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Now showing 1 - 10 of 13
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    Evaluation of the shortwave cloud radiative effect over the ocean by use of ship and satellite observations
    (München : European Geopyhsical Union, 2012) Hanschmann, T.; Deneke, H.; Roebeling, R.; Macke, A.
    In this study the shortwave cloud radiative effect (SWCRE) over ocean calculated by the ECHAM 5 climate model is evaluated for the cloud property input derived from ship based measurements and satellite based estimates and compared to ship based radiation measurements. The ship observations yield cloud fraction, liquid water path from a microwave radiometer, cloud bottom height as well as temperature and humidity profiles from radiosonde ascents. Level-2 products of the Satellite Application Facility on Climate Monitoring (CM~SAF) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) have been used to characterize clouds. Within a closure study six different experiments have been defined to find the optimal set of measurements to calculate downward shortwave radiation (DSR) and the SWCRE from the model, and their results have been evaluated under seven different synoptic situations. Four of these experiments are defined to investigate the advantage of including the satellite-based cloud droplet effective radius as additional cloud property. The modeled SWCRE based on satellite retrieved cloud properties has a comparable accuracy to the modeled SWCRE based on ship data. For several cases, an improvement through introducing the satellite-based estimate of effective radius as additional information to the ship based data was found. Due to their different measuring characteristics, however, each dataset shows best results for different atmospheric conditions.
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    Maritime aerosol network as a component of AERONET - First results and comparison with global aerosol models and satellite retrievals
    (München : European Geopyhsical Union, 2011) Smirnov, A.; Holben, B.N.; Giles, D.M.; Slutsker, I.; O'Neill, N.T.; Eck, T.F.; Macke, A.; Croot, P.; Courcoux, Y.; Sakerin, S.M.; Smyth, T.J.; Zielinski, T.; Zibordi, G.; Goes, J.I.; Harvey, M.J.; Quinn, P.K.; Nelson, N.B.; Radionov, V.F.; Duarte, C.M.; Losno, R.; Sciare, J.; Voss, K.J.; Kinne, S.; Nalli, N.R.; Joseph, E.; Krishna Moorthy, K.; Covert, D.S.; Gulev, S.K.; Milinevsky, G.; Larouche, P.; Belanger, S.; Horne, E.; Chin, M.; Remer, L.A.; Kahn, R.A.; Reid, J.S.; Schulz, M.; Heald, C.L.; Zhang, J.; Lapina, K.; Kleidman, R.G.; Griesfeller, J.; Gaitley, B.J.; Tan, Q.; Diehl, T.L.
    The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. Over 80 cruises were completed through early 2010 with deployments continuing. Measurement areas included various parts of the Atlantic Ocean, the Northern and Southern Pacific Ocean, the South Indian Ocean, the Southern Ocean, the Arctic Ocean and inland seas. MAN deploys Microtops hand-held sunphotometers and utilizes a calibration procedure and data processing traceable to AERONET. Data collection included areas that previously had no aerosol optical depth (AOD) coverage at all, particularly vast areas of the Southern Ocean. The MAN data archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we present results of AOD measurements over the oceans, and make a comparison with satellite AOD retrievals and model simulations.
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    The influence of dust optical properties on the colour of simulated MSG-SEVIRI Desert Dust infrared imagery
    (Katlenburg-Lindau : EGU, 2018) Banks, Jamie R.; Schepanski, Kerstin; Heinold, Bernd; Hünerbein, Anja; Brindley, Helen E.
