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arXiv

**Journal Articles**

- F Petropoulos, D Apiletti, V Assimakopoulos, M Z Babai, D K Barrow, S B Taieb, C Bergmeir, R J Bessa, J Bijak, J E Boylan, J Browell, C Carnevale, J L Castle, P Cirillo, M P Clements, C Cordeiro, F L C Oliveira, S de Baets, A Dokumentov, J Ellison, P Fiszeder, P H Franses, D T Frazier, M Gilliland, M S Gönül, P Goodwin, L Grossi, Y Grushka-Cockayne, M Guidolin, M Guidolin, U Gunter, X Guo, R Guseo, N Harvey, D F Hendry, R Hollyman, T Januschowski, J Jeon, V R R Jose, Y Kang, A B Koehler, S Kolassa, N Kourentzes, S Leva, F Li, K Litsiou, S Makridakis, G M Martin, A B Martinez, S Meeran, T Modis, K Nikolopoulos, D Önkal, A Paccagnini, A Panagiotelis, I Panapakidis, J M Pavía, M Pedio, D J Pedregal, P Pinson, P Ramos, D E Rapach, J J Reade, B Rostami-Tabar, M Rubaszek, G Sermpinis, H L Shang, E Spiliotis, A A Syntetos, P D Talagala, T S Talagala, L Tashman, D Thomakos, T Thorarinsdottir, E Todini, J R T Arenas, X Wang, R L Winkler, A Yusupova and F Ziel

Forecasting: theory and practice

*International Journal of Forecasting*, in press, 2022 [http] - S M Vandeskog, T L Thorarinsdottir, I Steinsland and F Lindgren

Quantile based modelling of diurnal temperature range with the five-parameter lambda distribution

*Environmetrics*, 33(4): e2719, 2022 [http] - T Roksvåg, J Lutz, L Grinde, A V Dyrrdal and T L Thorarinsdottir

Consistent intensity-duration-frequency curves by post-processing of estimated Bayesian posterior quantiles

*Journal of Hydrology*, 603(C):127000, 2021 [http] - Q Yuan, T L Thorarinsdottir, S Beldring, W K Wong and C-Y Xu

Bridging the scale gap: obtaining high-resolution stochastic simulations of gridded daily precipitation in a future climate

*Hydrology and Earth System Sciences*, 25: 5259-5275, 2021 [http] - F Krürger, S Lerch, T L Thorarinsdottir and T Gneiting

Predictive inference based on Markov chain Monte Carlo output

*International Statistical Review*, 89(2): 274-301, 2021 [http | arxiv] - C Heinrich, K H Hellton, A Lenkoski and T L Thorarinsdottir

Multivariate postprocessing methods for high-dimensional seasonal weather forecasts

*Journal of the American Statistical Association*, 116(535):1048-1059, 2021 [http | arxiv] - T L Thorarinsdottir, J Sillmann, M Haugen, N Gissibl and M Sandstad

Evaluation of CMIP5 and CMIP6 simulations of historical surface air temperature extremes using proper evaluation methods

*Environmental Research Letters*, 15:124041, 2020 [http] - M Jullum, T L Thorarinsdottir and F E Bachl

Estimating seal pup production in the Greenland Sea using Bayesian hierarchical modeling

*Journal of the Royal Statistical Society, Series C*, 69(2): 327-352, 2020 [http | arxiv] - O Haug, T L Thorarinsdottir, S H Soerbye and C L E Franzke

Spatial trend analysis of gridded temperature data at varying spatial scales

*Advances in Statistical Climatology, Meteorology and Oceanography*, 6: 1-12, 2020 [http | arxiv] - N Schuhen, T L Thorarinsdottir and A Lenkoski

Rapid adjustment and post-processing of temperature forecast trajectories

*Quarterly Journal of the Royal Meteorological Society*, 146: 963-978, 2020 [http | arxiv] - Q Yuan, T L Thorarinsdottir, S Beldring, W K Wong, S Huang and C-Y Xu

New approach for bias correction and stochastic downscaling of future projections for daily mean temperatures to a high-resolution grid

*Journal of Applied Meteorology and Climatology*, 58: 2617-2632, 2019 [http | arxiv] - T L Thorarinsdottir, K H Hellton, G H Steinbakk, L Schlichting and K Engeland

Bayesian regional flood frequency analysis for large catchments

*Water Resources Research*, 54(9): 6929-6947, 2018 [http] - P Guttorp and T L Thorarinsdottir

How to save Bergen from the sea? Decisions under uncertainty

*Significance*, 15(2): 14-18, 2018 [pdf] - F Kobierska, K Engeland and T L Thorarinsdottir

