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.

Cloud Detection with MODIS. Part I: Improvements in the MODIS Cloud Mask for Collection 5

2008 ◽  
Vol 25 (7) ◽  
pp. 1057-1072 ◽  
Author(s):  
Richard A. Frey ◽  
Steven A. Ackerman ◽  
Yinghui Liu ◽  
Kathleen I. Strabala ◽  
Hong Zhang ◽  
...  
Keyword(s):  
Near Infrared ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Cloud Detection ◽  
Stream Data ◽  
Water Vapor Absorption ◽  
Brightness Temperatures ◽  
Surface Temperatures ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask

Abstract Significant improvements have been made to the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask (MOD35 and MYD35) for Collection 5 reprocessing and forward stream data production. Most of the modifications are realized for nighttime scenes where polar and oceanic regions will see marked improvement. For polar night scenes, two new spectral tests using the 7.2-μm water vapor absorption band have been added as well as updates to the 3.9–12- and 11–12-μm cloud tests. More non-MODIS ancillary input data have been added. Land and sea surface temperature maps provide crucial information for mid- and low-level cloud detection and lessen dependence on ocean brightness temperature variability tests. Sun-glint areas are also improved by use of sea surface temperatures to aid in resolving observations with conflicting cloud versus clear-sky signals, where visible and near-infrared (NIR) reflectances are high, but infrared brightness temperatures are relatively warm. Day and night Arctic cloud frequency results are compared to those created by the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder-Extended (APP-X) algorithm. Day versus night sea surface temperatures derived from MODIS radiances and using only the MODIS cloud mask for cloud screening are contrasted. Frequencies of cloud from sun-glint regions are shown as a function of sun-glint angle to gain a sense of cloud mask quality in those regions. Continuing validation activities are described in Part II of this paper.

scholarly journals Cirrus cloud optical and microphysical property retrievals from eMAS during SEAC<sup>4</sup>RS using bi-spectral reflectance measurements within the 1.88  µm water vapor absorption band

2016 ◽  
Vol 9 (4) ◽  
pp. 1743-1753 ◽  
Author(s):  
Kerry Meyer ◽  
Steven Platnick ◽  
G. Thomas Arnold ◽  
Robert E. Holz ◽  
Paolo Veglio ◽  
...  
Keyword(s):  
Water Vapor ◽  
Absorption Band ◽  
Near Infrared ◽  
Single Layer ◽  
Distinct Advantage ◽  
Cirrus Cloud ◽  
Water Vapor Absorption ◽  
Cloud Particle ◽  
Infrared Wavelength ◽  
Vapor Absorption

Abstract. Previous bi-spectral imager retrievals of cloud optical thickness (COT) and effective particle radius (CER) based on the Nakajima and King (1990) approach, such as those of the operational MODIS cloud optical property retrieval product (MOD06), have typically paired a non-absorbing visible or near-infrared wavelength, sensitive to COT, with an absorbing shortwave or mid-wave infrared wavelength sensitive to CER. However, in practice it is only necessary to select two spectral channels that exhibit a strong contrast in cloud particle absorption. Here it is shown, using eMAS observations obtained during NASA's SEAC4RS field campaign, that selecting two absorbing wavelength channels within the broader 1.88 µm water vapor absorption band, namely the 1.83 and 1.93 µm channels that have sufficient differences in ice crystal single scattering albedo, can yield COT and CER retrievals for thin to moderately thick single-layer cirrus that are reasonably consistent with other solar and IR imager-based and lidar-based retrievals. A distinct advantage of this channel selection for cirrus cloud retrievals is that the below-cloud water vapor absorption minimizes the surface contribution to measured cloudy top-of-atmosphere reflectance, in particular compared to the solar window channels used in heritage retrievals such as MOD06. This reduces retrieval uncertainty resulting from errors in the surface reflectance assumption and reduces the frequency of retrieval failures for thin cirrus clouds.

scholarly journals Cirrus cloud optical and microphysical property retrievals from eMAS during SEAC<sup>4</sup>RS using bi-spectral reflectance measurements within the 1.88 μm water vapor absorption band

2016 ◽  
Author(s):  
K. Meyer ◽  
S. Platnick ◽  
G. T. Arnold ◽  
R. E. Holz ◽  
P. Veglio ◽  
...  
Keyword(s):  
Water Vapor ◽  
Absorption Band ◽  
Near Infrared ◽  
Single Layer ◽  
Distinct Advantage ◽  
Cirrus Cloud ◽  
Water Vapor Absorption ◽  
Cloud Particle ◽  
Infrared Wavelength ◽  
Vapor Absorption

