Satélites Meteorológicos e a -...
Transcript of Satélites Meteorológicos e a -...
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A Radiação que Define o Clima da Terra
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Transferência Radiativa absorção gasosa
O 2 e O 3
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Espectro de Absorção da Atmosfera
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Rayleigh
Mie
àtica Geom‚trica
K l
a =2 p r/ l
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Refletividade em 3.9 microns - gua e gelo
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IR3.9 mostra muito mais estruturas no topo que o IR10.8
(sens¡vel ao tamanho da particula de gelo)
3 1 3 1 1 1
1 1 3 3 1 1
3 3 2 2
1= nuvem de gelo com cristais muito pequenas
2= nuvens de gelo com pequenos cristais
3= nuvens de gelo com grandes cristais
Canal 04 (IR3.9) Canal 09 (IR10.8)
MSG-1, 20 Maio 2003, 13:30 UTC
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Identificação bidimensional
• bastante comum utilizar um crit‚rio de apenas duas vari veis. Os pixels se distribuem num "diagrama de orelha".
Estabelecendo patamares razo veis de R1, T4, podem ser identificados os elementos principais:
Superf¡cie Cumulos Estratos Cirros Cumulonimbos
Todavia, nÆo h informa‡Æo de textura (uma outra dimensÆo)
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Gelo / água das Nuvens
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Sensitivity to the Cloud Properties
Sensitivity to the ice content Sensitivity to the particle size
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Atividade Elétrica
Variation of average and standard deviation of CG lightning occurrence in 15 minute intervals by pixel (# CG lightning/pixel*15min) as a function of (a) Ice Particle
Effective Diameter (mm), (b) Ice Water Path (kg/m3) and of the (c) polarized Temperature Difference at 85 GHz (TBV-TBH).
Mattos and Machado, 2010 Submitted to Atmos. Res.
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Ratio 1.55/1.65um
ice Cloud Scanner Measurements
Mount Gibbes Experiment
July/2007
Vanderlei Martins water
ice
water
UMBC and NASA/GSFC UMBC and NASA/GSFC
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Channel 9 MSG (10.8 m m) Penetrative Clouds
Warmer Region = 200 K
U/V Shape Coldest Pixel = 189 K
03/08/2006
14:30UTC
Warmer Region = 200 K
Coldest pixel = 189 K
Very small ice clouds - new convection - updrafts Ring Shape
03/08/2006
17:00UTC
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WV – IR Channel Difference
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T = Tb3- Tb4
T ≥ - 2.0, >~10% Probability to have Lightning
Classify as Penetrative Clouds
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Transferência RadiativaETR
Ausência de Espalhamento (Equação de Schwarzchild)
Boa aproximação para propagação de radiação terrestre na atmosfera, na ausência de nuvens
Duas possíveis variações elementares para radiância espectral:
(1) atenuação de Ll incidente no volume de matéria:
(3) emissão à temperatura do volume de matéria:
'ds)'s,(),'s,(L),'s,(dL a
)1( lal=l ll
pp
ppTBsssTBL
s
a
sat
=
),(
))(,()',()',())'(,(),('
ltlltlall lll
Função de Planck: distribuição de valores de radiâncias espectrais emitidas por um corpo negro, em função de T e l (ou n)
emissividade elementar(Lei de Kirchoff)
l
=ll
1e
hc2T,B
kThc
5
2
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E l ?sT 4 T 200 hPa
E l
absor
‡Æo
l
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E l ?sT 4 T 500 hPa
E l
absor
‡Æo
l
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E l ?sT 4 T 950 hPa
E l
absor
‡Æo
l
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TYPICAL WEIGHTING FUNCTIONS FOR A MICROWAVE TEMPERATURE SOUNDER
(AMSU-A instrument)
h (km) Approximate center frequencies:
(Including stratospheric channels) AMSU-A (3-14)
Channel 1: 23.8 GHz (total Wv)
Channel 2: 31.5 GHz (window) 50 Channel 3: 50.3 GHz
Channel 4: 52.8 GHz
Channel 5: 53.6 GHz
Channel 6: 54.4 GHz
Channel 7: 54.9 GHz 14 40 Channel 8: 55.5 GHz (Tropopause)
Channels 9 to 14: 56.9 to 57.7 GHz 13 Channels 16 to 21: 60.3 to 61.3 GHz
(alternatively 58.2 to 59.3 GHz)
Channel 15: 90 GHz (liquid water) 12
30
h (km)
