Search Results
Long-term studies of mesosphere and lower-thermosphere summer length definitions based on mean zonal wind features observed for more than one solar cycle at middle and high latitudes in the Northern Hemisphere
2022, Jaen, Juliana, Renkwitz, Toralf, Chau, Jorge L., He, Maosheng, Hoffmann, Peter, Yamazaki, Yosuke, Jacobi, Christoph, Tsutsumi, Masaki, Matthias, Vivien, Hall, Chris
Specular meteor radars (SMRs) and partial reflection radars (PRRs) have been observing mesospheric winds for more than a solar cycle over Germany (g1/4g54g gN) and northern Norway (g1/4g69g gN). This work investigates the mesospheric mean zonal wind and the zonal mean geostrophic zonal wind from the Microwave Limb Sounder (MLS) over these two regions between 2004 and 2020. Our study focuses on the summer when strong planetary waves are absent and the stratospheric and tropospheric conditions are relatively stable. We establish two definitions of the summer length according to the zonal wind reversals: (1) the mesosphere and lower-thermosphere summer length (MLT-SL) using SMR and PRR winds and (2) the mesosphere summer length (M-SL) using the PRR and MLS. Under both definitions, the summer begins around April and ends around middle September. The largest year-to-year variability is found in the summer beginning in both definitions, particularly at high latitudes, possibly due to the influence of the polar vortex. At high latitudes, the year 2004 has a longer summer length compared to the mean value for MLT-SL as well as 2012 for both definitions. The M-SL exhibits an increasing trend over the years, while MLT-SL does not have a well-defined trend. We explore a possible influence of solar activity as well as large-scale atmospheric influences (e.g., quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO), major sudden stratospheric warming events). We complement our work with an extended time series of 31 years at middle latitudes using only PRR winds. In this case, the summer length shows a breakpoint, suggesting a non-uniform trend, and periods similar to those known for ENSO and QBO.
Ozone depletion in the Arctic and Antarctic stratosphere induced by wildfire smoke
2022, Ansmann, Albert, Ohneiser, Kevin, Chudnovsky, Alexandra, Knopf, Daniel A., Eloranta, Edwin W., Villanueva, Diego, Seifert, Patric, Radenz, Martin, Barja, Boris, Zamorano, Félix, Jimenez, Cristofer, Engelmann, Ronny, Baars, Holger, Griesche, Hannes, Hofer, Julian, Althausen, Dietrich, Wandinger, Ulla
A record-breaking stratospheric ozone loss was observed over the Arctic and Antarctica in 2020. Strong ozone depletion occurred over Antarctica in 2021 as well. The ozone holes developed in smoke-polluted air. In this article, the impact of Siberian and Australian wildfire smoke (dominated by organic aerosol) on the extraordinarily strong ozone reduction is discussed. The study is based on aerosol lidar observations in the North Pole region (October 2019-May 2020) and over Punta Arenas in southern Chile at 53.2°S (January 2020-November 2021) as well as on respective NDACC (Network for the Detection of Atmospheric Composition Change) ozone profile observations in the Arctic (Ny-Ålesund) and Antarctica (Neumayer and South Pole stations) in 2020 and 2021. We present a conceptual approach on how the smoke may have influenced the formation of polar stratospheric clouds (PSCs), which are of key importance in the ozone-depleting processes. The main results are as follows: (a) the direct impact of wildfire smoke below the PSC height range (at 10-12 km) on ozone reduction seems to be similar to well-known volcanic sulfate aerosol effects. At heights of 10-12 km, smoke particle surface area (SA) concentrations of 5-7 μm2 cm-3 (Antarctica, spring 2021) and 6-10 μm2 cm-3 (Arctic, spring 2020) were correlated with an ozone reduction in terms of ozone partial pressure of 0.4-1.2 mPa (about 30 % further ozone reduction over Antarctica) and of 2-3.5 mPa (Arctic, 20 %-30 % reduction with respect to the long-term springtime mean). (b) Within the PSC height range, we found indications that smoke was able to slightly increase the PSC particle number