Final report for Project Dynamical downscaling for SEACI. Principal Investigator: John McGregor

Transcription

1 Final report for Project Dynamical downscaling for SEACI Principal Investigator: John McGregor CSIRO Marine and Atmospheric Research, Tel: , Fax: , Address: PB1 Aspendale, Vic Co-Author: Kim Nguyen, CSIRO Marine and Atmospheric Research Updated: October

2 Abstract: A 50-year simulation has been successfully performed using CCAM for downscaling the NCEP reanalyses. Over the MDB region, seasonal rainfall biases are generally less than 0.5 mm/day. The simulated average daily maximum and minimum temperatures are found to be acceptable; the maximum temperatures tend to be up to 3 degrees too cool in autumn and winter; the minimum temperatures tend to be a little warm, except in Victoria in winter when they are up to 2 degrees too cool. The interannual variability of rainfall is well captured, with the El Nino years of 1972, 1977, 1982, 1991, 1994 and 1997 all displaying suitably reduced rainfall over the MDB region. A decline in pan evaporation is simulated over the MDB region, in broad agreement with observed trends. Project Objectives: Validate CCAM by comparing the simulated climatology, in particular rainfall and temperature, against observations taken within the study region. Produce derived fields (including surface fluxes and measures of potential evaporation) and compare them against available observations and observed trends. 1. Model description CCAM is formulated on the quasi-uniform conformal-cubic grid. The CCAM regional climate simulations for SEACI use a C72 global grid (6 x 72 x 72 grid points), with a nominal grid spacing of 138 km. By using the Schmidt (1977) transformation with a stretching factor of 0.15, CCAM then achieves a fine resolution of 20 km for the central panel which is located over eastern Australia. The grid is illustrated in Figure 1. The dynamical formulation of CCAM includes a number of distinctive features. The model is hydrostatic, with two-time-level semi-implicit time differencing. It employs semi-lagrangian horizontal advection with bi-cubic horizontal interpolation (McGregor, 1993; McGregor, 1996), in conjunction with total-variation-diminishing vertical advection. The grid is unstaggered, but the winds are transformed reversibly to/from C-staggered locations before/after the gravity wave calculations, providing improved dispersion characteristics (McGregor, 2005a). Three-dimensional Cartesian representation is used during the calculation of departure points, and also for the advection or diffusion of vector quantities. Further details of the model dynamical formulation are provided by McGregor (2005b). CCAM includes a fairly comprehensive set of physical parameterisations. The GFDL parameterisation for longwave and shortwave radiation (Schwarzkopf and Fels, 1991) is employed, with interactive cloud distributions determined by the liquid and ice-water scheme of Rotstayn (1997). The model employs a stability-dependent boundary layer scheme based on Monin-Obukhov similarity theory (McGregor et al., 1993), together with non-local vertical mixing (Holtslag and Boville, 1993) and also enhanced mixing of cloudy boundary layer air (Smith, 1990). A canopy scheme is included, as described by Kowalczyk et al. (1994), having six layers for soil temperatures, six layers for soil moisture (solving Richard's equation), and three layers for snow. CCAM also includes a simple parameterisation to enhance sea surface temperatures under conditions of low wind speed and large downward solar radiation, affecting the calculation of surface fluxes. The cumulus convection scheme uses the mass-flux closure described by McGregor (2003), and includes both downdrafts and detrainment. 54

3 Figure 1. The C72 conformal-cubic grid used for the CCAM simulations. 2. Simulation design CCAM can be run in stand-alone mode for a modestly stretched grid, requiring only initial conditions and prescribed fields for sea-ice and SST. For the simulation described in this paper, global nudging of winds above 500 hpa from the large-scale fields is also employed, with an e- folding time of 24 h. Outside the central high-resolution panel, gradually-increasing far-field nudging is also employed for surface pressures and winds between 900 hpa and 500 hpa. This technique is appropriate when comparisons are being made with specific years (such as when the forcing is being provided by reanalysis fields), or for climate change simulations where the far-field model resolution may be considered too coarse to provide a reliable climatology in the coarse region. A 50-year simulation from January 1951 to December 2000 was carried out with initial conditions, sea surface temperatures (SSTs) and global forcing of wind provided by the NCEP-1 reanalyses (Kalnay et al., 1996). The model output was saved twice per day at 00 GMT and 12 GMT. These data have been post-processed onto a 0.2 degree grid covering 130E - 160E and 50S - 5S. Many prognostic and diagnostic fields have been saved. 55

