| 1. |
- Ball, W. T., et al.
(author)
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The Upper Stratospheric Solar Cycle Ozone Response
- 2019
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In: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 46:3, s. 1831-1841
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Journal article (peer-reviewed)abstract
- The solar cycle (SC) stratospheric ozone response is thought to influence surface weather and climate. To understand the chain of processes and ensure climate models adequately represent them, it is important to detect and quantify an accurate SC ozone response from observations. Chemistry climate models (CCMs) and observations display a range of upper stratosphere (1-10 hPa) zonally averaged spatial responses; this and the recommended data set for comparison remains disputed. Recent data-merging advancements have led to more robust observational data. Using these data, we show that the observed SC signal exhibits an upper stratosphere U-shaped spatial structure with lobes emanating from the tropics (5-10 hPa) to high altitudes at midlatitudes (1-3 hPa). We confirm this using two independent chemistry climate models in specified dynamics mode and an idealized timeslice experiment. We recommend the BASIC(v2) ozone composite to best represent historical upper stratospheric solar variability, and that those based on SBUV alone should not be used. Plain Language Summary Changes in the output of the Sun are thought to influence surface weather and climate through a set of processes initiated by the enhancement of upper stratosphere (32-48 km) ozone. In order to understand and assess the solar impact on the climate system, it is important that models reproduce the observed solar signal. However, the recommended data set for comparison with climate models remains disputed. We use newly improved observed ozone composites to determine both why there is disagreement between composites and which is most likely to be correct. We find that artifact-corrected composites represent the response better than those based on SBUV data alone. Further, we identify a U-shaped spatial structure with lobes emanating from the tropics to high altitudes at midlatitudes. An idealized chemistry climate model experiment and simulations considering historical meteorological conditions both support this conclusion. The results are of benefit to satellite-instrument scientists and to those engaged in atmospheric and climate research using both observations and climate models. The results will be important for assessing the solar signal in currently active and future assessments of chemistry climate models (e.g., Chemistry-Climate Model Initiative). We recommend the BASICv2 ozone composite to best represent historical upper stratospheric variability.
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| 2. |
- Sofiev, M., et al.
(author)
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Designing an automatic pollen monitoring network for direct usage of observations to reconstruct the concentration fields
- 2023
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In: SCIENCE OF THE TOTAL ENVIRONMENT. - 0048-9697. ; 900
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Journal article (peer-reviewed)abstract
- We consider several approaches to a design of a regional-to-continent-scale automatic pollen monitoring network in Europe. Practical challenges related to the arrangement of such a network limit the range of possible solutions. A hierarchical network is discussed, highlighting the necessity of a few reference sites that follow an extended observations protocol and have corresponding capabilities. Several theoretically rigorous approaches to a network design have been developed so far. However, before starting the process, a network purpose, a criterion of its performance, and a concept of the data usage should be formalized. For atmospheric composition monitoring, developments follow one of the two concepts: a network for direct representation of concentration fields and a network for model-based data assimilation, inverse problem solution, and forecasting. The current paper demonstrates the first approach, whereas the inverse problems are considered in a follow-up paper. We discuss the approaches for the network design from theoretical and practical standpoints, formulate criteria for the network optimality, and consider practical constraints for an automatic pollen network. An application of the methodology is demonstrated for a prominent example of Germany's pollen monitoring network. The multi-step method includes (i) the network representativeness and (ii) redundancy evaluation followed by (iii) fidelity evaluation and improvement using synthetic data.
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