scholarly journals A development of cloud top height retrieval using thermal infrared spectra observed with GOSAT and comparison with CALIPSO data

2016 ◽  
Author(s):  
Y. Someya ◽  
R. Imasu ◽  
N. Saitoh ◽  
Y. Ota ◽  
K. Shiomi
Keyword(s):  
Measurement Errors ◽  
Thermal Infrared ◽  
Atmospheric Conditions ◽  
Cloud Detection ◽  
Low Cloud ◽  
Atmospheric Profile ◽  
Slicing Method ◽  
Cloud Tops ◽  
Spectral Channels ◽  
Good Agreement

Abstract. An algorithm based on CO2 slicing, which has been used for cirrus cloud detection using thermal infrared data, was developed for high-resolution radiance spectra from satellites. The channels were reconstructed based on sensitivity height information of the original spectral channels to reduce the effects of measurement errors. The selections of the reconstructed channel pairs were optimized for several atmospheric profile patterns using simultaneous studies assuming cloudy sky. That algorithm was applied to data by the Greenhouse gases Observing SATellite (GOSAT). The results were compared with those obtained from space-borne lidar instrument onboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Monthly mean cloud amounts from the slicing generally agreed with those from CALIPSO observations despite some differences caused by surface temperature biases, optically very thin cirrus, multilayer structures of clouds, extremely low cloud tops, and specific atmospheric conditions. Comparison of coincident data showed good agreement except some cases and revealed that the improved slicing method is more accurate than the traditional slicing method. Results also imply that improved slicing can detect low-level clouds with cloud top heights as low as approximately 1.5 km.

scholarly journals A development of cloud top height retrieval using thermal infrared spectra observed with GOSAT and comparison with CALIPSO data

2016 ◽  
Vol 9 (5) ◽  
pp. 1981-1992 ◽  
Author(s):  
Yu Someya ◽  
Ryoichi Imasu ◽  
Naoko Saitoh ◽  
Yoshifumi Ota ◽  
Kei Shiomi
Keyword(s):  
Measurement Errors ◽  
Thermal Infrared ◽  
Atmospheric Conditions ◽  
Cloud Detection ◽  
Low Cloud ◽  
Atmospheric Profile ◽  
Slicing Method ◽  
Cloud Tops ◽  
Spectral Channels ◽  
Selection Of

Abstract. An algorithm based on CO2 slicing, which has been used for cirrus cloud detection using thermal infrared data, was developed for high-resolution radiance spectra from satellites. The channels were reconstructed based on sensitivity height information of the original spectral channels to reduce the effects of measurement errors. Selection of the reconstructed channel pairs was optimized for several atmospheric profile patterns using simultaneous studies assuming a cloudy sky. That algorithm was applied to data by the Greenhouse gases Observing SATellite (GOSAT). Results were compared with those obtained from the space-borne lidar instrument on-board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Monthly mean cloud amounts from the slicing generally agreed with those from CALIPSO observations despite some differences caused by surface temperature biases, optically very thin cirrus, multilayer structures of clouds, extremely low cloud tops, and specific atmospheric conditions. Comparison of coincident data showed good agreement, except for some cases, and revealed that the improved slicing method is more accurate than the traditional slicing method. Results also imply that improved slicing can detect low-level clouds with cloud top heights as low as approximately 1.5 km.

scholarly journals Dust Aerosol Detection by the Modified CO2 Slicing Method

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1615 ◽  
Author(s):  
Yu Someya ◽  
Ryoichi Imasu ◽  
Kei Shiomi
Keyword(s):  
Inversion Layer ◽  
Temperature Inversion ◽  
Dust Aerosol ◽  
Aerosol Layer ◽  
Atmospheric Conditions ◽  
Cloud Detection ◽  
Dust Aerosols ◽  
Surface Skin Temperature ◽  
Slicing Method ◽  
Ground Based Lidar

