1. ECPC’s
Experimental Forecast System
There is a major change underway at the Scripps
Experimental Climate Prediction Center (ECPC). Previously, the ECPC used the
reanalysis I version (Kalnay et al. 1996) of the
National Centers for Environmental Prediction’s (NCEP’s)
medium range forecast (MRF) model or global spectral model (GSM; Roads et al.
2001a,b,2002) to make routine experimental global
forecasts. These global forecasts (daily out to 7days and weekly out to
16-weeks) start from the NCEP operational 00UTC global analysis and use persisted SST anomalies (+climatology).
These experimental GSM forecasts are being
replaced by an updated version of NCEP's seasonal
forecast model (SFM; Kanamitsu et al. 2002a), which
is based on updated physics from the NCEP/DOE reanalysis II (Kanamitsu et al. 2002b). The SFM has a nominal (a reduced
grid technique is used near the poles) horizontal resolution of T62 (about 2o).
There are 28 levels in the vertical sigma coordinate system. ECPC's SFM is run in a different fashion from the GSM.
Starting from slightly perturbed initial conditions, and forced with observed
SST anomalies, 10 simulations are made up to present. Then, an ensemble of forecast SSTs are used
to generate a 7-month forecast ensemble.
The forecast SSTs come from simplified models (3) for the tropical
Pacific and are produced by the IRI; four 7-month forecasts are produced for
each IRI SST prediction. This new SFM is being coupled to the MIT ocean model
and sometime in the future we hope to demonstrate that such a coupled system
will be as useful as current persisted or forecast SSTs as well as our current
uncoupled experimental ocean forecasts, which use forecast GSM anomalies to
drive a Pacific Ocean model (Auad et al. 2003).
A major advantage of the SFM over the GSM is
that the computer code of the SFM was completely rewritten to run on multiple
platforms with single and/or multiple shared memory machines. The code was
improved further to run on massively parallel processor (MPP) machines using
Message Passing Interface (MPI) routines. Normally the SFM runs on 64 LINUX
processors and takes 2 hours to make a 7-month forecast. Depending upon the
number of ensemble members, a normal 7-month forecast takes between 1-2 days.
During the rest of the month background runs are being made to augment the
growing ensemble climatology. In addition, as changes are made in the model new
climatologies have to be developed. It should also be
noted that there are a few physical parameterization differences between the
ECPC SFM and the NCEP SFM. The ECPC SFM
has an updated land surface model (Noah). However, it should be noted that the
NCEP SFM does start from observed initial conditions unlike the ECPC SFM, which
is starting from previous simulations. Ignoring the initial conditions is
generally thought to be reasonable when considering long-lead forecasts
(greater than a month) although there are certainly times and places when
initial conditions can be important even for seasonal forecasts (Reichler and Roads 2003, 2004, 2005a,b). Another difference between ECPC SFM and NCEP
SFM is the initial condition of the soil moisture. In the NCEP SFM, climatological
soil moisture is used while in the ECPC SFM; the simulated soil moisture is
used.
The ECPC SFM has not yet fully replaced the ECPC
GSM in part because the GSM is currently tightly linked to a number of
additional models and applications. The GSM forces a regional spectral model
(RSM; Juang et al. 1997; see also Chen et al. 1999;
Anderson et al. 2000a,b; Anderson and Roads 2002;
Roads et al. 2003a,b; Han and Roads 2004; Roads 2004a,b; Chen and Roads 2005)
in order to gain increased spatial resolution (e.g. 50-25 km resolution) for
several selected regions (e.g. US, CA). The GSM and RSM are based upon the same
physics used in the GSM (and SFM) and can, in principle, be updated as the GSM
(SFM) is updated. Current output products from the GSM/RSM include a fire
weather index and associated variables such as 2m-temperature, relative
humidity and 10m-windspeed as well as precipitation and soil moisture.
