Spatial and temporal variability of snowfall over Greenland from CloudSat observations

We use the CloudSat 2006&ndash;2016 data record to estimate snowfall over the Greenland Ice Sheet (GrIS). We first evaluate CloudSat snowfall retrievals with respect to remaining ground-clutter issues. Comparing CloudSat observations to the GrIS topography (obtained from airborne altimetry measurements during IceBridge) we find that at the edges of the GrIS spurious high-snowfall retrievals caused by ground clutter occasionally affect the operational snowfall product. After correcting for this effect, the height of the lowest valid CloudSat observation is about 1200&thinsp;m above the local topography as defined by IceBridge. We then use ground-based millimeter wavelength cloud radar (MMCR) observations obtained from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit, Greenland (ICECAPS) experiment to devise a simple, empirical correction to account for precipitation processes occurring between the height of the observed CloudSat reflectivities and the snowfall near the surface. Using the height-corrected, clutter-cleared CloudSat reflectivities we next evaluate various Z&ndash;S relationships in terms of snowfall accumulation at Summit through comparison with weekly stake field observations of snow accumulation available since 2007. Using a set of three Z&ndash;S relationships that best agree with the observed accumulation at Summit, we then calculate the annual cycle snowfall over the entire GrIS as well as over different drainage areas and compare the derived mean values and annual cycles of snowfall to ERA-Interim reanalysis. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34&plusmn;7.5&thinsp;cm&thinsp;yr&minus;1 liquid equivalent (where the uncertainty is determined by the range in values between the three different Z&ndash;S relationships used). In comparison, the ERA-Interim reanalysis product only yields 30&thinsp;cm&thinsp;yr&minus;1 liquid equivalent snowfall, where the majority of the underestimation in the reanalysis appears to occur in the summer months over the higher GrIS and appears to be related to shallow precipitation events. Comparing all available estimates of snowfall accumulation at Summit Station, we find the annually averaged liquid equivalent snowfall from the stake field to be between 20 and 24&thinsp;cm&thinsp;yr&minus;1, depending on the assumed snowpack density and from CloudSat 23&plusmn;4.5&thinsp;cm&thinsp;yr&minus;1. The annual cycle at Summit is generally similar between all data sources, with the exception of ERA-Interim reanalysis, which shows the aforementioned underestimation during summer months. </div

Validation of first chemistry mode retrieval results from the new limb-imaging FTS GLORIA with correlative MIPAS-STR observations

We report first chemistry mode retrieval results from the new airborne limb-imaging infrared FTS (Fourier transform spectrometer) GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) and comparisons with observations by the conventional airborne limb-scanning infrared FTS MIPAS-STR (Michelson Interferometer for Passive Atmospheric Sounding – STRatospheric aircraft). For GLORIA, the flights aboard the high-altitude research aircraft M55 Geophysica during the ESSenCe campaign (ESa Sounder Campaign 2011) were the very first in field deployment after several years of development. The simultaneous observations of GLORIA and MIPAS-STR during the flight on 16 December 2011 inside the polar vortex and under conditions of optically partially transparent polar stratospheric clouds (PSCs) provided us the first opportunity to compare the observations by two different infrared FTS generations directly. We validate the GLORIA results with MIPAS-STR based on the lower vertical resolution of MIPAS-STR and compare the vertical resolutions of the instruments derived from their averaging kernels. The retrieval results of temperature, HNO3, O3, H2O, CFC-11 and CFC-12 show reasonable agreement of GLORIA with MIPAS-STR and collocated in situ observations. For the horizontally binned hyperspectral limb images, the GLORIA sampling outnumbered the horizontal cross-track sampling of MIPAS-STR by up to 1 order of magnitude. Depending on the target parameter, typical vertical resolutions of 0.5 to 2.0 km were obtained for GLORIA and are typically a factor of 2 to 4 better compared to MIPAS-STR. While the improvement of the performance, characterization and data processing of GLORIA are the subject of ongoing work, the presented first results already demonstrate the considerable gain in sampling and vertical resolution achieved with GLORIA

Validation of first chemistry mode retrieval results from new limb-imaging FTS GLORIA with correlative MIPAS-STR observations

We report first chemistry mode retrieval results from the new airborne limb-imaging infrared FTS (Fourier transform spectrometer) GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) and comparisons with observations by the conventional airborne limb-scanning infrared FTS MIPAS-STR (Michelson Interferometer for Passive Atmospheric Sounding - STRatospheric aircraft). For GLORIA, the flights aboard the high-altitude research aircraft M55 Geophysica during the ESSenCe campaign (ESa Sounder Campaign 2011) were the very first in field deployment after several years of development. The simultaneous observations of GLORIA and MIPAS-STR during the flight on 16 December 2011 inside the polar vortex and under conditions of optically partially transparent polar stratospheric clouds (PSCs) provided us the first opportunity to compare the observations by two different infrared FTS generations directly. We validate the GLORIA results with MIPAS-STR based on the lower vertical resolution of MIPAS-STR and compare the vertical resolutions of the instruments derived from their averaging kernels. The retrieval results of temperature, HNO3, O3, H2O, CFC-11 and CFC-12 show reasonable agreement of GLORIA with MIPAS-STR and collocated in situ observations. For the horizontally binned hyperspectral limb images, the GLORIA sampling outnumbered the horizontal cross-track sampling of MIPAS-STR by up to 1 order of magnitude. Depending on the target parameter, typical vertical resolutions of 0.5 to 2.0 km were obtained for GLORIA and are typically a factor of 2 to 4 better compared to MIPAS-STR. While the improvement of the performance, characterization and data processing of GLORIA are the subject of ongoing work, the presented first results already demonstrate the considerable gain in sampling and vertical resolution achieved with GLORIA

