scholarly journals Satellite Observed Aerosol Optical Thickness and Trend around Megacities in the Coastal Zone

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Xuepeng Zhao
Keyword(s):  
Optical Thickness ◽  
Seasonal Variations ◽  
Confidence Level ◽  
Aerosol Optical Thickness ◽  
Positive Trend ◽  
Air Pollution Control ◽  
Industrialized Countries ◽  
Climate Data ◽  
Climate Data Record ◽  
Very High

Nearly 30-year aerosol optical thickness (AOT) climate data record (CDR) derived from the operational satellite observations of National Ocean and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) is used to study the AOT trends over seventeen megacities in the coast zone (MCCZ). Linear trends are derived from monthly and seasonal mean AOT in the past three decades and used in the analysis. The results indicate the following: (1) AOT around a MCCZ in fast developing countries has relatively high value and a positive trend with a confidence level generally above 95%; (2) AOT around a MCCZ in industrialized countries has relatively low value and a negative trend with a confidence level generally above 95%; (3) AOT values and their trends show distinct seasonal variations in MCCZ, which can be explained somewhat by the seasonal variations of meteorological conditions. AOT trend is an effective index for examining the efficacy of air pollution control policies implemented for these megacities.

scholarly journals The Impact of COVID-19 Lockdowns on Satellite-Observed Aerosol Optical Thickness over the Surrounding Coastal Oceanic Areas of Megacities in the Coastal Zone

Geographies ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 381-397
Author(s):  
Kai Wang ◽  
Xuepeng Zhao
Keyword(s):  
Optical Thickness ◽  
Satellite Observation ◽  
Dust Storms ◽  
Aerosol Optical Thickness ◽  
Climate Data ◽  
Aerosol Emission ◽  
The Impact ◽  
Climate Data Record ◽  
Global Oceans

Nearly 40 years of aerosol optical thickness (AOT) climate data record (CDR) derived from NOAA operational satellite Advanced Very High Resolution Radiometer (AVHRR) observation over the global oceans is used to study the AOT changes due to the COVID-19 lockdown over the surrounding coastal oceanic areas of 18 megacities in the coast zone (MCCZ). The AOT difference between the annual mean AOT values of 2020 with COVID-19 lockdown and 2019 without the lockdown along with the 2020 AOT annual anomaly are used to effectively identify the AOT changes that are a result of the lockdown. We found that for most of the 18 MCCZ, the COVID-19 lockdowns implemented to contain the spread of the coronavirus resulted in a decrease between 1% and 30% in AOT due to reduced anthropogenic emissions associated with the lockdowns. However, the AOT long-term trend and other aerosol interannual variations due to favorable or unfavorable meteorological conditions may mask AOT changes due to the lockdown effect in some MCCZ. Different seasonal variations of aerosol amount in 2020 relative to 2019 due to other natural aerosol emission sources not influenced by the lockdown, such as dust storms and natural biomass burning and smoke, may also conceal a limited reduction in the annual mean AOT due to the lockdown in MCCZ with relatively loose lockdown. This study indicates that the use of long-term satellite observation is helpful for studying and monitoring the aerosol changes due to the emission reduction associated with the COVID-19 lockdown in the surrounding coastal oceanic areas of MCCZ, which will benefit the future development of the mitigation strategy for air pollution and emissions in megacities.

scholarly journals A 40-year global dataset of visible channel remote sensing reflectances and coccolithophore bloom occurrence derived from the Advanced Very High Resolution Radiometer catalogue

2018 ◽  
Author(s):  
Benjamin R. Loveday ◽  
Timothy Smyth
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Atmospheric Correction ◽  
Global Ocean ◽  
Climate Data ◽  
Ancillary Data ◽  
Remote Sensing Reflectance ◽  
Data Files ◽  
Climate Data Record ◽  
Very High

Abstract. A consistently calibrated 40-year length dataset of visible channel remote sensing reflectance has been derived from the Advanced Very High Resolution Radiometer (AVHRR) sensor global time-series. The dataset uses as its source the Pathfinder Atmospheres – Extended (PATMOS-x) v5.3 Climate Data Record (CDR) for top-of-atmosphere (TOA) visible channel reflectances. This paper describes the theoretical basis for the atmospheric correction procedure and its subsequent implementation, including the necessary ancillary data files used and quality flags applied, in order to determine remote sensing reflectance. The resulting dataset is produced at daily, and archived at monthly, resolution, on a 0.1° × 0.1° grid at https://doi.pangaea.de/10.1594/PANGAEA.892175. The primary aim of deriving this dataset is to highlight regions of the global ocean affected by highly reflective blooms of the coccolithophorid Emiliania Huxleyi over the past 40 years.

