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  • 2020-2024  (74)
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  • 1
    Call number: AWI A11-22-94735
    Description / Table of Contents: Over the last decades, the rate of near-surface warming in the Arctic is at least double than elsewhere on our planet (Arctic amplification). However, the relative contribution of different feedback processes to Arctic amplification is a topic of ongoing research, including the role of aerosol and clouds. Lidar systems are well-suited for the investigation of aerosol and optically-thin clouds as they provide vertically-resolved information on fine temporal scales. Global aerosol models fail to converge on the sign of the Arctic aerosol radiative effect (ARE). In the first part of this work, the optical and microphysical properties of Arctic aerosol were characterized at case study level in order to assess the short-wave (SW) ARE. A long-range transport episode was first investigated. Geometrically similar aerosol layers were captured over three locations. Although the aerosol size distribution was different between Fram Strait(bi-modal) and Ny-Ålesund (fine mono-modal), the atmospheric column ARE was similar. The latter was related to the domination of accumulation mode aerosol. Over both locations top of the atmosphere (TOA) warming was accompanied by surface cooling. Subsequently, the sensitivity of ARE was investigated with respect to different aerosol and spring-time ambient conditions. A 10% change in the single-scattering albedo (SSA) induced higher ARE perturbations compared to a 30% change in the aerosol extinction coefficient. With respect to ambient conditions, the ARETOA was more sensitive to solar elevation changes compared to AREsur f ace. Over dark surfaces the ARE profile was exclusively negative, while over bright surfaces a negative to positive shift occurred above the aerosol layers. Consequently, the sign of ARE can be highly sensitive in spring since this season is characterized by transitional surface albedo conditions. As the inversion of the aerosol microphysics is an ill-posed problem, the inferred aerosol size distribution of a low-tropospheric event was compared to the in-situ measured distribution. Both techniques revealed a bi-modal distribution, with good agreement in the total volume concentration. However, in terms of SSA a disagreement was found, with the lidar inversion indicating highly scattering particles and the in-situ measurements pointing to absorbing particles. The discrepancies could stem from assumptions in the inversion (e.g. wavelength-independent refractive index) and errors in the conversion of the in-situ measured light attenuation into absorption. Another source of discrepancy might be related to an incomplete capture of fine particles in the in-situ sensors. The disagreement in the most critical parameter for the Arctic ARE necessitates further exploration in the frame of aerosol closure experiments. Care must be taken in ARE modelling studies, which may use either the in-situ or lidar-derived SSA as input. Reliable characterization of cirrus geometrical and optical properties is necessary for improving their radiative estimates. In this respect, the detection of sub-visible cirrus is of special importance. The total cloud radiative effect (CRE) can be negatively biased, should only the optically-thin and opaque cirrus contributions are considered. To this end, a cirrus retrieval scheme was developed aiming at increased sensitivity to thin clouds. The cirrus detection was based on the wavelet covariance transform (WCT) method, extended by dynamic thresholds. The dynamic WCT exhibited high sensitivity to faint and thin cirrus layers (less than 200 m) that were partly or completely undetected by the existing static method. The optical characterization scheme extended the Klett–Fernald retrieval by an iterative lidar ratio (LR) determination (constrained Klett). The iterative process was constrained by a reference value, which indicated the aerosol concentration beneath the cirrus cloud. Contrary to existing approaches, the aerosol-free assumption was not adopted, but the aerosol conditions were approximated by an initial guess. The inherent uncertainties of the constrained Klett were higher for optically-thinner cirrus, but an overall good agreement was found with two established retrievals. Additionally, existing approaches, which rely on aerosol-free assumptions, presented increased accuracy when the proposed reference value was adopted. The constrained Klett retrieved reliably the optical properties in all cirrus regimes, including upper sub-visible cirrus with COD down to 0.02. Cirrus is the only cloud type capable of inducing TOA cooling or heating at daytime. Over the Arctic, however, the properties and CRE of cirrus are under-explored. In the final part of this work, long-term cirrus geometrical and optical properties were investigated for the first time over an Arctic site (Ny-Ålesund). To this end, the newly developed retrieval scheme was employed. Cirrus layers over Ny-Ålesund seemed to be more absorbing in the visible spectral region compared to lower latitudes and comprise relatively more spherical ice particles. Such meridional differences could be related to discrepancies in absolute humidity and ice nucleation mechanisms. The COD tended to decline for less spherical and smaller ice particles probably due to reduced water vapor deposition on the particle surface. The cirrus optical properties presented weak dependence on ambient temperature and wind conditions. Over the 10 years of the analysis, no clear temporal trend was found and the seasonal cycle was not pronounced. However, winter cirrus appeared under colder conditions and stronger winds. Moreover, they were optically-thicker, less absorbing and consisted of relatively more spherical ice particles. A positive CREnet was primarily revealed for a broad range of representative cloud properties and ambient conditions. Only for high COD (above 10) and over tundra a negative CREnet was estimated, which did not hold true over snow/ice surfaces. Consequently, the COD in combination with the surface albedo seem to play the most critical role in determining the CRE sign over the high European Arctic.