Validation of first chemistry mode retrieval results from new limb-imaging FTS GLORIA with correlative MIPAS-STR observations

We report first chemistry mode retrieval results from the new airborne limb-imaging infrared FTS (Fourier transform spectrometer) GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) and comparisons with observations by the conventional airborne limb-scanning infrared FTS MIPAS-STR (Michelson Interferometer for Passive Atmospheric Sounding - STRatospheric aircraft). For GLORIA, the flights aboard the high-altitude research aircraft M55 Geophysica during the ESSenCe campaign (ESa Sounder Campaign 2011) were the very first in field deployment after several years of development. The simultaneous observations of GLORIA and MIPAS-STR during the flight on 16 December 2011 inside the polar vortex and under conditions of optically partially transparent polar stratospheric clouds (PSCs) provided us the first opportunity to compare the observations by two different infrared FTS generations directly. We validate the GLORIA results with MIPAS-STR based on the lower vertical resolution of MIPAS-STR and compare the vertical resolutions of the instruments derived from their averaging kernels. The retrieval results of temperature, HNO3, O3, H2O, CFC-11 and CFC-12 show reasonable agreement of GLORIA with MIPAS-STR and collocated in situ observations. For the horizontally binned hyperspectral limb images, the GLORIA sampling outnumbered the horizontal cross-track sampling of MIPAS-STR by up to 1 order of magnitude. Depending on the target parameter, typical vertical resolutions of 0.5 to 2.0 km were obtained for GLORIA and are typically a factor of 2 to 4 better compared to MIPAS-STR. While the improvement of the performance, characterization and data processing of GLORIA are the subject of ongoing work, the presented first results already demonstrate the considerable gain in sampling and vertical resolution achieved with GLORIA

GARRLiC and LIRIC: strengths and limitations for the characterization of dust and marine particles along with their mixtures

The Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marine-dominated and dust–marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements.The research leading to these results has received funding from the European Union’s Horizon 2020 Research and Innovation Programme ACTRIS-2 (grant agreement no. 654109). The work has been developed under the auspices of the ESA-ESTEC project “Characterization of Aerosol mixtures of Dust And Marine origin” contract no. IPL-PSO/FF/lf/14.489. The work was also supported by the European Research Council under the European Community’s Horizon 2020 research and innovation framework programme/ERC grant agreement 725698 (D-TECT). The publication was supported by the European Union’s Horizon 2020 Research and Innovation programme under grant agreement no. 602014, project ECARS (East European Centre for Atmospheric Remote Sensing). The authors acknowledge support through the Stavros Niarchos Foundation. BSC-DREAM8b simulations were performed on the Mare Nostrum supercomputer hosted by the Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC).Peer ReviewedPostprint (published version

Coincident in situ and triple-frequency radar airborne observations in the Arctic

The dataset collected during the Radar Snow Experiment (RadSnowExp) presents the first-ever airborne triple-frequency radar observations combined with almost perfectly co-located and coincident airborne microphysical measurements from a single platform, the National Research Council Canada (NRC) Convair-580 aircraft. The potential of this dataset is illustrated using data collected from one flight during an Arctic storm, which covers a wide range of snow habits from pristine ice crystals and low-density aggregates to heavily rimed particles with maximum size exceeding 10ĝmm. Three different flight segments with well-matched in situ and radar measurements were analyzed, giving a total of 49ĝmin of triple-frequency observations. The in situ particle imagery data for this study include high-resolution imagery from the Cloud Particle Imager (CPI) probe, which allows accurate identification of particle types, including rimed crystals and large aggregates, within the dual-frequency ratio (DFR) plane. The airborne triple-frequency radar data are grouped based on the dominant particle compositions and microphysical processes (level of aggregation and riming). The results from this study are consistent with the main findings of previous modeling studies, with specific regions of the DFR plane associated with unique scattering properties of different ice habits, especially in clouds where the radar signal is dominated by large aggregates. Moreover, the analysis shows close relationships between the triple-frequency signatures and cloud microphysical properties (particle characteristic size, bulk density, and level of riming)

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) and its operations from an unmanned aerial vehicle (UAV) during the AROMAT campaign

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is a compact remote sensing instrument dedicated to mapping trace gases from an unmanned aerial vehicle (UAV). SWING is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27 cm  ×  12 cm  ×  8 cm, and 6 W. SWING was developed in parallel with a 2.5 m flying-wing UAV. This unmanned aircraft is electrically powered, has a typical airspeed of 100 km h−1, and can operate at a maximum altitude of 3 km. We present SWING-UAV experiments performed in Romania on 11 September 2014 during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign, which was dedicated to test newly developed instruments in the context of air quality satellite validation. The UAV was operated up to 700 m above ground, in the vicinity of the large power plant of Turceni (44.67° N, 23.41° E; 116 m a. s. l. ). These SWING-UAV flights were coincident with another airborne experiment using the Airborne imaging differential optical absorption spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP), and with ground-based DOAS, lidar, and balloon-borne in situ observations. The spectra recorded during the SWING-UAV flights are analysed with the DOAS technique. This analysis reveals NO2 differential slant column densities (DSCDs) up to 13±0.6×1016 molec cm−2. These NO2 DSCDs are converted to vertical column densities (VCDs) by estimating air mass factors. The resulting NO2 VCDs are up to 4.7±0.4×1016 molec cm−2. The water vapour DSCD measurements, up to 8±0.15×1022 molec cm−2, are used to estimate a volume mixing ratio of water vapour in the boundary layer of 0.013±0.002 mol mol−1. These geophysical quantities are validated with the coincident measurements