A new regional climate model operating at the meso-gamma scale:
                        performance over Europe

Lindstedt, David; Lind, Petter; Kjellström, Erik; Jones, Colin

doi:10.3402/tellusa.v67.24138

Cited by 40 publications

(43 citation statements)

References 70 publications

(78 reference statements)

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“…1). In Merikarvia the simulated wind speed was between 9 and 15 m s −1 , which is regarded by Markowski and Richardson (2010) as the optimal velocity for snowbands to form.…”

Section: Simulated Featuresmentioning

confidence: 99%

“…This produces an unstable boundary layer over the water body. As a result, the turbulent heat and moisture fluxes from the water surface are large and generate shallow convection that induces small and intensive convective precipitation which can drift to the coast as snowbands (Markowski and Richardson, 2010;Mazon et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…As a rule of thumb, the temperature difference between the 850 hPa temperature and the water surface should be at least 13 • C (Markowski and Richardson, 2010). The most favourable conditions for sea-effect snowfall typically prevail after a warm autumn, if an Arctic air mass reaches a relatively warm water area during early winter.…”

Section: Introductionmentioning

confidence: 99%

“…According to Markowski and Richardson (2010), the former is usually over 75 km and the latter is 7-15 m s −1 . For sea-effect snowbands to form in Finland there are several typical restricting factors (Punkka, 2016;Ilmastokatsaus, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Intense sea-effect snowfall case on the western coast of Finland

et al. 2017

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Abstract.A new national daily snowfall record was measured in Finland on 8 January 2016 when it snowed 73 cm (31 mm as liquid water) in less than a day in Merikarvia on the western coast of Finland. The area of the most intense snowfall was very small, which is common in convective precipitation. In this work we used hourly weather radar images to identify the sea-effect snowfall case and to qualitatively estimate the performance of HARMONIE, a non-hydrostatic convection-permitting weather prediction model, in simulating the spatial and temporal evolution of the snowbands. The model simulation, including data assimilation, was run at 2.5 km horizontal resolution and 65 levels in vertical. HARMONIE was found to capture the overall sea-effect snowfall situation quite well, as both the timing and the location of the most intense snowstorm were properly simulated. Based on our preliminary analysis, the snowband case was triggered by atmospheric instability above the mostly ice-free sea and a low-level convergence zone almost perpendicular to the coastline. The simulated convective available potential energy (CAPE) reached a value of 87 J kg −1 near the site of the observed snowfall record.

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“…1). In Merikarvia the simulated wind speed was between 9 and 15 m s −1 , which is regarded by Markowski and Richardson (2010) as the optimal velocity for snowbands to form.…”

Section: Simulated Featuresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Intense sea-effect snowfall case on the western coast of Finland

et al. 2017

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“…Although the 10-year length is arbitrary, it is sufficiently long to include some inter-annual variability and to generate a reasonable sample of extreme events. The use of a NWP model in a long-term climate setting for the performance of extreme precipitation events for a 10-year period was recently demonstrated (Lindstedt et al, 2015). To evaluate the sensitivity of the model to the update frequency of the initial conditions, three types of downscaling approaches were conducted with ALARO-0 coupled to SURFEXv5 and are detailed below.…”

Section: Experimental Designmentioning

confidence: 99%

Reinitialised versus continuous regional climate simulations using ALARO-0 coupled to the land surface model SURFEXv5

et al. 2017

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Abstract. Dynamical downscaling in a continuous approach using initial and boundary conditions from a reanalysis or a global climate model is a common method for simulating the regional climate. The simulation potential can be improved by applying an alternative approach of reinitialising the atmosphere, combined with either a daily reinitialised or a continuous land surface. We evaluated the dependence of the simulation potential on the running mode of the regional climate model ALARO coupled to the land surface model Météo-France SURFace EXternalisée (SUR-FEX), and driven by the ERA-Interim reanalysis. Three types of downscaling simulations were carried out for a 10-year period from 1991 to 2000, over a western European domain at 20 km horizontal resolution: (1) a continuous simulation of both the atmosphere and the land surface, (2) a simulation with daily reinitialisations for both the atmosphere and the land surface and (3) a simulation with daily reinitialisations of the atmosphere while the land surface is kept continuous. The results showed that the daily reinitialisation of the atmosphere improved the simulation of the 2 m temperature for all seasons. It revealed a neutral impact on the daily precipitation totals during winter, but the results were improved for the summer when the land surface was kept continuous. The behaviour of the three model configurations varied among different climatic regimes. Their seasonal cycle for the 2 m temperature and daily precipitation totals was very similar for a Mediterranean climate, but more variable for temperate and continental climate regimes. Commonly, the summer climate is characterised by strong interactions between the atmosphere and the land surface. The results for summer demonstrated that the use of a daily reinitialised atmosphere improved the representation of the partitioning of the surface energy fluxes. Therefore, we recommend using the alternative approach of the daily reinitialisation of the atmosphere for the simulation of the regional climate.

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Effect of climate data on simulated carbon and nitrogen balances for Europe

et al. 2016

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In this study, we systematically assess the spatial variability in carbon and nitrogen balance simulations related to the choice of global circulation models (GCMs), representative concentration pathways (RCPs), spatial resolutions, and the downscaling methods used as calculated with LPJ‐GUESS. We employed a complete factorial design and performed 24 simulations for Europe with different climate input data sets and different combinations of these four factors. Our results reveal that the variability in simulated output in Europe is moderate with 35.6%–93.5% of the total variability being common among all combinations of factors. The spatial resolution is the most important factor among the examined factors, explaining 1.5%–10.7% of the total variability followed by GCMs (0.3%–7.6%), RCPs (0%–6.3%), and downscaling methods (0.1%–4.6%). The higher‐order interactions effect that captures nonlinear relations between the factors and random effects is pronounced and accounts for 1.6%–45.8% to the total variability. The most distinct hot spots of variability include the mountain ranges in North Scandinavia and the Alps, and the Iberian Peninsula. Based on our findings, we advise to conduct the application of models such as LPJ‐GUESS at a reasonably high spatial resolution which is supported by the model structure. There is no notable gain in simulations of ecosystem carbon and nitrogen stocks and fluxes from using regionally downscaled climate in preference to bias‐corrected, bilinearly interpolated CMIP5 projections.

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A new regional climate model operating at the meso-gamma scale: performance over Europe

Cited by 40 publications

References 70 publications

Intense sea-effect snowfall case on the western coast of Finland

Intense sea-effect snowfall case on the western coast of Finland

Reinitialised versus continuous regional climate simulations using ALARO-0 coupled to the land surface model SURFEXv5

Effect of climate data on simulated carbon and nitrogen balances for Europe

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