Aldrin, M., Holden, M., Guttorp, P., Skeie, R.B., Myhre, G. and Berntsen, T.K. (2012). Bayesian estimation of climate sensitivity based on a simple climate model fitted to observations of hemispheric temperatures and global ocean heat content.  Environmetrics, Vol. 23, p. 253-271, doi:10.1002/env.2140.

Guttorp, Peter. (2011). The role of statisticians in international science policy. Environmetrics, Vol. 22(7) p. 817-825, doi:10.1002/env.1109.

Guttorp, Peter; Craigmile, Peter F. (2011). Space-time modelling of trends in temperature series. Journal of Time Series Analysis, Vol. 32(4) p. 378-395, doi: 10.1111/j.1467-9892.2011.00733.x.

Guttorp, Peter; Xu, Jia. (2011). Climate change, trends in extremes, and model assessment for a long temperature time series from Sweden. Environmetrics, Vol. 22(3) p. 456-463, doi: 10.1002/env.1099.

Orskaug, Elisabeth; Scheel, Ida; Frigessi, Arnoldo; Guttorp, Peter; Haugen, Jan Erik; Tveito, Ole Einar; Haug, Ola. (2011). Evaluation of a dynamic downscaling of precipitation over the Norwegian mainland. Tellus. Series A, Dynamic meteorology and oceanography, Vol. 63(4) p. 746-756, doi: 10.1111/j.1600-0870.2011.00525.x.

Schmidt, AM; Guttorp, Peter; O’Hagan, A. (2011). Considering covariates in the covariance structure of spatial processes. Environmetrics, Vol. 22 (4) p. 487-500, doi: 10.1002/env.1101.

Smith, Richard L., Berliner, L. Mark, and Guttorp, Peter (2010). Statisticians Comment on Status of Climate Change Science. Amstat News, Issue 393, pp. 13-16.

Aldrin, M., Hobæk Haff, I. (2008). The effect of salting with magnesium chloride on the concentration of particulate matter in a road tunnel. Atmospheric Environment, Vol. 22, pp. 1762-1776. [pdf]

Natvig, Bent; Tvete, Ingunn (2007). Bayesian Hierarchical Space-time Modeling of Earthquake Data. Methodology and Computing in Applied Probability, Vol. 9, pp. 89-114.

Kausrud, Kyrre Linné; Viljugrein, Hildegunn; Frigessi, Arnoldo; Begon, Mike; Davis, Herwig Leirs, Stephen; Dubyanskiy, Vladimir; Stenseth, Nils Christian (2007). Climatically-driven synchrony of gerbil populations allows large-scale plague outbreaks. Proc Biol Sci. Vol. 274, pp. 1963-1969.

Larssen, Thorjørn; Huseby, Ragnar B.; Cosby, Bernard J.; Høst, Gudmund., Høgåsen, G.; Aldrin, Magne (2006). Forecasting Acidification Effects using a Bayesian Calibration and Uncertainty Propagation Approach. Environmental Science & Technology, Vol. 40, pp. 7841-7847. [pdf]

Frigessi, Arnoldo; Holden, Marit; Marshall, Clare; Viljugrein, Hildegunn; Stenseth, Nils. Chr.; Holden, Lars; Ageyev, Vladimir and Klassovskiy, Nikolay L. (2005). Bayesian population dynamics of interacting species: great gerbils and fleas in Kazakhstan. Biometrics, Vol. 61, No. 1, pp. 230-238.

Aldrin, M. and Hobæk Haff, I. (2005). Generalised additive modelling of air pollution, traffic volume and meteorology. Atmospheric Environment, Vol 39, pp. 2145-2155. [pdf]

Hirst, D.; Storvik, G. and Syversveen, A.R. (2003). A hierarchical modelling approach to combining environmental data at different resolutions. Applied Statistics, Vol. 52, pp. 377-390.

Hirst, D. and Storvik, G. (2003). Estimating Critical load exceedance by combining the EMEP model with data from measurement stations. The Science of Total Environment, Vol. 310, pp. 163-170.

Aldrin, Magne (2002). Reduced-rank regression. In El-Shaarawi, A.H. and Piegorsch, W.W. (eds.). Encyclopedia of Environmetrics, pp. 1724-1728, ISBN 04771-899976. [pdf]

Hirst, David (2002). Critical loads. In El-Shaarawi, A.H. and Piegorsch, W.W. (eds.). Encyclopedia of Environmetrics, Vol. 1, pp. 443-447, ISBN 04771-899976.

Høst, Gudmund (2002). Statistics and the environmental sciences: Approaches to model combination. In Anderson, C.W.; Barnett, V.; Chatwin, P.C. and El-Shaarawi, A.H. (eds.). Quantitative Methods for Current Environmental Issues, ISBN 1-85233-294-8.

Høst, Gudmund (2002). Simulated Annealing. In El-Shaarawi, A.H. and Piegorsch, W.W. (eds.). Encyclopedia of Environmetrics, Vol. 4, pp. 2001-2002, ISBN 04771-899976.

Storvik, Geir (2002). Gibbs Sampling. In El-Shaarawi, A.H. and Piegorsch, W.W. (eds.). Encyclopedia of Environmetrics, Vol. 2, pp. 899-905, ISBN 04771-899976.

Storvik, Geir (2002). Stochastic Simulation and Monte Carlo Methods. In El-Shaarawi, A.H. and Piegorsch, W.W. (eds.). Encyclopedia of Environmetrics, Vol. 4, pp. 2002-2007, ISBN 04771-899976.

Storvik, Geir (2002). S-plus. In El-Shaarawi, A.H. and Piegorsch, W.W. (eds.). Encyclopedia of Environmetrics, Vol. 4, pp. 1897-1899, ISBN 04771-899976.

Hisdal, Hilde; Tallaksen, Lene M. and Frigessi Arnoldo (2002). Handling non-extreme events in extreme value modelling of droughts. In van Lanen, H. and Demuth, S. (eds.). FRIEND 2002-Regional Hydrology: Bridging the Gap between Research and Practice. No. 274.

Storvik, Geir; Frigessi, Arnoldo and Hirst, David (2002). Space-time Gaussian fields and their time-autoregressive representation. Statistical Modelling Vol. 2, pp. 139-161.

Høst, Gudmund (2002). Discussion of statistical issues in weather forecasting. Scandinavian Journal of Statistics, Vol. 29, pp. 239-241.

Hirst, David. J.; Kåresen, Kjetil; Høst, Gudmund and Posch, Max (2000). Estimating the exceedance of critical loads in Europe by considering local variability in deposition. Atmospheric Environment, 34, pp. 3789-3800.

Høst, Gudmund (1999). Bayesian Estimation of European Sulphur Emissions Using Monitoring Data and an Acid Deposition Model. Environmental and Ecological Statistics, Vol. 6, No 4, pp. 381-399.

Høst, G. (1999). Kriging by Local Polynomials. Computational Statistics and Data Analysis Vol. 29, Nr. 3.

Divino, F. and Frigessi, A. (1998). Bayesian identification of algae in the Venice lagoon: parametric models with covariates (in Italian). Problemi Statistici nel Telerilevamento, Rubettino editore.

Frigessi, A. and Høst, G. (1998). Spatial models with covariates in environmental applications. XXXIX Riunione Scientifica della Societa' Italiana di Statistica 14-17 April 1998.

Høst, G. (1998). Discussion of model-based geostatistics, by Diggle, Tawn & Moyeed. Applied Statistics, Vol. 47, Nr. 3.