Biografi

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PhD i miljøvitenskap, arbeidet siden mer enn 15 år i GIS-sektoren. Erfaring som konsulent, lærer, forsker og prosjektleder for nasjonale og internasjonale prosjekt og grupper og har arbeidserfaring fra land som Kina og Ecuador.

De viktigste forskningsområdene er bruk av GIS i flere miljøsektorer, inkludert klimaendringer, forurenset grunn og vannkvalitet. Bidratt til utvikliing av GIS-baserte verktøy som Spatial Decision Support System konsekvensutredning for klimaendringer (DESYCO) og WebGIS for klimadata. Har også jobbet med metoder og tilpasningstiltak for å møte klimaendringene ved kystsoner. Arbeidserfaring fra MultiCriteria Decision Analysis (MCDA).

I de siste årene har han deltatt i internasjonale samarbeidsprosjekter i utviklingsland.

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Sammendrag

Northern latitudes are experiencing faster warming than other regions in the world, which is partly explained by the snow albedo feedback. In Norway, mean temperatures have been increasing since the 1990s, with 2014 being the warmest year on record, 2.2 °C above normal (1961–1990). At the same time, a concurrent reduction in the land area covered by snow has been reported. In this study, we present a detailed spatial and temporal (monthly and seasonal) analysis of trends and changes in snow indices based on a high resolution (1 km) gridded hydro-meteorological dataset for Norway (seNorge). During the period 1961–2010, snow cover extent (SCE) was found to decrease, notably at the end of the snow season, with a corresponding decrease in snow water equivalent except at high elevations. SCE for all Norway decreased by more than 20,000 km2 (6% of the land area) between the periods 1961–1990 and 1981–2010, mainly north of 63° N. Overall, air temperature increased in all seasons, with the highest increase in spring (particularly in April) and winter. Mean monthly air temperatures were significantly correlated with the monthly SCE, suggesting a positive land–atmosphere feedback enhancing warming in winter and spring.

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Sammendrag

Runoff prediction in ungauged catchments has been a challenging topic over recent decades. Much research have been conducted including the intensive studies of the PUB (Prediction in Ungauged Basins) Decade of the International Association for Hydrological Science. Great progress has been made in the field of regionalization study of hydrological models; however, there is no clear conclusion yet about the applicability of various methods in different regions and for different models. This study made a comprehensive assessment of the strengths and limitations of existing regionalization methods in predicting ungauged stream flows in the high latitudes, large climate and geographically diverse, seasonally snow-covered mountainous catchments of Norway. The regionalization methods were evaluated using the water balance model – WASMOD (Water And Snow balance MODeling system) on 118 independent catchments in Norway, and the results show that: (1) distance-based similarity approaches (spatial proximity, physical similarity) performed better than regression-based approaches; (2) one of the combination approaches (combining spatial proximity and physical similarity methods) could slightly improve the simulation; and (3) classifying the catchments into homogeneous groups did not improve the simulations in ungauged catchments in our study region. This study contributes to the theoretical understanding and development of regionalization methods.