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- Hosseini, Seyyed Hasan, et al.
(author)
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Evaluation of a new X-band weather radar for operational use in south Sweden
- 2020
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In: Water Science and Technology. - : IWA Publishing. - 0273-1223 .- 1996-9732. ; 81:8, s. 1623-1635
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Journal article (peer-reviewed)abstract
- The performance of a new type of X-band Weather Radar (WR) for Sweden during a pilot run is studied. Compared to the conventional C-band WRs, the X-band WR covers a smaller area but with a higher spatiotemporal resolution, making it suitable for urban hydrological applications. Rainfall estimations from different elevation angles of the radar (levels) are compared at one-minute and single-event timescales with the observations of several rain gauges at different ranges using hyetographs. In general, the estimations aligned well with observations and the best match appeared for ranges as long as 5–10 km. Seemingly, radar estimations suffered from overshooting of lower lying showers by higher level scans in longer ranges (19–30 km) and from the reflectivity contamination due to moving objects in short ranges (<1 km). Also, the effective range of the radar dropped sharply for the moments when a cloudburst was located over the radar. Although various sources of error could affect the X-band WR rainfall estimates, higher resolution spatiotemporal rainfall monitoring for wider areas will benefit from an integration of data from a network of X-band WRs.
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| 2. |
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| 3. |
- Hosseini, Seyyed Hasan, et al.
(author)
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Kombinerade X-bandsanläggningar som väderradar : Jämförelse med etablerade metoder för regnmätning
- 2022
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Reports (other academic/artistic)abstract
- In this research report, a new methodology has been developed in order to integrate several X-band radar data sets in to one complete set. Furthermore, a direct and an indirect evaluation have been conducted compared to stationary rain gauges and C-band radar. In the indirect analysis, the input data sets were integrated into runoff models for Ellinge and Lundåkra WWTP where the results were compared to measured incoming flow to the sewage plants.
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| 4. |
- Karagiorgos, Konstantinos, et al.
(author)
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Rain data crowdsourcing for improving urban flood risk management : Exploring the potential in Sweden
- 2022
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Conference paper (peer-reviewed)abstract
- <p>Urban flooding causes considerable societal damage and necessitates increased climate adaptation measures. Extreme rain events' rapid and local character make them difficult to observe, assess, predict, and warn about. One example is the flood event in Malm&#246; in 2014, not only in terms of rain intensities and volumes but also the fact that the more intense parts of the rainfall fell across central Malm&#246; with adverse consequences (approx. SEK 100 million for 1400 claims). &#160;These extreme hydrological events are generally predicted to become more frequent and damaging in Sweden due to the warming climate.</p><p>The overarching aim of this study is to develop an approach to improve urban rain safety by establishing a participatory system for collecting data to support urban flood risk modelling for the adaptation of cities to intense rainfall. Nowadays, meteorological information to improve flood risk modelling can be obtained from non-traditional sources such as privately owned weather stations and social media. Crowdsourcing techniques linked to public engagement via citizen science are frequently used across different scientific areas to supplement traditional data collection.</p><p>Our analysis compiles data from available platforms (WeatherObervationWebsite (WOW) by SMHI, Netatmo platform and WunderMap website) for different case studies. The data will be organised in databases; and validated with SMHI-certified automatic rain gauges, municipal gauges, radar data and integrated gridded products.</p><p>The approach presented opens up insights into the measurement accuracy and issues in operational crowdsourcing of private rain measurements. The new type of rain data will be used for testing their applicability with flood models. The particular focus in the testing will be on the effect of model output from added spatial resolution in rain measurements.</p>
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| 5. |
- Nyberg, Lars, et al.
(author)
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New data sources for cloudburst risk assessment and management
- 2022
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In: Vatten: tidskrift för vattenvård /Journal of Water Management and research. - 0042-2886. ; 78:2
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Journal article (other academic/artistic)abstract
- Urban flooding causes large societal damages and increased climate adaptation measures is needed. Therapid and local character of extreme rain events make them difficult to observe and predict, and to issuewarnings for. There is also a lack of data on urban flood damages, mainly because of scarce and nonsystematic data collection and management. In this paper, we present the approaches behind the new research project SPARC. The overarching aim of the project is to improve urban rain safety by establishinga participatory system for crowdsourcing of data, to support urban flood risk modelling and adaptation ofcities to intense rainfall. The project will also investigate flood damage mechanisms on the built environment as well as evaluate and communicate small-scale adaptation measures. Municipal water and wastewater utility organizations and insurance industry representatives will be included in a trans-disciplinaryprocess, also including crowdsourcing in a citizen science approach.
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| 6. |
- Westerberg, Marcus, 1990-
(author)
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Prostate cancer incidence, treatment and mortality : Empirical longitudinal register-based studies and methods for handling missing data
- 2022
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Doctoral thesis (other academic/artistic)abstract
- The diagnostic activity for prostate cancer has increased substantially in Sweden, primarily due to increased use of prostate-specific antigen (PSA) testing in asymptomatic men, and this has led to a large increase in diagnoses. There have also been changes in the diagnostic workup, guidelines, treatment strategies, and more effective treatments have been introduced in different phases of the disease. This thesis aims to increase the understanding of consequences of changes in diagnostic activity and treatment, with a focus on empirical studies, methodological development, and handling of missing data.In paper I, the survival of men with metastatic prostate cancer was investigated across calendar time periods by use of Kaplan-Meier analyses and Cox regression. The median survival from diagnosis increased with six months comparing men diagnosed 1998-2001 with men diagnosed 2010-2015, while median PSA decreased.In paper II, a discrete time multivariate longitudinal model was combined with a proxy for the unobserved level of diagnostic activity to produce prognoses of incidence and mortality. Simulations indicated that a higher diagnostic activity was associated with fewer men diagnosed with metastatic disease and fewer prostate cancer deaths.In paper III, we looked for clinical variables predictive of the survival of men with castration-resistant prostate cancer (CRPC). A new data base was created including longitudinal data on prescriptions of hormonal treatment, PSA, and cause of death. We found that PSA doubling time and PSA at time of CRCP were highly predictive and could be used for treatment decision.In paper IV, we estimated annual incidence of metastatic prostate cancer using different methods for handling missing data in metastatic status (M stage). Missing data in M stage was high and varied over calendar time and risk groups, yet each method indicated a downward trend in incidence. Although men with unknown metastatic status cannot be assumed to have nonmetastatic disease in general, this may be reasonable among those with tumour characteristics that indicate a low risk of metastases.In paper V, the estimation of multivariate longitudinal models was considered in a context where some events are observed on a coarser level (e.g. grouped) at some time points, causing gaps in the data. The likelihood function, score and observed information were derived under an independent coarsening mechanism. A simulation study was conducted comparing properties of several estimators including direct maximum likelihood and Monte Carlo Expectation Maximisation.
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