Additional RSM products are provided to drive the US National Fire Danger
Rating System Indices (Roads et al. 2005) and surface hydrologic models.
2.
Forecast Skill Evaluations
Seven years worth of forecasts (364 forecasts)
were previously used to develop GSM/RSM forecast climatologies,
which are dependent upon season as well as forecast lead-time. Both means and
standard deviations were derived in order to provide normalized anomalies. As
discussed by Roads et al. (2001a,b, 2002, 2003), Chen
et al. (2001), Roads (2004a,b, 2005), the GSM/RSM provides skillful forecasts
of temperature, precipitation, and soil moisture and fire danger indices at
long forecast ranges. Although the greatest skill occurs initially and then
rapidly decays, monthly and seasonal averages can still demonstrate significant
skill (Reichler and Roads 2003a,b,c,d),
which may be comparable to empirical long-range forecast methodologies.
ECPC SFM forecast skill evaluations are still
underway in collaboration with the IRI and NCEP and will be reported upon
later. Suffice it to say that the ECPC SFM has skill comparable to other
forecast models used by IRI, namely ECHAM, NCAR’s
CCM, NASA’s NSIPP GCM and COLA’s GCM. In fact, ECPC SFM forecast products now
contribute to the making of better multi-model ensemble forecasts at the IRI
and NCEP.
As a preliminary evaluation of the SFM
forecasts, we have been comparing the GSM anomaly forecasts with the
corresponding SFM forecasts. It should be noted here that the GSM is
initialized at the beginning of the month, whereas the SFM ensemble members are
initialized one month earlier from continuous simulations using observed SSTs.
The GSM and SFM also have different base climatologies
(5 years for the GSM and 52 years for the SFM). Nonetheless, there are some
remarkable agreements as well as some major disagreements. We first show the
comparison in which the SFM is forced by persisted SSTs. There are many
similarities and some differences. We then show SFM forecasts forced by the IRI
forecast tropical SSTs.
Fig. 1 shows that during MAM,
both models show forecast temperature anomalies being high over Alaska, Canada,
central and S. America, Africa, S.E. Asia and the US northwest. Anomalies are
low over Siberia and the Southeast US. There are a few differences. GSM has
Europe below normal while the SFM has it above normal.
Fig. 2 shows that during MAM
both models are forecasting above normal precipitation over the central to
western Pacific Ocean Above normal precipitation is also being forecast for the
southwest US and Europe. Slightly below normal precipitation is being forecast
over Australia and Africa. There are certainly some differences. For example,
the SFM tends to be dry over Central Africa and the Indonesian Archipelago,
whereas the GSM has above normal rainfall in these regions.
3. Global
seasonal GSM forecasts and US monthly RSM forecasts for additional months
Below normal temperatures (Fig. 3) are being forecast for most of the central US, Canada, and
the Middle East. Above normal temperatures are being forecast for S. America,
Africa and Australia and which may be related to persistent above normal
temperatures in the central Pacific. Above normal temperatures are also being forecast for most SH land areas, including
Antarctica. Above normal temperatures
over northern Asia and the northwest US and Canada are
forecast to change to below normal temperatures later in the summer.
Precipitation (Fig. 4) also shows this persistent character in the tropics, which
may be related to a persistent tropical SST. Above normal precipitation is
being forecast by the SFM over the southern Indian Ocean, the equatorial
Pacific, the US Northwest, and below normal precipitation is being forecast
over South Africa, India, and the Indonesian Archipelago.
The 500 mb height
forecast anomalies associated with these forecast precipitation and temperature
anomalies (Fig. 5) indicates that
the central US low temperature and high precipitation are associated with
offshore highs on both coasts, which changes to a low over the Northwest and a
high over the Gulf of Mexico. The strong Antarctic high at the beginning of the
northern hemisphere summer changes to a strong low at the end. The forecast
lows over Russia, Greenland, Australia persist from April to Sept., as does the
anomalous high off the coast of S. America.
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