across all satellite cloud datasets. Computed surface radiant fluxes are compared to surface observations at 85 globally distributed land (37) and ocean buoy (48) sites as well as several other publicly available global surface radiant flux data products. Computed monthly mean downward fluxes from SYN1deg have a bias (standard deviation) of 3.0 W m−2 (5.7%) for shortwave and −4.0 W m−2 (2.9%) for longwave compared to surface observations. The standard deviation between surface downward shortwave flux calculations and observations at the 3-hourly time scale is reduced when the diurnal cycle of cloud changes is explicitly accounted for. The improvement is smaller for surface downward longwave flux owing to an additional sensitivity to boundary layer temperature/humidity, which has a weaker diurnal cycle compared to clouds.

scholarly journals An Approach for Improving Cirrus Cloud-Top Pressure/Height Estimation by Merging High-Spatial-Resolution Infrared-Window Imager Data with High-Spectral-Resolution Sounder Data

2012 ◽  
Vol 51 (8) ◽  
pp. 1477-1488 ◽  
Author(s):  
Elisabeth Weisz ◽  
W. Paul Menzel ◽  
Nadia Smith ◽  
Richard Frey ◽  
Eva E. Borbas ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Infrared Imaging ◽  
High Spatial Resolution ◽  
High Sensitivity ◽  
Satellite Observation ◽  
High Spectral Resolution ◽  
Vertical Resolution ◽  
Absorption Bands ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Top Pressure

AbstractThe next-generation Visible and Infrared Imaging Radiometer Suite (VIIRS) offers infrared (IR)-window measurements with a horizontal spatial resolution of at least 1 km, but it lacks IR spectral bands that are sensitive to absorption by carbon dioxide (CO2) or water vapor (H2O). The CO2 and H2O absorption bands have high sensitivity for the inference of cloud-top pressure (CTP), especially for semitransparent ice clouds. To account for the lack of vertical resolution, the “merging gradient” (MG) approach is introduced, wherein the high spatial resolution of an imager is combined with the high vertical resolution of a sounder for improved CTP retrievals. The Cross-Track Infrared Sounder (CrIS) is on the same payload as VIIRS. In this paper Moderate Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) data are used as proxies for VIIRS and CrIS, respectively, although the approach can be applied to any imager–sounder pair. The MG method establishes a regression relationship between gradients in both the sounder radiances convolved to imager bands and the sounder CTP retrievals. This relationship is then applied to the imager radiance measurements to obtain CTP retrievals at imager spatial resolution. Comparisons with Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud altitudes are presented for a variety of cloud scenes. Results demonstrate the ability of the MG algorithm to add spatial definition to the sounder retrievals with a higher accuracy and precision than those obtained solely from the imager.

scholarly journals Cloud-top pressure retrieval with DSCOVR EPIC oxygen A- and B-band observations

2020 ◽  
Vol 13 (10) ◽  
pp. 5259-5275
Author(s):  
Bangsheng Yin ◽  
Qilong Min ◽  
Emily Morgan ◽  
Yuekui Yang ◽  
Alexander Marshak ◽  
...  
Keyword(s):  
Single Layer ◽  
Computation Time ◽  
Observation Data ◽  
Atmospheric Conditions ◽  
Analytic Equation ◽  
Retrieval Processes ◽  
The Difference ◽  
High Level ◽  
Cloud Top Pressure ◽  
Layer Cloud

Abstract. An analytic transfer inverse model for Earth Polychromatic Imaging Camera (EPIC) observations is proposed to retrieve the cloud-top pressure (CTP) with the consideration of in-cloud photon penetration. In this model, an analytic equation was developed to represent the reflection at the top of the atmosphere from above cloud, in cloud, and below cloud. The coefficients of this analytic equation can be derived from a series of EPIC simulations under different atmospheric conditions using a nonlinear regression algorithm. With estimated cloud pressure thickness, the CTP can be retrieved from EPIC observation data by solving the analytic equation. To simulate the EPIC measurements, a program package using the double-k approach was developed. Compared to line-by-line calculation, this approach can calculate high-accuracy results with a 100-fold computation time reduction. During the retrieval processes, two kinds of retrieval results, i.e., baseline CTP and retrieved CTP, are provided. The baseline CTP is derived without considering in-cloud photon penetration, and the retrieved CTP is derived by solving the analytic equation, taking into consideration in-cloud and below-cloud interactions. The retrieved CTPs for the oxygen A and B bands are smaller than their related baseline CTP. At the same time, both baseline CTP and retrieved CTP at the oxygen B band are larger than those at the oxygen A band. Compared to the difference in baseline CTP between the B band and A band, the difference in retrieved CTP between these two bands is generally reduced. Out of around 10 000 cases, in retrieved CTP between the A and B bands we found an average bias of 93 mb with a standard deviation of 81 mb. The cloud layer top pressure from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements is used for validation. Under single-layer cloud situations, the retrieved CTPs for the oxygen A band agree well with the CTPs from CALIPSO, the mean difference of which within 5 mb in the case study. Under multiple-layer cloud situations, the CTPs derived from EPIC measurements may be larger than the CTPs of high-level thin clouds due to the effect of photon penetration.

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 Detection of multi-layer and vertically-extended clouds using A-train sensors

2010 ◽  
Vol 3 (1) ◽  
pp. 233-247 ◽  
Author(s):  
J. Joiner ◽  
A. P. Vasilkov ◽  
P. K. Bhartia ◽  
G. Wind ◽  
S. Platnick ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Simple Algorithm ◽  
Cloud Detection ◽  
Ozone Monitoring Instrument ◽  
Detection Scheme ◽  
Summer Hemisphere ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Top Pressure ◽  
Layer Cloud

Abstract. The detection of multiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (12 km×24 km at nadir) and at the 5 km×5 km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (~20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

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