4 Figure 2. Seasonally-averaged rainfall (mm/day), with observations (top) and CCAM (bottom). Figure 3. Bias of seasonally-averaged rainfall (mm/day). 56

5 Figure 4. Seasonally-averaged maximum temperatures (degrees C), with observations (top) and CCAM (bottom). Figure 5. Bias of seasonally-averaged maximum temperatures (degrees C). 57

6 Figure 6. Seasonally-averaged minimum temperatures (degrees C), with observations (top) and CCAM (bottom). Figure 7. Bias of seasonally-averaged minimum temperatures (degrees C). 3. Seasonal averages of rainfall and temperature The 50-year ( ) monthly-mean CCAM rainfall was averaged to produce seasonal averages for December, January and February (DJF), March, April and May (MAM), June, July and August 58

7 (JJA) and September, October and November (SON). These averages may be compared in Figure 2 against the observed seasonal rainfall, and the maximum and minimum temperatures provided by the Bureau of Meteorology. In general, CCAM simulates well the mean rainfall patterns (Figure 2), with biases (Figure 3) less than 0.5 mm/day over the MDB. The larger rainfall along the Great Dividing Range and the eastern coast is well captured for all seasons. The simulation slightly overestimates the SON rainfall over the northern part of the MDB. Outside the MDB region, the DJF rainfall is underestimated in the northernmost part of Australia. The average daily-maximum surface air temperatures (Figures 4 and 5) are generally well simulated for DJF and SON, although they are a little cool in the northern part of the MDB in SON (corresponding to the overestimated rainfall in the same location). For MAM and JJA the maximum temperatures are too cool for much of the MDB, by degrees for MAM and 2-3 degrees for JJA. The patterns of the average daily-minimum surface air temperatures (Figures 6 and 7) are well simulated, although the minimum temperatures tend to be up to 1 or 2 degrees too warm for most seasons. In contrast, in JJA the minimum temperatures are 1-2 degrees too cool over much of Victoria. 4. Interannual variability The interannual variability of the simulation is illustrated by means of time series of the annual averages for rainfall and pan evaporation. The averages are taken over land points for two regions: Region 1: the GRDC southern region, 134E - 154E and 39S - 32S Region 2: a larger MDB region, 141E - 154E and 39S - 25S. Figure 8 shows the annual rainfall for region 1. Overall, there is very good agreement between the CCAM simulation and the observations regarding the interannual behaviour. Before 1955, the agreement is not as good, and the simulated rainfall is mostly less than observed; it may be that it takes a few years for the simulated deep soil moistures to settle down. In the following years, up till about 1975, the simulated rainfall also tends to be somewhat lower than observed. This cannot be attributed to equilibration of the soil moisture, but is most likely due to deficiencies of the NCEP reanalysis during that period with regard to the upper-level winds used by the simulation. Note that satellite data was only available for the latter half of the reanalysis period. The El Nino years of 1972, 1977, 1982, 1991, 1994 and 1997 are well captured by low rainfall in the time series. Figure 9 for the larger region 2 shows similar results for the time series, and similar agreement with the observations, although the simulated rainfall minimum is not as pronounced for the 1977 El Nino year. A paper is in preparation describing the simulation and the good agreement found between the observed and simulated rainfall trends. 59

8 Rainfall Obs CCAM Figure 8. Time series of observed and simulated annual rainfall for region 1 (the southern GRDC region) for Rainfall Obs CCAM Figure 9. As for Figure 8, but showing the time series for the larger region 2. In the CCAM simulation, we also explicitly calculate pan evaporation, by predicting at each time step the water temperature for a pan located at each grid point. Sensible and latent heat fluxes are calculated as part of this process. Figure 10 shows the time series for the annual pan evaporation averaged over both regions. Both time series indicate a decreasing trend for pan evaporation of 0.9 mm/yr/yr for region 1, and 2.4 mm/yr/yr for the larger region 2. These trends are broadly consistent with the Australia-wide decreasing trends of 4.4 mm/yr/yr from reported by Roderick and Farquhar (2004). A second paper will be prepared describing the pan evaporation results, and this will also include comparisons with the recent high-quality analyses of the Bureau of Meteorology. 60

