scholarly journals The semianalytical cloud retrieval algorithm for SCIAMACHY – I. The validation

2005 ◽  
Vol 5 (2) ◽  
pp. 1995-2015 ◽  
Author(s):  
A. A. Kokhanovsky ◽  
V. V. Rozanov ◽  
T. Nauss ◽  
C. Reudenbach ◽  
J. S. Daniel ◽  
...  
Keyword(s):  
Retrieval Algorithm ◽  
Look Up Table ◽  
Ozone Monitoring ◽  
Scanning Imaging ◽  
Using Data ◽  
The Look ◽  
Along Track ◽  
Spectrometer Data ◽  
Resolution Spectrometer ◽  
Absorption Spectrometer

Abstract. A recently developed cloud retrieval algorithm for the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) is briefly presented and validated using independent and well tested cloud retrieval techniques based on the look-up-table approach for MODeration resolutIon Spectrometer data. The results of the cloud top height retrievals using measurements in the oxygen A-band by an airborne crossed Czerny-Turner spectrograph and the Global Ozone Monitoring Experiment (GOME) instrument are compared with those obtained from airborne dual photography and retrievals using data from Along Track Scanning Radiometer (ATSR-2), respectively.

scholarly journals The semianalytical cloud retrieval algorithm for SCIAMACHY I. The validation

2006 ◽  
Vol 6 (7) ◽  
pp. 1905-1911 ◽  
Author(s):  
A. A. Kokhanovsky ◽  
V. V. Rozanov ◽  
T. Nauss ◽  
C. Reudenbach ◽  
J. S. Daniel ◽  
...  
Keyword(s):  
Retrieval Algorithm ◽  
Modis Data ◽  
Look Up Table ◽  
Ozone Monitoring ◽  
Scanning Imaging ◽  
Using Data ◽  
The Look ◽  
Along Track ◽  
Resolution Spectrometer ◽  
Absorption Spectrometer

Abstract. A recently developed cloud retrieval algorithm for the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) is briefly presented and validated using independent and well tested cloud retrieval techniques based on the look-up-table approach for MODeration resolutIon Spectrometer (MODIS) data. The results of the cloud top height retrievals using measurements in the oxygen A-band by an airborne crossed Czerny-Turner spectrograph and the Global Ozone Monitoring Experiment (GOME) instrument are compared with those obtained from airborne dual photography and retrievals using data from Along Track Scanning Radiometer (ATSR-2), respectively.

scholarly journals FRESCO-B: a fast cloud retrieval algorithm using oxygen B-band measurements from GOME-2

2019 ◽  
Vol 12 (4) ◽  
pp. 2485-2498 ◽  
Author(s):  
Marine Desmons ◽  
Ping Wang ◽  
Piet Stammes ◽  
L. Gijsbert Tilstra
Keyword(s):  
Satellite Data ◽  
Surface Albedo ◽  
Cloud Fraction ◽  
Mean Difference ◽  
Retrieval Algorithm ◽  
Retrieval Scheme ◽  
Ozone Monitoring ◽  
The Difference ◽  
Scanning Imaging ◽  
Absorption Spectrometer

Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A band) algorithm is a simple, fast and robust algorithm used to retrieve cloud information in operational satellite data processing. It has been applied to GOME-1 (Global Ozone Monitoring Experiment), SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography), GOME-2 and more recently to TROPOMI (Tropospheric Monitoring Instrument). FRESCO retrieves effective cloud fraction and cloud pressure from measurements in the oxygen A band around 761 nm. In this paper, we propose a new version of the algorithm, called FRESCO-B, which is based on measurements in the oxygen B band around 687 nm. Such a method is interesting for vegetated surfaces where the surface albedo is much lower in the B band than in the A band, which limits the ground contribution to the top-of-atmosphere reflectances. In this study we first perform retrieval simulations. These show that the retrieved cloud pressures from FRESCO-B and FRESCO differ only between −10 and +10 hPa, except for high, thin clouds over vegetation where the difference is larger (about +15 to +30 hPa), with FRESCO-B yielding higher pressure. Next, inter-comparison between FRESCO-B and FRESCO retrievals over 1 month of GOME-2B data reveals that the effective cloud fractions retrieved in the O2 A and B bands are very similar (mean difference of 0.003), while the cloud pressures show a mean difference of 11.5 hPa, with FRESCO-B retrieving higher pressures than FRESCO. This agrees with the simulations and is partly due to deeper photon penetrations of the O2 B band in clouds compared to the O2 A-band photons and partly due to the surface albedo bias in FRESCO. Finally, validation with ground-based measurements shows that the FRESCO-B cloud pressure represents an altitude within the cloud boundaries for clouds that are not too far from the Lambertian reflector model, which occurs in about 50 % of the cases.