and surface area concentration. In particular, a smoke-related additional ozone loss of 1-2 mPa (10 %-20 % contribution to the total ozone loss over Antarctica) was observed in the 14-23 km PSC height range in September-October 2020 and 2021. Smoke particle number concentrations ranged from 10 to 100 cm-3 and were about a factor of 10 (in 2020) and 5 (in 2021) above the stratospheric aerosol background level. Satellite observations indicated an additional mean column ozone loss (deviation from the long-term mean) of 26-30 Dobson units (9 %-10 %, September 2020, 2021) and 52-57 Dobson units (17 %-20 %, October 2020, 2021) in the smoke-polluted latitudinal Antarctic belt from 70-80°S. Copyright:
Importance of size representation and morphology in modelling optical properties of black carbon: comparison between laboratory measurements and model simulations
2022, Romshoo, Baseerat, Pöhlker, Mira, Wiedensohler, Alfred, Pfeifer, Sascha, Saturno, Jorge, Nowak, Andreas, Ciupek, Krzysztof, Quincey, Paul, Vasilatou, Konstantina, Ess, Michaela N., Gini, Maria, Eleftheriadis, Konstantinos, Robins, Chris, Gaie-Levrel, François, Müller, Thomas
Black carbon (BC) from incomplete combustion of biomass or fossil fuels is the strongest absorbing aerosol component in the atmosphere. Optical properties of BC are essential in climate models for quantification of their impact on radiative forcing. The global climate models, however, consider BC to be spherical particles, which causes uncertainties in their optical properties. Based on this, an increasing number of model-based studies provide databases and parameterization schemes for the optical properties of BC, using more realistic fractal aggregate morphologies. In this study, the reliability of the different modelling techniques of BC was investigated by comparing them to laboratory measurements. The modelling techniques were examined for bare BC particles in the first step and for BC particles with organic material in the second step. A total of six morphological representations of BC particles were compared, three each for spherical and fractal aggregate morphologies. In general, the aggregate representation performed well for modelling the particle light absorption coefficient σabs, single-scattering albedo SSA, and mass absorption cross-section MACBC for laboratory-generated BC particles with volume mean mobility diameters dp,V larger than 100nm. However, for modelling Ångström absorption exponent AAE, it was difficult to suggest a method due to size dependence, although the spherical assumption was in better agreement in some cases. The BC fractal aggregates are usually modelled using monodispersed particles, since their optical simulations are computationally expensive. In such studies, the modelled optical properties showed a 25% uncertainty in using the monodisperse size method. It is shown that using the polydisperse size distribution in combination with fractal aggregate morphology reduces the uncertainty in measured σabs to 10% for particles with dp,V between 60-160nm. Furthermore, the sensitivities of the BC optical properties to the various model input parameters such as the real and imaginary parts of the refractive index (mre and mim), the fractal dimension (Df), and the primary particle radius (app) of an aggregate were investigated. When the BC particle is small and rather fresh, the change in the Df had relatively little effect on the optical properties. There was, however, a significant relationship between app and the particle light scattering, which increased by a factor of up to 6 with increasing total particle size. The modelled optical properties of BC are well aligned with laboratory-measured values when the following assumptions are used in the fractal aggregate representation: mre between 1.6 and 2, mim between 0.50 and 1, Df from 1.7 to 1.9, and app between 10 and 14nm. Overall, this study provides experimental support for emphasizing the importance of an appropriate size representation (polydisperse size method) and an appropriate morphological representation for optical modelling and parameterization scheme development of BC.
