Disentangling the impact of air-sea interaction and boundary layer cloud formation on stable water isotope signals in the warm sector of a Southern Ocean cyclone

Stable water isotopes in marine boundary layer water vapour are strongly influenced by the strength of air–sea fluxes. Air–sea fluxes in the extratropics are modulated by the large-scale atmospheric flow, for instance by the advection of warm and moist air masses in the warm sector of extratropical cyclones. A distinct isotopic composition of the water vapour in the latter environment has been observed over the Southern Ocean during the 2016/2017 Antarctic Circumnavigation Expedition (ACE). Most prominently, the secondary isotope variable deuterium excess (d=δ2H–8⋅δ18O) shows negative values in the cyclones’ warm sector. In this study, three mechanisms are proposed and evaluated to explain these observed negative d values. We present three single-process air parcel models, which simulate the evolution of δ2H, δ18O, d and specific humidity in an air parcel induced by decreasing ocean evaporation, dew deposition and upstream cloud formation. Simulations with the isotope-enabled numerical weather prediction model COSMOiso, which have previously been validated using observations from the ACE campaign, are used to (i) validate the air parcel models, (ii) quantify the relevance of the three processes for stable water isotopes in the warm sector of the investigated extratropical cyclone and (iii) study the extent of non-linear interactions between the different processes. This analysis shows that we are able to simulate the evolution of d during the air parcel's transport in a realistic way with the mechanistic approach of using single-process air parcel models. Most importantly, we find that decreasing ocean evaporation and dew deposition lead to the strongest d decrease in near-surface water vapour in the warm sector and that upstream cloud formation plays a minor role. By analysing COSMOiso backward trajectories we show that the persistent low d values observed in the warm sector of extratropical cyclones are not a result of material conservation of low d. Instead, the latter Eulerian feature is sustained by the continuous production of low d values due to air–sea interactions in new air parcels entering the warm sector. These results improve our understanding of the relative importance of air–sea interaction and boundary layer cloud formation on the stable water isotope variability of near-surface marine boundary layer water vapour. To elucidate the role of hydrometeor–vapour interactions for the stable water isotope variability in the upper parts of the marine boundary layer, future studies should focus on high-resolution vertical isotope profiles.publishedVersio

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90ĝ€¯d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and "hotspots"of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question

Disentangling the impact of air-sea interaction and boundary layer cloud formation on stable water isotope signals in the warm sector of a Southern Ocean cyclone

Stable water isotopes in marine boundary layer water vapour are strongly influenced by the strength of air-sea fluxes. Air-sea fluxes in the extratropics are modulated by the large-scale atmospheric flow, for instance by the advection of warm and moist air masses in the warm sector of extratropical cyclones. A distinct isotopic composition of the water vapour in the latter environment has been observed over the Southern Ocean during the 2016/2017 Antarctic Circumnavigation Expedition (ACE). Most prominently, the secondary isotope variable deuterium excess (d =delta H-2-8 center dot delta O-18) shows negative values in the cyclones' warm sector. In this study, three mechanisms are proposed and evaluated to explain these observed negative d values. We present three single-process air parcel models, which simulate the evolution of delta H-2, delta O-18, d and specific humidity in an air parcel induced by decreasing ocean evaporation, dew deposition and upstream cloud formation. Simulations with the isotope-enabled numerical weather prediction model COSMOiso, which have previously been validated using observations from the ACE campaign, are used to (i) validate the air parcel models, (ii) quantify the relevance of the three processes for stable water isotopes in the warm sector of the investigated extratropical cyclone and (iii) study the extent of non-linear interactions between the different processes. This analysis shows that we are able to simulate the evolution of d during the air parcel's transport in a realistic way with the mechanistic approach of using single-process air parcel models. Most importantly, we find that decreasing ocean evaporation and dew deposition lead to the strongest d decrease in near-surface water vapour in the warm sector and that upstream cloud formation plays a minor role. By analysing COSMOiso backward trajectories we show that the persistent low d values observed in the warm sector of extratropical cyclones are not a result of material conservation of low d. Instead, the latter Eulerian feature is sustained by the continuous production of low d values due to air-sea interactions in new air parcels entering the warm sector. These results improve our understanding of the relative importance of air-sea interaction and boundary layer cloud formation on the stable water isotope variability of near-surface marine boundary layer water vapour. To elucidate the role of hydrometeor-vapour interactions for the stable water isotope variability in the upper parts of the marine boundary layer, future studies should focus on high-resolution vertical isotope profiles.ISSN:1680-7375ISSN:1680-736

