seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day

Lussana, Cristian; Saloranta, Tuomo; Skaugen, Thomas; Magnusson, Jan; Tveito, Ole Einar; Andersen, Jess

doi:10.5194/essd-10-235-2018

Cited by 106 publications

(130 citation statements)

References 43 publications

(41 reference statements)

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“…The model uses input grid data of precipitation and temperature (observations and forecasts) based on a rough interpolation and does not yet utilize the improved grid data provided by MET at the end of 2016 (Saloranta, 2016;Lussana et al, 2018). An improved version of the model is scheduled to be operative in 2018/2019.…”

Section: Discussionmentioning

confidence: 99%

The Norwegian forecasting and warning service for rainfall- and snowmelt-induced landslides

Krøgli

Devoli

Colleuille

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. The Norwegian Water Resources and Energy Directorate (NVE) have run a national flood forecasting and warning service since 1989. In 2009, the directorate was given the responsibility of also initiating a national forecasting service for rainfall-induced landslides. Both services are part of a political effort to improve flood and landslide risk prevention. The Landslide Forecasting and Warning Service was officially launched in 2013 and is developed as a joint initiative across public agencies between NVE, the Norwegian Meteorological Institute (MET), the Norwegian Public Road Administration (NPRA) and the Norwegian Rail Administration (Bane NOR). The main goal of the service is to reduce economic and human losses caused by landslides. The service performs daily a national landslide hazard assessment describing the expected awareness level at a regional level (i.e. for a county and/or group of municipalities). The service is operative 7 days a week throughout the year. Assessments and updates are published at the warning portal http://www.varsom.no/ at least twice a day, for the three coming days. The service delivers continuous updates on the current situation and future development to national and regional stakeholders and to the general public. The service is run in close cooperation with the flood forecasting service. Both services are based on the five pillars: automatic hydrological and meteorological stations, landslide and flood historical database, hydro-meteorological forecasting models, thresholds or return periods, and a trained group of forecasters. The main components of the service are herein described. A recent evaluation, conducted on the 4 years of operation, shows a rate of over 95 % correct daily assessments. In addition positive feedbacks have been received from users through a questionnaire. The capability of the service to forecast landslides by following the hydro-meteorological conditions is illustrated by an example from autumn 2017. The case shows how the landslide service has developed into a well-functioning system providing useful information, effectively and on time.

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Section: Discussionmentioning

confidence: 99%

The Norwegian forecasting and warning service for rainfall- and snowmelt-induced landslides

Krøgli

Devoli

Colleuille

et al. 2018

Nat. Hazards Earth Syst. Sci.

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“…valley bottoms) and few stations are located above 1000 m a.s.l. (Lussana et al, 2018a). The hourly precipitation values have been obtained by using a two-step procedure.…”

Section: Gridded Observations (Gridobs)mentioning

confidence: 99%

“…The hourly precipitation values have been obtained by using a two-step procedure. The spatial interpolation method described by Lussana et al (2018a) has been applied independently to daily and hourly precipitation totals. This method is built on classical methods (such as optimal interpolation and successivecorrection schemes) and (spatial) scale-separation using geographical coordinates and elevation as complimentary information in the interpolation.…”

Section: Gridded Observations (Gridobs)mentioning

confidence: 99%

“…It is based on iterating a statistical interpolation scheme over a decreasing sequence of spatial scales, from synoptic to kilometre scale. Further details can be found in Lussana et al (2018a). The daily precipitation totals have been disaggregated to an hourly time with a procedure similar to the one described by Vormoor and .…”

Section: Gridded Observations (Gridobs)mentioning

confidence: 99%

“…Snow maps of depth, water equivalent, snowmelt, snow wetness and skiing conditions are also produced operationally on a daily basis and published at http://www.seNorge.no (last access: 18 June 2018) and http://www.xgeo.no (last access: 18 June 2018) (Saloranta, 2016), and these maps are used by the national snow avalanche service (Barfod et al, 2013;. Both these applications use gridded near-real-time observations of temperature and precipitation (Mohr, 2008;Lussana et al, 2018a).…”