    Satellite imagery of atmospheric mineral dust is sensitive to the optical properties of the dust, governed by the mineral refractive indices, particle size, and particle shape. In infrared channels the imagery is also sensitive to the dust layer height and to the surface and atmospheric environment. Simulations of mineral dust in infrared "Desert Dust" imagery from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) have been performed, using the COSMO-MUSCAT (COSMO: COnsortium for Small-scale MOdelling; MUSCAT: MUltiScale Chemistry Aerosol Transport Model) dust transport model and the Radiative Transfer for TOVS (RTTOV) program, in order to investigate the sensitivity of the imagery to assumed dust properties. This paper introduces the technique and performs initial validation and comparisons with SEVIRI measurements over North Africa for daytime hours during 6 months covering June and July of 2011–2013. Using T-matrix scattering theory and assuming the dust particles to be spherical or spheroidal, wavelength- and size-dependent dust extinction values are calculated for a number of different dust refractive index databases, along with several values of the particle aspect ratio, denoting the particle shape. The consequences for the infrared extinction values of both the particle shape and the particle orientation are explored: this analysis shows that as the particle asphericity increases, the extinctions increase if the particles are aligned horizontally, and decrease if they are aligned vertically. Randomly oriented spheroidal particles have very similar infrared extinction properties as spherical particles, whereas the horizontally and vertically aligned particles can be considered to be the upper and lower bounds on the extinction values. Inputting these values into COSMO-MUSCAT-RTTOV, it is found that spherical particles do not appear to be sufficient to describe fully the resultant colour of the dust in the infrared imagery. Comparisons of SEVIRI and simulation colours indicate that of the dust types tested, the dust refractive index dataset produced by Volz (1973) shows the most similarity in the colour response to dust in the SEVIRI imagery, although the simulations have a smaller range of colour than do the observations. It is also found that the thermal imagery is most sensitive to intermediately sized particles (radii between 0.9 and 2.6 µm): larger particles are present in too small a concentration in the simulations, as well as with insufficient contrast in extinction between wavelength channels, to have much ability to perturb the resultant colour in the SEVIRI dust imagery.
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    An EARLINET early warning system for atmospheric aerosol aviation hazards
    (Katlenburg-Lindau : EGU, 2020) Papagiannopoulos, Nikolaos; D’Amico, Giuseppe; Gialitaki, Anna; Ajtai, Nicolae; Alados-Arboledas, Lucas; Amodeo, Aldo; Amiridis, Vassilis; Baars, Holger; Balis, Dimitris; Binietoglou, Ioannis; Comerón, Adolfo; Dionisi, Davide; Falconieri, Alfredo; Fréville, Patrick; Kampouri, Anna; Mattis, Ina; Mijić, Zoran; Molero, Francisco; Papayannis, Alex; Pappalardo, Gelsomina; Rodríguez-Gómez, Alejandro; Solomos, Stavros; Mona, Lucia
    A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identification of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the European Aerosol Research Lidar Network (EARLINET) delivers high-resolution preprocessed data: the calibrated total attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high resolution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the retrieval of the particle backscatter is implemented. This improved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is applied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Finokalia, Greece, and, second, an intrusion of volcanic particles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demonstrates the network's preparedness to offer insight into natural hazards that affect the aviation sector. © 2020 Author(s).
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    Impact of particle shape on the morphology of noctilucent clouds
    (Katlenburg-Lindau : EGU, 2015) Kiliani, J.; Baumgarten, G.; Lübken, F.-J.; Berger, U.
    Noctilucent clouds (NLCs) occur during summer in the polar region at altitudes around 83 km. They consist of ice particles with a typical size around 50 nm. The shape of NLC particles is less well known but is important both for interpreting optical measurements and modeling ice cloud characteristics. In this paper, NLC modeling of microphysics and optics is adapted to use cylindrical instead of spherical particle shape. The optical properties of the resulting ice clouds are compared directly to NLC three-color measurements by the Arctic Lidar Observatory for Middle Atmosphere Research (ALOMAR) Rayleigh/Mie/Raman (RMR) lidar between 1998 and 2014. Shape distributions including both needle- and disc-shaped particles are consistent with lidar measurements. The best agreement occurs if disc shapes are 60 % more common than needles, with a mean axis ratio of 2.8. Cylindrical particles cause stronger ice clouds on average than spherical shapes with an increase of backscatter at 532 nm by ≈ 30 % and about 20 % in ice mass density. This difference is less pronounced for bright than for weak ice clouds. Cylindrical shapes also cause NLCs to have larger but a smaller number of ice particles than for spherical shapes.
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    The noctilucent cloud (NLC) display during the ECOMA/MASS sounding rocket flights on 3 August 2007: Morphology on global to local scales
    (München : European Geopyhsical Union, 2009) Baumgarten, G.; Fiedler, J.; Fricke, K.H.; Gerding, M.; Hervig, M.; Hoffmann, P.; Müller, N.; Pautet, P.-D.; Rapp, M.; Robert, C.; Rusch, D.; von Savigny, C.; Singer, W.