Abstract. Previous bi-spectral imager retrievals of cloud optical thickness (COT) and effective particle radius (CER) based on the Nakajima and King (1990) approach, such as those of the operational MODIS cloud optical property retrieval product (MOD06), have typically paired a non-absorbing visible or near-infrared wavelength, sensitive to COT, with an absorbing shortwave or midwave infrared wavelength sensitive to CER. However, in practice it is only necessary to select two spectral channels that exhibit a strong contrast in cloud particle absorption. Here it is shown, using eMAS observations obtained during NASA's SEAC4RS field campaign, that selecting two absorbing wavelength channels within the broader 1.88 μm water vapor absorption band, namely the 1.83 and 1.93 μm channels that have sufficient differences in ice crystal single scattering albedo, can yield COT and CER retrievals for thin to moderately thick single-layer cirrus that are reasonably consistent with other solar and IR imager-based and lidar-based retrievals. A distinct advantage of this channel selection for cirrus cloud retrievals is that the surface contribution to measured cloudy TOA reflectance is minimized due to below-cloud water vapor absorption, thus reducing retrieval uncertainty resulting from errors in the surface reflectance assumption, as well as reducing the frequency of retrieval failures for thin cirrus clouds.

scholarly journals An Algorithm to Retrieve Total Precipitable Water Vapor in the Atmosphere from FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) Data

2020 ◽  
Vol 12 (21) ◽  
pp. 3469
Author(s):  
Bilawal Abbasi ◽  
Zhihao Qin ◽  
Wenhui Du ◽  
Jinlong Fan ◽  
Chunliang Zhao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Near Infrared ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Optical Remote Sensing ◽  
Statistical Regression ◽  
Sensing Applications ◽  
Medium Resolution ◽  
Spectral Imager

The atmosphere has substantial effects on optical remote sensing imagery of the Earth’s surface from space. These effects come through the functioning of atmospheric particles on the radiometric transfer from the Earth’s surface through the atmosphere to the sensor in space. Precipitable water vapor (PWV), CO2, ozone, and aerosol in the atmosphere are very important among the particles through their functioning. This study presented an algorithm to retrieve total PWV from the Chinese second-generation polar-orbiting meteorological satellite FengYun 3D Medium Resolution Spectral Imager 2 (FY-3D MERSI-2) data, which have three near-infrared (NIR) water vapor absorbing channels, i.e., channel 16, 17, and 18. The algorithm was improved from the radiance ratio technique initially developed for Moderate-Resolution Imaging Spectroradiometer (MODIS) data. MODTRAN 5 was used to simulate the process of radiant transfer from the ground surfaces to the sensor at various atmospheric conditions for estimation of the coefficients of ratio technique, which was achieved through statistical regression analysis between the simulated radiance and transmittance values for FY-3D MERSI-2 NIR channels. The algorithm was then constructed as a linear combination of the three-water vapor absorbing channels of FY-3D MERSI-2. Measurements from two ground-based reference datasets were used to validate the algorithm: the sun photometer measurements of Aerosol Robotic Network (AERONET) and the microwave radiometer measurements of Energy’s Atmospheric Radiation Measurement Program (ARMP). The validation results showed that the algorithm performs very well when compared with the ground-based reference datasets. The estimated PWV values come with root mean square error (RMSE) of 0.28 g/cm2 for the ARMP and 0.26 g/cm2 for the AERONET datasets, with bias of 0.072 g/cm2 and 0.096 g/cm2 for the two reference datasets, respectively. The accuracy of the proposed algorithm revealed a better consistency with ground-based reference datasets. Thus, the proposed algorithm could be used as an alternative to retrieve PWV from FY-3D MERSI-2 data for various remote sensing applications such as agricultural monitoring, climate change, hydrologic cycle, and so on at various regional and global scales.

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 Water vapor detection in the transmission spectra of HD 209458 b with the CARMENES NIR channel

2019 ◽  
Vol 630 ◽  
pp. A53 ◽  
Author(s):  
A. Sánchez-López ◽  
F. J. Alonso-Floriano ◽  
M. López-Puertas ◽  
I. A. G. Snellen ◽  
B. Funke ◽  
...  
Keyword(s):  
Water Vapor ◽  
Near Infrared ◽  
Signal To Noise Ratio ◽  
Principal Component ◽  
Large Change ◽  
Large Error ◽  
Water Vapor Absorption ◽  
Stable Conditions ◽  
Multi Band ◽  
Hot Jupiter

Aims. We aim at detecting water vapor in the atmosphere of the hot Jupiter HD 209458 b and perform a multi-band study in the near infrared with CARMENES. Methods. The water vapor absorption lines from the atmosphere of the planet are Doppler-shifted due to the large change in its radial velocity during transit. This shift is of the order of tens of km s−1, whilst the Earth’s telluric and the stellar lines can be considered quasi-static. We took advantage of this shift to remove the telluric and stellar lines using SYSREM, which performs a principal component analysis including proper error propagation. The residual spectra contain the signal from thousands of planetary molecular lines well below the noise level. We retrieve the information from those lines by cross-correlating the residual spectra with models of the atmospheric absorption of the planet. Results. We find a cross-correlation signal with a signal-to-noise ratio (S/N) of 6.4, revealing H2O in HD 209458 b. We obtain a net blueshift of the signal of –5.2 −1.3+2.6 km s−1 that, despite the large error bars, is a firm indication of day- to night-side winds at the terminator of this hot Jupiter. Additionally, we performed a multi-band study for the detection of H2O individually from the three near infrared bands covered by CARMENES. We detect H2O from its 0.96–1.06 μm band with a S/N of 5.8, and also find hints of a detection from the 1.06–1.26 μm band, with a low S/N of 2.8. No clear planetary signal is found from the 1.26–1.62 μm band. Conclusions. Our significant H2O signal at 0.96–1.06 μm in HD 209458 b represents the first detection of H2O from this band individually, the bluest one to date. The unfavorable observational conditions might be the reason for the inconclusive detection from the stronger 1.15 and 1.4 μm bands. H2O is detected from the 0.96–1.06 μm band in HD 209458 b, but hardly in HD 189733 b, which supports a stronger aerosol extinction in the latter, in line with previous studies. Future data gathered at more stable conditions and with larger S/N at both optical and near-infrared wavelengths could help to characterize the presence of aerosols in HD 209458 b and other planets.

