ALBERT

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.

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.

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.

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 20. March 2019 until 30. September 2019. The variables are in netcdf format for each measurement day. The used instrument for the measurement period was SP1A31.

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 27. March 2020 until 30. September 2020. The variables are in netcdf format for each measurement day. The used instrument for the measurment period was SP1A33.

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 2018 until 30. September 2018. The variables are in netcdf format for each measurement day. The used instrument for the measurment period was SP1A31.

Description: Although several methods exist for the determination of the flux of an atmospheric species, the airborne eddy correlation method has the advantage of providing direct flux measurements that are representative of regional spatial domains. The design criteria pertinent to the construction of chemical instrumentation suitable for use in airborne eddy correlation flux measurements are discussed. A brief overview of the advantages and limitations of the current instrumentation used to obtain flux measurements for CO, CH4, O3, CO2, and water vapor are given. The intended height of the measurement within the convective boundary layer is also shown to be an important design criteria. The sensitivity, or resolution, which is required in the measurement of a scalar species to obtain an adequate species flux measurement is discussed. The relationship between the species flux resolution and the more commonly stated instrumental resolution is developed and it is shown that the standard error of the flux estimate is a complicated function of the atmospheric variability and the averaging time that is used. The use of the recently proposed intermittent sampling method to determine the species flux is examined. The application of this technique may provide an opportunity to expand the suite of trace gases for which direct flux measurements are possible.

Description: Some of the design problems that are now being addressed in consideration of a microcontroller for the upcoming GAS payload are discussed. Microcontrollers will be used to run the experiments and to collect and store the data from those experiments. Some of the requirements for a microcontroller are to be small, lightweight, have low power consumption, and high reliability. Some of the solutions that were developed to meet these design requirements are discussed. At present, the experiment is still in the design stage and the final design may change from what is presented here. The search for new integrated circuits which will do all that is needed all in one package continues.

Description: The development of the fast-response ozone detector for the Electra aircraft is described. The selection of a technique to meet the design goal of 10-Hz detection is examined in terms of detection principles, instrument sampling parameters, signal conditioning, and aircraft and sampling environment. An instrument which employs a NO technique for detection of ozone with a reaction chamber volume of 16 cu cm, a pressure of 60 torr, and a sample flow of 1000 standard cu cm/min was developed. Laboratory and flight testings of the detector were conducted in order to evaluate its performance. The data reveal that the fast-response ozone detector is highly reliable with a response of 0.1 sec to 90 percent of reading, has a lower detection limit of 1 ppbv, and an S/N of 20 at 20 ppbv ozone.

Description: Image data is a critical component of the scientific information acquired by space missions. Compression of image data is required due to the limited bandwidth of the data transmission channel and limited memory space on the acquisition vehicle. This need becomes more pressing when dealing with multispectral data where each pixel may comprise 300 or more bytes. An autonomous, real time, on-board image analysis system for an exploratory vehicle such as a Mars Rover is developed. The completed system will be capable of interpreting image data to produce reduced representations of the image, and of making decisions regarding the importance of data based on current scientific goals. Data from multiple sources, including stereo images, color images, and multispectral data, are fused into single image representations. Analysis techniques emphasize artificial neural networks. Clusters are described by their outlines and class values. These analysis and compression techniques are coupled with decision-making capacity for determining importance of each image region. Areas determined to be noise or uninteresting can be discarded in favor of more important areas. Thus limited resources for data storage and transmission are allocated to the most significant images.