The effect of 3°C global warming on hail in Europe

Hail is a severe weather phenomenon in the Alpine region causing extensive damage to life and infrastructure. However, it is still unclear how hail events change in a future warmer climate. In the scClim project, we conducted convection-permitting regional climate simulations over Europe using the model COSMO with a ∼ 2.2 km horizontal resolution. The simulations encompass both present-day climate conditions for 2011–2021 and a climate scenario with a 3◦C global warming using a pseudo-global-warming approach. ERA5 reanalyses were used as boundary conditions and a CMIP6 simulation (MPI-ESM1-2-HR) for the large-scale climate-change signal. The simulations, with integrated online diagnostics for hail and lighting, provide total precipitation and maximum hail size estimates every 5 minutes, together with the maximum hourly lightning potential. This detailed model output allows for hail cell tracking in the climate simulations and the analysis of hail events in a warmer climate. The present-day simulation has been validated against observations of temperature, precipitation, hail and lightning. For hail in particular, the model validation with radar-based, station-based and crowd-sourced observations shows an overall good model performance in simulating hail on spatial, diurnal and seasonal scales. This allows further study of the climate signal of hail as simulated with the pseudo-global-warming approach. We plan to show first results of the simulation with a 3◦C global warming, namely, the changes in the spatial distribution and seasonal cycle of hail in Europe as well as the lifetime, storm area and location of hail cells

Using global reanalysis data to quantify and correct airflow distortion bias in shipborne wind speed measurements

At sea, wind forcing is responsible for the formation and development of surface waves and represents an important source of near-surface turbulence. Therefore, processes related to near-surface turbulence and wave breaking, such as sea spray emission and air–sea gas exchange, are often parameterised with wind speed. Thus, shipborne wind speed measurements provide highly relevant observations. They can, however, be compromised by flow distortion due to the ship's structure and objects near the anemometer that modify the airflow, leading to a deflection of the apparent wind direction and positive or negative acceleration of the apparent wind speed. The resulting errors in the estimated true wind speed can be greatly magnified at low wind speeds. For some research ships, correction factors have been derived from computational fluid dynamic models or through direct comparison with wind speed measurements from buoys. These correction factors can, however, lose their validity due to changes in the structures near the anemometer and, thus, require frequent re-evaluation, which is costly in either computational power or ship time. Here, we evaluate if global atmospheric reanalysis data can be used to quantify the flow distortion bias in shipborne wind speed measurements. The method is tested on data from the Antarctic Circumnavigation Expedition onboard the R/V Akademik Tryoshnikov, which are compared to ERA-5 reanalysis wind speeds. We find that, depending on the relative wind direction, the relative wind speed and direction measurements are biased by −37 % to +22 % and -17∘ to +11∘ respectively. The resulting error in the true wind speed is +11.5 % on average but ranges from −4 % to +41 % (5th and 95th percentile). After applying the bias correction, the uncertainty in the true wind speed is reduced to ±5 % and depends mainly on the average accuracy of the ERA-5 data over the period of the experiment. The obvious drawback of this approach is the potential intrusion of model biases in the correction factors. We show that this problem can be somewhat mitigated when the error propagation in the true wind correction is accounted for and used to weight the observations. We discuss the potential caveats and limitations of this approach and conclude that it can be used to quantify flow distortion bias for ships that operate on a global scale. The method can also be valuable to verify computational fluid dynamic studies of airflow distortion on research vessels

Seamless coupling of kilometer-resolution weather predictions and climate simulations with hail impact assessments for multiple sectors (scClim)

Hail is a significant contributor to weather-related damages in Switzerland, driving a demand for actionable information on hail risks across sectors in current and future climate. The ongoing research project scClim (https://scclim.ethz.ch/) addresses this demand, uniting complementary expertise to establish a seamless model chain from observing and modeling the weather and climate to the quantification of hail impacts on agriculture, buildings, and cars. In this talk, an overview of the interdisciplinary research project is provided. The project is structured into five strongly interconnected subprojects. Subproject A engages in a close dialogue with key stakeholders to co-design a hail impact assessment platform, incorporating outcomes from the other subproject for practical applications. Subproject B develops an algorithm to track hail cells and applies it to operational weather forecasts and climate simulations to investigate hail cell characteristics. The kilometer-scale convection-permitting climate simulations over Europe are conducted with the regional model COSMO, with the HAILCAST hail growth model embedded. These simulations provide case studies and a 10-year climatology of present-day conditions and a 3◦C global warming scenario using a pseudoglobal-warming approach. Subproject C generates a multi-decadal time series of past hailday occurrences in the Swiss radar domain to identify the drivers of inter-annual hail variability and changes in hail seasonality. Additionally, it explores the potential of polarimetric data from the Swiss weather radar network to provide information about the probability and size of hail on the ground. Subprojects D and E construct hail damage models for crops, buildings, and cars to extend the open-source impact modeling platform CLIMADA. The applied vulnerability curves are calibrated with damage data from 2002 to 2021, which was obtained from insurance companies. Ultimately, the developed framework is used to assess the implications of climate change for future hail risks in the addressed sectors

