South America Low Level Jet field EXperiment

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South America Low Level Jet field EXperiment

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U.S. CLIVAR Pan American Workshop Boulder,
September 2003
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Outline

• SALLJ Scientific Goals and Specific Objectives
• SALLJEX Components - Participant Countries
• Activities during SALLJEX
• Work in progress
• Follow up activities

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VAMOS/ MESASouth America Monsoon System 1st
tier SALLJ
To understand the role of the South American
low-level jet in moisture and energy exchange
between the tropics and extratropics and related
aspects of regional hydrology, climate and
climate variability
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VAMOS/SALLJ Program Specific objectives

• obtain an improved description of the temporal
  and spatial structure of the SALLJ based on
  expanded monitoring activities and special field
  experiments,
• evaluate the veracity of numerical representation
  (forecasts and analyses) of SALLJ against special
  observations and,
• determine improvements of initial state
  representation and model parameterizations
  required to improve prediction.

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Fill the Gap .
Operational Radiosonde coverage at 12 UTC
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Salljex Components

• Upper-air network enhancement
• Daily precipitation network enhancement
• NOAA/P-3 Missions
• Modeling
• NOAA/OGP Educational and outreach Program
• Teachers in the field

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VAMOS/SALLJEXperiment
Participant countries Argentina, Bolivia,
Brazil, Chile, USA, Paraguay, Perú Main
participant institutions (in alphabetic order)
AASANA - Bolivia, CIMA - Argentina, CPTEC - INPE
- Brasil, DINAC - DNM - Paraguay, NCAR - JOSS -
USA, NSF(ATM) - USA, NSF(IAI/GEO) - USA, NOAA
(PACS/OGP)- USA, NOAA(NSSL/ERL), SENAMHI - Perú,
Servicio Meteorológico Nacional - Argentina,
Universidad of Buenos Aires - Argentina,
University of Chile - Chile, University of São
Paulo - Brasil, University of Utah - USA SALLJEX
Project office G. Emanuel, J. Meitin
(UCAR/JOSS), C. Ereño (ICPO) Main funding
sources NOAA/OGP and NSF (USA), FAPESP (Brazil),
ANPCyT (Argentina)
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SALLJEX Timeline
2002
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15
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15
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15
October
November
December
2003
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15
1
15
1
15
March
February
January
Basic observing period (Upper-air obs)
Special Observing Period (Upper-air obs P-3
Missions)
Intensive Observing Periods (Upper-air obs)
SALLJEX raingauge observating system
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SALLJEX observational components Upper air

• 4504 Pilot balloon observations in 26 stations
• 279 extra Radiosondes over Argentina, 200 over
  Bolivia and Paraguay and 120 over Brazil

140 extra observers
Approximately between 4 and 6 observers at each
site
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Upper-air data coverage
From PACS/SONET web page
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SALLJEX observational components Raingauges

• 795 installed raingauges
• More than 1500 raingauges were made available

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Salljex Observational components NOAA P3

• Objectives
• Diurnal variations of the SALLJ
• Detailed description of the 3-dimensional
  structure of the SALLJ
• The relationship between MCCs and the SALLJ
• Description of the heat low over the Chaco and NW
  Argentina

• 99.1 flight hours to cover 13 missions

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SALLJEX components Modeling Groups from
Argentina, Brazil, Chile and US issued daily
weather forecasts

• NOGAPS model Analysis
• University of Utah Model Analysis
• ETA/CPTEC 40 km res., 00 and 12 UTC FC
• ETA/CPTEC 20 km res., 12 UTC FC
• ETA/UMD 80 km res., 00 UTC FC
• LAHM/CIMA 60 km res., 00 UTC FC
• NCEP/AVN 100 km res., 00 UTC FC
• RAMS/UBA 20 km res., 00 UTC FC
• RAMS/USP 25 km res., 00 and 12 UTC FC
• U of Chile MM5 30 km res., 12 UTC FC

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SALLJEX Legacy

• Data
• Research
• Predictability improvement

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SALLJEX DATA MANAGEMENT

• NOAA P-3 flight level data (preliminary/final)
• NOAA P-3 airborne radar data
• Processing Upper Air Sounding Data
• Upper-air data (raobs, pibals)
• Model run files
• Satellite files and imagery
• Precipitation data
• SALLJEX Data Management Link
• http//www.joss.ucar.edu/salljex/dm/
• The SALLJEX web site includes an on line field
  catalog, instructions for data submission, data
  policy and data management plan.

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Wind Profiles and quantity of observations at
some stations over SALLJEX area
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Case studies

• January 22-23 MCS

• MCS Flight and system environmental conditions
  (USA - Argentina)
• Cold surge after the strong LLJ (Brazil, Chile,
  Argentina)

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How does SALLJEX contribute to MESA modeling?

• VAMOS/MESA Modeling GoalTo improve seasonal to
  interannual climate and hydrological
  predictions.Strategy is to focus on1- Testing
  of hypothesis with models. 2- Detecting
  deficiencies in the models and improving
  performance.3- Developing new parameterizations
  and model components.

SALLJEX provides a unique opportunity to
calibrate and improve models
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A coordinated experiment to assess models
performance during SALLJEX
The 17-18 January 2003 MCS .... Not predicted by
models
13 UTC, January 18
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Exp 1 80 km Covering South America
Exp 2 20 km Covering SALLJEX area
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EXP 1
EXP 2
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Initializationdiscrepancies between SALLJEX
data and GDAS Analysis
Mariscal Estig.
Resistencia
JVG
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Forecast verificationDetecting deficiencies in
the models first step toward improvement
GDAS
Radiosonde data
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Evaluate the veracity of numerical representation
(forecasts and analyses) of SALLJ related paterns
against special observations
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(No Transcript)
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Data Assimilation Preliminary results

• Data from the SALLJEX were assimilated in the
  AGCM CPTEC/COLA , using the PSAS scheme, and
  results show large differences comparing with
  outputs using NCEP analysis without assimilation
  of these data.
• differences in moisture associated with the
  presence of the MCS, and occurence of
  precipitation.

Iracema Cavalcanti, Dirceu Herdies and José
Marengo CPTEC - Brazil
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Initial uncertainty a key issue to improve
forecasts
Uncertainty over the whole globe

• Impact of uncertainty in the initial condition
  over SALLJEX region it can explain much of the
  simulated uncertainty over the area up to 7 days

A. C. Saulo, L. A. Byerle, J. Paegle, and J. N.
Paegle
Uncertainty only over SALLJEX area
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What follows up

• SALLJEX Data Workshop to be held in Buenos Aires,
  Argentina 10-12 December 2003
• Assess progress in meeting SALLJEX objectives
• Strengthen collaborations between SALLJEX
  participants, and
• Broaden participation to expand usage of SALLJEX
  data in modeling and empirical studies