    During the ECOMA/MASS rocket campaign large scale NLC/PMC was observed by satellite, lidar and camera from polar to mid latitudes. We examine the observations from different instruments to investigate the morphology of the cloud. Satellite observations show a planetary wave 2 structure. Lidar observations from Kühlungsborn (54° N), Esrange (68° N) and ALOMAR (69° N) show a highly dynamic NLC layer. Under favorable solar illumination the cloud is also observable by ground-based cameras. The cloud was detected by cameras from Trondheim (63° N), Juliusruh (55° N) and Kühlungsborn. We investigate planetary scale morphology and local scale gravity wave structures, important for the interpretation of the small scale rocket soundings. We compare in detail the lidar observations with the NLC structure observed by the camera in Trondheim. The ALOMAR RMR-lidar observed only a faint NLC during the ECOMA launch window, while the camera in Trondheim showed a strong NLC display in the direction of ALOMAR. Using the high resolution camera observations (t~30 s, Δx<5 km) and the wind information from the meteor radar at ALOMAR we investigate the formation and destruction of NLC structures. We observe that the NLC brightness is reduced by a factor of 20–40 within 100 s which can be caused by a temperature about 15 K above the frostpoint temperature. A horizontal temperature gradient of more than 3 K/km is estimated.
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    A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1)
    (München : European Geopyhsical Union, 2017) Forkel, Matthias; Dorigo, Wouter; Lasslop, Gitta; Teubner, Irene; Chuvieco, Emilio; Thonicke, Kirsten
    Vegetation fires affect human infrastructures, ecosystems, global vegetation distribution, and atmospheric composition. However, the climatic, environmental, and socioeconomic factors that control global fire activity in vegetation are only poorly understood, and in various complexities and formulations are represented in global process-oriented vegetation-fire models. Data-driven model approaches such as machine learning algorithms have successfully been used to identify and better understand controlling factors for fire activity. However, such machine learning models cannot be easily adapted or even implemented within process-oriented global vegetation-fire models. To overcome this gap between machine learning-based approaches and process-oriented global fire models, we introduce a new flexible data-driven fire modelling approach here (Satellite Observations to predict FIre Activity, SOFIA approach version 1). SOFIA models can use several predictor variables and functional relationships to estimate burned area that can be easily adapted with more complex process-oriented vegetation-fire models. We created an ensemble of SOFIA models to test the importance of several predictor variables. SOFIA models result in the highest performance in predicting burned area if they account for a direct restriction of fire activity under wet conditions and if they include a land cover-dependent restriction or allowance of fire activity by vegetation density and biomass. The use of vegetation optical depth data from microwave satellite observations, a proxy for vegetation biomass and water content, reaches higher model performance than commonly used vegetation variables from optical sensors. We further analyse spatial patterns of the sensitivity between anthropogenic, climate, and vegetation predictor variables and burned area. We finally discuss how multiple observational datasets on climate, hydrological, vegetation, and socioeconomic variables together with data-driven modelling and model–data integration approaches can guide the future development of global process-oriented vegetation-fire models.
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    Tobac 1.2: Towards a flexible framework for tracking and analysis of clouds in diverse datasets
    (Katlenburg-Lindau : Copernicus, 2019) Heikenfeld, Max; Marinescu, Peter J.; Christensen, Matthew; Watson-Parris, Duncan; Senf, Fabian; van den Heever, Susan C.; Stier, Philip
    We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two-or three-dimensional timevarying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the threedimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data. © 2019 Author(s).
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    Sources, seasonality, and trends of southeast US aerosol: an integrated analysis of surface, aircraft, and satellite observations with the GEOS-Chem chemical transport model
    (Katlenburg-Lindau : EGU, 2015) Kim, P.S.; Jacob, D.J.; Fisher, J.A.; Travis, K.; Yu, K.; Zhu, L.; Yantosca, R.M.; Sulprizio, M.P.; Jimenez, J.L.; Campuzano-Jost, P.; Froyd, K.D.; Liao, J.; Hair, J.W.; Fenn, M.A.; Butler, C.F.; Wagner, N.L.; Gordon, T.D.; Welti, A.; Wennberg, P.O.; Crounse, J.D.; St. Clair, J.M.; Teng, A.P.; Millet, D.B.; Schwarz, J.P.; Markovic, M.Z.; Perring, A.E.