9 Epan Reg1 trend Reg2 trend Epan reg1 Epan reg2 Figure 10. Time series of simulated pan evaporation (mm/year) averaged over regions 1 and 2 for List of publication titles: No publications to date. References Holtslag, A. A. M., and B. A. Boville, 1993: Local versus non-local boundary layer diffusion in a global climate model. J. Climate, 6, Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, R. Jenne, and D. Joseph, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteorol. Soc., 77, Kowalczyk, E. A., J. R. Garratt, and P. B. Krummel, 1994: Implementation of a soil-canopy scheme into the CSIRO GCM -regional aspects of the model response. CSIRO Div. Atmospheric Research Tech. Paper No. 32, 59 pp. McGregor, J. L., 1993: Economical determination of departure points for semi- Lagrangian models. Mon. Wea. Rev., 121, McGregor, J. L., 1996: Semi-Lagrangian advection on conformal-cubic grids. Mon. Wea. Rev., 124, McGregor, J. L., 2003: A new convection scheme using a simple closure. In "Current issues in the parameterization of convection", BMRC Research Report 93, McGregor, J. L., 2005a: Geostrophic adjustment for reversibly staggered grids. Mon. Wea. Rev., 133, McGregor, J. L., 2005b: C-CAM: Geometric aspects and dynamical formulation [electronic publication]. CSIRO Atmospheric Research Tech. Paper No. 70, 43 pp. McGregor, J. L., H. B. Gordon, I. G. Watterson, M. R. Dix, and L. D. Rotstayn, 1993: The CSIRO 9-level atmospheric general circulation model. CSIRO Div. Atmospheric Research Tech. Paper No. 26, 89 pp. Roderick, M. L., and G. D. Farquahar, 2004: Changes in Australian pan evaporation from 1970 to Int. J. Climatology, 24,

10 Rotstayn, L.D., 1997: A physically based scheme for the treatment of stratiform clouds and precipitation in large-scale models. I: Description and evaluation of the microphysical processes. Quart. J. Roy. Meteor. Soc., 123, Schmidt, F., 1977: Variable fine mesh in spectral global model. Beitr. Phys. Atmos., 50, Schwarzkopf, M. D., and S. B. Fels, 1991: The simplified exchange method revisited: an accurate, rapid method for computation of infrared cooling rates and fluxes. J. Geophys. Res., 96, Smith, R. N. B., 1990: A scheme for predicting layer clouds and their water content in a general circulation model. Quart. J. Roy. Meteor. Soc., 116,

11 Project Milestone Reporting Table To be completed prior to commencing the project Milestone description 1 (brief) (up to 33% of project activity) 1. Compare alternative downscaling techniques (wind forcing from upper-air versus far-field) Performance indicators 2 (1-3 dot points) Complete satisfactory 10-year trial simulation Produce promising interannual rainfall behaviour in the trial simulation Completion date 3 xx/xx/xxxx Budget 4 for Milestone ($) Completed at each Milestone date Progress 5 (1-3 dot points) 31/7/06 33k Completed None Recommended changes to workplan 6 (1-3 dot points) 2. Complete the simulation from at 20 km resolution 3. Comparison of model output with available observations Completion of full simulation Satisfactory climatology of rainfall and maximum and minimum temperatures Complete an analysis of rainfall, extremes and trends against available observations Produce an analysis of maximum and minimum temperatures Analyse measures of potential evaporation produced by the simulation Examine the model output with regard to behaviour during El Nino years. 4 page report produced. 30/11/06 34k Completed the full simulation, producing a very acceptable climatology of rainfall and maximum and minimum temperatures 31/12/06 33k An analysis of the required fields has been performed. The simulation has produced good interannual behaviour of rainfall. Many diagnostic and prognostic fields have been saved 12-hourly, including the simulated pan evaporation. A report has been prepared. None 63