    Type of Medium: Dissertations
    Pages: x, 136 Seiten , Illustrationen, Diagramme, Karten
    Language: English
    Note: Dissertation, Universität Potsdam, 2021 , CONTENTS 1 INTRODUCTION 1.1 Motivation: Aerosol and cloud relevance to Arctic amplification 1.2 Theoretical background 1.2.1 Atmospheric aerosol 1.2.2 Aerosol in the Arctic 1.2.3 Cirrus clouds 1.3 Research questions 2 METHODS 2.1 lidar remote sensing techniqu 2.1.1 Elastic and Raman lidar equations 2.1.2 lidar signal corrections 2.1.3 Derivation of particle optical properties and related uncertainties 2.2 Lidar systems 2.2.1 Ground-based system KARL 2.2.2 Air-borne system AMALi 2.2.3 Space-borne system CALIOP 2.3 Ancillary instrumentation 2.3.1 Radiosondes 2.3.2 Sun-photometers 2.3.3 Radiation sensors 2.4 Modeling tools 2.4.1 Air mass backward trajectories 2.4.2 Aerosol microphysics retrieval algorithm 2.4.3 Radiative transfer model SCIATRAN 2.4.4 Multiple-scattering correction model 2.4.5 Simplified cloud radiative effect model 3 ARCTIC AEROSOL PROPERTIES AND RADIATIVE EFFECT (CASE STUDIES) 3.1 Aerosol in the upper troposphere (Spring) 3.1.1 Overview of aerosol observations and air mass origin 3.1.2 Modification of aerosol optical and microphysical properties 3.1.3 Aerosol radiative effect (ARE) 3.2 Sensitivities of the spring-time Arctic ARE 3.2.1 Sensitivity on aerosol related parameters 3.2.2 Sensitivity on ambient conditions 3.3 Aerosol in the lower troposphere (Winter) 3.3.1 Overview of remote sensing and in-situ measurements 3.3.2 Aerosol properties from the remote sensing perspective: KARL and CALIOP 3.3.3 Aerosol microphysical properties from in-situ and remote sensing perspectives 3.4 Discussion and Conclusions 4 DEVELOPMENT OF A CIRRUS CLOUD RETRIEVAL SCHEME 4.1 Fine-scale cirrus cloud detection 4.1.1 Selection of cirrus clouds 4.1.2 Wavelet Covariance Transform method 4.1.3 Revised detection method: Dynamic Wavelet Covariance Transform 4.2 Comparison of dynamic and static cirrus detection 4.3 Cirrus cloud optical retrievals 4.3.1 Existing cirrus optical retrievals: double-ended Klett and Raman 4.3.2 Temporal averaging within stationary periods 4.3.3 Revised optical retrieval: constrained Klett method 4.4 Comparison to established optical retrievals 4.5 How uncertainties in cirrus detection affect the optical retrievals? 4.6 Discussion 4.6.1 Limitations of cirrus retrieval schemes 4.6.2 Strengths of the revised retrieval scheme 4.7 Conclusions 5 LONG-TERM ANALYSIS OF ARCTIC CIRRUS CLOUD PROPERTIES 5.1 Overview of cirrus occurrence and meteorological conditions over Ny-Ålesund 5.2 Quality assurance of optical properties 5.2.1 Specular reflection effect 5.2.2 Investigation of extreme cirrus lidar ratio values 5.2.3 Multiple-scattering correction 5.3 Overview of cirrus optical properties over Ny-Ålesund 5.4 Inter-relations of cirrus properties 5.5 Dependence on meteorological conditions 5.5.1 Cirrus clouds in the tropopause 5.6 CRE estimation at TOA: sensitivity analysis 5.7 Conclusions 6 CONCLUSIONS AND OUTLOOK A CIRRUS DETECTION SENSITIVITIES a.1 Wavelet Covariance Transform - dilation sensitivity a.2 Wavelet Covariance Transform - wavelength dependency B CIRRUS OPTICAL CHARACTERIZATION SENSITIVITIES b.1 Reference value accuracy and limitations b.2 Inherent uncertainties of constrained Klett C MULTIPLE-SCATTERING CORRECTION FOR CIRRUS CLOUDS D SEASONAL CIRRUS PROPERTIES: DESCRIPTIVE STATISTICS BIBLIOGRAPHY
    Location: AWI Reading room
    Branch Library: AWI Library
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  • 2
    Publication Date: 2024-04-20