Dust aerosols, which have diverse and strong influences on the environment, must be monitored. Satellite data are effective for monitoring atmospheric conditions globally. In this work, the modified CO2 slicing method, a cloud detection technique using thermal infrared data from space, was applied to GOSAT data to detect the dust aerosol layer height. The results were compared using lidar measurements. Comparison of horizontal distributions found for northern Africa during summer revealed that both the relative frequencies of the low level aerosol layer from the slicing method and the dust frequencies of CALIPSO are high in northern coastal areas. Comparisons of detected layer top heights using collocated data with CALIPSO and ground-based lidar consistently showed high detection frequencies of the lower level aerosol layer, although the slicing method sometimes produces overestimates. This tendency is significant over land. The main causes of this tendency might be uncertainty of the surface skin temperature and a temperature inversion layer in the atmosphere. The results revealed that obtaining the detailed behavior of dust aerosols using the modified slicing method alone is difficult.

Investigating the vibrational behaviour of a rotating two-blade propeller by using a self-tracking method

2018 ◽  
Vol 233 (3) ◽  
pp. 835-847 ◽  
Author(s):  
Mohammad-Reza Ashory ◽  
Farhad Talebi ◽  
Heydar R Ghadikolaei ◽  
Morad Karimpour
Keyword(s):  
Natural Frequency ◽  
Measurement Errors ◽  
Mode Shapes ◽  
Model Parameters ◽  
Test Results ◽  
Modal Assurance Criterion ◽  
Tracking Method ◽  
Strong Resemblance ◽  
Test Scenarios ◽  
Good Agreement

This study investigated the vibrational behaviour of a rotating two-blade propeller at different rotational speeds by using self-tracking laser Doppler vibrometry. Given that a self-tracking method necessitates the accurate adjustment of test setups to reduce measurement errors, a test table with sufficient rigidity was designed and built to enable the adjustment and repair of test components. The results of the self-tracking test on the rotating propeller indicated an increase in natural frequency and a decrease in the amplitude of normalized mode shapes as rotational speed increases. To assess the test results, a numerical model created in ABAQUS was used. The model parameters were tuned in such a way that the natural frequency and associated mode shapes were in good agreement with those derived using a hammer test on a stationary propeller. The mode shapes obtained from the hammer test and the numerical (ABAQUS) modelling were compared using the modal assurance criterion. The examination indicated a strong resemblance between the hammer test results and the numerical findings. Hence, the model can be employed to determine the other mechanical properties of two-blade propellers in test scenarios.

scholarly journals Evaluation of rainfall retrievals from SEVIRI reflectances over West Africa using TRMM-PR and CMORPH

2011 ◽  
Vol 15 (2) ◽  
pp. 437-451 ◽  
Author(s):  
E. L. A. Wolters ◽  
B. J. J. M. van den Hurk ◽  
R. A. Roebeling
Keyword(s):  
West Africa ◽  
Temporal Resolution ◽  
Rain Rate ◽  
Thermal Infrared ◽  
Occurrence Frequency ◽  
Added Value ◽  
Inter Tropical Convergence Zone ◽  
Trmm Pr ◽  
Spatio Temporal ◽  
Good Agreement

