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The influence of the North Sea on coastal precipitation in the Netherlands in the present-day and future climate

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Abstract

Coastal precipitation in the Netherlands for present-day and future climate using observations and simulations with the KNMI regional climate model RACMO2 is studied. Overall a good correspondence between RACMO2 and the observations is found for the present-day climate. Yet, the model generally simulates too sharp gradients in precipitation amounts near the coast line, and the maximum in precipitation is shifted towards the sea compared to the observations. The seasonal cycle of coastal precipitation (here the difference between precipitation near the coast and inland) is well linked to the land sea temperature contrast. Yet, this is not a one-to-one relation and other effects (like atmospheric stability) are likely to be important as well. Variations from year to year in monthly coastal precipitation correlate well with variations in strength of the cyclonic westerly circulation in the periods August to November. A moderate sensitivity to sea surface temperatures (≈6 mm month−1 K−1) has also been found. In simulations of climate change a small increase in coastal precipitation is generally found, except for the spring period. Using a more realistic prescription of North Sea temperatures (from a slab ocean model) only marginally changes these results. The increase in coastal precipitation is tempered by a decrease in land sea temperature contrast, and considerably larger increases of coastal precipitation could be expected if the temperature rise over sea equalled the temperature rise over land. Despite the fact that the overall changes in coastal effect appear relatively moderate, impact on more extreme events could be considerable, increasing the probability of exceeding extreme thresholds by a factor two or more.

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References

  • Benestad R, Melsom A (2002) Is there a link between unusually wet autumns in southeastern norway and sea-surface temperature anomalies? Clim Res 23:677–779

    Article  Google Scholar 

  • Buishand A, Brandsma T, De Martino G, Spreeuw H (2011) Ruimtelijke verdeling van neerslagtrends in nederland in de afgelopen 100 jaar. H2O 24:31–33

    Google Scholar 

  • Buishand A, Velds C (1980) Neerslag en verdamping, Klimaat van Nederland, vol 1. Staatsuitgeverij, Den Haag. http://www.knmi.nl/bibliotheek/knmipubDIV/Neerslag_en_verdamping.pdf

  • Christensen JH, Kjellström E, Giorgi FF, Lenderink G, Rummukainen M (2010) Weight assignment in regional climate models. Clim Res 44(2–3):179–194. doi:10.3354/cr00916. http://www.int-res.com/abstracts/cr/v44/n2-3/p179-194/

    Google Scholar 

  • Dee DP et al (2011) The era-interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137(656):553–597. doi:10.1002/qj.828

  • François C, Brisson A, Borgne PL, Marsouin A (2002) Definition of a radiosounding database for sea surface brightness temperature simulations: application to sea surface temperature retrieval algorithm determination. Remote Sens Environ 81(2–3):309– 326. doi:10.1016/S0034-4257(02)00008-1

    Article  Google Scholar 

  • Hewitt C, Griggs D (2004) Ensembles-based predictions of climate changes and their impacts (ENSEMBLES). EOS 85:566

    Article  Google Scholar 

  • K-1 model developers (2004) K-1 coupled model (MIROC) description, k-1 technical report. Tech. rep., Center for Climate System Research, University of Tokyo. Hasumi H, Emori S (eds), p 34

  • Kjellström E, Ruosteenoja K (2007) Present-day and future precipitation in the baltic sea region as simulated in a suite of regional climate models. Clim Change 81:281–291. doi:10.1007/s10584-006-9219-y

    Article  Google Scholar 

  • Lebeaupin C, Ducrocq V, Giordani H (2006) Sensitivity of torrential rain events to the sea surface temperature based on high-resolution numerical forecasts. J Geophys Res 111. doi:10.1029/2005JD006541

  • Lenderink G, van Meijgaard E, Selten F (2009) Intense coastal rainfall in the netherlands in response to high sea water temperatures: analysis of the event of august 2006 from the perspective of a changing climate. Clim Dyn 32:19–33. doi:10.1007/s00382-008-0366-x

    Article  Google Scholar 

  • Lenderink G, van Ulden A, van den Hurk B, Keller F (2007) A study on combining global and regional climate model results for generating climate scenarios of temperature and precipitation for the netherlands. Clim Dyn 29(2):157–176. doi:10.1007/s00382-007-0227-z