    We use an ensemble of surface (EPA CSN, IMPROVE, SEARCH, AERONET), aircraft (SEAC4RS), and satellite (MODIS, MISR) observations over the southeast US during the summer–fall of 2013 to better understand aerosol sources in the region and the relationship between surface particulate matter (PM) and aerosol optical depth (AOD). The GEOS-Chem global chemical transport model (CTM) with 25 × 25 km2 resolution over North America is used as a common platform to interpret measurements of different aerosol variables made at different times and locations. Sulfate and organic aerosol (OA) are the main contributors to surface PM2.5 (mass concentration of PM finer than 2.5 μm aerodynamic diameter) and AOD over the southeast US. OA is simulated successfully with a simple parameterization, assuming irreversible uptake of low-volatility products of hydrocarbon oxidation. Biogenic isoprene and monoterpenes account for 60 % of OA, anthropogenic sources for 30 %, and open fires for 10 %. 60 % of total aerosol mass is in the mixed layer below 1.5 km, 25 % in the cloud convective layer at 1.5–3 km, and 15 % in the free troposphere above 3 km. This vertical profile is well captured by GEOS-Chem, arguing against a high-altitude source of OA. The extent of sulfate neutralization (f = [NH4+]/(2[SO42−] + [NO3−]) is only 0.5–0.7 mol mol−1 in the observations, despite an excess of ammonia present, which could reflect suppression of ammonia uptake by OA. This would explain the long-term decline of ammonium aerosol in the southeast US, paralleling that of sulfate. The vertical profile of aerosol extinction over the southeast US follows closely that of aerosol mass. GEOS-Chem reproduces observed total column aerosol mass over the southeast US within 6 %, column aerosol extinction within 16 %, and space-based AOD within 8–28 % (consistently biased low). The large AOD decline observed from summer to winter is driven by sharp declines in both sulfate and OA from August to October. These declines are due to shutdowns in both biogenic emissions and UV-driven photochemistry. Surface PM2.5 shows far less summer-to-winter decrease than AOD and we attribute this in part to the offsetting effect of weaker boundary layer ventilation. The SEAC4RS aircraft data demonstrate that AODs measured from space are consistent with surface PM2.5. This implies that satellites can be used reliably to infer surface PM2.5 over monthly timescales if a good CTM representation of the aerosol vertical profile is available.
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    High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data
    (München : European Geopyhsical Union, 2015) Nunalee, C.G.; Horváth, Á.; Basu, S.
    Recent decades have witnessed a drastic increase in the fidelity of numerical weather prediction (NWP) modeling. Currently, both research-grade and operational NWP models regularly perform simulations with horizontal grid spacings as fine as 1 km. This migration towards higher resolution potentially improves NWP model solutions by increasing the resolvability of mesoscale processes and reducing dependency on empirical physics parameterizations. However, at the same time, the accuracy of high-resolution simulations, particularly in the atmospheric boundary layer (ABL), is also sensitive to orographic forcing which can have significant variability on the same spatial scale as, or smaller than, NWP model grids. Despite this sensitivity, many high-resolution atmospheric simulations do not consider uncertainty with respect to selection of static terrain height data set. In this paper, we use the Weather Research and Forecasting (WRF) model to simulate realistic cases of lower tropospheric flow over and downstream of mountainous islands using the default global 30 s United States Geographic Survey terrain height data set (GTOPO30), the Shuttle Radar Topography Mission (SRTM), and the Global Multi-resolution Terrain Elevation Data set (GMTED2010) terrain height data sets. While the differences between the SRTM-based and GMTED2010-based simulations are extremely small, the GTOPO30-based simulations differ significantly. Our results demonstrate cases where the differences between the source terrain data sets are significant enough to produce entirely different orographic wake mechanics, such as vortex shedding vs. no vortex shedding. These results are also compared to MODIS visible satellite imagery and ASCAT near-surface wind retrievals. Collectively, these results highlight the importance of utilizing accurate static orographic boundary conditions when running high-resolution mesoscale models.