    Description: During the ACLOUD aircraft campaign (23.5.2017 - 26.6.2017) the AMALi Lidar was installed mostly nadir pointing. This dataset contains the cloud top altitude from those measurements (altitudes with a strong signal increase) as well as a cloud mask, derived from the optical depth of the column at 1 second resolution. The majority of the data was collected northwest of the Svalbard archipelago. More details on the campaign can be found in Wendisch 2018 and Ehrlich 2019 and here (https://home.uni-leipzig.de/~ehrlich/ACLOUD_wiki_doku). Please check the data documentation (https://download.pangaea.de/reference/108729/attachments/readme_documentation_AMALi_cloudtop.pdf) before using this dataset.
    Keywords: AC; AC3; ACLOUD; airborne; airborne lidar; airborne measurements; Airborne Mobile Aerosol Lidar; aircraft; Aircraft; AMALi; Arctic; Arctic Amplification; Binary Object; Binary Object (File Size); cloud; cloud top altitude; Date/Time of event; Event label; Latitude of event; Lidar; Longitude of event; mixed-phase clouds; P5_206_ACLOUD_2017; P5_206_ACLOUD_2017_1705230601; P5_206_ACLOUD_2017_1705250701; P5_206_ACLOUD_2017_1705270801; P5_206_ACLOUD_2017_1705270902; P5_206_ACLOUD_2017_1705291001; P5_206_ACLOUD_2017_1706021201; P5_206_ACLOUD_2017_1706051301; P5_206_ACLOUD_2017_1706081401; P5_206_ACLOUD_2017_1706131601; P5_206_ACLOUD_2017_1706141701; P5_206_ACLOUD_2017_1706161801; P5_206_ACLOUD_2017_1706182001; P5_206_ACLOUD_2017_1706202101; P5_206_ACLOUD_2017_1706252301; Polar 5; POLAR 5; RF04; RF05; RF06; RF07; RF08; RF11; RF13; RF14; RF16; RF17; RF18; RF20; RF21; RF23; Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 14 data points
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  • 3
    Publication Date: 2024-04-20
    Description: The star photometer at AWIPEV is a permanent installation and fills the measurement gap of the sun photometer during polar night by using the brightness of defined stars. The instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument. To minimize measuring errors bright and, as a local advantage, circumpolar stars are chosen for photometry. The three stars gamma Gem, beta UMa and alpha Lyr are used for both types of measurement. The star alpha Aql has only been used for two star measurement yet. The measuring principle of a star photometer is the same as for the sun. There are two different possibilities to determine the AOD (aerosol optical depth) using a star photometer. One star measurement requires a calibration at very clear nights, just like Langley calibration for sun photometers. For the two star measurement a calibration is not needed in advance. But on the other hand the second method is much more effective by atmospheric inhomogeneities and horizontally stratified layers. In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the star photometer at AWIPEV for the time 10 Nov. 2010 to 21. Feb 2021. The variables are in netcdf format for each measurement day. The used instrument for the entire measurment period was star04.
    Keywords: Angstrom-Exponent; AOD; AWI_Meteo; AWIPEV; AWIPEV_based; Binary Object; Binary Object (File Size); Binary Object (Media Type); DATE/TIME; KOL03; Koldewey; Meteorological Long-Term Observations @ AWI; Ny-Ålesund; Photometer; remote sensing; Research station; RS; Spitsbergen, Svalbard; Star photometer star04; Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 350 data points
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  • 4
    Publication Date: 2024-04-20
    Description: In this data set the raw data of the data set doi:10.1594/PANGAEA.937183 are given for the star photometer at AWIPEV for the time 10 Nov. 2010 to 21. Feb 2021. The data is provided in one tar.gz-file. The variables are then in netcdf format for each measurement day. The used star photometer was star04 for the entire measurment period.