11 AMSU-A (16-21)
10 20 80
9 21
8 20 60 7 10 19
6 18 17
4 16 5 40
3 0
0 0.5 1.0 0 0.5 1.0
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1990
10.6 to 10.7 GHz band
2000 From G. Rochard.
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Tipos de Órbitas
Polar
Equatorial
Geoestacionário
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Composite Image from GOES West, GOES East,
Meteosat-5, -7, GMS
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Órbita Polar
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Varredura ao Longo da
Trajetória do Satélite
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Varredura Cônica Varredura Cross Tracking
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Molniya Orbit
Four satellites would extend the coverage to the
two Poles, 24 hours a day.
From Joint Center for Satellite Data Assimilation
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Órbitas
36 graus 26 graus
Vermelho - 500 km
Verde - 650 km
Azul 800 km
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Geoestacionário - Varredura por
Rotação
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INTRODUÇÃO A IMAGEM DIGITAL
A imagem digital: Matriz de pontos (pixels)
colunas
Cor: RGB (107,78,26) Cada pixel possui:
- localização: linha e coluna 2 0 2 7
- resolução radiométrica: níveis de cinza (cor)
- resolução espacial: 800 x 600, 1024 x 768 Computador: m quina bin ria
Cada bit pode conter dois valores: 0 ou 1 101 10 00 1 imagem 8 bits => 2 8 = 256 valores
imagem 10 bits => 2 10 = 1024 valores 10110001 2 = 177 10
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A Resolução Radiométrica
A resolu‡Æo radiom‚trica ‚ dada pelo n£mero de valores digitais representando
n¡veis de cinza, usados para expressar os dados coletados pelo sensor.
Quanto maior o n£mero de valores, maior ‚ a resolu‡Æo radiom‚trica.
5 bit 1 bit (32 níveis de cinza) (2 n¡veis de cinza)
O número de níveis de cinza ‚ comumente expresso em função do número de dígitos
bin rios (bits) necess rios para armazenar, em forma digital, o valor do n¡vel m ximo.
O valor em bits ‚ sempre uma potˆncia de 2. Assim, 5 bits significam (2) 5 = 32 n¡veis de cinza.
Os sat‚lites LANDSAT e SPOT tˆm resolu‡Æo radiom‚trica de 8 bits, o que significa o registro de imagens
em 256 n¡veis de cinza.
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Nova Geração de Satélites
METOP ( substitui o NOAA nas órbitas PM) - 2006 -
hyperspectral
NPP ( satélite intermediário entre NOAA e NPOESS - ira
substituir parcialmente EOS) - lan‡amento 2011
MSG - 2003 e MTG 2018
NPOESS - 2014 ( nova serie de POE que ira substituir os
NOAA/METOP)
GOES-R - Nova geração formato e ingestão diferente
GPM - 2014
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NOAA N - N' NOAA K L M METOP
Taxa de HRPT-Taxa de Dados 665.4 Kbps 665.4 Kbps 3.5 Mbps Dados dos
Ano de Lan‡amento 1998 2000 2002 2005 2007 2006 2010 2015 Instrumentos
Radi“metro Imageador 622 kb/s AVHRR/3 AVHRR/3 AVHRR/3
2,9 kb/s HIRS/3 HIRS/4 HIRS/4 Sondadores
3,2 kb/s AMSU-A AMSU-A AMSU-A (Advanced Microwave
Sounding Unit) 3,9 kb/s AMSU-B MHS MHS (Microw. Humid. Sound.)
1500 kb/s IASI IR Atmosph. Sound. Interfer.
Outros Instrumentos:
60 kb/s ASCAT Advanced SCATterometer
60 kb/s GRAS GNSS Atmosph. Sounder
400 kb/s GOME Global Ozone Monitoring
Experiment
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Características dos Canais do Instrumento AVHRR/3
N£mero Resolução Comprimento
do Uso T¡pico no Nadir de onda (um)
Canal
Mapeamento da superf¡cie e das
1 1,09 km 0.58 - 0.68 nuvens, durante o dia; ¡ndice de
vegetação.
