For
Indonesia, Sri Diharto noted that
the meteorological agency of
Indonesia (BMG) operates a seasonal
prediction scheme dividing the
country into 102 rainfall districts
called seasonal forecasting areas.
The
forecast methodology uses
statistical models that still depend
on rainfall data, which is variable
across place and time. The seasonal
forecast techniques are:
-
Statistical (regression)
techniques based on
relationships between rainfall
and SOI.
-
Probability methods based on the
rainfall time-series for that
district.
-
Auto-regressive techniques based
on the time-series.
-
Utilization of seasonal
forecasts and current
information on the SOI issued in
the seasonal outlooks of the BOM
(Australia).
-
General synoptic experience in
monitoring the situation at the
time of issuance of the forecast
ENSO
parameter sensitivity differs from
one seasonal forecasting area to
another. To account for this
difference, the seasonal prediction
scheme relies on statistical
analogues of past rainfall patterns.
A method that uses rainfall data and
ENSO parameters needs to be
developed further to incorporate
other meteorological parameters such
as upper air data (wind and water
vapor content).
One of
the major constraints to providing
statistical analogue forecasts was
non-availability of past rainfall
data in a usable format. Hence,
archiving and processing past
rainfall data is a priority for the
BMG. The major endeavour will be
processing the data and storing it
digitally for retrieval and use.
To
overcome the constraints, future
actions will include:
-
Replacing conventional
meteorological monitoring
sensors at collaborating
stations with tele-metered
sensors and using satellite
communication.
-
Exploring other meteorological
parameters in the forecast
methodology.
-
Improving database management to
facilitate research activities.
-
Improving data quality through
instrument calibration.
-
Encouraging staff to do applied
research.
Aida
Jose reported that there is a lack
of understanding in the region of
ENSO influences. The reduction of
global ENSO forecasts into local
climate forecasts using numerical
regional climate models is
non-existent, in part because of
insufficient scientific personnel
who can understand and translate the
ENSO forecasts. This is crucial
given the need for local ENSO-based
forecasts and their limitations to
be easily understood by various
end-users.
In the
absence of an appropriate numerical
regional or local climate model for
the Philippines, translation of ENSO
forecasts was carried out using the
approach of forecasting potential
impacts on local climate by analogy.
The following information was used
as diagnostic tools for downscaling
global ENSO forecasts into local
seasonal climate forecasts.
|
El Nino |
La Nina |
|
Extended dry season
Early end of rainy season
Weak monsoon activity
Less number of tropical
cyclones
Above normal sea level
pressure
Above normal air temperature
|
Short dry season
Early onset of rainy season
Strong monsoon activity
More number of tropical
cyclones
Below normal sea level
pressure |
|
Dry weather conditions
|
Wetter weather conditions |
The
Philippines meteorological agency (PAGASA)
also derived indicators to assess
potential impacts of predicted
climate variables on various sectors
such as agriculture and water
resources. The methodology was based
on the principle of potential impact
assessment by analogy, involving
translation of ENSO forecasts to
impacts on local climate and then to
potential impacts on various
sectors.
Some
of the constraints encountered in
the translation of ENSO forecasts
into local climate forecasts include
but are not limited to:
-
Climate parameters other than
ENSO and modes of atmospheric
variability that interplay other
than the air-sea interaction in
the Central and Eastern
Equatorial Pacific, or the ENSO
that impacts the climate
variability in the Philippines.
Such parameters include SST
anomalies in the South China Sea
and the Indian Ocean, the
Quasi-Biennial Oscillation (QBO)
and the Madden Julian
Oscillation (MJO).
-
Existence of some degree of
uncertainty (inherent?) in the
various General Circulation
Models used in generating ENSO
forecasts and disparity in their
results.
-
Selection and application of
suitable local climate models
for the Philippines has yet to
be done.
Suggested measures to overcome
constraints include:
-
More studies on the dynamics of
ENSO influences in the region.
-
Formal training and/or
fellowship programs in graduate
programs, or immersion
experience in global climate
centers.
-
An
operational numerical regional
climate model to predict ENSO
influence on the local climate.
-
More interfacing opportunities
between local climate forecast
producers and end-users.
-
A
guidance manual for an
integrated ENSO impact
assessment is needed to provide
a easy, coherent flow of
information, effective
collaboration and feedback
mechanism.
Constraints in Vietnam, according to
Pham Duc Thi, relate to
non-integration of global ENSO
parameters into a long-range
forecasting scheme in quantitative
terms. However, ENSO forecasts have
been recently used for making-long
range forecasts qualitatively. A
considerable research effort is
required to develop human resources
as well as equipment to use global
ENSO forecasts for translation of
global ENSO parameters into local
weather variables in quantitative
terms.