    Keywords: Arctic; Arctic aerosol; AWIPEV; AWIPEV_based; Koldewey; Ny-Ålesund; Photometer; remote sensing; Research station; RS; Spitsbergen, Svalbard; Star Photometer; Svalbard
    Type: Dataset
    Format: application/gzip, 2 MBytes
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  • 5
    Publication Date: 2024-04-20
    Description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions. The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument. In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at AWIPEV for the time 19. March 2012 until 30. September 2012. The variables are in netcdf format for each measurement day.
    Keywords: Angstrom Parameter; AOD; AWIPEV; AWIPEV_based; Binary Object; Binary Object (File Size); Binary Object (Media Type); DATE/TIME; KOL03; Koldewey; Ny-Ålesund; Research station; RS; Spitsbergen, Svalbard; Sun photometer; Sun photometer, SP1a (Dr. Schulz & Partner GmbH); Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 196 data points
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  • 6
    Publication Date: 2024-04-20
    Description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions. The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument. In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at AWIPEV for the time 21. March 2013 until 30. September 2013. The variables are in netcdf format for each measurement day.
    Keywords: Angstrom Parameter; AOD; AWIPEV; AWIPEV_based; Binary Object; Binary Object (File Size); Binary Object (Media Type); DATE/TIME; KOL03; Koldewey; Ny-Ålesund; remote sensing; Research station; RS; Spitsbergen, Svalbard; Sun photometer; Sun photometer, SP1a (Dr. Schulz & Partner GmbH); Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 194 data points
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  • 7
    Publication Date: 2024-04-20
    Description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions. The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument. In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at AWIPEV for the time 10. March 2015 until 30. September 2015. The variables are in netcdf format for each measurement day. The used instrument for the measurement period was SP1A33.
    Keywords: Angstrom Parameter; AOD; Arctic; Arctic aerosol; AWIPEV; AWIPEV_based; Binary Object; Binary Object (File Size); Binary Object (Media Type); DATE/TIME; KOL03; Koldewey; Ny-Ålesund; Research station; RS; Spitsbergen, Svalbard; Sun photometer; Sun photometer, SP1a (Dr. Schulz & Partner GmbH); Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 205 data points
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  • 8
    Publication Date: 2024-04-20
    Description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions. The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument. In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at AWIPEV for the time 19. March 2014 until 30. September 2014. The variables are in netcdf format for each measurement day. The used instrument for the measurement period was SP1A33.
    Keywords: Angstrom Parameter; AOD; Arctic; Arctic aerosol; AWIPEV; AWIPEV_based; Binary Object; Binary Object (File Size); Binary Object (Media Type); DATE/TIME; KOL03; Koldewey; Ny-Ålesund; Research station; RS; Spitsbergen, Svalbard; Sun photometer; Sun photometer, SP1a (Dr. Schulz & Partner GmbH); Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 159 data points
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  • 9
    Publication Date: 2024-04-20
    Description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions. The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument. In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at AWIPEV for the time 8. March 2016 until 30. September 2016. The variables are in netcdf format for each measurement day. The used instrument for the measurement period was SP1A31.
    Keywords: Angstrom Parameter; AOD; Arctic; Arctic aerosol; AWIPEV; AWIPEV_based; Binary Object; Binary Object (File Size); Binary Object (Media Type); DATE/TIME; KOL03; Koldewey; Ny-Ålesund; Research station; RS; Spitsbergen, Svalbard; Sun photometer; Sun photometer, SP1a (Dr. Schulz & Partner GmbH); Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 207 data points
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  • 10
    Publication Date: 2024-04-20
    Description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions. The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument. In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at AWIPEV for the time 18. March 2017 until 30. September 2017. The variables are in netcdf format for each measurement day. The used instrument for the measurement period was SP1A31.
    Keywords: Angstrom Parameter; AOD; AWIPEV; AWIPEV_based; Binary Object; Binary Object (File Size); Binary Object (Media Type); DATE/TIME; KOL03; Koldewey; Ny-Ålesund; Research station; RS; Spitsbergen, Svalbard; Sun photometer; Sun photometer, SP1a (Dr. Schulz & Partner GmbH); Svalbard
    Type: Dataset
    Format: text/tab-separated-values, 197 data points
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