Mapeamento das fronteiras terra- gua; 2 1,09 km 0.725 - 1.00
¡ndice de vegetação
3A 1,09 km 1.58 - 1.64 Detecção de neve e gelo
Mapeamento noturno de nuvens,
monitoramento da temperatura da 3B 1,09 km 3.55 - 3.93
superfície do mar, detecção de
queimadas
Mapeamento noturno de nuvens,
4 1,09 km 10.30 - 11.30 monitoramento da temperatura da
superf¡cie do mar.
Mapeamento noturno de nuvens,
5 1,09 km 11.50 - 12.50 monitoramento da temperatura da
superf¡cie do mar.
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NPP• Visible/Infrared Imager Radiometer Suite)
Raytheon Santa Barbara– 0.4 km imaging and 0.8 km radiometer resolution– 22 spectral bands covering 0.4 to 12.5 mm– Automatic dual VNIR and triple DNB gains– Spectrally and radiometrically calibrated– EDR-dependent swath widths of 1700, 2000, and 3000 km
• Crosstrack InfraRed Sounder (CrIS) ITT Ft Wayne
– 158 SWIR (3.92 to 4.64 mm) channels– 432 MWIR (5.71 to 8.26 mm) channels– 711 LWIR (9.14 to 15.38 mm) channels– 3x3 detector array with 15 km ground center-to-center– 2200 km swath width
• Advanced Technology Microwave Sounder (ATMS) - NASA
Northrop Grumman Electronics– CrIS companion cross track scan– Profiling at 23, 50 to 57, 183 GHz– Surface measurements at 31.4, 88, 165 GHz– 1.1, 3.3, and 5.2 deg (SDRs resampled)– 2300 km swath width
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Ozone Mapping and Profiler Suite (OMPS)
Ball AerospaceTotal ozone column 300 to 380 nm with 1.0 nm resolutionNadir ozone profile 250 to 310 nm with 1.0 nm resolutionLimb ozone profile 290 to 1000 nm with 2.4 to 54 nm resolutionSwath width of 2800 km for total column
NPP - (continuação)
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Produtos NPOESSRegistros de Dados Ambientais
VIIRS – Conjunto Imageador/Radiômetro Visível/Infra-
vermelho
Propriedades Ambientais Mostradas em Pontos Locais VIIRS
Alturas do Topo de Nuvens
Camadas de Nuvens
Total de Água Precipitável
Temperatura da Superfície
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GOES-12 - Imagem a cada 15 minutos
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GOES-R
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Meteosat Third Generation + Jason
+ METOP
Missions are under discussion: ? High Resolution Fast Imagery (HRFI) mission: successor to MSG SEVIRI HRV
mission ? Full Disk High Spectral Resolution Imagery (FDHSI) mission: successor to
mission of other SEVIRI channels ? IR Sounding Mission ? Ozone UV sounding mission ? Data Collection Platform mission ? Lightning imagery mission
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TRMM - Tropical Rainfall Measuring Mission
O primeiro radar meteorológico embarcado em uma plataforma orbital transmite 64 pulsos de 1.6 m s
O radar amostra cada pulso transmitido em altitudes separadas por 250 m a partir da superf¡cie at‚ a
altura de 20 km, tirando a m‚dia da refletividade dos ecos espalhados pelas gotas de chuva. Essa faixa
de altitude produz 80 valores verticais que juntamente com 49 valores horizontais produzem o perfil
vertical tridimensional da chuva, a uma resoluçao espacial de 4 km.
