Transcript Celeste Saulo CIMA and Dept. of Atmos. and Ocean Sciences University of Buenos Aires Argentina With many thanks to and Pedro Leite Silva Dias,

Celeste Saulo
CIMA and Dept. of Atmos. and Ocean Sciences
University of Buenos Aires
Argentina
With many thanks to and Pedro Leite Silva Dias, LNCC and IAG
University of Sao Paulo
Brazil
Currently serving the WWRP JSC, the CLIVAR WGSIP panel and
the Southern Hemisphere THORPEX scientific committee
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
 Meeting
the objectives of this Workshop
 THORPEX (WWRP)-VAMOS (WCRP)
 La Plata Basin
 Some scientific grounds supporting
potential predictability ahead of 2 weeks
over LPB
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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


It is necessary to develop a seamless approach to weather
and seasonal prediction.
It is also necessary to promote a seamless approach to the
application of sub-seasonal to seasonal predictions through
physical and social science researchers, service providers
and users
Need to leverage the work of existing programs and such a
collaborative initiative should be focused on:
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Coupled global modeling and data assimilation
MJO and organized tropical convection
Polar processes
Surface-atmosphere interactions
Stratosphere-troposphere interactions
Ensemble prediction systems (EPS)
Data bases for research
Forecasting system design
Societal and economic benefits from improved sub-seasonal to
seasonal prediction
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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 THORPEX
/ GIFS (Global Interactive
Forecast System):
• The objective of the GIFS is the production of
internationally coordinated, ensemble-based
probabilistic advance warnings and forecasts for
high impact weather events to mitigate loss of
life and property
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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 To
facilitate the GIFS development phase,
it is proposed to establish a GIFS Forecast
Demonstration Project (GIFS-FDP), to
develop products to meet the needs and
requirements of the operational weather
forecast community and evaluate the
benefit of those products in an
operational context
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Compared with the products available currently in
the existing SWFDP programme, GIFS-FDP will
introduce the following enhancements:
 Scientifically driven development of new types of
products to highlight forecasts of severe weather;
 Products based on multi-model, rather than singlemodel, ensembles;
 Statistically bias corrected and downscaled
information as opposed to direct output from
numerical ensemble forecasts
 Longer range outlooks including week-2 forecasts
(as opposed to current guidance limited to 3-5
days range) for long term planning and mitigation
efforts related to possible future high-impact
weather events.

Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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A general problem with >15d forecasts and
seasonal forecasts:
• lack of power in the intraseasonal time
scale
Power spectra of meridional wind at 40S , 60W
– CPTEC – From seasonal forecasting model
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S. Ferraz and P. Silva Dias – 2010 – prep.
To understand the sources of summertime precipitation
variability over the Americas (in order to improve its
prediction), by means of addressing
The influence of ENSO on monsoon rainfall;
Relative roles of SSTs (both tropical and extratropical
SSTs) and soil moisture on monsoon rainfall;
 Why the rainfall patterns favor the dipole structure
(e.g. the dipole between rainfall over the Great Plains
and the Southwest ; and the SACZ and subtropical
plains in South America)?
 Climate and weather link: Intraseasonal variability
 The limit of predictability
 Diurnal cycle associated and mesoscale variability
with monsoon rainfall


Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Global
Americas
Seasonal to
interannual
Impact of IC/BC
(land, SST,
atmosphere) on
…
Larger scale
variability
Seamless prediction
Monsoon
predictability
VAMOS
modeling
VAMOS
metrics for
applications
Warm season
precipitation over
the Americas
Initial state
specification
Parameterization
quality
Resolution
issues
Convection
Clouds and
radiation feedbacks
on
1 to 14 days
Diurnal
cycle
Model errors
and model
biases
Model
development
Ultimate goal
IMPROVE PREDICTION
Ensemble
forecasting
Model
verification
Model products
to meet users
needs
High impact
weather forecast
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(re-visited, originally presented at GIFS-TIGGE WG8 Meeting,
Geneva, February 2010)
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Area:
3.100.000 km2
Inhabitants:
201.656.965
La Plata Basin, is formed by
the discharge of waters
from five countries:
Argentina, Brazil, Uruguay,
Bolivia and Paraguay. Its
population surpasses 200
millions.
It accounts for the
generation of most of the
electricity, the food and the
exports of these countries
Mega-cities:
Sao Paulo-Buenos Aires
Other large cities: Asunción-Sucre-Montevideo
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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20S
> 1800 mm
30S
Mean annual cycle (derived from CMAP
1979-2000)
a) Over the whole basin
b) Over the monsoonal region
c) Over the southern-central region
Caffera and Berbery, 2005
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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 Heavy
and/or persistent rains (frequently
leading to floods and slides)
• SACZ (summer) – blocking events (winter) – MCS
(spring and summer) – cyclogenesis (autumn and
spring)
 Severe
storms (tornado, wind gusts, hail,
intense precipitation, lighting, etc)
 Droughts
 Warm/cold spells
 Late Frosts
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Intraseasonal variability in South America
1st EOF leading pattern of
10-90-day filtered OLR
variability
Weakened SACZ
Intensified SACZ
Intensified SALLJ
poleward progression
Inhibited SALLJ
poleward progression
L
- T.
H
H
SOUTH AMERICAN SEE-SAW
PATTERN
L
- T.
+ T.
ano
m
anom
Higher frequency of
extreme daily rainfall
events at the
subtropics
(Liebmann, Kiladis, Saulo,
Vera, and Carvalho, 2004)
(Gonzalez, Vera, Liebmann,
Kiladis, 2008)
H
L
anom
+ T.
ano
m
Higher frequency of
heat waves and
extreme daily
temperature events
at the subtropics
(Cerne , Vera, and
Liebmann, 2007, Cerne
and Vera, 2010)
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 intraseasonal
oscillations (MJO, SASS)
SASS index based on
filtered OLR anomalies
(1st EOF component).
After Gonzalez et al 2008

Soil moisture memory time scale (days) for GSWP-2
(1986-1995) 1°resolution. Dirmeyer et al 2009
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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
There are 3 main subbasins. The potential
for flooding occurs at
any time of the year
The largest
contribution during
flood episodes comes
from the Paraná River.
Both the Paraná and
the Uruguay rivers can
at least triple the mean
river discharge during
flood events (Berbery
and Barros 2002).
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Time scale ~ 24 days
Time scale ~ 2.5 months
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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From LPB implementation plan, 2005
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Most extreme 1% PFs in each
category for each 2-degree
latitude-longitude box (after
Zipser et al, BAMS, 2006)
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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M. Seluchi (CONGREMET X, 2009)
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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 La
Plata Basin Regional Hydroclimate
project (WCRP,
http://www.eol.ucar.edu/projects/lpb/)
 Claris – LPB (supported by the EC,
http://www.claris-eu.org/)
 CHUVA = Cloud processes of tHe main
precipitation systems in Brazil: A
contribUtion to cloud resolVing modeling
and to the GPM (GlobAl Precipitation
Measurement) (Supported by Brazil
national agency)
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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 What
climatological and hydrological factors
determine the frequency of occurrence and
spatial extent of floods and droughts?
 How predictable is the regional weather and
climate variability and its impact on
hydrological, agricultural and social systems of
the basin?
 What are the impacts of global climate change
and land use change on regional weather,
climate, hydrology and agriculture? Can their
impacts be pre-dicted, at least in part?
CHUVA Project
Lead: Luiz Agusto Toledo Machado
Experiments
New experiment at Foz de Iguazu
From 9-11-2012 to 1-2-2013
Joint effort with LPB field activities
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 Considerable
model and operational
capacity in Brazil (CPTEC and
Universities) and Argentina (NWS, CIMA
and Universities)
 Virtual Center for monitoring and
forecasting severe weather for
Southeastern South America
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Progress with Multi-Model Ensemble (NWP)
Global Models: CPTEC, NCEP, UKMET
Regional Models - increasing number of participants
•CPTEC regional model (ETA)
•Brazilian Navy (DWD model)
•Smaller domain – limited to S/SE
•Univ. of São Paulo – BRAMS
•Federal University of Rio de Janeiro - WRF
•National Laboratory for Computational Sciences – ETA,BRAMS
•Univ. of Buenos Aires - WRF and BRAMS
•Federal University of Santa Maria - BRAMS
•3 regional offices - WRF
This is work has been supporting regional activities on the
THORPEX/TIGGE - WMO.
?
Complex case...
11-12 days of useful forecast
Note that this is particularly
difficult period to forecast!
Large
discrepancies
7-8 days of usefull forecast
http://wrf.cima.fcen.uba.ar

