| 1. |
- Bengtsson, Lars, et al.
(författare)
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Long- term change of daily and multi- daily precipitation in southern Sweden
- 2014
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Ingår i: Hydrological Processes. - : Wiley. - 1099-1085 .- 0885-6087. ; 28:6, s. 2897-2911
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Tidskriftsartikel (refereegranskat)abstract
- Daily rain series from southern Sweden with records dating back to the 1870s have been analysed to investigate the trends of daily and multi-day precipitation of different return periods with emphasis on the extremes. Probabilities of extreme storms were determined as continuously changing values based on 25 years of data. An extra set of data was used to investigate changes in Skane, the southernmost peninsula of Sweden. Another 30-year data set of more than 200 stations of a dense gauge network in Skane was used to investigate the relation between very large daily rainfall and annual precipitation. The annual precipitation has increased significantly all over southern Sweden due to increased winter precipitation. There is a trend of increasing maximum annual daily precipitation at only one station, where the annual maximum often occurs in winter. The number of events with a short return period is increasing, but the number of more extreme events has not increased. Daily and multi-daily design storms of long return periods determined from extreme value analysis with updating year by year are not higher today than during the last 100 years. The largest daily storms are not related to stations with annual rainfall but seem to occur randomly. Copyright (c) 2013 John Wiley & Sons, Ltd.
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| 2. |
- Notz, Dirk, et al.
(författare)
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Arctic Sea Ice in CMIP6
- 2020
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Ingår i: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 47:10
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Tidskriftsartikel (refereegranskat)abstract
- We examine CMIP6 simulations of Arctic sea‐ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea‐ice area, capturing the observational estimate within the multimodel ensemble spread. The CMIP6 multimodel ensemble mean provides a more realistic estimate of the sensitivity of September Arctic sea‐ice area to a given amount of anthropogenic CO2 emissions and to a given amount of global warming, compared with earlier CMIP experiments. Still, most CMIP6 models fail to simulate at the same time a plausible evolution of sea‐ice area and of global mean surface temperature. In the vast majority of the available CMIP6 simulations, the Arctic Ocean becomes practically sea‐ice free (sea‐ice area <1 × 106 km2) in September for the first time before the Year 2050 in each of the four emission scenarios SSP1‐1.9, SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5 examined here.
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| 3. |
- Persson, Peter, et al.
(författare)
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Lessons of Feedback in Higher Education in Sweden
- 2018
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Ingår i: 10:e Pedagogiska Inspirationskonferensen 2018. - 2003-3761 .- 2003-377X. ; 10
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Lessons learned in the feedback process are atwo-sided coin that ultimately guide the PhD candidatetowards becoming an independent researcher as well aseducating “reader/docents” in their role as supervisor.Building on a brief literature review, observations from 14interviewed PhD candidates were reflected upon and these arethe suggested lessons learned. The study’s preliminary findingssuggest that feedback is most productive when it is organized,systematic, and tends to offer guidance rather than directinstruction. Perhaps of greatest significance is the need to haveconsistent dialogue about the feedback’s form and contentbetween student and supervisor(s).
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| 4. |
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| 5. |
- Rana, Arun
(författare)
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Climate Change Effects on Rainfall and Management of Urban Flooding
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Flooding in urban basins is intensifying due to increasing urbanization and climate change and variability. This thesis presents how the effects of climate change and high-intensive rainfall on the urban drainage system and management of flooding in urban areas of were studied in Mumbai, India and Southern Sweden, including Skåne and Gothenburg. Various statistical and analytical tools were applied to study trends and extreme events in two study areas. The impact of climate change on Mumbai was studied using nine GCM simulations with bias correction using DBS methodology. For Gothenburg, RCM output and observations were used to predict the characteristics of rainfall. Through use of transient DBS processed projection data, an impact analysis (climate and extreme value statistics) was performed for the future period of the years 2010 to 2099. Trend analysis using the student t-test and the Mann-Kendall test was also performed. Further, Random Cascade modelling was applied on daily rainfall data to reproduce high temporal resolution data for Mumbai. The method can be used for development of IDF curves. The generated data were used for flood modelling in the area and the generation of flood maps. Trends for monthly, seasonal, and annual precipitation were studied for Mumbai (1951-2004). For Southern Sweden, daily and multi-day precipitation trends were studied. Long-term precipitation trends were determined using the Mann-Kendall test, the student t-test, and linear regression. The trends for rainfall in Mumbai were corroborated with climatic indices using multivariate statistical tools, namely PCA and SVD. PCA was also used for explaining variability in RCM-generated precipitation in Gothenburg. Analytical analyses were made of the drainage systems in Mumbai and Gothenburg. Finally, an integrated two dimensional (2D) hydrodynamic runoff model was used to simulate storm-water flooding and related processes in the metropolitan areas of Mumbai, India. The analysis revealed a high degree of variability in rainfall over Mumbai. A significant decreasing trend for long-term southwest monsoon rainfall was found. Also, a decrease in average maximum daily rainfall was indicated. The southwest monsoon rainfall over Mumbai was found to be inversely related to the Indian Ocean dipole, the El Ninõ-Southern Oscillation, and the East Atlantic Pattern. In Southern Sweden, however, annual precipitation has increased significantly due to increasing winter precipitation. There is an increasing trend for maximum annual daily precipitation at one location where the annual maximum often occurs in winter. The number of events with short return periods is increasing, but the number of other extreme events has not increased. Evaluation of the baseline period using the DBS bias correction method showed that observed and scaled rainfall data are strongly correlated and that these can represent various key statistics including mean, variance, and extreme values. The analysis of future long-term climate projections revealed a positive significant trend for 4 out of 9 model simulations for daily extreme rainfall during the period 2010-2099. In the case of Gothenburg, the results obtained pointed towards the usefulness of high resolution RCMs for impact studies. In random cascade modelling, very good agreement between modelled and observed disaggregation rainfall series was found for time scales larger than 1/2 h when short-term data were available. Established IDF-curves showed that the current design standard for Mumbai City has a return period of less than one year. Thus, annual recurring flooding problems in Mumbai appear evident. This was further emphasized in results from flood modelling and analytical studies.