Section: Introductionmentioning

confidence: 99%

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Forcing the SURFEX/Crocus snow model with combined hourly meteorological forecasts and gridded observations in southern Norway

et al. 2018

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Abstract. In Norway, 30 % of the annual precipitation falls as snow. Knowledge of the snow reservoir is therefore important for energy production and water resource management. The land surface model SURFEX with the detailed snowpack scheme Crocus (SURFEX/Crocus) has been run with a grid spacing of 1 km over an area in southern Norway for 2 years (1 September 2014-31 August 2016). Experiments were carried out using two different forcing data sets: (1) hourly forecasts from the operational weather forecast model AROME MetCoOp (2.5 km grid spacing) including post-processed temperature (500 m grid spacing) and wind, and (2) gridded hourly observations of temperature and precipitation (1 km grid spacing) combined with meteorological forecasts from AROME MetCoOp for the remaining weather variables required by SURFEX/Crocus. We present an evaluation of the modelled snow depth and snow cover in comparison to 30 point observations of snow depth and MODIS satellite images of the snow-covered area. The evaluation focuses on snow accumulation and snowmelt. Both experiments are capable of simulating the snowpack over the two winter seasons, but there is an overestimation of snow depth when using meteorological forecasts from AROME MetCoOp (bias of 20 cm and RMSE of 56 cm), although the snow-covered area in the melt season is better represented by this experiment. The errors, when using AROME MetCoOp as forcing, accumulate over the snow season. When using gridded observations, the simulation of snow depth is significantly improved (the bias for this experiment is 7 cm and RMSE 28 cm), but the spatial snow cover distribution is not well captured during the melting season. Underestimation of snow depth at high elevations (due to the low elevation bias in the gridded observation data set) likely causes the snow cover to decrease too soon during the melt season, leading to unrealistically little snow by the end of the season. Our results show that forcing data consisting of postprocessed NWP data (observations assimilated into the raw NWP weather predictions) are most promising for snow simulations, when larger regions are evaluated. Post-processed NWP data provide a more representative spatial representation for both high mountains and lowlands, compared to interpolated observations. There is, however, an underestimation of snow ablation in both experiments. This is generally due to the absence of wind-induced erosion of snow in the SURFEX/Crocus model, underestimated snowmelt and biases in the forcing data.

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Boreal tree species change as a climate mitigation strategy: impact on ecosystem C and N stocks and soil nutrient levels

et al. 2021

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To increase the annual uptake of CO 2 as well as the long-term storage of carbon (C) in forests, the Norwegian government consider large-scale replacements of native, deciduous forests with fastergrowing species like Norway spruce. To assess the effects of tree species change on ecosystem C and nitrogen (N) stocks and soil chemistry, we used a paired plot approach including stands of native downy birch and planted 45-to 60-yr-old Norway spruce. The birch stands were used as reference for the assessment of differences following the tree species change. We found significantly higher C and N stocks in living tree biomass in the spruce stands, whereas no significant differences were found for dead wood. The cover of understory species groups, and the C and N stocks of the aboveground understory vegetation were significantly higher in the birch stands. The tree species change did not affect the soil organic carbon (SOC) stock down to 1 m soil depth; however, the significantly higher stock in the forest floor of the spruce stands suggested a re-distribution of SOC within the profile. There was a significant positive correlation between the SOC stock down to 30 cm soil depth and the total ecosystem C stock for the birch stands, and a negative correlation for the spruce stands. Significant effects of tree species change were found for C and N concentrations, C/N, exchangeable acidity, base saturation, and exchangeable Ca, K, Mg, Na, S, and Fe in the organic horizon or the upper mineral soil layer. The total ecosystem C stock ranged between 197 and 277 Mg/ha for the birch stands, and 297 and 387 Mg/ha for the spruce stands. The ecosystem C accumulation varied between 32 and 142 Mg/ha over the past 45-60 yr, whereas the net ecosystem C capture was considerably lower and potentially negative. Our results suggest that the potential to meet the governments' targets to increase C sequestration depend on the C debt incurred from the removed birch stands, the rotation length, and potentially also the susceptibility of the different stand types to future risk factors related to climate change.

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seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day

Cited by 106 publications

References 43 publications

The Norwegian forecasting and warning service for rainfall- and snowmelt-induced landslides

The Norwegian forecasting and warning service for rainfall- and snowmelt-induced landslides

Forcing the SURFEX/Crocus snow model with combined hourly meteorological forecasts and gridded observations in southern Norway

Boreal tree species change as a climate mitigation strategy: impact on ecosystem C and N stocks and soil nutrient levels

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