Geometria de imageamento dos sensores a bordo do sat‚lite TRMM (FONTE: NASA/NASDA)
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GPM Unify and advance global precipitation measurements from a
constellation of dedicated and operational satellites for
research and applications
GPM CORE (65 o ) GPM LIO (40 o ) Ku-Ka band radar (Low-Inclination Observatory)
10-183 GHz radiometer
Precipitation physics Asynoptic observatory observations
Reference standard Improved sampling for for intercalibration of near-realtime monitoring
constellation of hurricanes and precipitation midlatitude storms
measurements
Next-generation global precipitation products through
advanced active & passive microwave sensor measurements
a consistent framework for inter-satellite calibration (radiance & rain rates)
international collaboration in algorithm development and ground validation
Cornerstone for the CEOS Precipitation Constellation under GOESS & GEO
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GPM Core Observatory Sensors
JAXA Dual-Frequency (Ku-Ka band) Precipitation Radar (DPR):
Increased sensitivity for light rain and
snow detection
Better measurement accuracy
Detailed microphysical information for
improving radiometer rain retrievals
NASA Wide-Band (10-183 GHz) Microwave Imager (GMI):
High spatial resolution
Improved light rain & snow detection
Improved signals of solid precipitation
over land (especially over snow-covered surfaces)
Accuracy & stable calibration to serve
as a radiometeric reference for constellation radiometers
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IV Curso de Sat‚lites Meteorol¢gicos - 28 de junho a 07 de julho de 2006
The Challenge: Global Earth Observation, a System of Systems
Aqua
GRACE CALIPSO Cloudsat
TRMM GIFTS
SSMIS
TOPEX Landsat NPP
MSG GOES-R
Meteor/
SAGE
NOAA/ COSMIC/GPS
POES
SeaWiFS NPOESS
Terra Jason SORCE Aura ICESat
WindSat
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Intervalo !!!
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Ferramentas para Previsão
Imediata Utilizando Radar e
Satélites
Luiz Augusto Toledo Machado
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Exemplo de desenvolvimento da brisa marítima
lago
Rio
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Exemplo de imagem GOES ao amanhecer mostrando
convecção organizada durante a noite pela Brisa terrestre..
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Exemplo do desenvolvimento de convecção devido a brisa vale
Montanha
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Em condições de vento fracos, áreas de cobertura de nuvens pela manha
pode influenciar o desenvolvimento da convecção no período da tarde,
devido um aquecimento diferencial.
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Cisalhamento Associado com
a Convecção Profunda
Nuvens Altas
Nuvens Baixas
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Niamey - 2006 - AMMA Experiment
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0 1 2 3 4 5 6
Forecast Length, hours
.2
.4
.6
.8
1.0
Accuracy of Rainfall Nowcasts>1 mm/h
GRID MESH 20 km - Jun-Oct 2002
Courtesy of Shingo Yamada - JMA
NWP
Cri
tica
l Su
cce
ss In
dex
(C
SI)
Cross over region
Predictability
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Parâmetros Termodinâmicos
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= T.1000
P
0.286
V = TV .1000
P
0.286
e = T.1000
P
0.286(10.28Q)
.EXP Q(1 0,81.Q).
3376
TCOND 2.54
QLgzTch vp =
CAPE =1
g
TVp TVe
TVe
dz
FLC
NBL
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7000
6000
ABLE-2B 5000 CAPE
(J/ KG ) AF 4000 BE
BO 3000 VH
TB
MA 2000
1000
0
330 340 350 360 370
EQUIVALENT PO TENTI AL TEMPERATURE (K)
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Rain Cells and the Richardson Space
2600
2400 2
R = 0.9741 >= 20000 pix 2200
CAPE
M‚dia
(J.kg )
15000-20000 pix -1 2000 10000-15000 pix
1800 5000-10000 pix
1600 1000 - 5000 pix
1400 500 - 1000 pix
1200 < 500 pix
1000 .
800 Expon. (.)
600
400
4 6 8 10 12 14 16 18
-1 Shear M‚dio (m.s )
2000
1800 R 2 = 0.9631
>= 55 dBz CAPE
M‚dia
(J.kg )
1600 -1 50-54 dBz
1400 45-49 dBz
40-44 dBz 1200
30-39 dBz
1000 20-29 dBz
. 800
Expon. (.)
600
400
4 6 8 10 12
-1 Shear M‚dio (m.s )
Results from Marco Aurelio Teixeira Master Degree
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MCS Size Distributions
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Observa-se desde células isoladas da ordem de poucas centenas de metros até grandes aglomerados convectivos da ordem de milhares de quilômetros com ciclos de vida da ordem de dias e compostos por diferentes tipos de nuvens. Ao observar tais fenômenos, através de uma imagem de satélite, deparamos com nuvens menores que o tamanho da resolução do pixel até aglomerados de nuvens da ordem de milhares de quilômetros. Nakazawa (1988) define "super cloud clusters" como sendo um conjunto de sistemas convectivos em diferentes estágios do ciclo de vida com escalas horizontais da ordem de 2000 km. Os SCM (Sistemas Convectivo de Mesoescala), são responsáveis pela maior parte da precipitação nos trópicos e em várias localidades de latitudes médias durante a estação quente. No final nas décadas de 70 e 80 foram definidos vários tipos de SCMs: linhas de instabilidade (Houze, 1977), "non squall lines" (Tollerud e Esbensem, 1985) e MCC-Complexos Convectivos de Mesoescala (Maddox, 1980).