    Google Scholar 

  • Malda D, Vilà-Guerau de Arellano J, van den Berg WD, Zuurendonk IW (2007) The role of atmospheric boundary layer-surface interactions on the development of coastal fronts. Ann Geophys 25(2):341–360. doi:10.5194/angeo-25-341-2007. http://www.ann-geophys.net/25/341/2007/

    Google Scholar 

  • Messager C, Gallée H, Brasseur O (2004) Precipitation sensitivity to regional sst in a regional climate in a regional climate simulation during the west african monsoon for two dry years. Clim Dyn 22:249–266. doi:10.1007/s00382-003-0381-x

    Google Scholar 

  • Persson P, Neiman P, Walter B, Bao J-W, Ralph F (2005) Contributions from california coastal-zone surface fluxes to heavy coastal precipitation: a caljet case study during the strong el niño of 1998. Mon Weather Rev 133:1175–1198

    Article  Google Scholar 

  • Reynolds R, Rayner N, Smith T, Stokes D, Wang W (2002) An improved in situ and satellite SST analysis for climate. J Clim 15(13):1609–1625

    Article  Google Scholar 

  • Roeckner E et al (2003) The atmospheric general circulation model echam5, part i: Model description. MPI Rep., p 349

  • van den Hurk B et al (2007) New climate change scenarios for the netherlands. Water Sci Technol 56:27–33. doi:10.2166/wst.2007.533

    Article  Google Scholar 

  • van Meijgaard E, van Ulft LH, van de Berg W, Bosveld FC, van den Hurk BJJM, Lenderink G, Siebesma AP (2008) The knmi regional atmospheric climate model racmo, version 2.1. KNMI Technical Report TR-302, KNMI

  • van Oldenborgh GJ, Drijfhout S, van Ulden A, Haarsma R, Sterl A, Severijns C, Hazeleger W, Dijkstra H (2009) Western europe is warming much faster than expected. Clim Past 5(1):1–12. doi:10.5194/cp-5-1-2009. http://www.clim-past.net/5/1/2009/

    Google Scholar 

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Correspondence to J. J. Attema.

Slab model

Slab model

The ocean slab model is given by the following equation:

$$\frac{\partial T}{\partial t} = \frac{1}{h c_{p} \rho}( Q + F ) - \frac{1}{\beta} ( T - T_{ext}). $$
(3)

The slab layer has a thickness h. Experience shows that optimal depths are between 5 and 35 m; smaller values lead to too large fluctuations with the weather, whereas a too large depth effectively turns off the model. The thickness is limited by the observed ocean depth, which is in particular relevant near the coast. The change in slab temperature T is then given by the energy balance at the surface F and a prescribed energy flux Q (the Q-flux). The last relaxation term is used to prevent a too strong divergence between the simulated T and the temperature provided by the boundary (T ext ). The relaxation time (β) is set to 1 month for the North Sea, and smoothly drops to 1 week elsewhere.

Using the slab model is a two step process. First, a normal run with an accurate, high resolution SST is done from which T high and F high are used to determine Q:

$$Q = h c_p \rho \frac{\partial T_{high}}{\partial t}- F_{high} $$
(4)

To get good statistics a sufficiently long period should be used; in the literature, typically a 15 years run with a climatological SST is taken. Here, we use a satellite derived SST for the period 1996–2010. The Q-flux is determined per month, using monthly averages. Note that the Q-flux is model specific: it depends on any model bias or error in the radiation.

The Q-flux can then be used in a run with the slab model turned on. This effectively means running with a perturbation on the climatology of the high resolution SST. Combining 3 and 4 we get:

$$\frac{\partial}{\partial t} (T - T_{high} )= \frac{1}{h c_p \rho} ( F - F_{high} ) - \frac{1}{\beta} ( T - T_{ext} ) $$
(5)

The term on the left represents the deviation from the climatological temperature; this is determined by the local energy balance (influenced by the weather). The last term is a relaxation back to the external SST as set in the boundaries.

With the slab model, and using a coarse resolution SST as input, a large part of the coastal warming as visible in the high resolution satellite observations is retrieved (see the bottom part of Fig. 2). Although ocean currents, and thus advection of heat, are not included explicitly in the slab model, they are included indirectly via the prescribed Q-flux. Consequently, the slab model can only be used for climate integrations when it is assumed that no large changes in ocean circulation occur.

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Attema, J.J., Lenderink, G. The influence of the North Sea on coastal precipitation in the Netherlands in the present-day and future climate. Clim Dyn 42, 505–519 (2014). https://doi.org/10.1007/s00382-013-1665-4

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