Evaluation of design flood estimates -- a case study for Norway

*Hydrology Research*, 49(2): 450-465, 2017 [preprint | http] - J Sillmann, T Thorarinsdottir, N Keenlyside, N Schaller, L V Alexander, G Hegerl, S I Seneviratne, R Vautard, X Zhang and F W Zwiers

Understanding, modeling and predictig weather and climate extremes: Challenges and opportunities

*Weather and Climate Extremes*, 18: 65-74, 2017 [pdf | http] - T L Thorarinsdottir, P Guttorp, M Drews, P Skougaard Kaspersen and K de Bruin

Sea level adaptation decisions under uncertainty

*Water Resources Research*, 53(10): 8147-8163, 2017 [tech | http] - R Benestad, J Sillmann, T L Thorarinsdottir, P Guttorp, M d S Mesquita, M R Tye, P Uotila, C Fox Maule, P Thejll, M Drews and K M Parding

New vigour involving statisticians to overcome ensemble fatigue

*Nature Climate Change*, 7: 697-703, 2017 [http] - S Lerch, T L Thorarinsdottir, F Ravazzolo and T Gneiting

Forecaster's dilemma: Extreme events and forecast evaluation

*Statistical Science*, 32(1): 106-127, 2017 [bib | arxiv | http] - G H Steinbakk, T L Thorarinsdottir, T Reitan, L Schlichting, S Hølleland and K Engeland

Propagation of rating curve uncertainty in design flood estimation

*Water Resources Research*, 52(9): 6897-6915, 2016 [bib | tech | http] - T L Thorarinsdottir, M Scheuerer and C Heinz

Assessing the calibration of high-dimensional ensemble forecasts using rank histograms

*Journal of Computational and Graphical Statistics*, 25(1): 105-122, 2016 [bib | arxiv | http] - E-M Didden, T L Thorarinsdottir, A Lenkoski and C Schnörr

Shape from texture using locally scaled point processes

*Image Analysis & Stereology*, 34: 161-170, 2015 [bib | arxiv | pdf] - F E Bachl, A Lenkoski, T L Thorarinsdottir and C Garbe

Bayesian motion detection for dust areosols

*Annals of Applied Statistics*, 9(3): 1298-1327, 2015 [bib | arxiv | http] - L V Hansen, T L Thorarinsdottir, E Ovcharov, T Gneiting and D Richards

Gaussian random particles with flexible Hausdorff dimension

*Advances in Applied Probability*, 47(2): 307-327, 2015 [bib | tech | arxiv | http] - A V Dyrrdal, A Lenkoski, T L Thorarinsdottir and F Stordal

Bayesian hierarchical modeling of extreme hourly precipitation in Norway

*Environmetrics*, 26(2): 89-106, 2015 [bib | arxiv | http] - K Feldmann, M Scheuerer and T L Thorarinsdottir

Spatial postprocessing of ensemble forecasts for temperature using nonhomogeneous Gaussian regression

*Monthly Weather Review*, 143(3): 955-971, 2015 [bib | arxiv | http] - K Willett, C Williams, I Jolliffe, R Lund, L Alexander, S Brönniman, L A Vincent, S Easterbrook, V Venema, D Berry, R Warren, G Lopardo, R Auchmann, E Aguilar, M Menne, C Gallagher, Z Hausfather, T Thorarinsdottir and P W Thorne

A framework for benchmarking of homogenisation algorithm performance on the global scale

*Geoscientific Instrumentation, Methods and Data Systems Discussions*, 3: 187-200, 2014 [pdf] - T L Thorarinsdottir, T Gneiting and N Gissibl

Using proper divergence functions to evaluate climate models

*SIAM/ASA Journal on Uncertainty Quantification*, 1(1): 522-534, 2013 [bib | http | arxiv] - R Schefzik, T L Thorarinsdottir and T Gneiting

Uncertainty quantification in complex simulation models using ensemble copula coupling

*Statistical Science*, 28(4): 616-640, 2013 [bib | http | arxiv] - S Lerch and T L Thorarinsdottir

Comparing nonhomogeneous regression models for probabilistic wind speed forecasting

*Tellus A*, 65: 21206, 2013 [bib | http | arxiv] - T L Thorarinsdottir

Calibration diagnostics for point process models via the probability integral transform

*Stat*2(1): 150-158, 2013 [bib | http | arxiv] - A Möller, A Lenkoski, and T L Thorarinsdottir

Multivariate probabilistic forecasting using Bayesian model averaging and copulas

*Quarterly Journal of the Royal Meteorological Society*, 139(673): 982-991, 2013 [bib | http | arxiv] - L V Hansen and T L Thorarinsdottir