Understanding aerosol microphysical properties from 10 years of data collected at Cabo Verde based on an unsupervised machine learning classification
2022, Gong, Xianda, Wex, Heike, Müller, Thomas, Henning, Silvia, Voigtländer, Jens, Wiedensohler, Alfred, Stratmann, Frank
The Cape Verde Atmospheric Observatory (CVAO), which is influenced by both marine and desert dust air masses, has been used for long-term measurements of different properties of the atmospheric aerosol from 2008 to 2017. These properties include particle number size distributions (PNSD), light-absorbing carbon (LAC) and concentrations of cloud condensation nuclei (CCN) together with their hygroscopicity. Here we summarize the results obtained for these properties and use an unsupervised machine learning algorithm for the classification of aerosol types. Five types of aerosols, i.e., marine, freshly formed, mixture, moderate dust and heavy dust, were classified. Air masses during marine periods are from the Atlantic Ocean and during dust periods are from the Sahara Desert. Heavy dust was more frequently present during wintertime, whereas the clean marine periods were more frequently present during springtime. It was observed that during the dust periods CCN number concentrations at a supersaturation of 0.30g% were roughly 2.5 times higher than during marine periods, but the hygroscopicity (κ) of particles in the size range from g1/4g30 to g1/4g175gnm during marine and dust periods were comparable. The long-term data presented here, together with the aerosol classification, can be used as a basis to improve our understanding of annual cycles of the atmospheric aerosol in the eastern tropical Atlantic Ocean and on aerosol-cloud interactions and it can be used as a basis for driving, evaluating and constraining atmospheric model simulations.
The realization of autonomous, aircraft-based, real-time aerosol mass spectrometry in the upper troposphere and lower stratosphere
2022, Dragoneas, Antonis, Molleker, Sergej, Appel, Oliver, Hünig, Andreas, Böttger, Thomas, Hermann, Markus, Drewnick, Frank, Schneider, Johannes, Weigel, Ralf, Borrmann, Stephan
We report on the developments that enabled the field deployment of a fully automated aerosol mass spectrometer, especially designed for high-altitude measurements on unpressurized aircraft. The merits of the two main categories of real-time aerosol mass spectrometry, i.e. (a) single-particle laser desorption and ionization and (b) continuous thermal desorption and electron impact ionization of aerosols, have been integrated into one compact apparatus with the aim to perform in situ real-time analysis of aerosol chemical composition. The demonstrated instrument, named the ERICA (European Research Council Instrument for Chemical composition of Aerosols), operated successfully aboard the high-altitude research aircraft M-55 Geophysica at altitudes up to 20 km while being exposed to ambient conditions of very low atmospheric pressure and temperature. A primary goal of those field deployments was the in situ study of the Asian tropopause aerosol layer (ATAL). During 11 research flights, the instrument operated for more than 49 h and collected chemical composition information of more than 150 000 single particles combined with quantitative chemical composition analysis of aerosol particle ensembles. This paper presents in detail the technical characteristics of the main constituent parts of the instrument, as well as the design considerations for its integration into the aircraft and its autonomous operation in the upper troposphere and lower stratosphere (UTLS). Additionally, system performance data from the first field deployments of the instrument are presented and discussed, together with exemplary mass spectrometry data collected during those flights.
The vertical aerosol type distribution above Israel – 2 years of lidar observations at the coastal city of Haifa
2022, Heese, Birgit, Floutsi, Athena Augusta, Baars, Holger, Althausen, Dietrich, Hofer, Julian, Herzog, Alina, Mewes, Silke, Radenz, Martin, Schechner, Yoav Y.