scholarly journals Aerosol seasonal variations over urban sites in Ukraine and Belarus according to AERONET and POLDER measurements

2013 ◽  
Vol 6 (6) ◽  
pp. 10731-10759 ◽  
Author(s):  
G. Milinevsky ◽  
V. Danylevsky ◽  
V. Bovchaliuk ◽  
A. Bovchaliuk ◽  
Ph. Goloub ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Seasonal Variations ◽  
Urban Areas ◽  
Late Summer ◽  
Single Scattering ◽  
Aerosol Optical Thickness ◽  
Saharan Dust ◽  
Coarse Mode ◽  
Modal Radius ◽  
Urban Sites

Abstract. The paper presents an investigation of aerosol seasonal variations in several urban sites in the East European region. Our analysis of seasonal variations of optical and physical aerosol parameters is based on the sun-photometer 2008–2012 data from three urban ground-based AERONET sites in Ukraine (Kyiv, Kyiv-AO, and Lugansk) and one site in Belarus (Minsk), as well as on satellite POLDER instrument data for urban areas in Ukraine. Aerosol amount and optical thickness values exhibit peaks in the spring (April–May) and late summer (August), whereas minimum values are seen in late autumn over the Kyiv and Minsk sites. The results show that aerosol fine mode particles are most frequently detected during the spring and late summer seasons. The seasonal variation similarity in the two regions points to the resemblance in basic aerosol sources which are closely related to properties of aerosol particles. However the aerosol amount and properties change noticeably from year to year and from region to region. The analysis of seasonal aerosol optical thickness variations over the urban sites in the eastern and western parts of Ukraine according to both ground-based and POLDER data exhibits the same traits. In particular, over Kyiv, the values of the Angstrom exponent are lower in April of 2011 than in 2009 and 2010, while aerosol optical thickness values are almost the same, which can be explained by an increase in the amount of coarse mode particles in the atmosphere, such as Saharan dust. Moreover, the coarse mode particles prevailed over suburbs and the center of Kyiv during a third of all available days of observation in 2012. In general, the fine and coarse mode particles' modal radii averaged over 2008–2012 range from 0.1 to 0.2 μm and 2 to 5 μm, respectively, during the period from April to September. The single scattering albedo and refractive index values of these particles correspond to a mix of urban-industrial, biomass burning, and dust aerosols. In addition, strongly absorbing particles were observed in the period from October to March, and the modal radius of fine and coarse mode particles changed from month to month widely.

scholarly journals Detailed characterisation of AVHRR global cloud detection performance of the CM SAF CLARA-A2 climate data record based on CALIPSO-CALIOP cloud information

2017 ◽  
Author(s):  
Karl-Göran Karlsson ◽  
Nina Håkansson
Keyword(s):  
Optical Thickness ◽  
Detection Performance ◽  
Polar Regions ◽  
Cloud Detection ◽  
Climate Data ◽  
Data Record ◽  
Cloud Optical Thickness ◽  
Land Surfaces ◽  
Cloud Mask ◽  
Climate Data Record

Abstract. The cloud detection performance of the cloud mask being used in the CM SAF cloud, albedo and surface radiation dataset from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated in detail using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. Validation results, including their global distribution, have been calculated from collocations of AVHRR and CALIOP measurements over a ten-year period (2006–2015). The sensitivity of the results to the cloud optical thicknesses of CALIOP-observed clouds were studied leading to the conclusion that the global cloud detection sensitivity (defined as the minimum cloud optical thickness for which 50 % of clouds could be detected) was estimated to 0.225. After applying this optical thickness threshold to the CALIOP cloud mask, results were found to be basically unbiased over most of the globe except over the polar regions where a considerably underestimation of cloudiness could be seen during the polar winter. The probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest portions of Greenland and Antarctica, showing that also a large fraction of optically thick clouds remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud’s geographical position. Best results were achieved over oceanic surfaces at mid-to-high latitudes were at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 over the geographically highest parts of Greenland and Antarctica. The validation method is suggested to be applied also to other satellite-based CDRs and validation results are proposed to be used in Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulation Package (COSP) simulators for cloud detection characterisation of various cloud CDRs from passive imagery.

scholarly journals Probabilistic Cloud Masking for the Generation of CM SAF Cloud Climate Data Records from AVHRR and SEVIRI Sensors