A note on moving average models for Gaussian random fields

*Statistics and Probability Letters*, 83(3): 850-855, 2013 [bib | http | tech] - T L Thorarinsdottir, M Scheuerer, and K Feldmann

Statistical post-processing of ensemble forecasts

*Promet*, 37(3/4):43-52, 2012 (in German, invited paper) [bib | pdf] - P Friederichs and T L Thorarinsdottir

Forecast verification for extreme value distributions with an application to probabilistic peak wind prediction

*Environmetrics*, 23(7):579-594, 2012 [bib | http | arxiv] - N Schuhen, T L Thorarinsdottir, and T Gneiting

Ensemble model output statistics for wind vectors

*Monthly Weather Review*, 140(10):3204-3219, 2012 [bib | http | arxiv] - P Guttorp and T L Thorarinsdottir

What happened to discrete chaos, the Quenouille process, and the sharp Markov property? Some history of stochastic point processes

*International Statistical Review*, 80(2):253-268, 2012 [bib | http | tech] - T L Thorarinsdottir and M S Johnson

Probabilistic wind gust forecasting using non-homogeneous Gaussian regression

*Monthly Weather Review*, 140(3):889-897, 2012 [bib | http] - T L Thorarinsdottir and T Gneiting

Probabilistic forecasts of wind speed: Ensemble model output statistics by using heteroskedastic censored regression

*Journal of the Royal Statistical Society Series A: Statistics in Society*, 173(2):371-388, 2010 [bib | http | tech] - E B V Jensen and T L Thorarinsdottir

A spatio-temporal model for functional magnetic resonance imaging data - with a view to resting state networks

*Scandinavian Journal of Statistics*, 34(3):587-614, 2007 [bib | http | tech] - M H Neumann and T L Thorarinsdottir

Asymptotic minimax estimation in nonparametric autoregression

*Mathematical Methods of Statistics*, 15(4):374-397, 2007 [bib | pdf] - T L Thorarinsdottir

Bayesian image restoration, using configurations

*Image Analysis & Stereology*, 25:129-143, 2006 [bib | pdf]

**Book Chapters**

- T L Thorarinsdottir and N Schuhen

Chapter 6 - Verification: assessment of calibration and accuracy

In S Vannitsem, D S Wilks and J W Messner (Eds.),*Statistical Postprocessing of Ensemble Forecasts*, pp. 155-186. Elsevier, 2018. [tech | http] - P Guttorp and T L Thorarinsdottir

Bayesian inference for non-Markovian point processes

In E Porcu, J M Montero, and M Schlather (Eds.),*Advances and Challenges in Space-time Modelling of Natural Events*, pp. 79-102. Lecture Notes in Statistics, Volume 207. Springer: Berlin Heidelberg, 2012 [bib | http | tech]

**Proceedings**

- T L Thorarinsdottir and E B V Jensen

Modelling resting state networks in the human brain

In R Lechnerová, I Saxl, and V Beneš, editors,*Proceedings S4G: International Conference on Stereology, Spatial Statistics and Stochastic Geometry*, pp. 137-147, 2006 [bib | pdf]

**Working Papers**

- T Erhardt, C Czado and T L Thorarinsdottir

Evaluation of time series models under non-stationarity with application to the comparison of regional climate models

arXiv:1702.00728, 2017 [arxiv] - A Möller, T L Thorarinsdottir, A Lenkoski and T Gneiting

Spatially adaptive, Bayesian estimation for probabilistic temperature forecasts

arXiv:1507.05066, 2015 [bib | arxiv] - T Gneiting and T L Thorarinsdottir

Predicting inflation: professional experts versus no-change forecasts

arXiv:1010.2318, 2010 [bib | arxiv]

**Comments**

- A Lenkoski and T L Thorarinsdottir

Comments on: Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings by W Ehm, T Gneiting, A Jordan and F Krüger

*Journal of the Royal Statistical Society, Series B*, 78(3): 548, 2016 [http] - T L Thorarinsdottir and A Løland

Comments on: Space-time wind speed forecasting for improved power system dispatch by X Zhu, M G Genton, Y Gu and L Xie

*TEST*, 23(1): 32-33, 2014 [bib | http]

**Project and Meeting Reports**

- P Guttorp and T L Thorarinsdottir

Local climate projections: A little money goes a long way

*Eos*, 100, doi:10.1029/2019EO133113, 2019 [http] - T L Thorarinsdottir and K de Bruin

Challenges of climate change adaptation

*Eos*, 97, doi:10.1029/2016EO062121, 2016 [http]

[The full workshop report is available here] - T L Thorarinsdottir, J Sillmann and R Benestad

Studying statistical methodology in climate research

*EOS Transactions*, 95(15): 129, 2014 [bib | http]

Last updated May 29, 2022 by TLT