2005/11/18
ECPC CEOP Contributions
Ruane, A., J. Roads, M. Kanamitsu, E. Bainto
Scripps ECPC
UCSD, 0224
La Jolla, CA 92093-0224
aruane@ucsd.edu
http://ecpc.ucsd.edu/
The Scripps Institution of Oceanography's Experimental Climate Prediction Center (ECPC)
works in collaboration with NCEP to analyze and develop their global and regional atmospheric
models. In particular, the ECPC is currently using both the NCEP/DOE Reanalysis II model
(RII; Kanamitsu et al. 2002; Roads et al. 2002, Roads 2003) and the NCEP seasonal forecast
model (SFM; Kanamitsu et al. 2002) to provide model output for CEOP (see e.g. Roads et al.
2003). Physical characteristics of these two models in comparison to other NCEP models are
shown in Table 1. The resolutions of both of these two models are T62L28 and they are both
initialized from the RII.
The outputs from the two ECPC models (SFM and RII) include analysis files (F00), and forecast
files every 3hours (F03 and F06) from short-range 6-hour forecasts initialized every 6 hours (00,
06, 12, 18 UTC). In addition, every 24 hours (12 UTC), the 6 hour forecast is extended to 36
hours and again model output will be made available every 3 hours of the forecast. Table 2
shows the output schedule. This output is available from the beginning of CEOP (Jul. 1, 2001Dec. 31, 2004). Note that there are several time derivatives that can be defined ranging from the
difference of analysis variables to the difference of forecast variables. The tendencies of forecast
variables define the local tendencies, which may be important for deducing moisture and heat
convergences that are otherwise calculated from instantaneous atmospheric variables. The
differences between forecast variables and analysis variables are also important for deducing
analysis increments.
Raw ECPC output files (F00, F03, F06, ...) provided to MPI:
PGB (2.5 degree 144x73x17 grid linear grid with pressure levels) ~2 MB (GRIB)
o
Multiple atmospheric variables on 17- pressure levels
(1000,925,850,700,600,500,400,300,250,200,150,100,70,50,30,20,10 mb)
FLX (T62, on 192x94 gaussian grid) ~2 MB (GRIB)
o
Surface fluxes, precipitation, land parameters
DIV (L28T62, on 192x94x28 gausian grid with sigma levels. ft03+ only) ~5 MB (GRIB)
o
Heating diagnostics converted to mass-weighted variables. Vertical integrals of
o
heating profiles.
SGB (L28T62, on 192x94x28 gaussian grid with sigma levels) ~18 MB (GRIB)
o
Gridded atmospheric variables and diagnostics on 28 sigma levels
ECP (L28T62, on 192x94x28 gaussian grid with sigma levels) ~15 MB (GRIB)
o
Gridded atmospheric variables and dynamical processes (moisture, moisture flux,
o
convergence, energy flux, etc.), 3-D mass-weighted variables and vertical integrals
o
on 28 sigma levels.
MOLTS (41 stations x 28 layers) 0.4 MB (NetCDF)
o
Processed from PGB, FLX, DIV, DIA, SGB, SFB, ECP files after the forecast.
o
There are 41 columns corresponding to 41 observation sites and 108 variables
o
described in Table 3. Note that some variables differ in dimensionality and grid
o
spacing.
These files are provided in individual directories labeled yyyymmddhh, where the hh
corresponds to the initial analysis of the starting time (00, 06, 12, 18).
Auxiliary files, stored locally at ECPC (not submitted to CEOP via MPI) include
SIG (L28T62) 3.5 MB, binary
o
Atmospheric forecast variables (spectral)
SFC (T62) 3.6 MB, binary
o
Land surface forecast variables (grid-point)
Fortran and Matlab software is being developed to read these files and generate MOLTS and
gridded output for WESP and monsoon science requirements. The variables and the original raw
ECPC output are provided in Table 3. For the 3.5 years of CEOP, it is estimated that the raw
output files will be just under a TB for the analysis files; the forecast files will be another TB.
Together, both models will be about 2 TB in size.
Characteristics of the MOLTS sites, taken from the SFC files, are shown in Table 4. These
characteristics show the station number, name, geographic location, the corresponding model
location and grid points, along with the station roughness, soil type and vegetation type.
References
Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G.
White, J. Woolen, Y. Zhu, A. Leetma, R. Reynolds, M. Chelliah, W. Ebisuzaki, W.
Higgins, J. Janowiak, K.C. Mo, R. Jenne, and D. Joseph, 1996: The NCEP/NCAR 40Year Reanalysis Project, Bulletin of the American Meteorological Society, 77:437-471.
Kanamitsu, M., A. Kumar, H.-M. H. Juang, W. Wang, F. Yang, J. Schemm, S.-Y. Hong,
P. Peng, W. Chen and M. Ji, 2002a: NCEP Dynamical Seasonal Forecast System
2000. Bull. Amer. Met. Soc., 83, 1019-1037.
Kanamitsu, M., W. Ebisuzaki, J. Woolen, J. Potter and M. Fiorino, 2002b: NCEP/DOE AMIP-II
Reanalysis (R-2). Bull. Amer. Met. Soc. 83, 1631-1643.
Roads, J., M. Kanamitsu, R. Stewart, 2002: CSE Water and Energy Budgets in the NCEP-DOE
Reanalysis II. J. Hydrometeorology , Vol. 3, Issue 3, p. 227-248.
Roads, J., 2003: The NCEP/NCAR, NCEP/DOE, TRMM: Tropical Atmosphere Hydrologic
Cycles. Journal of Hydrometeorology (in press).
Roads, J., M. Bosilovich, M. Kanamitsu, M. Rodell, 2003: CEOP Pilot Data Comparisons.
CEOP Newsletter March 2003, Issue 3, pp. 2-5.