CGCM – seasonal climate
• 7 months forecast
• 10 members ensembles, Coupled model initialization:
 Atmos: NCEP análises for 10 consecutive days
 Ocean: forced OGCM run with prescribed atmos fluxes
• Resolution:
 Atmos: T062L28
 Ocean: ¼ x ¼ lat-lon, 10S-10N, over the Atlantic
 O-A Coupling latitute belt: 40S – 40N
• Prognostic fields: Precipitation, SST (global, Niño Index).

CGCM – extended weather
• 30 days forecast
• 2 members per day (00 and 12 UTC)
• Resolution
 Atmos: T126L28
 Ocean: ¼ x ¼ lat-lon, 10S-10N, Atlantic sector, 2 deg. extratropics
 O-A Coupling latitute belt: 65S – 65N
• Prognostic fields: SLP, Geopot. Height, Temperature, Precip., SST
Thanks to Paulo Nobre, Marta Malagutti, Emanuel Giarolla, Domingos Urbano, Roberto de Almeida
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Virtual Center for monitoring
and forecasting severe
weather for Southeastern
South America
Brasil - INMET - Brasilia
INPE/CPTEC - C. Paulista
DHN - Niteroi
SIMEPAR - Curitiba
CLIMERH - Florianopolis
Paraguay - Dinac
Uruguay - Dinamet
Argentina - SMN
Courtesy of M. Seluchi,
CPTEC, Brazil
Heavy
rainfall prediction is a critical issue
Although available, not enough use of ensemble products is
currently done by forecast centers
Advantage of ensemble forecasting applied to severe weather has
to be demonstrated
Potential of longer range forecasts should be explored and
tailored to fulfill users needs
Efforts could be made to also link to hydrological prediction
(given the high potential for flood occurrence over the area), which
is currently experimental but based on deterministic forecasts
It would be of great interest to assess the impact of additional
observations on forecast quality (particularly for MCS’s and
explosive cyclogenesis). We could probably combine an FDP with a
field experiment, with main focus on the impact of targeted
observations on precipitation forecast skill
Air quality forecasts could be also incorporated, with a focus on
aspects related with health
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 Foster
linkages between WCRP and WWRP
in the “seamless approach” context
 Relevance of “La Plata Basin” in terms of
research topics, heavy precipitation events
occurrence –many related with underlying
lower frequency variability-, operational
challenges (and weaknesses), economical
and societal impacts, history of
collaborative work –including research,
operations and capacity building-,
involvement of developing countries
 How to proceed?
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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 Technical
aspects
 Product development according to
regional needs
 Capacity building
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There is a basic mismatch since TIGGE is “real time” and has
limited data sets. It may be possible to extend some TIGGE
forecasts from 15 to 90 days to look at the “first” season (CPTEC
may extend from 30 d to 90 d with new computer ).
The CHFP organizes runs only 4 times /y with ~10 member
ensembles – the TIGGE data could fit in the early part of the case
studies. Thus the research project should focus on the first season
and move to running once month. Initially it may be worth looking
at the past 3 years from the start of the TIGGE archive out to 15
days and the CHFP archive for longer timescales.
Organizationally a sub‐group of WGSIP should work with a TIGGE
sub‐group on this topic.
Technical liaison would be essential – a technical person from
CHFP should liaise with a TIGGEGIFS expert (possibly from
NCAR).
GIFS-TIGGE WG8, Geneva, February 2010
Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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Conclusions (WGIP 13TH SESSION – Buenos
Aires, Argentina, 29-31 July 2010
•Need closer collaboration with TIGGE, primarily with centers
doing > 15 day forecasts;
•Experience in handling data sets : TIGGE of the order of
Pb/yr
• Investigate how much ocean <=>atmosphere coupling impact
skill
•Role of resolution on skill;
•Scale interactions;
•Ensemble techniques: use of patterns (PNA,EU,… MJO..,
monsoon indices etc.)
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Workshop on “Sub-seasonal to Seasonal Prediction”
Exeter, 1-3 December 2010
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