For the first time, vertically resolved long-term lidar measurements of the aerosol distribution were conducted in Haifa, Israel. The measurements were performed by a PollyXT multi-wavelength Raman and polarization lidar. The lidar was measuring continuously over a 2-year period from March 2017 to May 2019. The resulting data set is a series of manually evaluated lidar optical property profiles. To identify the aerosol types in the observed layers, a novel aerosol typing method that was developed at TROPOS is used. This method applies optimal estimation to a combination of lidar-derived intensive aerosol properties to determine the statistically most-likely contribution per aerosol component in terms of relative volume. A case study that shows several elevated aerosol layers illustrates this method and shows, for example, that coarse dust particles are observed up to 5ĝ€¯km height over Israel. From the whole data set, the seasonal distribution of the observed aerosol components over Israel is derived. Throughout all seasons, coarse spherical particles like sea salt and hygroscopically grown continental aerosol were observed. These particles originate from continental Europe and were transported over the Mediterranean Sea. Sea-salt particles were observed frequently due to the coastal site of Haifa. The highest contributions of coarse spherical particles are present in summer, autumn, and winter. During spring, mostly coarse non-spherical particles that are attributed to desert dust were observed. This is consistent with the distinct dust season in spring in Israel. An automated time-height-resolved air mass source attribution method identifies the origin of the dust in the Sahara and the Arabian deserts. Fine-mode spherical particles contribute significantly to the observed aerosol mixture during all seasons. These particles originate mainly from the industrial region at the bay of Haifa.
Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks
2022, Schimmel, Willi, Kalesse-Los, Heike, Maahn, Maximilian, Vogl, Teresa, Foth, Andreas, Garfias, Pablo Saavedra, Seifert, Patric
In mixed-phase clouds, the variable mass ratio between liquid water and ice as well as the spatial distribution within the cloud plays an important role in cloud lifetime, precipitation processes, and the radiation budget. Data sets of vertically pointing Doppler cloud radars and lidars provide insights into cloud properties at high temporal and spatial resolution. Cloud radars are able to penetrate multiple liquid layers and can potentially be used to expand the identification of cloud phase to the entire vertical column beyond the lidar signal attenuation height, by exploiting morphological features in cloud radar Doppler spectra that relate to the existence of supercooled liquid. We present VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn), a retrieval based on deep convolutional neural networks (CNNs) mapping radar Doppler spectra to the probability of the presence of cloud droplets (CD). The training of the CNN was realized using the Cloudnet processing suite as supervisor. Once trained, VOODOO yields the probability for CD directly at Cloudnet grid resolution. Long-term predictions of 18 months in total from two mid-latitudinal locations, i.e., Punta Arenas, Chile (53.1 S, 70.9 W), in the Southern Hemisphere and Leipzig, Germany (51.3 N, 12.4 E), in the Northern Hemisphere, are evaluated. Temporal and spatial agreement in cloud-droplet-bearing pixels is found for the Cloudnet classification to the VOODOO prediction. Two suitable case studies were selected, where stratiform, multi-layer, and deep mixed-phase clouds were observed. Performance analysis of VOODOO via classification-evaluating metrics reveals precision > 0.7, recall ≈ 0.7, and accuracy ≈ 0.8. Additionally, independent measurements of liquid water path (LWP) retrieved by a collocated microwave radiometer (MWR) are correlated to the adiabatic LWP, which is estimated using the temporal and spatial locations of cloud droplets from VOODOO and Cloudnet in connection with a cloud parcel model. This comparison resulted in stronger correlation for VOODOO (≈ 0.45) compared to Cloudnet (≈ 0.22) and indicates the availability of VOODOO to identify CD beyond lidar attenuation. Furthermore, the long-term statistics for 18 months of observations are presented, analyzing the performance as a function of MWR-LWP and confirming VOODOO's ability to identify cloud droplets reliably for clouds with LWP > 100 g m-2. The influence of turbulence on the predictive performance of VOODOO was also analyzed and found to be minor. A synergy of the novel approach VOODOO and Cloudnet would complement each other perfectly and is planned to be incorporated into the Cloudnet algorithm chain in the near future.