There
are significant sub-national
variations and interactions with
other non-ENSO processes. In using
tropical cyclones as a local weather
variable, there is a need to know
not just frequency, but also cyclone
intensity. An inability to produce
quantitative forecasts and limited
experience with dynamic modeling are
other constraints. In Vietnam, there
are plans to:
-
Study ENSO interaction with
other relevant processes.
-
Incorporate local knowledge in
making forecasts.
-
Focus on parameters where skill
is high.
Discussion Points
In
considering the translation of ENSO
parameters into local weather
variables, participants questioned
how dynamic modeling is done for
multiple impacts. In Vietnam,
multiple events can be a limitation
on resources. For example, a serious
drought may be followed by floods,
which could then be followed by
storms and landslides. The
sequential occurrence of multiple
extreme weather events like droughts
followed by floods, which would then
be followed by storms and
landslides, needs to be factored
into the modeling of long-range
forecasts.
Climate variability is a continuous
process and causes severe weather
events even in neutral years. Hence,
the sea surface temperature patterns
in the Central Eastern Pacific
constantly cause regional climate
variations. Climate forecasts need
to be evolved to capture all flavors
of sea surface temperature patterns,
regardless of the occurrence of El
Nino and La Nina.
One of
the biggest problems in translating
ENSO parameters into local weather
variables is that the current models
come from "developed countries". The
variables are fed into global
models, but then the information
from them must be translated to
reflect impacts at local level.
The
release of climate information to
the general public and the
government can be problematic;
therefore, the role of the media is
crucial to developing awareness and
improving reactions to an ENSO
forecast. The same definitions and
vocabulary may not be shared by
sector agencies and the national
meteorological agencies. The lack of
common vocabulary poses a serious
difficulty for decision-makers and
the media to appreciate
uncertainties inherent in long-range
forecasts. The development of a
common, understood vocabulary may be
the link to effective communication
with the media, the sector agencies
and the public. One example of this
is in Indonesia, where the
agriculture sector requests
forecasts from the meteorological
agency to make a forecast, but has a
different interpretation of the
meaning of the results, which are
reported as "normal", "above normal"
or "below normal" rainfall. When the
agriculture agencies are not
satisfied with the information, they
try to do their own analysis and
forecasts, which wastes money and
resources. The key to this problem
may be improved communication about
climate information among the
sectors.
End-users of climate forecast
information have unrealistic
expectations of the meteorological
service, which shoulders a huge
responsibility for the information
that they release, given that
different users will interpret the
information to serve their own
interests. To the extent that the
public does not know how to
interpret the degree of uncertainty
in the forecasts, some countries
have found that it helps to focus on
one type of forecast that can be
done well. For example, in Vietnam,
forecasts are concentrated on
typhoon predictions. As confidence
builds in the meteorological
services, it will be easier to
convey other types of forecasts.
Recommendations
Following the presentations and
discussions, the participants
focused on several issues of
importance. These included the need
to downscale information and make
models useful locally, as well as
ways that meteorological agencies
should work to present useful
information. The participants
suggested the following:
-
Undertake a comprehensive
assessment of long-range
forecast methodologies in each
country to identify gaps and
measures to address them, to
enable meteorological agencies
to downscale global long-range
forecasts into actionable
formats for use by policy-makers
and end-users.
-
Integrate user' needs and
suggestions to provide
user-friendly long-range
forecasts.
-
Conduct more studies on the
dynamics of ENSO influences in
the region.
-
Develop an operational numerical
regional climate model to
predict ENSO influence on the
local climate.
-
Develop a mechanism for
intermediate interpretation of
long-range forecasts that are
based on ENSO parameters into
locally usable information to
remove the barriers to
incorporating probabilistic
forecast information into
decision-making processes.
-
Address the critical gap between
short-range and long-range
forecasts. Mechanisms exist in
all three countries for
transmission of short- and
medium-range forecast
information by meteorological
agencies to forecast user
organizations. The long-range
climate forecasts are also
routinely transmitted by
meteorological organizations to
user organizations. However,
since long-range forecasts based
on global ENSO indices are of a
probabilistic nature, user
organizations are unable to
utilize them effectively for
decision-making.
-
Encourage capacity-building
efforts to enable user
departments and applied research
organizations to process and
refine long-range forecast
information products into usable
information for decision-making
and policy-planning purposes.
This may also effectively reduce
the gap between short- and
long-term forecasts.
-
Develop an institutional
arrangement to promote
continuous dialogue among local
climate forecast producers,
intermediary research
institutions, policy-makers and
various end-users.
-
Develop and promote formal
training and fellowships in
graduate schools, or immersion
experiences for trainees in
global climate forecast centers.
-
Undertake concerted efforts to
educate the public about the
nuances of climate issues and
climate forecasts.
-
Undertake systematic efforts to
develop common definitions and
vocabulary.