scholarly journals Volcanic ash detection and retrievals from MODIS data by means of Neural Networks

2011 ◽  
Vol 4 (3) ◽  
pp. 2567-2598 ◽  
Author(s):  
M. Picchiani ◽  
M. Chini ◽  
S. Corradini ◽  
L. Merucci ◽  
P. Sellitto ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Confusion Matrix ◽  
Classification Problem ◽  
Cloud Detection ◽  
Cloud Properties ◽  
Mandatory Requirement ◽  
Mt Etna ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Time Basis ◽  
Ash Cloud

Abstract. Volcanic ash clouds detection and retrieval represent a key issue for the aviation safety due to the harming effects they can provoke on aircrafts. A lesson learned from the recent Icelandic Eyjafjalla volcano eruption is the need to obtain accurate and reliable retrievals on a real time basis. The current most widely adopted procedures for ash detection and retrieval are based on the Brightness Temperature Difference (BTD) inversion observed at 11 and 12 μm that allows volcanic and meteo clouds discrimination. While ash cloud detection can be readily obtained, a reliable quantitative ash cloud retrieval can be so time consuming to prevent its utilization during the crisis phase. In this work a fast and accurate Neural Network (NN) approach to detect and retrieve volcanic ash cloud properties has been developed using multispectral IR measurements collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) over Mt. Etna volcano during 2001, 2002 and 2006 eruptive events. The procedure consists in two separate steps: the ash detection and ash mass retrieval. The detection is reduced to a classification problem by identifying two classes of "ashy" and "non-ashy" pixels in the MODIS images. Then the ash mass is estimated by means of the NN, replicating the BTD-based model performances. The results obtained from the entire procedure are very encouraging; indeed the confusion matrix for the test set has an accuracy greater than 90 %. Both ash detection and retrieval show a good agreement when compared to the results achieved by the BTD-based procedure. Moreover, the NN procedure is so fast to be extremely attractive in all the cases when the quick response time of the system is a mandatory requirement.

scholarly journals CLAAS: the CM SAF cloud property data set using SEVIRI

2014 ◽  
Vol 14 (8) ◽  
pp. 4297-4311 ◽  
Author(s):  
M. Stengel ◽  
A. Kniffka ◽  
J. F. Meirink ◽  
M. Lockhoff ◽  
J. Tan ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spatial Scales ◽  
Sampling Rate ◽  
High Temporal Resolution ◽  
Cloud Detection ◽  
Data Set ◽  
Cloud Property ◽  
Temporal Sampling ◽  
Cloud Properties ◽  
The Impact

Abstract. An 8-year record of satellite-based cloud properties named CLAAS (CLoud property dAtAset using SEVIRI) is presented, which was derived within the EUMETSAT Satellite Application Facility on Climate Monitoring. The data set is based on SEVIRI measurements of the Meteosat Second Generation satellites, of which the visible and near-infrared channels were intercalibrated with MODIS. Applying two state-of-the-art retrieval schemes ensures high accuracy in cloud detection, cloud vertical placement and microphysical cloud properties. These properties were further processed to provide daily to monthly averaged quantities, mean diurnal cycles and monthly histograms. In particular, the per-month histogram information enhances the insight in spatio-temporal variability of clouds and their properties. Due to the underlying intercalibrated measurement record, the stability of the derived cloud properties is ensured, which is exemplarily demonstrated for three selected cloud variables for the entire SEVIRI disc and a European subregion. All data products and processing levels are introduced and validation results indicated. The sampling uncertainty of the averaged products in CLAAS is minimized due to the high temporal resolution of SEVIRI. This is emphasized by studying the impact of reduced temporal sampling rates taken at typical overpass times of polar-orbiting instruments. In particular, cloud optical thickness and cloud water path are very sensitive to the sampling rate, which in our study amounted to systematic deviations of over 10% if only sampled once a day. The CLAAS data set facilitates many cloud related applications at small spatial scales of a few kilometres and short temporal scales of a~few hours. Beyond this, the spatiotemporal characteristics of clouds on diurnal to seasonal, but also on multi-annual scales, can be studied.

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