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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.
- ItemA generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations: An example from the Amazon region(Katlenburg-Lindau : Copernicus, 2018) Rammig, Anja; Heinke, Jens; Hofhansl, Florian; Verbeeck, Hans; Baker, Timothy R.; Christoffersen, Bradley; Ciais, Philippe; De Deurwaerder, Hannes; Fleischer, Katrin; Galbraith, David; Guimberteau, Matthieu; Huth, Andreas; Johnson, Michelle; Krujit, Bart; Langerwisch, Fanny; Meir, Patrick; Papastefanou, Phillip; Sampaio, Gilvan; Thonicke, Kirsten; von Randow, Celso; Zang, Christian; Rödig, EdnaComparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25% and up to 60%, respectively. Our comparison metrics provide a quantitative measure for model-data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.
- ItemTwo-thirds of global cropland area impacted by climate oscillations(London : Nature Publishing Group, 2018) Heino, M.; Puma, M.J.; Ward, P.J.; Gerten, D.; Heck, V.; Siebert, S.; Kummu, M.The El Niño Southern Oscillation (ENSO) peaked strongly during the boreal winter 2015-2016, leading to food insecurity in many parts of Africa, Asia and Latin America. Besides ENSO, the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) are known to impact crop yields worldwide. Here we assess for the first time in a unified framework the relationships between ENSO, IOD and NAO and simulated crop productivity at the sub-country scale. Our findings reveal that during 1961-2010, crop productivity is significantly influenced by at least one large-scale climate oscillation in two-thirds of global cropland area. Besides observing new possible links, especially for NAO in Africa and the Middle East, our analyses confirm several known relationships between crop productivity and these oscillations. Our results improve the understanding of climatological crop productivity drivers, which is essential for enhancing food security in many of the most vulnerable places on the planet.
- ItemThe Effect of Obliquity-Driven Changes on Paleoclimate Sensitivity During the Late Pleistocene(Hoboken, NJ : Wiley, 2018) Köhler, Peter; Knorr, Gregor; Stap, Lennert B.; Ganopolski, Andrey; de Boer, Bas; van de Wal, Roderik S. W.; Barker, Stephen; Rüpke, Lars H.We reanalyze existing paleodata of global mean surface temperature ΔTg and radiative forcing ΔR of CO2 and land ice albedo for the last 800,000 years to show that a state-dependency in paleoclimate sensitivity S, as previously suggested, is only found if ΔTg is based on reconstructions, and not when ΔTg is based on model simulations. Furthermore, during times of decreasing obliquity (periods of land ice sheet growth and sea level fall) the multimillennial component of reconstructed ΔTg diverges from CO2, while in simulations both variables vary more synchronously, suggesting that the differences during these times are due to relatively low rates of simulated land ice growth and associated cooling. To produce a reconstruction-based extrapolation of S for the future, we exclude intervals with strong ΔTg-CO2 divergence and find that S is less state-dependent, or even constant state-independent), yielding a mean equilibrium warming of 2–4 K for a doubling of CO2.
- ItemDo new sea spray aerosol source functions improve the results of a regional aerosol model?(Amsterdam [u.a.] : Elsevier Science, 2018) Barthel, Stefan; Tegen, Ina; Wolke, RalfSea spray aerosol particle is a dominating part of the global aerosol mass load of natural origin. Thus, it strongly influences the atmospheric radiation balance and cloud properties especially over the oceans. Uncertainties of the estimated climate impacts by this aerosol type are partly caused by the uncertainties in the particle size dependent emission fluxes of sea spray aerosol particle. We present simulations with a regional aerosol transport model system in two domains, for three months and compared the model results to measurements at four stations using various sea spray aerosol particle source source functions. Despite these limitations we found the results using different source functions are within the range of most model uncertainties. Especially the model's ability to produce realistic wind speeds is crucial. Furthermore, the model results are more affected by a function correcting the emission flux for the effect of the sea surface temperature than by the use of different source functions. © 2018 The Authors
- ItemImplementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0)(Katlenburg-Lindau : Copernicus, 2018) von Bloh, Werner; Schaphoff, Sibyll; Müller, Christoph; Rolinski, Susanne; Waha, Katharina; Zaehle, SönkeThe well-established dynamical global vegetation, hydrology, and crop growth model LPJmL is extended with a terrestrial nitrogen cycle to account for nutrient limitations. In particular, processes of soil nitrogen dynamics, plant uptake, nitrogen allocation, response of photosynthesis and maintenance respiration to varying nitrogen concentrations in plant organs, and agricultural nitrogen management are included in the model. All new model features are described in full detail and the results of a global simulation of the historic past (1901-2009) are presented for evaluation of the model performance. We find that the implementation of nitrogen limitation significantly improves the simulation of global patterns of crop productivity. Regional differences in crop productivity, which had to be calibrated via a scaling of the maximum leaf area index, can now largely be reproduced by the model, except for regions where fertilizer inputs and climate conditions are not the yield-limiting factors. Furthermore, it can be shown that land use has a strong influence on nitrogen losses, increasing leaching by 93 %.
- ItemLPJmL4 - A dynamic global vegetation model with managed land - Part 1: Model description(Göttingen : Copernicus GmbH, 2018) Schaphoff, S.; Von Bloh, W.; Rammig, A.; Thonicke, K.; Biemans, H.; Forkel, M.; Gerten, D.; Heinke, J.; Jägermeyr, J.; Knauer, J.; Langerwisch, F.; Lucht, W.; Müller, C.; Rolinski, S.; Waha, K.This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.
- ItemSimple models for the simulation of submarine melt for a Greenland glacial system model(München : European Geopyhsical Union, 2018) Beckmann, Johanna; Perrette, Mahé; Ganopolski, AndreyTwo hundred marine-terminating Greenland outlet glaciers deliver more than half of the annually accumulated ice into the ocean and have played an important role in the Greenland ice sheet mass loss observed since the mid-1990s. Submarine melt may play a crucial role in the mass balance and position of the grounding line of these outlet glaciers. As the ocean warms, it is expected that submarine melt will increase, potentially driving outlet glaciers retreat and contributing to sea level rise. Projections of the future contribution of outlet glaciers to sea level rise are hampered by the necessity to use models with extremely high resolution of the order of a few hundred meters. That requirement in not only demanded when modeling outlet glaciers as a stand alone model but also when coupling them with high-resolution 3-D ocean models. In addition, fjord bathymetry data are mostly missing or inaccurate (errors of several hundreds of meters), which questions the benefit of using computationally expensive 3-D models for future predictions. Here we propose an alternative approach built on the use of a computationally efficient simple model of submarine melt based on turbulent plume theory. We show that such a simple model is in reasonable agreement with several available modeling studies. We performed a suite of experiments to analyze sensitivity of these simple models to model parameters and climate characteristics. We found that the computationally cheap plume model demonstrates qualitatively similar behavior as 3-D general circulation models. To match results of the 3-D models in a quantitative manner, a scaling factor of the order of 1 is needed for the plume models. We applied this approach to model submarine melt for six representative Greenland glaciers and found that the application of a line plume can produce submarine melt compatible with observational data. Our results show that the line plume model is more appropriate than the cone plume model for simulating the average submarine melting of real glaciers in Greenland.