Influences of sources and weather dynamics on atmospheric deposition of Se species and other trace elements

Atmospheric deposition is an important source of the micronutrient selenium for terrestrial ecosystems and food chains. However, the factors determining the total concentrations and chemical forms (speciation) of selenium in atmospheric deposition remain poorly understood. Here, aerosol samples were collected weekly over 5 years at Pic du Midi Observatory (French Pyrenees), alongside highly temporally resolved samples of aerosols, precipitation, and cloud water taken during a 2-month campaign. Firstly, measurements of selenium, other elements, and water isotopes were combined with sophisticated modelling approaches (aerosol-chemistry-climate SOCOL-AERv2 model and air parcel backward trajectories and Lagrangian moisture source analyses). Aerosol selenium measurements agreed well with SOCOL-AERv2-predicted values, and interestingly, higher fluxes of selenium and other elements were associated with deep convective activity during thunderstorms, highlighting the importance of local cloud dynamics in high deposition fluxes. Our results further indicate the coupling of element and water cycles from source to cloud formation, with decoupling during precipitation due to below-cloud scavenging. Secondly, selenium speciation was investigated in relation to sulfur speciation, organic composition, and moisture sources. While in the 5-year aerosol series, selenite (SeIV) was linked to anthropogenic source factors, in wet deposition it was related to pH and Atlantic moisture sources. We also report an organic selenium fraction, tracing it back to a marine biogenic source in both aerosols and wet deposition. With a comprehensive set of observations and model diagnostics, our study underscores the role of weather system dynamics alongside source contributions in explaining the atmospheric supply of trace elements to surface environments.ISSN:1680-7375ISSN:1680-736

Influences of sources and weather dynamics on atmospheric deposition of Se species and other trace elements

Atmospheric deposition is an important source of the essential trace element selenium (Se) to terrestrial ecosystems and food chains. The fate of Se supplied to surface environments by atmospheric deposition strongly depends on total Se concentrations as well as its chemical form (speciation). However, the factors determining total Se and its speciation in atmospheric deposition remain poorly understood. Here, we applied different chemical measurements to aerosol samples taken at a weekly resolution over 5 years (2015–2019), as well as precipitation and cloud water samples taken during a field campaign of two months in 2019 at Pic du Midi Observatory (French Pyrenees; 2877 m a.s.l.) and combined these observations with sophisticated modelling approaches. The high-altitude site enables the investigation of local and long-range elemental transport from both marine and continental sources and the role of different weather systems in elemental deposition. Total concentrations of trace elements were measured in aerosol extracts and wet deposition, and Se speciation was obtained with an optimized chromatographic method coupled to inductively coupled plasma tandem mass spectrometry (LC-ICP-MS/MS). These analyses were combined with molecular organic compound analysis by pyrolysis-gas chromatography mass spectrometry (Py-GC-MS). For modelling the source contributions to Se, we used a combination of i) a Eulerian approach with the atmospheric aerosol-chemistry-climate model SOCOL-AERv2, and ii) a Lagrangian approach with air parcel backward trajectories and a moisture source diagnostics. While weekly Se measurements in the 2015–2020 aerosol time series agreed very well (r~0.8) with SOCOL-AERv2 model results, the higher Se concentrations (>0.05 ng·m-3) observed in summer were underestimated by the model. We could explain these higher concentrations in summer by convection related to thunderstorms that led to high aerosol loadings and which are not resolved explicitly in the model. In addition, convective events, associated with continental moisture sources, also explained the highest concentrations of Se and most other trace elements in wet deposition, due to efficient below cloud scavenging, indicating the importance of local cloud dynamics on the supply of Se and other, essential and non-essential, trace elements to surface environments. While data for water isotopes in precipitation indicated an uncoupling of hydrological and trace element cycling related to below cloud scavenging, cloud water isotopes and trace elements showed high correlations indicating that the water and trace element cycles are strongly coupled from the source to the formation of clouds with a possible decoupling occurring during precipitation. Furthermore, cloud water showed more regional trace element and moisture sources than precipitation samples. With this comprehensive set of observations and model diagnostics we could explain inorganic Se speciation in unprecedented detail by linking moisture sources and organic chemical compounds in aerosols to speciation data of Se and S, indicating local vs long-range transport and anthropogenic vs natural Se sources. We report for the first-time organic Se in precipitation (and aerosols), for which we could elucidate a marine biogenic source. Our study thus provides new insights into the factors explaining atmospheric deposition of Se and other trace elements and highlights the importance of weather system dynamics in addition to source contributions for the atmospheric supply of trace elements to surface environments

Precipitation over the Southern Ocean: comparison of several ship-based measurement techniques during the Antarctic Circumnavigation Expedition

Published in: Geophysical Research Abstracts. Vol. 21, EGU2019-15209, 2019 - EGU General Assembly 2019. © Author(s) 2019. CC Attribution 4.0 license