Abstract. This paper describes the evaluation of the KNMI Cloud Physical Properties – Precipitation Properties (CPP-PP) algorithm over West Africa. The algorithm combines condensed water path (CWP), cloud phase (CPH), cloud particle effective radius (re), and cloud-top temperature (CTT) retrievals from visible, near-infrared and thermal infrared observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) satellites to estimate rain occurrence frequency and rain rate. For the 2005 and 2006 monsoon seasons, it is investigated whether the CPP-PP algorithm is capable of retrieving rain occurrence frequency and rain rate over West Africa with sufficient accuracy, using Tropical Monsoon Measurement Mission Precipitation Radar (TRMM-PR) as reference. As a second goal, it is assessed whether SEVIRI is capable of monitoring the seasonal and daytime evolution of rainfall during the West African monsoon (WAM), using Climate Prediction Center Morphing Technique (CMORPH) rainfall observations. The SEVIRI-detected rainfall area agrees well with TRMM-PR, with the areal extent of rainfall by SEVIRI being ~10% larger than from TRMM-PR. The mean retrieved rain rate from CPP-PP is about 8% higher than from TRMM-PR. Examination of the TRMM-PR and CPP-PP cumulative frequency distributions revealed that differences between CPP-PP and TRMM-PR are generally within +/−10%. Relative to the AMMA rain gauge observations, CPP-PP shows very good agreement up to 5 mm h−1. However, at higher rain rates (5–16 mm h−1) CPP-PP overestimates compared to the rain gauges. With respect to the second goal of this paper, it was shown that both the accumulated precipitation and the seasonal progression of rainfall throughout the WAM is in good agreement with CMORPH, although CPP-PP retrieves higher amounts in the coastal region of West Africa. Using latitudinal Hovmüller diagrams, a fair correspondence between CPP-PP and CMORPH was found, which is reflected by high correlation coefficients (~0.7) for both rain rate and rain occurrence frequency. The daytime cycle of rainfall from CPP-PP shows distinctly different patterns for three different regions in West Africa throughout the WAM, with a decrease in dynamical range of rainfall near the Inter Tropical Convergence Zone (ITCZ). The dynamical range as retrieved from CPP-PP is larger than that from CMORPH. It is suggested that this results from both the better spatio-temporal resolution of SEVIRI, as well as from thermal infrared radiances being partly used by CMORPH, which likely smoothes the daytime precipitation signal, especially in case of cold anvils from convective systems. The promising results show that the CPP-PP algorithm, taking advantage of the high spatio-temporal resolution of SEVIRI, is of added value for monitoring daytime precipitation patterns in tropical areas.

Identification of the Velocity, Thickness, and Interfacial Roughness of Coating Using Full Time-Domain URCPS: Cross-Correlation-Based Inverse Problem

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Zhiyuan Ma ◽  
Li Lin ◽  
Shijie Jin ◽  
Mingkai Lei
Keyword(s):  
Time Domain ◽  
Measurement Errors ◽  
Cross Correlation ◽  
Inversion Method ◽  
Full Time ◽  
Interfacial Roughness ◽  
Measured Velocity ◽  
Detection Frequency ◽  
Relative Errors ◽  
Good Agreement

Aiming at characterizing interfacial roughness of thin coatings with unknown sound velocity and thickness, we derive a full time-domain ultrasonic reflection coefficient phase spectrum (URCPS) as a function of interfacial roughness based on the phase screen approximation theory. The constructed URCPS is used to determine the velocity, thickness, and interfacial roughness of specimens through the cross-correlation algorithm. The effect of detection frequency on the roughness measurement is investigated through the finite element method. A series of simulations were implemented on Ni-coating specimens with a thickness of 400 μm and interfacial roughness of 1.9–39.8 μm. Simulation results indicated that the measurement errors of interfacial roughness were less than 10% when the roughness satisfies the relationship of Rq = 1.6–10.0%λ. The measured velocity and thicknesses were in good agreement with those imported in simulation models with less than 9.3% error. Ultrasonic experiments were carried out on two Ni-coating specimens through a flat transducer with an optimized frequency of 15 MHz. Compared with the velocities measured by time-of-flight (TOF) method, the relative errors of inversed velocities were all less than 10%. The inversed thicknesses were in good agreement with those observed by optical microscopy with less than 10.9% and 7.6% error. The averaged interfacial roughness determined by the ultrasonic inversion method was 16.9 μm and 30.7 μm, respectively. The relative errors were 5.1% and 2.0% between ultrasonic and confocal laser scanning microscope (CLSM) method, respectively.

