Claudia von Brömssen

A lot of my work is focused on research and support for reserachers and governmental agencies on statistical analysis for environmenta assessment data. My main intrest lies in statistical methodology for the analysis of temporal trends.

Since 2018 I am the manager of the centre for statistics at SLU. Between 2017 and 2023 I was the group leader of the group Applied statistics and mathematics at the Department of Energy and technology. 

Moreover, I work with statistical consultancy for researchers at SLU. Much of this work relates to the generalized linear and additive mixed model framework, as well as to experimental and study design. This part of my position is financed by the  centre for statistics.

I have been teaching on various levels anf for different programs at SLU and Linköpings universitet. At the moment I teach mainly statistics courses for Ph. D. students in other subjects than statistics. 

My reserach is about visualising and understanding patterns in environmental monitoring data with a focus on trend detection and analysis. I use data-driven statistical methods in order to not limit the analysis by setting unreasonable assumptions. My latest publications are about setting temporal trends in a spatial perspective with the goal to better understand which factors influence changes in time. 

My research is based on data from environmental monitoring data that are freely available. The goal is to create greater use of all information that is already available in collected data. To do this I develop new appropriate statistical methods that can be used for environmental monitoring data in Sweden.

I am Ph. D. in statistics (2003, Linköpings universitet). Since 2007 I work as senior lecturer at SLU. 2023 I became a docent in biomtry and in 2024 I was given the title 'excellent teacher' at SLU.

von Brömssen, C., Fölster J., Eklöf K., Temporal trend evaluation in monitoring programs with high spatial resolution and low temporal resolution using geographically weighted regression models, Environmental Monitoring and Assessment, 195, 2023. https://doi.org/10.1007/s10661-023-11172-2 

von Brömssen, C., Fölster J., Kyllmar K., Bieroza M., Modeling Complex Concentration-Discharge Relationships with Generalized Additive Models, Environmental Modeling and Assessment, 28, 2023. https://doi.org/10.1007/s10666-023-09915-z

von Brömssen, C., Betnér, S., Fölster, J., Eklöf, K., 2021. A toolbox for visualizing trends in large-scale environmental data. Environ. Model. Softw. 136, 104949. https://doi.org/10.1016/j.envsoft.2020.104949 

Eklöf K., von Brömssen C., Amvrosiadi N., Fölster J., Wallin M.B., Bishop K., Brownification on hold: What traditional analyses miss in extended surface water records, Water Research, 203, 2021. https://doi.org/10.1016/j.watres.2021.117544

von Brömssen, C., Röös, E., 2020. Why statistical testing and confidence intervals should not be used in comparative life cycle assessments based on Monte Carlo simulations. Int. J. Life Cycle Assess. https://doi.org/10.1007/s11367-020-01827-4 

von Brömssen C, Fölster J, Futter M, McEwan K. Statistical models for evaluating suspected artefacts in long-term environmental monitoring data. Environ Monit Assess (2018) 190: 558. https://doi.org/10.1007/s10661-018-6900-3

Grimvall Anders, Von Brömssen Claudia, Lindström Göran. Using process-based models to filter out natural variability in observed concentrations of nitrogen and phosphorus in river water . Environmental Monitoring And Assessment, 186 (8), pp.5135-5152. 2014. https://doi.org/10.1007/s10661-014-3765-y

Burauskaite-Harju A, Grimvall A and von Brömssen C. A test for network-wide trends in rainfall extremes. International Journal of Climatology, vol. 32 nr 1 86-9. 2012. https://doi.org/10.1002/joc.2263

Libiseller, C., Grimvall, A., 2002. Performance of partial Mann-Kendall tests for trend detection in the presence of covariates. Environmetrics 13, 71–84. https://doi.org/10.1002/env.507 

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