CAMP: An instrumented platform for balloon-borne aerosol particle studies in the lower atmosphere
2022, Pilz, Christian, Düsing, Sebastian, Wehner, Birgit, Müller, Thomas, Siebert, Holger, Voigtländer, Jens, Lonardi, Michael
Airborne observations of vertical aerosol particle distributions are crucial for detailed process studies and model improvements. Tethered balloon systems represent a less expensive alternative to aircraft to probe shallow atmospheric boundary layers (ABLs). This study presents the newly developed cubic aerosol measurement platform (CAMP) for balloon-borne observations of aerosol particle microphysical properties. With an edge length of 35 cm and a weight of 9 kg, the cube is an environmentally robust instrument platform intended for measurements at low temperatures, with a particular focus on applications in cloudy Arctic ABLs. The aerosol instrumentation on board CAMP comprises two condensation particle counters with different lower detection limits, one optical particle size spectrometer, and a miniaturized absorption photometer. Comprehensive calibrations and characterizations of the instruments were performed in laboratory experiments. The first field study with a tethered balloon system took place at the Leibniz Institute for Tropospheric Research (TROPOS) station in Melpitz, Germany, in the winter of 2019. At ambient temperatures between-8 and 15 C, the platform was operated up to a 1.5 km height on 14 flights under both clear-sky and cloudy conditions. The continuous aerosol observations at the ground station served as a reference for evaluating the CAMP measurements. Exemplary profiles are discussed to elucidate the performance of the system and possible process studies. Based on the laboratory instrument characterizations and the observations during the field campaign, CAMP demonstrated the capability to provide comprehensive aerosol particle measurements in cold and cloudy ABLs.
Management-induced changes in soil organic carbon on global croplands
2022, Karstens, Kristine, Bodirsky, Benjamin Leon, Dietrich, Jan Philipp, Dondini, Marta, Heinke, Jens, Kuhnert, Matthias, Müller, Christoph, Rolinski, Susanne, Smith, Pete, Weindl, Isabelle, Lotze-Campen, Hermann, Popp, Alexander
Soil organic carbon (SOC), one of the largest terrestrial carbon (C) stocks on Earth, has been depleted by anthropogenic land cover change and agricultural management. However, the latter has so far not been well represented in global C stock assessments. While SOC models often simulate detailed biochemical processes that lead to the accumulation and decay of SOC, the management decisions driving these biophysical processes are still little investigated at the global scale. Here we develop a spatially explicit data set for agricultural management on cropland, considering crop production levels, residue returning rates, manure application, and the adoption of irrigation and tillage practices. We combine it with a reduced-complexity model based on the Intergovernmental Panel on Climate Change (IPCC) tier 2 method to create a half-degree resolution data set of SOC stocks and SOC stock changes for the first 30 cm of mineral soils. We estimate that, due to arable farming, soils have lost around 34.6 GtC relative to a counterfactual hypothetical natural state in 1975. Within the period 1975-2010, this SOC debt continued to expand by 5 GtC (0.14 GtCyr-1) to around 39.6 GtC. However, accounting for historical management led to 2.1 GtC fewer (0.06 GtCyr-1) emissions than under the assumption of constant management. We also find that management decisions have influenced the historical SOC trajectory most strongly by residue returning, indicating that SOC enhancement by biomass retention may be a promising negative emissions technique. The reduced-complexity SOC model may allow us to simulate management-induced SOC enhancement - also within computationally demanding integrated (land use) assessment modeling.
Comparison of particle number size distribution trends in ground measurements and climate models
2022, Leinonen, Ville, Kokkola, Harri, Yli-Juuti, Taina, Mielonen, Tero, Kühn, Thomas, Nieminen, Tuomo, Heikkinen, Simo, Miinalainen, Tuuli, Bergman, Tommi, Carslaw, Ken, Decesari, Stefano, Fiebig, Markus, Hussein, Tareq, Kivekäs, Niku, Krejci, Radovan, Kulmala, Markku, Leskinen, Ari, Massling, Andreas, Mihalopoulos, Nikos, Mulcahy, Jane P., Noe, Steffen M., van Noije, Twan, O'Connor, Fiona M., O'Dowd, Colin, Olivie, Dirk, Pernov, Jakob B., Petäjä, Tuukka, Seland, Øyvind, Schulz, Michael, Scott, Catherine E., Skov, Henrik, Swietlicki, Erik, Tuch, Thomas, Wiedensohler, Alfred, Virtanen, Annele, Mikkonen, Santtu
Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.