Célula Isolada - Multi-Células - Super Cloud ClusterDezenas de metros centenas de quilômetros milhares de quilômetros
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?Convection is organized in a large range of scales, from individual
cumulus cloud up to large mesoscale convective systems of
hundreds kilometers composed by different cloud types lasting for
more than one day.
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The MCS Organization as function of the Easterly Waves in Africa
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The MCS Organization as function of the Diurnal Cycle - Africa and Atlantic Ocean
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The MCS Organization as function of the Diurnal Cycle - Amazonas
70 GOES - Average High Cloud Fraction (Tir<235K) = 21.3 %
12:30 - 14:30 LST
60 14:30 - 16:30 LST
% Cloud
Fraction
(Tir<235
K)
16:30 - 18:30 LST
50
40
30
20
10
(B) 0
0 50 100 150 200 250 300 350 400
Effective radius (km)
![Page 84: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/84.jpg)
MCS Average Properties
![Page 85: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/85.jpg)
MCS Characteristics and Life Cycle
![Page 86: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/86.jpg)
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--- Size Tir< 245K
--- Size Tir< 210 K
--- Minimum Tir
![Page 88: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/88.jpg)
MCS Vertical Distribution
![Page 89: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/89.jpg)
(a) (b)
(c) (d)
![Page 90: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/90.jpg)
Composite of the reflectivity vertical profile at different lifetime Weather Radar - S BAND
These figures show the increase of the ice phase as the cloud evolves to the mature stage.
Cloud with longer lifetime show intense liquid water phase at the initiation stage.
![Page 91: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/91.jpg)
Expansão da área e a Divergência em Altos Níveis
![Page 92: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/92.jpg)
Time
AT1
AT2
AT3
vt
A
AAE
.
1=
=
![Page 93: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/93.jpg)
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150
100
50
0
-50
No
rma
lize
d A
rea
Ex
pa
sio
n ( 1
/s)x
10
-6
2220181614121086420
Local Time (LST)
16
12
8
4
0
-4
-8
Wa
ter
va
po
r -
Win
d D
ive
rge
nc
e (
1/s
) -
20
0 h
Pa
x1
0-6
2.5
2.0
1.5
1.0
0.5
Ra
dio
ss
on
de
- W
ind
Div
erg
en
ce
( 1
/s)
- 2
00
hP
ax
10
-6
Normalized area Expansion
Radiossonde - Wind Divergence
Water Vapor - Wind Divergence
Hourly average area expansion, water vapor wind divergence and wind
divergence from radiossonde for 200 hPa level at WETAMC/LBA region.
![Page 96: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/96.jpg)
1.0
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
1614121086420
140
120
100
80
60
40
20
(1/ql)(dql/dt)
(1/a)(da/dt) DIV Surface
t
Ql
Qlt
A
AAE v
=
= 11 .
![Page 97: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/97.jpg)
Schematic diagram of the convective system life cycle size evolution.
160
140
120
100
80
60
40
20
0
Conve
ctive
Syste
m r
adiu
s (
km
)
140120100806040200
Time (minutes)
d(area)/dt=>lifetime/life cycle
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300
250
200
150
100
AE
- (
1/are
a)(
area
/t)
*10-6
s-1
16151413121110987654321
T - Life Cycle Duration (hours)
500
400
300
200
100
0
Num
ber of Convective S
ystem
Areal Expansion Rate (AE)
Number of CSs
AE=(281 - 271e-0.30*T
)*10-6
Normalized area expansion (10-6 s-1) as a function of the convective system
life duration (hours). The number of cases is also plotted (right axis).
