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1 Regional Climate Model 2 Calculating Cloud Base Heights Supplementary Material to accompany Climate Change Scenario for Costa Rican Montane Forests A. V. Karmalkar, R. S. Bradley, H. F. Diaz 1 Regional Climate Model The PRECIS (Providing REgional Climates for Impact Studies) model is derived from the third-generation Hadley Center regional climate model (HadRM3) and is based on HadAM3P, an improved version of the atmo- spheric component of the latest Hadley Center coupled AOGCM (HadCM3). It is an atmospheric and land surface model of limited area and high reso- lution and can be positioned over any part of the globe. Dynamical flow, clouds and precipitation, radiative processes, the land surface and the deep soil are all described. It is forced at the lateral boundaries by HadAM3P GCM. The lateral boundary conditions comprise the standard atmospheric variables of surface pressure, horizontal wind components and measures of atmospheric temperature and humidity. The surface boundary conditions include observed sea surface temperatures (SSTs) and sea-ice. There is no prescribed constraint at the upper boundary of the model. The model has 19 vertical levels, the lowest at ∼50m and the highest at 0.5 hPa with terrain-following σ-coordinates (σ = pressure/surface pressure) used for the bottom four levels, purely pressure coordinates for the top three levels and a combination in between. Due to its fine resolution, the model requires a timestep of 5 minutes to maintain numerical stability. We carried out sim- ulations over the region of Central America (Fig.S1) at a resolution of 25 km. The model results presented in this paper are based on one member of the ensemble. 2 Calculating Cloud Base Heights Along the windward slopes of Costa Rica, the moisture-laden air is orograph- ically uplifted as the trade winds encounter the cordillera. If we assume an air parcel that cools at a dry adiabatic lapse rate without an input or loss of moisture, then we can calculate the lifting condensation level (LCL), the level at which a raising air parcel becomes saturated. The LCL coincides with the cloud base level. The vapor pressure and the saturation vapor 1 pressure are calculated using the following equations. L 1 1 e = e0 × exp − (1) Rv T0 TD L 1 1 es = e0 × exp − (2) Rv T0 T where, T0 = 273.15K, e0 = 0.611kP a, T is surface air temperature, and TD is the dew point temperature. Relative humidity (RH) is given as, e RH = × 100 (3) es Since the model gives us T and RH at the surface, TD can be calculated. Equations (1),(2) and (3) result in the following formula for the dew point temperature as a function of T and RH. T ln(RH/100)−1 TD = T 1 − (4) L/Rv 6 −1 −1 −1 where, L = 2.453 × 10 JKg , and Rv = 461JK Kg . Now we can calculate the pressure at the LCL (mbar) using the following formula (Geogagakos and Bras, 1984), 1 P = P (5) LCL 3.5 surf T −TD 223.15 + 1 where, Psurf is the surface pressure. The pressure at LCL allows us to cal- culate the cloud base heights using model geopotential heights. The cloud bases are calculated for dry season months (Dec-Feb) using mean monthly T and RH values. This exercise is to determine what the altitude of cloud formation would be if the air from lower elevations is lifted adiabatically. This is one of the reasons why we chose grid-points with elevation less than 800 m for this analysis. Furthermore, the horizontal grid resolution of the model is larger in size than any individual cloud, and the model RH does not reach 100% for individual grid-points (Fig.S2). For this reason, the LCL estimates always lie above the grid-point elevation, which is not always true for higher elevations. Also the altitude of cloud formation cannot be deter- mined by looking at 100% RH surface. Therefore there is some difficulty in estimating the actual height of the cloud bank. Nevertheless, the relative humidity surface can be used as a grid-scale cloud cover proxy. Figure S2 2 shows the RH values as a function of elevation along a transect in Costa Rica for the control and SRES A2 runs. These show a reduction in RH at all elevations in future. Reference Georgakakos, K.P. and Bras, R.L. (1984). A hydrologically useful station precipitation model. 1.Formulation. Water Resources Research, 20 (11), 1585-1596. 3.
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