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- ItemThe Fifth International Workshop on Ice Nucleation phase 2 (FIN-02): Laboratory intercomparison of ice nucleation measurements(Katlenburg-Lindau : Copernicus, 2018) DeMott, Paul J.; Möhler, Ottmar; Cziczo, Daniel J.; Hiranuma, Naruki; Petters, Markus D.; Petters, Sarah S.; Belosi, Franco; Bingemer, Heinz G.; Brooks, Sarah D.; Budke, Carsten; Burkert-Kohn, Monika; Collier, Kristen N.; Danielczok, Anja; Eppers, Oliver; Felgitsch, Laura; Garimella, Sarvesh; Grothe, Hinrich; Herenz, Paul; Hill, Thomas C. J.; Höhler, Kristina; Kanji, Zamin A.; Kiselev, Alexei; Koop, Thomas; Kristensen, Thomas B.; Krüger, Konstantin; Kulkarni, Gourihar; Levin, Ezra J. T.; Murray, Benjamin J.; Nicosia, Alessia; O'Sullivan, Daniel; Peckhaus, Andreas; Polen, Michael J.; Price, Hannah C.; Reicher, Naama; Rothenberg, Daniel A.; Rudich, Yinon; Santachiara, Gianni; Schiebel, Thea; Schrod, Jann; Seifried, Teresa M.; Stratmann, Frank; Sullivan, Ryan C.; Suski, Kaitlyn J.; Szakáll, Miklós; Taylor, Hans P.; Ullrich, Romy; Vergara-Temprado, Jesus; Wagner, Robert; Whale, Thomas F.; Weber, Daniel; Welti, André; Wilson, Theodore W.; Wolf, Martin J.; Zenker, JakeThe second phase of the Fifth International Ice Nucleation Workshop (FIN-02) involved the gathering of a large number of researchers at the Karlsruhe Institute of Technology's Aerosol Interactions and Dynamics of the Atmosphere (AIDA) facility to promote characterization and understanding of ice nucleation measurements made by a variety of methods used worldwide. Compared to the previous workshop in 2007, participation was doubled, reflecting a vibrant research area. Experimental methods involved sampling of aerosol particles by direct processing ice nucleation measuring systems from the same volume of air in separate experiments using different ice nucleating particle (INP) types, and collections of aerosol particle samples onto filters or into liquid for sharing amongst measurement techniques that post-process these samples. In this manner, any errors introduced by differences in generation methods when samples are shared across laboratories were mitigated. Furthermore, as much as possible, aerosol particle size distribution was controlled so that the size limitations of different methods were minimized. The results presented here use data from the workshop to assess the comparability of immersion freezing measurement methods activating INPs in bulk suspensions, methods that activate INPs in condensation and/or immersion freezing modes as single particles on a substrate, continuous flow diffusion chambers (CFDCs) directly sampling and processing particles well above water saturation to maximize immersion and subsequent freezing of aerosol particles, and expansion cloud chamber simulations in which liquid cloud droplets were first activated on aerosol particles prior to freezing. The AIDA expansion chamber measurements are expected to be the closest representation to INP activation in atmospheric cloud parcels in these comparisons, due to exposing particles freely to adiabatic cooling. The different particle types used as INPs included the minerals illite NX and potassium feldspar (K-feldspar), two natural soil dusts representative of arable sandy loam (Argentina) and highly erodible sandy dryland (Tunisia) soils, respectively, and a bacterial INP (Snomax®). Considered together, the agreement among post-processed immersion freezing measurements of the numbers and fractions of particles active at different temperatures following bulk collection of particles into liquid was excellent, with possible temperature uncertainties inferred to be a key factor in determining INP uncertainties. Collection onto filters for rinsing versus directly into liquid in impingers made little difference. For methods that activated collected single particles on a substrate at a controlled humidity at or above water saturation, agreement with immersion freezing methods was good in most cases, but was biased low in a few others for reasons that have not been resolved, but could relate to water vapor competition effects. Amongst CFDC-style instruments, various factors requiring (variable) higher supersaturations to achieve equivalent immersion freezing activation dominate the uncertainty between these measurements, and for comparison with bulk immersion freezing methods. When operated above water saturation to include assessment of immersion freezing, CFDC measurements often measured at or above the upper bound of immersion freezing device measurements, but often underestimated INP concentration in comparison to an immersion freezing method that first activates all particles into liquid droplets prior to cooling (the PIMCA-PINC device, or Portable Immersion Mode Cooling chAmber-Portable Ice Nucleation Chamber), and typically slightly underestimated INP number concentrations in comparison to cloud parcel expansions in the AIDA chamber; this can be largely mitigated when it is possible to raise the relative humidity to sufficiently high values in the CFDCs, although this is not always possible operationally. Correspondence of measurements of INPs among direct sampling and post-processing systems varied depending on the INP type. Agreement was best for Snomax® particles in the temperature regime colder than -10°C, where their ice nucleation activity is nearly maximized and changes very little with temperature. At temperatures warmer than -10°C, Snomax® INP measurements (all via freezing of suspensions) demonstrated discrepancies consistent with previous reports of the instability of its protein aggregates that appear to make it less suitable as a calibration INP at these temperatures. For Argentinian soil dust particles, there was excellent agreement across all measurement methods; measures ranged within 1 order of magnitude for INP number concentrations, active fractions and calculated active site densities over a 25 to 30°C range and 5 to 8 orders of corresponding magnitude change in number concentrations. This was also the case for all temperatures warmer than -25°C in Tunisian dust experiments. In contrast, discrepancies in measurements of INP concentrations or active site densities that exceeded 2 orders of magnitude across a broad range of temperature measurements found at temperatures warmer than -25°C in a previous study were replicated for illite NX. Discrepancies also exceeded 2 orders of magnitude at temperatures of -20 to -25°C for potassium feldspar (K-feldspar), but these coincided with the range of temperatures at which INP concentrations increase rapidly at approximately an order of magnitude per 2°C cooling for K-feldspar. These few discrepancies did not outweigh the overall positive outcomes of the workshop activity, nor the future utility of this data set or future similar efforts for resolving remaining measurement issues. Measurements of the same materials were repeatable over the time of the workshop and demonstrated strong consistency with prior studies, as reflected by agreement of data broadly with parameterizations of different specific or general (e.g., soil dust) aerosol types. The divergent measurements of the INP activity of illite NX by direct versus post-processing methods were not repeated for other particle types, and the Snomax° data demonstrated that, at least for a biological INP type, there is no expected measurement bias between bulk collection and direct immediately processed freezing methods to as warm as -10°C. Since particle size ranges were limited for this workshop, it can be expected that for atmospheric populations of INPs, measurement discrepancies will appear due to the different capabilities of methods for sampling the full aerosol size distribution, or due to limitations on achieving sufficient water supersaturations to fully capture immersion freezing in direct processing instruments. Overall, this workshop presents an improved picture of present capabilities for measuring INPs than in past workshops, and provides direction toward addressing remaining measurement issues.
