WORLD METEOROLOGICAL ORGANIZATION
____________________
GPC-SIF/Doc. 5.7
(7.II.2003)
_________
COMMISSION FOR BASIC SYSTEMS
WORKSHOP OF GLOBAL PRODUCERS OF
SEASONAL TO INTERANNUAL FORECASTS
ITEM: 5.7
Original: ENGLISH
Geneva, 10-13 February 2003
Long Range Forecasts in the Meteorological Service of Canada
(Submitted by J.G. Desmarais)
GPC-SIF/Doc. 5.7
Long Range Forecasts in the Meteorological Service of Canada
1.
INTRODUCTION
In the Fall of 1995, the Canadian Meteorological Centre (CMC) began producing the Meteorological
Service of Canada (MSC) seasonal temperature and precipitation anomaly forecasts using objective
methods; an ensemble approach using dynamical models is used for season 1 whereas a statistical
method is used for seasons 2 to 4.
Seasonal forecasts information is put without restriction on the Weather link of the Meteorological
Service
of
Canada
web
page
at
the
following
address:
http://weatheroffice.ec.gc.ca/saisons/index_e.html
Information depicted on the web page includes the seasonal forecasts themselves, skill charts,
verification of previous forecasts, climatology used, as well as current anomalies for SST’s, ice and
snow.
In addition, some probabilistic experimental products are produced operationally and put on the
Intranet. These are not available outside the MSC.
2.
ISSUE AND LEAD TIMES.
The seasonal forecasts are issued on the first day of December, March, June and September. Since
the forecasts are issued approximately 21 days prior to start of the "official season", it might be more
appropriate to call them "90-day" or "3-month" forecasts. However, the word "seasonal" is used
because of the importance seasons have for the public and media.
The forecasts for season 1 are issued with zero lead time whereas the forecasts for seasons 2 to 4 are
issued with lead times of 3, 6 and 9 months respectively.
3.
FORECAST PARAMETERS
For seasons 1 to 4, a 90-day temperature and precipitation anomaly outlook based on a priori 3-equally
probable categories: "ABOVE NORMAL", "NEAR NORMAL" and "BELOW NORMAL". Categories
correspond to +/- .43 standard deviation of the climatology.
4.
MODELS AND TECHNIQUES USED TO PRODUCE THE SEASONAL FORECASTS.
4.1 SEASON 1:
Season 1 forecasts are produced using a dynamical approach. Two ensembles of 6 twenty-four hour
time-lagged runs are produced: 6 from a T63 L23 version of the SEF previous operational prediction
model, and 6 from a T32L10 General Circulation Model (GCM2). For both models, the first run is done 96
days prior to issuing the forecast, and the subsequent 5 runs are done with a one-day lag (i.e. 95, 94,…
and 91 days prior to issuing).
Both models use the same initial operational analyses. SST anomalies observed over the previous 30
days are added to climatological values over the 3-month period (anomaly persistence); snow is gradually
relaxed towards climatology at the end of the first month, except for the GCM2, where it is a prognostic
variable. The analyzed ice edge is gradually relaxed towards climatology within the first month.
The surface air temperature anomaly forecast is done using 1000-500 hPa thickness (DZ) anomaly
extracted from the 12 member ensemble. The 2 sets of 6 forecasts are averaged separately for both
models. A hybridization of the two DZ forecasts is done using a Best Linear Unbiased Estimator
(BLUE) method. The hybridized thickness anomaly is then related to the surface temperature
anomalies at 264 Canadian stations by a "perfect prog" (PP) technique (linear regression analysis).
Precipitation forecast is simply the ensemble average of the seasonal precipitation anomaly amount.
The anomaly field is normalized to take into account the individual models standard deviations. This
GPC-SIF/Doc. 5.7, p. 2
ensures that the variance of the forecasts is close to the observed inter-annual variance. The anomaly
is calculated using as a climate the average of the Historical Forecast Project (HFP) runs.
Temperature and precipitation anomalies are then compared to the model climatology in order to
produce the 3-category forecasts. The threshold to be different from normal is ±0.43 times the model
inter-annual standard deviation.
Probabilistic forecasts for temperature, precipitation and 1000-500 hPa thickness anomalies over the
global domain are also made by counting the number of members in each category (ABOVE, NEAR and
BELOW NORMAL) divided by the ensemble size as a probability of occurrence. The predicted fields are
direct model surface air temperature and precipitation. These for now are available only as guidance
within the MSC.
Definition of anomaly:
Three equiprobable categories (ABOVE, NEAR and BELOW NORMAL) for the period 1963-1993, for
temperature and precipitation.
Bias removal:
The climatic drift in both models is removed using their known climatology. The models climatology