![Page 99: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/99.jpg)
Propagação
![Page 100: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/100.jpg)
Tracking of Convective Systems
TRACKING OF CLOUD ORGANIZATION IN SYNOPTIC SCALE - 1984 to 1990 JAN-FEB
20
10
0
-10 LATITU
DE
-20
-30
-40
-50
-120 -100 -80 -60 -40 -20 0 20
LONGITUDE
![Page 101: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/101.jpg)
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Easterly Waves - Hurricanes - MCS Trajectories
![Page 103: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/103.jpg)
Radar/Satellite
![Page 104: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/104.jpg)
MCS Propagation
www.cptec.inpe.br AGU - Foz do Iguaçu August 2010
Results from Marco Aurelio Teixeira Master Degree
MCS Direction of Propagation obtained from Fortracc
Mid-level Wind – Density weighted average Wind (6 km)
Apparent Force
( pV
)
( apV
)
( advV
)
Steering-level model, Moncrieff and Green 1972 : In a general sense, sqrt (CAPE) dependence of the squall-line speed derives from the convective Richardson number: R = CAPE/1/2 (U-c)^2 where U-c is the surface relative inflow to the squall line. So the travel speed equal to the mid-level
wind at the "steering level") is c = U + sqrt (2 * CAPE/R).
Propagating model, Moncrieff and Miller : This model travels faster than the wind at any level . Propagation speed in an unsheared atmosphere approximately, c = UM + 0.3 sqrt CAPE.
![Page 105: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/105.jpg)
Rain Cells Propagation
www.cptec.inpe.br AGU - Foz do Iguaçu August 2010
63
16
5
11
5
0
10
20
30
40
50
60
70
<=25° 25° - 50° 50° - 75° 75° - 100° >100°
[°]
Fre
qu
ên
cia
[%
]
Frequencies for θ . The difference between the Apparent Force and the Average CAPE Gradient (ACG) directions.
( apV
)
CAPE)
θ
Results from Marco Aurelio Teixeira Master Degree
![Page 106: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/106.jpg)
Rain Cells Propagation
www.cptec.inpe.br AGU - Foz do Iguaçu August 2010
y = 1.7017x + 0.0798
R2 = 0.5263
0
4
8
12
16
20
0 2 4 6 8
Módulo GMC x 10-3
[m.s-2
]
Mó
du
lo V
ap
[m
.s-1
]
BA
a=
Vectors are considered linearly dependent
Considering the present situation:
CAPEapV =1702
a is Time unit and correspond to a Seconds
Considering a Uniformly Accelerated Motion
1702=a CAPE) = m/s2
=
=
=
0
0
1702
.
08,0 1702
apVapV
VatV
xy
CAPE
Time is 30 minutes – 1800 s
MCS – actually rain cells moves as combination of
008,000 == apVV
tadvVpV CAPE = .
Results from Marco Aurelio Teixeira Master Degree
![Page 107: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/107.jpg)
MCS and Precipitation
![Page 108: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/108.jpg)
Hourly average area expansion, rainfall and area fraction of brightness
temperature of 235K for WETAMC/LBA region.
![Page 109: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/109.jpg)
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MCS and Microphysics Properties -> Information for
the understand of cloud processes
![Page 111: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/111.jpg)
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Atividade Elétrica
Mattos and Machado, 2010 Submitted to Atmos. Res.
![Page 113: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/113.jpg)
Técnicas de Previsão o FORTRACC
Slide: 62 Version 1.1, 30 June 2004
![Page 114: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/114.jpg)
-50 -49 -48 -47 -46 -45 -44-25
-24
-23
-22
-21
Río Tieté
Océ
ano Atlá
ntico
Limite Bacia del Prata
Instante Inicial
Metodologia de tracking
![Page 115: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/115.jpg)
-50 -49 -48 -47 -46 -45 -44-25
-24
-23
-22
-21
Río Tieté
Océ
ano Atlá
ntico
Limite Bacia del Prata
Siguiente Imagen: t + delta t
Metodologia de tracking
![Page 116: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/116.jpg)
-50 -49 -48 -47 -46 -45 -44-25
-24
-23
-22
-21
Río Tieté
Océ
ano Atlá
ntico
Limite Bacia del Prata
Instante Inicial
Metodologia de tracking
PRONOSTICO
![Page 117: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/117.jpg)
• ESTIMATIVA DA VELOCIDADE E DIREÇÃO MÉDIA DE PROPAGAÇÃO
T-2 T T- T T T+ T
V(t-1)
V(t)
VP(t)
V=V(t)-VP(t)
V(t)+ VVE(t+1)=
![Page 118: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/118.jpg)
TENDÊNCIA DE CRESCIMENTO E
DESENVOLVIMENTO DO SC
A partir dos trabalhos de Machado and Laurent (2002) o
modelo do ciclo de vida de um SC pode ser estimado a partir
da seguinte equa‡Æo
Porem, o valor 1/A*(dA/ dt) sÆo tipicamente retas
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• TENDÊNCIA DE CRESCIMENTO E DESENVOLVIMENTO DO SC
(1/A) (DA/DT) 10^6
-300
-200
-100
0
100
200
300
400
0 1 2 3 4 5 6 7 8 9
TIME
(1/A
)(D
A/D
T)
10
^6
0-2 2-4.4 4.4-8.4 8.4-11.3
![Page 120: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/120.jpg)
Previsao do fortracc para 120 minutosDescargas elétricas
Chuva HidroestimadorRadar
![Page 121: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/121.jpg)
Figura 4.1 – Valores do parâmetro VIL, para a região do Radar de São Roque, as
18:00Z no dia 01 de novembro de 2006.