- ItemConcentration and variability of ice nuclei in the subtropical maritime boundary layer(Katlenburg-Lindau : EGU, 2018) Welti, André; Müller, Konrad; Fleming, Zoë L.; Stratmann, FrankMeasurements of the concentration and variability of ice nucleating particles in the subtropical maritime boundary layer are reported. Filter samples collected in Cabo Verde over the period 2009-2013 are analyzed with a drop freezing experiment with sensitivity to detect the few rare ice nuclei active at low supercooling. The data set is augmented with continuous flow diffusion chamber measurements at temperatures below -24 °C from a 2-month field campaign in Cabo Verde in 2016. The data set is used to address the following questions: what are typical concentrations of ice nucleating particles active at a certain temperature? What affects their concentration and where are their sources? Concentration of ice nucleating particles is found to increase exponentially by 7 orders of magnitude from -5 to -38 °C. Sample-to-sample variation in the steepness of the increase indicates that particles of different origin, with different ice nucleation properties (size, composition), contribute to the ice nuclei concentration at different temperatures. The concentration of ice nuclei active at a specific temperature varies over a range of up to 4 orders of magnitude. The frequency with which a certain ice nuclei concentration is measured within this range is found to follow a lognormal distribution, which can be explained by random dilution during transport. To investigate the geographic origin of ice nuclei, source attribution of air masses from dispersion modeling is used to classify the data into seven typical conditions. While no source could be attributed to the ice nuclei active at temperatures higher than -12 °C, concentrations at lower temperatures tend to be elevated in air masses originating from the Sahara.
- ItemReconstruction of global gridded monthly sectoral water withdrawals for 1971-2010 and analysis of their spatiotemporal patterns(Göttingen : Copernicus GmbH, 2018) Huang, Z.; Hejazi, M.; Li, X.; Tang, Q.; Vernon, C.; Leng, G.; Liu, Y.; Döll, P.; Eisner, S.; Gerten, D.; Hanasaki, N.; Wada, Y.Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5°) sectoral water withdrawal dataset for the period 1971-2010, which distinguishes six water use sectors, i.e., irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971-2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. The reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.
- ItemAn automatic observation-based aerosol typing method for EARLINET(Katlenburg-Lindau : EGU, 2018) Papagiannopoulos, Nikolaos; Mona, Lucia; Amodeo, Aldo; D'Amico, Giuseppe; Gumà Claramunt, Pilar; Pappalardo, Gelsomina; Alados-Arboledas, Lucas; Guerrero-Rascado, Juan Luís; Amiridis, Vassilis; Kokkalis, Panagiotis; Apituley, Arnoud; Baars, Holger; Schwarz, Anja; Wandinger, Ulla; Binietoglou, Ioannis; Nicolae, Doina; Bortoli, Daniele; Comerón, Adolfo; Rodríguez-Gómez, Alejandro; Sicard, Michaël; Papayannis, Alex; Wiegner, MatthiasWe present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a reference dataset is set up consisting of already classified EARLINET data. Using this dataset, we defined 8 aerosol classes: clean continental, polluted continental, dust, mixed dust, polluted dust, mixed marine, smoke, and volcanic ash. The effect of the number of aerosol classes has been explored, as well as the optimal set of intensive parameters to separate different aerosol types. Furthermore, the algorithm is trained with literature particle linear depolarization ratio values. As a second step (testing phase), we apply the method to an already classified EARLINET dataset and analyze the results of the comparison to this classified dataset. The predictive accuracy of the automatic classification varies between 59% (minimum) and 90% (maximum) from 8 to 4 aerosol classes, respectively, when evaluated against pre-classified EARLINET lidar. This indicates the potential use of the automatic classification to all network lidar data. Furthermore, the training of the algorithm with particle linear depolarization values found in the literature further improves the accuracy with values for all the aerosol classes around 80%. Additionally, the algorithm has proven to be highly versatile as it adapts to changes in the size of the training dataset and the number of aerosol classes and classifying parameters. Finally, the low computational time and demand for resources make the algorithm extremely suitable for the implementation within the single calculus chain (SCC), the EARLINET centralized processing suite.