4th GPM International Workshop 1517, June 2004 Greenbelt, Maryland, U.S.A

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4th GPM International Workshop15-17, June
2004Greenbelt, Maryland, U.S.A

• GPM Research Actions in Brazil
• Presentation Roberto Vicente Calheiros,
  IPMet/UNESP
• Contributions Augusto J. Pereira Filho 1
• Carlos A. Morales 2
• Edson Eiji Sano 3
• Juan Ceballos 4
• Luiz Augusto Machado 5
• Roberto V. Calheiros 6
• 1,2 Institute of Astronomy, Geophysics and
  Atmospheric Sciences IAG/USP
• 3 Brazilian Agriculture Research Organization
  EMBRAPA
• 4,5 Environmental Satellite Division
  DSA/CPTEC/INPE
• 6 Meteorological Research Institute
  IPMet/UNESP

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BRAZILIAN SPACE AGENCY (AEB)BRAZILIAN NUCLEUS OF
THE INTERNATIONAL PROGRAM FOR PRECIPITATION
MEASUREMENT(GPM-BRAZIL)

• A decision was reached to stablish the Brazilian
  participation in the GPM, AEB acting as the
  national coordinator and link institution
• GPM-Brazil nucleus coordinates activities from
  Brazilian institutions and estimulates the use of
  available data
• Lines of action
• a) validation of modeling
• b) data availability
• c) research
• d) development of sensors
• e) release
• Instruments of action specific projects, under
  the responsibility of one or more national
  institutions
• Structure
• a) Coordination Comittee (CCO)
• b) Management
• c) Participating institutions
• d) Assessors
• e) Users

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Gauge, Radar and Satellite Rainfall(IAG/USP)
(ONE)
Map of Eastern São Paulo State, Brazil. The SPWR
is at 23o 36' 00'' South and 45o 58' 20" West.
Inner and outer radii are 120 km and 240 km,
respectively. The DAEE rain gauge network is also
shown. Data sets are compared within the 300 km2
area.  
Scatter diagram of gauge spatial mean rainfall
against radar and satellite ones (left) as well
as satellite against radar (right). It is
indicated the respective variance coefficients.
(From Pereira Filho et al, 2003)
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Gauge, Radar and Satellite Rainfall(IAG/USP)
(two)
Maps of satellite (left) and radar (right) total
rainfall accumulation for the entire data set
(Table 1). Color scale indicates total rainfall
(mm). Numbers in the radar map (right) identifies
areas where the total rainfall was underestimated
by ground clutter suppression (1, 2 and 3) and
contamination (4), range effect (e.g., 5) and
signal processing (e.g., 7).
(From Augusto J. Pereira Filho, Andrew J. Negri,
and P.T. Nakayama An Intercomparison of Gauge,
Radar and Satellite Rainfall in the Tropics,
IPWG/CGMS, 1st Workshop, Madrid, Spain, 23-27
September, 2003, 8pp)
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IWVC FROM HIGH MICROWAVE CHANNELS
(HSB)(DAS/CPTEC) (ONE)
Estimated IVW(Kg/m2))
150 GHz Channel
183/- 1GHz Channel
Comparison of total IVW as estimated from HSB
channels and radiosonde measurements
(From Wagner Flauber Araújo Lima and Luiz A. T.
Machado Analysis of the HSB sensor in
estimating the ILWC of WV a study applied to the
RACCI/LBA, submitted, XIII Congremet, Fortaleza,
CE, Brazil, August 2004, in Portuguese)
183/-3GHz Channel
183/-7GHz Channel
Brightness temperature (K) as a function of IWLC
in a CB cloud for a) 150 GHz, b) 183 /- 1 GHz,
c) 183 /-3 GHz and d) 183 /-7GHz. Curves refer
to rainfall rates of 0, 5 and 10 Kg/m2
respectively
(From W.F. Araújo Lima, L.A T.Machado and C. A.
Morales Analysis of the HSB Channels potential
to estimate precipitation, submited, XIII
Congremet, Fortaleza, CE, Brazil, August 2004, in
Portuguese)
Radiosonde IVW (Kg/m2)
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MULTI-SENSOR VALIDATION (DSA/CPTEC) (TWO)

• Validation Based on Radar-Satellite DCP (Data
  Collection Platform) Measurements

From (L. A. T. Machado, personal communication)
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RAINFALL FROM HIGH MICROWAVE CHANNELS (HSB)
(DAS/CPTEC) (THREE)

• Modeling Radiative Transfer
• Microwave Hydrometeors Interactions

150 GHz Channel
150 GHz
184-1 GHz
183 - 3 GHz
Rainfall rate (mm/h)
From (L. A. T. Machado, personal communication)
183 - 7 GHz
CAPPI 3 km
CAPPI 7 km
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MICROWAVE IMAGER PLATFORM(DAS/CPTEC) (FOUR)

• Technological Development (in house) Satellite
  in Tropical Orbit
• Passive Microwavve Sensor. Second GPM Phase
  (around 2010).

