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

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 IAGUniversity of Sao Paulo

Brazil

Currently serving the WWRP JSC, the CLIVAR WGSIP panel and the Southern Hemisphere THORPEX scientific committee

Exeter, 1-3 December 2010Workshop on “Sub-seasonal to Seasonal Prediction”

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

Exeter, 1-3 December 2010Workshop on “Sub-seasonal to Seasonal Prediction” 2

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: • 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

Exeter, 1-3 December 20103

Workshop on “Sub-seasonal to Seasonal Prediction”

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


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



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 single-model, 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.

A general problem with >15d forecasts and seasonal forecasts:• lack of power in the intraseasonal time scale

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

Power spectra of meridional wind at 40S , 60W – CPTEC – From seasonal forecasting model

S. Ferraz and P. Silva Dias – 2010 – prep.S. Ferraz and P. Silva Dias – 2010 – prep.

7

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 rainfallExeter, 1-3 December 2010Workshop on “Sub-seasonal to Seasonal

Prediction” 8

1 to 14 days

Seamless prediction

GlobalGlobal

Diurnal cycle

Diurnal cycle

Monsoon predictabilit

yLarger scale variability

Clouds and radiation

feedbacks on

Clouds and radiation

feedbacks on

VAMOS modeling

Initial state specificatio

n

Initial state specificatio

n

Model developmen

t

Parameterization quality

Parameterization qualityResolutio

n issuesResolution issues

Model products to meet users

needs

Model products to meet users

needs

VAMOS metrics for applications

VAMOS metrics for applications

Ultimate goalIMPROVE PREDICTION

Warm season precipitation

over the Americas

Model errors and model

biases

Model errors and model

biases

Americas

Americas

Seasonal to interannual

Impact of IC/BC (land,

SST, atmosphere)

on

Impact of IC/BC (land,

SST, atmosphere)

on

Ensemble forecastin

g

Ensemble forecastin

g

High impact weather forecast

Model verificatio

n

Model verificatio

n

…

Convection

Convection

9

(re-visited, originally presented at GIFS-TIGGE WG8 Meeting, Geneva, February 2010)

Exeter, 1-3 December 2010 10Workshop on “Sub-seasonal to Seasonal Prediction”

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

Area: 3.100.000 km2

Inhabitants: 201.656.965

Mega-cities: Sao Paulo-Buenos AiresOther large cities: Asunción-Sucre-Montevideo



Caffera and Berbery, 2005

Mean annual cycle (derived from CMAP 1979-2000)

a) Over the whole basin

b) Over the monsoonal region

c) Over the southern-central region

20S

30S



> 1800 mm

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 Intra seasonal to

seasonal time scales

signatureExeter, 1-3 December 2010

13Workshop on “Sub-seasonal to Seasonal

Prediction”

H

LH

+ T. anom

- T. anom

L

H

L- T. anom+ T.

anom

SOUTH AMERICAN SEE-SAW PATTERN

Higher frequency of extreme daily rainfall events at

the subtropics

(Liebmann, Kiladis, Saulo, Vera, and Carvalho, 2004)

(Gonzalez, Vera, Liebmann, Kiladis,

2008)

Higher frequency of heat waves and extreme

daily temperature events at the

subtropics

(Cerne , Vera, and Liebmann, 2007,

Cerne and Vera, 2010)

1st EOF leading pattern of 10-90-day filtered

OLR variability

Weakened SACZ

Intensified SALLJ poleward progression

Intensified SACZ

Inhibited SALLJ poleward progression

Intraseasonal variability in South America

14

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

Exeter, 1-3 December 2010 17Workshop on “Sub-seasonal to Seasonal Prediction”

There are 3 main sub-basins. 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). Exeter, 1-3 December 2010


Prediction”



Time scale ~ 24 days Time scale ~ 2.5 months

From LPB implementation plan, 2005 Exeter, 1-3 December 2010


Prediction”

Most extreme 1% PFs in each category for each 2-degree latitude-longitude box (after Zipser et al, BAMS, 2006)




M. Seluchi (CONGREMET X, 2009)



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)


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 ProjectLead: Luiz Agusto Toledo Machado

Experiments

New experiment at Foz de Iguazu From 9-11-2012 to 1-2-2013

Joint effort with LPB field activities2626

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


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

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.

?

11-12 days of useful forecast

Note that this is particularly difficult period to forecast!

7-8 days of usefull forecast

Complex case...

Large discrepancies

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

31

Brasil - INMET - Brasilia

INPE/CPTEC - C. Paulista

SIMEPAR - Curitiba

CLIMERH - Florianopolis

Uruguay - Dinamet

ArgentinaArgentina - - SMNSMN

Paraguay - Dinac

DHN - Niteroi

Virtual Center for monitoring and forecasting severe

weather for Southeastern South America

Courtesy of M. Seluchi, CPTEC, Brazil

Heavy rainfall prediction is a critical issueAlthough available, not enough use of ensemble products is currently done by forecast centersAdvantage of ensemble forecasting applied to severe weather has to be demonstratedPotential of longer range forecasts should be explored and tailored to fulfill users needsEfforts 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 forecastsIt 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 skillAir quality forecasts could be also incorporated, with a focus on aspects related with health

33

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?Exeter, 1-3 December 2010Workshop on “Sub-seasonal to Seasonal

Prediction” 34

Technical aspects Product development according to

regional needs Capacity building

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

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.)

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.)

37


Documents

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