comes from the 26-year hindcast of the seasonal Historical Forecasting Project (HFP1 protocol), for the
period 1969-1994.
4.2 SEASONS 2 to 4:
Seasonal temperature and precipitation anomaly forecasts for seasons 2 to 4 (3 to 9 months lead
times) at Canadian stations using a statistical technique of Canonical Correlation Analysis or CCA
The analyzed field of SSTA’s over the previous twelve months are used to forecast the temperature
and precipitation anomalies at various lead times. The SSTA’s are obtained from the CMC global
analysis of mean monthly SST, for each of the 12 months preceding the date on which the forecast is
issued. The SSTA’s are averaged spatially over 10 X 10 degree grid cells and over three-month
periods. The statistical relationships between the observed SSTA’s and the subsequent temperature
and precipitation anomalies have been developed from a 39-year data set (1956 to 1994). Equations
are available to generate forecasts for lead times of up 9 months. The CCA forecasts are produced for
51 selected Canadian stations for temperature, and 69 stations for precipitation. These are then used
to produced anomaly forecasts maps over Canada.
5.
SKILL
The seasonal anomaly forecasts are of interest but of limited use if one cannot give some estimate of
confidence. This is why skill products have to be used in conjunction with the forecasts themselves.
Forecasts skill is established based on the HFP runs. Skill maps (percent correct) for the seasonal
temperature and precipitation anomaly forecasts for seasons 1 to 4 are posted on the web page.
6.
PRODUCTS ON PUBLIC SITE:
Domain:
Canada and Arctic regions.
Seasonal temperature and precipitation anomalies forecasts:
Graphical maps of temperature and precipitation anomalies in 3 equiprobable categories (ABOVE,
NEAR and BELOW NORMAL) for four consecutive 3-months period.
Skill maps:
Each forecast map is accompanied by a skill map depicting the percentage correct of forecasts in
either category in the HFP period. The significant skill threshold for a 26-season HFP set is established
at 45% and is therefore enhanced.
In addition, skill maps for each 3-month period and for each season for temperature and precipitation
are available.
GPC-SIF/Doc. 5.7, p. 3
Verification data:
Verification of past seasonal forecasts since their implementation is available either in chart format or
as contingency tables. Categories used to verify are the same as used in forecasts, i.e. ABOVE, NEAR
and BELOW NORMAL.
Climatological data:
Maps/tables of climatological temperature and precipitation for the various seasons are available.
7.
EXPERIMENTAL PRODUCTS ON INTRANET
Domain:
Global (with a Canadian sub-window)
Probabilistic forecasts of ABOVE, NEAR and BELOW NORMAL categories for surface temperature,
precipitation and 1000-500 hPa thickness anomalies.
These forecast probabilities are calculated by counting the number of individual members in each of
the three categories at every location and then by dividing by the ensemble size. Charts are shown by
sets of three depicting respectively probabilities for ABOVE, NEAR and BELOW NORMAL categories
of the forecast variable. Model outputs are corrected for model drift using HFP1 data.
8.
OTHER GLOBAL DATA AND PRODUCTS
Raw HFP data:
Raw HFP data are available on the web site of the Climate Research Branch of the MSC, at the
following address:
http://www.cccma/data/hfp/hfp.shtml
Hindcast data for both SEF and GCM2 models are available for a series of variables on a 97 X 48 grid
(global) and on a 51 X 55 polar stereographic grid for both Northern and Southern Hemisphere.
Variables available are surface temperature, precipitation, T700, and geopotential heights for 500 and
1000 hPa levels.
Forecasts:
Global forecasts for both the SEF and GCM2 models will shortly be available on web site of the
Climate Research Branch and on the same grid as the HFP data. Individual member monthly means
for the same variables as for the HFP’s will be available.
9.
CURRENT/FUTURE ACTIVITIES
Progress will be slow in the current year, since a major code conversion related to a change in
supercomputer (from NEC to IBM) will take place.
Some of the activities currently taking place and planned for the future are:

The SEF and GCM2 models used in seasonal prediction will be replaced by 2 new models, i.e. the
GEM-DM (same model as the one used in operational NWP at the CMC) and the GCM3 models.
hindcast runs using these 2 new models are currently being produced under the HFP2 protocol (30
years of forecasts, 1970-2000).

Produce 3-month forecasts every month, instead of every 3 months.

The HFP2 protocol will allow to produce 3-month forecasts both with zero and one month lead
times (for the first 90-day period).

Probabilistic maps available on the MSC web site.