GMI GPM Microwave Imager
From (L. A. T. Machado, personal communication)
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Gabor FilteringIPMet/UNESP (ONE)
The filtered images in the frequency domain, (
real part)
CAPPI de 3,5 km (Bauru), do dia 11JAN03,
aproximadamente às 0130H local
Proceed to classification through a NNW varying
the parameter set
(From R.V. Calheiros, R.Machado, C..A.Thompson,
Zildene P. Emidio, submited to the XIII
Congremet, Fortaleza, CE, Brazil, August 2004 in
Portuguese)
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Brightness temperature Reflectivity (Z-R)
relationshipsIPMet/UNESP (TWO)Tb x Z
Tb-Z relationship curves solid/red-16
Sept-night, dashed/blue-01 Oct-day,
dash/dot/blue-21 Oct-day, solid/green-30
Oct-night , dash/red-07 Sept-night, solid/blue-12
Oct-day, all from 2002.
(From R.V.Calheiros, R. Machado and M.A. Lima
Cell Detection at Far Ranges Supporting Tb-Z
relationships, Sixth International Symposium on
Hydrological Applications of Weather Radar,
Melbourne, Australia, 2-4 February 2004)
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PRELIMINARY DATA ANALYSESValidation of
Satellite Observations (Falcon DIAL) 04/03/04
(THREE)

• Explanation of Next Slide
• Impact of smoothing imposed by the sensors
  Field Of View (FOV) - a,b,c
• Vertical cut through horizontal pixel 289 - Fig.
  d (orig.) and Fig. e (filtered)
• Horizontal profile at 12,7km height Figs f, g,
  h, without filtering, for a
• 13km FOV and 50km FOV, respectively

(Courtesy DLR)
From TroCCiBras PROGRESS REPORT January to May
2004

• Gerhard Held and Roberto Vicente Calheiros,
  general and scientific coordinators - TroCCiBras,
  TROCCINOX e HIBISCUS Teams

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Validation of Satellite Observations TroCCiBras
04/03/04 (FOUR)
(R.Calheiros R. Machado)
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(FIVE)
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USE OF AIRS OBSERVATIONS TO SIMULATE
HSB(DSA/CPTEC)

• (From Rodrigo Augusto Ferreira deSouza,
  Simulations of Brigthness Temperature for the
  HSB Channels from AIRS Information and
  Performance Analysis of Aqua Soundings over
  Brazil, PhD Thesis /INPE, 2003,adviser Juan
  Ceballos/DAS).
• Partial compensation for HSB loss was sought use
  made of AIRS data from cloud-free pixels
• AIRS WV channels were correlated with the 4 HSB
  channels over oceans for September (actual HSB
  data) highest correlated AIRS channels were
  selected for analysis.
• Similarity with HSB Jacobian criterion was
  applied to evaluate AIRS simulation ability a
  linear combination of a reduced number of AIRS
  channels was found to closely assess brightness
  temperatures in tropical continental environment
  with a m.s.e, within about 1 K
• Atmospheric profiles for clear sky pixels with
  HSB-simulated and AMSU-A channnels input were
  retrieved over Rondonia (September-October 2002,
  Dry-to-Wet LBA Campaign) the profiles follow, in
  general, the radiosonde profiles and were within
  sensor specifications, i.e., 1.5 K for
  temperature and 1,5g/Kg for humidity, a
  behaviour not attained in the region by the NASA
  retrieval procedures (versions b-30 and c-01)

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BRAZILIAN GEOESTATIONARY SATELLITE (SGB)
(ONE)(2009)
Implementation of the Communications Navigation
Surveillance (CSN)/Air Traffic Management (ATM)
Concept
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BRAZILIAN GEOESTATIONARY SATELLITE (SGB) (TWO)
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GPM APPLICATION IN AGRICULTURE (one)
The Embrapas Interest in GPM Data
1. Crop yield prediction
Embrapa (Brazilian Agriculture Research
Organization) is interested in the precip data
from GPM to improve its annual crop yield
prediction. The accuracy of crop yield prediction
depends strongly on the availability of
spatially-based rainfall data. The countrys
raingage distribution is poor in some
regions, including most of the Cerrados biome,
the most important region in Brazil for grain
production. We expect that GPM can provide
accurate precipitation data in order to improve
our water balance models.
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GPM APPLICATION IN AGRICULTURE (two)
SourceEMBRAPA