scholarly journals Recent satellite-based trends of tropospheric nitrogen dioxide over large urban agglomerations worldwide

2014 ◽  
Vol 14 (17) ◽  
pp. 24311-24348
Author(s):  
P. Schneider ◽  
W. A. Lahoz ◽  
R. van der A
Keyword(s):  
Nitrogen Dioxide ◽  
Linear Trend ◽  
Urban Agglomerations ◽  
Seasonal Model ◽  
Tropospheric No2 ◽  
Small Set ◽  
Scanning Imaging ◽  
Using Data ◽  
Increasing Trends ◽  
Absorption Spectrometer

Abstract. Trends in tropospheric nitrogen dioxide (NO2) concentrations over 66 large urban agglomerations worldwide have been computed using data from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument onboard the Envisat platform for the period August 2002 to March 2012. A seasonal model including a linear trend was fitted to the satellite-based time series over each site. The results indicate distinct spatial patterns in trends. While agglomerations in Europe, North America, and some locations in East Asia/Oceania show decreasing tropospheric NO2 levels on the order of −5 % yr−1, rapidly increasing levels of tropospheric NO2 are found for agglomerations in large parts of Asia, Africa, and South America. The site with the most rapidly increasing absolute levels of tropospheric NO2 was found to be Tianjin in China with a trend value of 3.04 (±0.47) × 1015 molecules cm−2 yr−1, whereas the site with the most rapidly increasing relative trend was Kabul in Afghanistan with 14.3 (±2.2) % yr−1. In total, 34 sites exhibited increasing trends of tropospheric NO2 throughout the study period, 24 of which were found to be statistically significant. A total of 32 sites showed decreasing levels of tropospheric NO2 during the study period, of which 20 sites did so at statistically significant magnitudes. Overall, going beyond the relatively small set of megacities investigated previously, this study provides the first consistent analysis of recent changes in tropospheric NO2 levels over most large urban agglomerations worldwide.

scholarly journals The semianalytical cloud retrieval algorithm for SCIAMACHY II. The application to MERIS and SCIAMACHY data

2006 ◽  
Vol 6 (12) ◽  
pp. 4129-4136 ◽  
Author(s):  
A. A. Kokhanovsky ◽  
W. von Hoyningen-Huene ◽  
V. V. Rozanov ◽  
S. Noël ◽  
K. Gerilowski ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Optical Thickness ◽  
Retrieval Algorithm ◽  
Imaging Spectrometer ◽  
Vicarious Calibration ◽  
Medium Resolution ◽  
Resolution Imaging ◽  
Cloud Optical Thickness ◽  
Scanning Imaging ◽  
Absorption Spectrometer

Abstract. The SemiAnalytical CloUd Retrieval Algorithm (SACURA) is applied to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. In particular, we derive simultaneously cloud optical thickness (COT) and cloud top height (CTH), using SCIAMACHY measurements in the visible (442 nm, COT) and in the oxygen A-band (755–775 nm, CTH). Some of the results obtained are compared with those derived from the Medium Resolution Imaging Spectrometer (MERIS), which has better spatial resolution and observes almost the same scene as SCIAMACHY. The same cloud algorithm is applied to both MERIS and SCIAMACHY data. In addition, we perform the vicarious calibration of SCIAMACHY at the wavelength 442 nm, using MERIS measurements at the same wavelength. Differences in the retrieved COT for the same cloud field obtained using MERIS and SCIAMACHY measurements are discussed.

scholarly journals A MAX-DOAS aerosol profile retrieval algorithm for high altitude measurements: application to measurements at Schneefernerhaus (UFS), Germany

2019 ◽  
Author(s):  
Zhuoru Wang ◽  
Ka Lok Chan ◽  
Klaus-Peter Heue ◽  
Adrian Doicu ◽  
Thomas Wagner ◽  
...  
Keyword(s):  
High Altitude ◽  
Environmental Research ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Scaling Factors ◽  
Total Uncertainty ◽  
Look Up Table ◽  
Sun Photometer ◽  
The Look ◽  
The Cost