2020 ◽  
Vol 12 (4) ◽  
pp. 713
Author(s):  
Karl-Göran Karlsson ◽  
Erik Johansson ◽  
Nina Håkansson ◽  
Joseph Sedlar ◽  
Salomon Eliasson
Keyword(s):  
Skill Score ◽  
Surface Radiation ◽  
Orthogonal Polarization ◽  
Climate Data ◽  
Infrared Imager ◽  
Avhrr Data ◽  
Cloud Optical Thickness ◽  
Climate Data Record ◽  
Cloud Screening ◽  
Very High

Cloud screening in satellite imagery is essential for enabling retrievals of atmospheric and surface properties. For climate data record (CDR) generation, cloud screening must be balanced, so both false cloud-free and false cloudy retrievals are minimized. Many methods used in recent CDRs show signs of clear-conservative cloud screening leading to overestimated cloudiness. This study presents a new cloud screening approach for Advanced Very-High-Resolution Radiometer (AVHRR) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) imagery based on the Bayesian discrimination theory. The method is trained on high-quality cloud observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The method delivers results designed for optimally balanced cloud screening expressed as cloud probabilities together with information on for which clouds (minimum cloud optical thickness) the probabilities are valid. Cloud screening characteristics over 28 different Earth surface categories were estimated. Using independent CALIOP observations (including all observed clouds) in 2010 for validation, the total global hit rates for AVHRR data and the SEVIRI full disk were 82% and 85%, respectively. High-latitude oceans had the best performance, with a hit rate of approximately 93%. The results were compared to the CM SAF cLoud, Albedo, and surface RAdiation dataset from AVHRR data–second edition (CLARA-A2) CDR and showed general improvements over most global regions. Notably, the Kuipers’ Skill Score improved, verifying a more balanced cloud screening. The new method will be used to prepare the new CLARA-A3 and CLAAS-3 (CLoud property dAtAset using SEVIRI, Edition 3) CDRs in the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project.

Regional advanced very high resolution radiometer–derived climatology of aerosol optical thickness and size

2005 ◽  
Vol 110 (D23) ◽  
Author(s):  
Igor V. Geogdzhayev ◽  
Michael I. Mishchenko ◽  
Edward I. Terez ◽  
Galina A. Terez ◽  
Genady K. Gushchin
Keyword(s):  
High Resolution ◽  
Optical Thickness ◽  
Aerosol Optical Thickness ◽  
Very High

scholarly journals A long-term record of blended satellite and in situ sea surface temperature for climate monitoring, modeling and environmental studies

2016 ◽  
Author(s):  
V. Banzon ◽  
T. M. Smith ◽  
C. Liu ◽  
W. Hankins
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Sea Surface ◽  
Climate Data ◽  
Volcanic Aerosols ◽  
Climate Data Record ◽  
Very High

Abstract. This paper describes a blended sea-surface temperature (SST) dataset that is part of the National Oceanic and Atmospheric Administration (NOAA) Climate Data Record (CDR) Program product suite. Using optimum interpolation (OI), in situ and satellite observations are combined on a daily and 0.25° spatial grid to form an SST analysis, i.e., a spatially complete field. A large-scale bias adjustment of the input infrared SSTs is made using buoy and ship observations as a reference. This is particularly important for the time periods when volcanic aerosols from the El Chichon and Mt. Pinatubo eruptions are widespread globally. The main source of SSTs is the Advanced Very High Resolution Radiometer (AVHRR), available from late 1981 to the present, which is also the temporal span of this CDR. The input and processing choices made to ensure a consistent dataset that meets the CDR requirements is summarized. A brief history and an explanation of the forward production schedule for the preliminary and science-quality final product is also provided. The dataset is produced and archived at the newly formed National Centers for Environmental Information (NCEI) in Network Common Data Form (netCDF) at http://doi.org/doi:10.7289/V5SQ8XB5 .

scholarly journals Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record

2018 ◽  
Vol 11 (1) ◽  
pp. 633-649 ◽  
Author(s):  
Karl-Göran Karlsson ◽  
Nina Håkansson
Keyword(s):  
Optical Thickness ◽  
Detection Sensitivity ◽  
Polar Regions ◽  
Cloud Detection ◽  
Climate Data ◽  
Data Record ◽  
Cloud Optical Thickness ◽  
Land Surfaces ◽  
Climate Data Record

Abstract. The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006–2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50 % of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid- to high latitudes where at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts with the highest altitudes over Greenland and Antarctica. It is suggested to quantify the detection performance of other CDRs in terms of a sensitivity threshold of cloud optical thickness, which can be estimated using active lidar observations. Validation results are proposed to be used in Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulation Package (COSP) simulators for cloud detection characterization of various cloud CDRs from passive imagery.

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