Figura 4.2 – Valores de refletividade em dBZ, do CAPPI no nível de 3 km, as
18:00Z no dia 01 de novembro de 2006. O círculo indica uma região com 150 km de
raio de atuação do Radar de São Roque.
Figura 4.3 – Valores de refletividade em dBZ, do CAPPI no nível de 3 km, as
18:30Z no dia 01 de novembro de 2006. O círculo corresponde a uma distância de
150 km do Radar de São Roque.
VIL (kg/m²) – Conteúdo Integrado de Água Líquida
30 minutos mais tarde …..
dhZMdhVIL
topo
base
topo
base
== 7/461044.3
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VIL > 10 kg/m²CAPPI – 3 km 20 dBz
![Page 123: Satélites Meteorológicos e a - INPEchuvaproject.cptec.inpe.br/portal/saoluis/curso/LA/la_ufrj.pdf · Satélites Luiz Augusto Toledo Machado Luiz.Machado@cptec.inpe.br . Exemplo](https://reader034.fdocumentos.com/reader034/viewer/2022050517/5fa15aab5bbe04796c6cf43d/html5/thumbnails/123.jpg)
Controle (considerando-se os valores máximos que ocorreram entre 45 min antes do evento severo e 45 min depois)
22/12/05 18/12/05 03/01/06 01/11/06 18/11/06 20/11/06 28/11/06 29/11/06 04/12/06 15/12/06 Media(M) Desvio Padrão(DP) M-2DP M-1DP M-1.5DP
VIL(kg/m²) 64.37 56.24 47.96 53.38 77.58 74.158 77.928 72.946 69.894 77.026 67.1482 11.04207229 45.06406 56.1061 50.58509
DVIL(g/m³) 4.16879 3.5157 3.03977 3.36234 4.84909 4.63523 4.8708 4.62231 4.36877 4.81448 4.224728 0.679547569 2.865633 3.54518 3.205407
ALT20(km) 16 16 15.8 15.6039 16 16 16 15.6883 16 16 15.90922 0.153348556 15.60252 15.7559 15.6792
ALT35(km) 16 16 14.5593 14.4245 16 15.8874 16 15.4124 16 16 15.62836 0.626684961 14.37499 15.0017 14.68833
ALT45(km) 15.8955 13.4482 12.2271 11.87 15.3921 15.278 15.9622 14.558 14.8579 16 14.5489 1.528738676 11.49142 13.0202 12.25579
Max.Ref.(dBZ) 59.282 61.628 62.256 62.86 63.152 71.03 65.288 63.404 64.486 61.154 63.454 3.157635543 57.13873 60.2964 58.71755
ALT.Max.Ref.(km) 7.6 5.4 5.6 6 6 7.6 8.2 8.4 9 9.4 7.32 1.467272602 4.385455 5.85273 5.119091
DH/DT(m/s) 0 0.77 -0.22 1.63 0 0.47 0.67 - 0 0 0.368889 - - - -
1/A*DA/DT ((*10^6)/s) 958.8 -51.2 -190.1 - 19.4 487.8 - - 117.3 - - - - - -
ALT45-ALT_0°(km) 11.7 9.35 8.03 7.57 11.09 10.98 11.36 9.96 10.16 11.3 10.15 1.437149957 7.2757 8.71285 7.994275
POH 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1
Limiares testados
Índice de Severidade
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Obrigado