scholarly journals Measurement of aerosol optical depth and sub-visual cloud detection using the optical depth sensor (ODS)

2016 ◽  
Vol 9 (2) ◽  
pp. 455-467 ◽  
Author(s):  
D. Toledo ◽  
P. Rannou ◽  
J.-P. Pommereau ◽  
A. Sarkissian ◽  
T. Foujols
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Diffuse Radiation ◽  
Dust Storms ◽  
Saharan Dust ◽  
Cloud Detection ◽  
Depth Sensor ◽  
Data Set ◽  
Good Agreement

Abstract. A small and sophisticated optical depth sensor (ODS) has been designed to work in the atmosphere of Mars. The instrument measures alternatively the diffuse radiation from the sky and the attenuated direct radiation from the Sun on the surface. The principal goals of ODS are to retrieve the daily mean aerosol optical depth (AOD) and to detect very high and optically thin clouds, crucial parameters in understanding the Martian meteorology and climatology. The detection of clouds is undertaken at twilight, allowing the detection and characterization of clouds with opacities below 0.03 (sub-visual clouds). In addition, ODS is capable to retrieve the aerosol optical depth during nighttime from moonlight measurements. Recently, ODS has been selected at the METEO meteorological station on board the ExoMars 2018 Lander. In order to study the performance of ODS under Mars-like conditions as well as to evaluate the retrieval algorithms for terrestrial measurements, ODS was deployed in Ouagadougou (Africa) between November 2004 and October 2005, a Sahelian region characterized by its high dust aerosol load and the frequent occurrence of Saharan dust storms. The daily average AOD values retrieved by ODS were compared with those provided by a CIMEL sunphotometer of the AERONET (Aerosol Robotic NETwork) network localized at the same location. Results represent a good agreement between both ground-based instruments, with a correlation coefficient of 0.77 for the whole data set and 0.94 considering only the cloud-free days. From the whole data set, a total of 71 sub-visual cirrus (SVC) were detected at twilight with opacities as thin as 1.10−3 and with a maximum of occurrence at altitudes between 14 and 20 km. Although further optimizations and comparisons of ODS terrestrial measurements are required, results indicate the potential of these measurements to retrieve the AOD and detect sub-visual clouds.

In-Flight Validation of the ECOSTRESS, Landsats 7 and 8 Thermal Infrared Spectral Channels Using the Lake Tahoe CA/NV and Salton Sea CA Automated Validation Sites

2020 ◽  
Vol 58 (2) ◽  
pp. 1294-1302 ◽  
Author(s):  
Simon J. Hook ◽  
Kerry Cawse-Nicholson ◽  
Julia Barsi ◽  
Robert Radocinski ◽  
Glynn C. Hulley ◽  
...  
Keyword(s):  
Lake Tahoe ◽  
Thermal Infrared ◽  
Salton Sea ◽  
Infrared Spectral ◽  
Spectral Channels

scholarly journals An empirical method to correct for temperature-dependent variations in the overlap function of CHM15k ceilometers

2016 ◽  
Vol 9 (7) ◽  
pp. 2947-2959 ◽  
Author(s):  
Maxime Hervo ◽  
Yann Poltera ◽  
Alexander Haefele
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Correction Method ◽  
Empirical Method ◽  
Cloud Base ◽  
Atmospheric Conditions ◽  
Cloud Detection ◽  
Temperature Dependent ◽  
Night Time ◽  
Gradient Based