Abstract. We present a new aerosol profile retrieval algorithm for Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements at high altitude sites. The study is based on the long-term measurement (February 2012 to February 2016) at the Environmental Research Station Schneefernerhaus (UFS), Germany, which is located near the summit of Zugspitze, at an altitude of 2,650 m. Due to the low signal to noise ratio, commonly used MAX-DOAS retrieval algorithms based on the optimal estimation method are not suitable for the retrieval of high altitude measurements. We developed a new retrieval algorithm using an O4 differential slant column density (DSCD) look-up table. The look-up table consists of simulated O4 DSCDs corresponding to numerous possible aerosol profiles. The sensitivities of O4 absorption to several parameters were investigated for the design and parameterization of the look-up table. In the retrieval, the simulated O4 DSCDs for each possible profile are derived by interpolating the look-up table to the observation geometries. The cost functions are calculated for each aerosol profile in the look-up table based on the simulated O4 DSCDs, the O4 DSCD observations as well as the measurement uncertainties. Valid profiles are selected from all the possible profiles according to the cost function, and the optimal solution is defined as the weighted mean of all valid profiles. A comprehensive error analysis is performed to better estimate the total uncertainty. Based on the assumption that the look-up table covers all the possible profiles under clear sky conditions, we determined a set of O4 DSCD scaling factors for different elevation angles and wavelengths. The dependence of the scaling factors on elevation angle might be partly related to the specific properties of the high altitude station, e.g. the highly structured topography, horizontal gradients of the aerosol extinction and the systematic dependence of the surface albedo on altitude. The retrieved aerosol optical depths (AODs) are compared to coincident and co-located sun photometer observations. High correlation coefficients of 0.733 and 0.798 are found for measurements at 360 and 477 nm, respectively. However, especially in summer the sun photometer AODs are systematically higher than the MAX-DOAS retrievals by a factor of 2. The discrepancy might be related to the limited measurement range of the MAX-DOAS, and is probably also related to the decreased sensitivity of the MAX-DOAS measurements at higher altitudes. Our results also show maximum AOD and maximum Ångström exponent in summer which is consistent with observations from an AERONET station located ~ 43 km of the MAX-DOAS.

Assessment of the look-up table using the tubular and bundle CHF data and modification of the bundle correction factor

Kerntechnik ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. 192-202
Author(s):  
D. K. Chandraker ◽  
P. K. Vijayan ◽  
D. Saha ◽  
R. K. Sinha
Keyword(s):  
Correction Factor ◽  
Look Up Table ◽  
The Look

scholarly journals Development of Multilayer-Based Map Matching to Enhance Performance in Large Truck Fleet Dispatching

2021 ◽  
Vol 10 (2) ◽  
pp. 79
Author(s):  
Ching-Yun Mu ◽  
Tien-Yin Chou ◽  
Thanh Van Hoang ◽  
Pin Kung ◽  
Yao-Min Fang ◽  
...  
Keyword(s):  
Data Structures ◽  
Spatial Data ◽  
Spatial Information ◽  
Data Retrieval ◽  
Spatial Data Mining ◽  
Map Matching ◽  
Matching Algorithm ◽  
Table Method ◽  
Look Up Table ◽  
The Look

Spatial information technology has been widely used for vehicles in general and for fleet management. Many studies have focused on improving vehicle positioning accuracy, although few studies have focused on efficiency improvements for managing large truck fleets in the context of the current complex network of roads. Therefore, this paper proposes a multilayer-based map matching algorithm with different spatial data structures to deal rapidly with large amounts of coordinate data. Using the dimension reduction technique, the geodesic coordinates can be transformed into plane coordinates. This study provides multiple layer grouping combinations to deal with complex road networks. We integrated these techniques and employed a puncture method to process the geometric computation with spatial data-mining approaches. We constructed a spatial division index and combined this with the puncture method, which improves the efficiency of the system and can enhance data retrieval efficiency for large truck fleet dispatching. This paper also used a multilayer-based map matching algorithm with raster data structures. Comparing the results revealed that the look-up table method offers the best outcome. The proposed multilayer-based map matching algorithm using the look-up table method is suited to obtaining competitive performance in identifying efficiency improvements for large truck fleet dispatching.

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