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| 6. |
- Rana, Arun, et al.
(författare)
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Contrasting regional and global climate simulations over South Asia
- 2020
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Ingår i: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 54:5-6, s. 2883-2901
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Tidskriftsartikel (refereegranskat)abstract
- Two ensembles of climate simulations, one global and one regional, are used to investigate model errors and projected climate change in seasonal mean temperature and precipitation over South Asia. The global ensemble includes ten global climate models (GCMs). In the regional ensemble all ten GCMs are downscaled by a regional climate model-RCA4 over South Asia at 50 km resolution. Our focus is on the Indian Summer Monsoon season (June-August) and we show that RCA4 can reproduce, reduce or amplify large-scale GCM biases depending on regions and GCMs. However, the RCA4 bias pattern in precipitation is similar across the simulations, regardless of forcing GCM, indicating a strong RCA4 imprint on the simulated precipitation. For climate change, the results indicate, that RCA4 can change the signal projected by the GCM ensemble and its individual members. There are a few RCA4 simulations with a substantial reduction of projected warming by RCA4 compared to the driving GCMs and with a large regional increase in precipitation absent in the GCMs. We also found that in a number of subregions warm RCA4 biases are related to stronger warming and vice versa, while there is no such dependency in the GCM ensemble. Neither the GCM nor the RCA4 ensemble shows any significant dependency between projected changes and biases for precipitation. Our results implicate that using only RCMs and excluding GCMs, a commonly established approach, can significantly change the message on future regional climate change.
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| 7. |
- Rana, Arun, et al.
(författare)
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Development of IDF-curves for tropical india by random cascade modeling
- 2013
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Ingår i: Hydrology and Earth System Sciences Discussions. - : Copernicus GmbH. - 1812-2108. ; 10:4, s. 4709-4738
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Tidskriftsartikel (refereegranskat)abstract
- Efficient design of urban drainage systems is based on statistical analysis of past rainfall events at fine time scales. However, fine time scale rainfall data are usually lacking in many parts of the world. A possible way forward is to develop methods to derive fine time scale rain intensities from daily observations. This paper applied cascade-based disaggregation modeling for generation of fine time scale rainfall data for Mumbai, India from daily rainfall data. These data were disaggregated to 10-min values. The model was used to disaggregate daily data for the period 1951–2004 and develop intensity-duration-frequency (IDF) relationships. This disaggregation technique is commonly used assuming scale-invariance using constant parameters. For the Mumbai rains it was found better to use parameters dependent on time scale and rain volume. Very good agreement between modeled and observed disaggregation series was found for the time scales larger than 1/2 h for the 1/2-yr period when short term data were available. Although the parameters were allowed to change with time scale, the rain intensities of duration shorter than 1/2 h were overestimated. When IDF-curves had been established, they showed that the current design standard for Mumbai city, 25 mm h−1, has a return period of less than one year. Thus, annual recurring flooding problems in Mumbai appear evident.
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| 8. |
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| 9. |
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| 10. |
- Rana, Arun, et al.
(författare)
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Performance evaluation of regional climate models (RCMs) in determining precipitation characteristics for Gothenburg, Sweden
- 2014
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Ingår i: Hydrology Research. - : IWA Publishing. - 1998-9563 .- 0029-1277 .- 2224-7955. ; 45:4-5, s. 703-714
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Tidskriftsartikel (refereegranskat)abstract
- Regional climate models (RCMs) are used for forecasting future climate including precipitation characteristics. Performances of five different RCMs for predicting the precipitation characteristics for Gothenburg, Sweden were evaluated against the daily observed precipitation over the period 1961 to 2009. Statistical analysis was done on annual, monthly, multi-daily, and daily data. The statistical techniques used include principal component analysis (PCA), comparison of annual maximum, frequency of exceedances determined from Poisson distribution, comparison of frequency distributions, and Mann-Kendall technique for investigating trend over time. Inter-annual variability and autocorrelation between years were also investigated. The results obtained point towards the usefulness of these high-resolution RCMs. It was observed that all the models give the annual maximum precipitation within 3 mm of the observed data. As for the observed series, no trends were found for monthly or seasonal data. The number of exceedances above threshold accepted Poisson distribution hypothesis with the mean exceedances from RCM-PROMES being very close to the mean exceedances from the observed data. PCA also indicated that PROMES came closest to explaining the observed data. The presented statistical methods can be used for bias correction of raw RCM data in future studies.
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