Abstract. Imperfections in a lidar's overlap function lead to artefacts in the background, range and overlap-corrected lidar signals. These artefacts can erroneously be interpreted as an aerosol gradient or, in extreme cases, as a cloud base leading to false cloud detection. A correct specification of the overlap function is hence crucial in the use of automatic elastic lidars (ceilometers) for the detection of the planetary boundary layer or of low cloud. In this study, an algorithm is presented to correct such artefacts. It is based on the assumption of a homogeneous boundary layer and a correct specification of the overlap function down to a minimum range, which must be situated within the boundary layer. The strength of the algorithm lies in a sophisticated quality-check scheme which allows the reliable identification of favourable atmospheric conditions. The algorithm was applied to 2 years of data from a CHM15k ceilometer from the company Lufft. Backscatter signals corrected for background, range and overlap were compared using the overlap function provided by the manufacturer and the one corrected with the presented algorithm. Differences between corrected and uncorrected signals reached up to 45 % in the first 300 m above ground. The amplitude of the correction turned out to be temperature dependent and was larger for higher temperatures. A linear model of the correction as a function of the instrument's internal temperature was derived from the experimental data. Case studies and a statistical analysis of the strongest gradient derived from corrected signals reveal that the temperature model is capable of a high-quality correction of overlap artefacts, in particular those due to diurnal variations. The presented correction method has the potential to significantly improve the detection of the boundary layer with gradient-based methods because it removes false candidates and hence simplifies the attribution of the detected gradients to the planetary boundary layer. A particularly significant benefit can be expected for the detection of shallow stable layers typical of night-time situations. The algorithm is completely automatic and does not require any on-site intervention but requires the definition of an adequate instrument-specific configuration. It is therefore suited for use in large ceilometer networks.

PATMOS-x v6.0: Improvements to AVHRR Cloud Climate Record and Analysis of the Updated Data

2020 ◽  
Author(s):  
Coda Phillips ◽  
Michael Foster ◽  
Andrew Heidinger
Keyword(s):  
High Resolution ◽  
Detection Accuracy ◽  
Cloud Detection ◽  
Edge Preserving ◽  
Brightness Temperatures ◽  
Cloud Properties ◽  
Satellite Sensors ◽  
The Difference ◽  
Climate Analysis ◽  
Spectral Channels

<p>Since 1978, an Advanced Very-High-Resolution Radiometer (AVHRR) has flown onboard 17 polar-orbiting satellites. Together, they are the longest global record from a homogeneous set of satellite sensors. The Pathfinder Atmosphere’s Extended (PATMOS-x) dataset is a long-term cloud record derived from the AVHRR radiances, and suitable for climate analysis. It has demonstrated intersensor stability and has been rigorously compared with other cloud datasets.</p><p>However, the AVHRR alone has only limited spectral information, so cloud detection during nighttime or over ice is challenging. Therefore, performance degrades over regions with extreme diurnal patterns or low temperatures such as the poles, despite our interest.</p><p>The next production version of PATMOS-x will include numerous algorithmic changes as well as the use of High-resolution Infrared Radiation Sounder (HIRS) spectral channels to improve detection accuracy in previously difficult conditions. The low-resolution HIRS soundings are upsampled to match the AVHRR pixels through an edge-preserving process called “fusion”. The higher-resolution AVHRR imagery guides the upsampling and the resulting combination is spectrally consistent with the AVHRR and has a high spatial resolution.</p><p>For cloud detection, the difference between the AVHRR and HIRS 11μm and HIRS 6.7μm brightness temperatures has been added as a feature in the naive Bayesian cloud detector. The effect on cloud precision is seen especially in the Antarctic where false-positive cloud detections have decreased dramatically.</p><p>Other cloud properties can be improved with the new spectral channels. For example, the new cloud phase algorithm uses the HIRS 6.7μm to determine cloud phase and the AVHRR and HIRS 11μm-13.3μm beta ratio identifies overlapping clouds. Also, the 11μm, 12μm, and HIRS 13.3μm are used in the new cloud height algorithm.</p><p>We report on the development of this new version of the PATMOS-x cloud climate dataset, and the methods used to calibrate and homogenize the participating sensors. Finally, observed trends in the improved dataset will be examined and related to the old dataset. In particular, attention will be given to whether high-latitude analysis of climatic trends is finally possible on the new dataset.</p>

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