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Desempenho de algoritmos estimadores de
precipitação
Frederico Angelis
Medições de precipitação podem ser realizadas por: Pluviômetro (báscula ou totalizador), radar ou satélite.
Pluviômetro a melhor medida local, mas depende do vento e de pássaros, insetos, calibração, etc...difícil extrapolar no espaço medidas pontuais.
Radar – ótima cobertura e alta resolução temporal, somente em torno de 100 km do radar – problemas – altura do feixe com a distância, abertura do feixe, precisa saber a distribuição de gotas, atenuação . Z AR
Z= N(D)D6dD
Satélite – medida global, baixa resolução temporal – IR – relação indireta altura do topo – precipitação, MW sobre o oceano medida direta, sobre o continente espessura da camada de gelo e precipitação. Problema, não vê chuva de nuvens quentes e relações variam em função do ciclo de vida. Modelo – Precisa melhorar a previsão de precipitação – não se conhece direito a microfísica e os modelos não descrevem as distribuições
b
Por outro lado a precipitação é a variável de maior interesse da meteorologia. Saber quanto choveu é algo que depende da resolução espacial e temporal .
Precipitação é a variável meteorológica de maior variabilidade espacial e temporal
Rainfall Signatures from MW
Nimbostratus
Cumulonimbus
0 C
0 C
0 C
0 C
Emission – freq’s <40 GHz Scattering – freq’s >40 GHz
the increase of the ice phase as
the cloud evolves to the mature
stage.
the ice content increases as
well the precipitation.
Motivação
Sensitivity to the Cloud Properties
=> High sensitivity to the cloud, especially its ice phase
Sensitivity to the ice content
Sensitivity to the particle size
Microfísica das Nuvens
GV - Physical Approach – Field Campaign
WORKING GROUP – 1
CHARACTERISTICS OF THE PRECIPITATING SYSTEMS AS FUNCTION OF THE REGION AND LIFE
STAGE
Responsible : Luiz Machado
WORKING GROUP – 2
PRECIPITATION ESTIMATION – DEVELOPMENT AND VALIDATION ALGORITHM
Responsible : Carlos Angelis
WORKING GROUP – 3
ELETRIFICATION PROCESS: MOVING FROM CLOUDS TO THUNDERSTORMS
Responsible: Carlos Morales
WORKING GROUP – 4
CHARACTERISTICS OF THE BOUNDARY LAYER FOR DIFFERENT CLOUD PROCESSES AND
PRECIPITATION REGIMES
Responsible: Gilberto Fisch
WORKING GROUP – 5
MODEL IMPROVEMENTS AND VALIDATION, WITH FOCUS IN CLOUD MICROPHYSICS AND AEROSOL
INTERACTIONS, FOR SATELLITE PRECIPITATION ESTIMATES IN BRAZIL
Responsible: Maria Assunção Dias
NASA Precipitation Measurement Missions Science Team -26-29 October 2009 - Salt Lake City
CHUVA Project
CHUVA Field Campaign Schedule
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEZ
2010 ALCANTARA
2011 CHUVA
WORKSHOP#1
FORTALEZA FORTALEZA BELÉM BELEM SAO LUIZ PARAITINGA
SAO LUIZ PARAITINGA
2012 CHUVA -
WORKSHOP#2
FOZ DO
IGUAÇU
FOZ DO
IGUAÇU
FOZ DO
IGUAÇU
2013 FOZ DO
IGUAÇU
BRASÍLIA BRASÍLIA
2014 MANAUS MANAUS MANAUS MANAUS
The Pre-CHUVA Experiment and the CHUVA Project
Transportation from São Luiz to Alcântara
4 - Delta Village
3 - Airport
THIES Disdrom
eter
2 NASA Rain
Gauges
INPE Rain
Gauge
Parsivel Disdrom
eter
JOSS Disdrom
eter
THIES Disdrom
eter
2 INPE Rain
Gauges
Measurement Scheme
for the Main line
300 meters
300 meters
300 meters
300 meters
GPS
30º
90º
ADMIRARI
MP3000A LIDAR
300 meters
2.00 km
7.50 km
1.80 km
3.90 km
$
2 - INPE
INPE Rain
Gauge
THIES Disdrome
ter
JOSS Disdrome
ter 5 – Anem.
Tower
GPS
Parsivel Disdrome
ter
2 NASA Rain
Gauge
1 - RADAR
INPE Rain
Gauge
Volumetric
and RHI RADAR
90º
$
Radiosonde RS92
INPE SITE
Instrumentation
RADAR site X Band dual polarization
Meteorological Radar
INPE Rain Gauge
Meteorological Wheather
Station
Radiosonde RS92
Instrumentation
INPE site
GPS
INPE Rain Gauge
2 NASA Rain Gauges
THIES Disdromet
er
JOSS Disdrometer
Parsivel Disdromet
er
Instrumentation
Airport Site
THIES Disdrometer
2 NASA Rain Gauges
INPE Rain Gauge
Parsivel Disdromet
er
MP3000A Radiometer
JOSS Disdrometer
Soil Moisture
GPS
LIDAR
Instrumentation
Delta Village Site
ADMIRARI THIES
Disdrometer
2 INPE Rain Gauges
Instrumentation
UECE Airplane
OAP200X - Hydrometeors
30-450um
FSSP – Raindrops Distribution
2-47um
Equipments Installation
cold
warm
Ice cloud warm
cold
warm
DSD (Joss)
0
50
100
150
200
250
radar vila2 inpe aero vila1 slz
Accumulated Rain Gauge (mm)
0
2
4
6
8
10
12
14
radar vila2 inpe aero vila1 slz
Rain Gauge No. Of Days With Rain
Warm Events
March 21th
MP3000
ADMIRARI
Thies Disdrometers (inpe and Village sites)
Fortaleza Campaign
Main Target Study: Warm Clouds and MCSs organized by Easterly Waves
From 21 March to 29 April 2011 – The GPM Planning Meeting and the CEOS –
PC will be held during this period in Fortaleza
Additional Data: Aircraft for microphysical measurements (if the airplane will be OK) and S
and X Band radar.
Fundação Cearense de Meteorologia e Recursos Hídricos Secretaria de Ciência, Tecnologia e Ensino Superior Governo do Estado do Ceará
Radar de Fortaleza (Banda X)
Radar de Quixeramobim (Banda S)
Sítios Experimentais da Região Metropolitana de Fortaleza Lidar
Container de química
Radiômetro de microondas
Estação meteorológica
Equipamentos de fluxos
Disdrômetros (Joss e Parsivel)
Pluviômetros
GPS
Micro- radar
Radar móvel
GPS
Pluviômetro
Disdrômetros (Thies)
Disdrometro (Parsivel)
Pluviômetro NASA
Radiossondagem Disdrômetro (Parsivel)
Pluviômetro NASA
Central na FUNCEME com
conexão internet, bancada
para trabalho e dois PCs.
Disdrômetro (Thies)
Disdrometro (Thies)
Pluviômetro
Estação meteorológica
Radar banda X
Sítios Experimentais Mossoró Quixeramobim Fortaleza
Guarda Municipal/Defesa Civil
INMET
Belem Campaign
Main Target Study: Tropical Squall Lines and Local Convection
From 30 May to 9 July 2011
Additional Data: S Band Radar
Controlled Meteorological balloons are small
altitude-controlled platforms with bi-directional satellite
communication and long-duration flight capability _ Voss and Fitzgerald collaboration
Belem Squall Lines Climatology : 2000 to 2006
Classification : CCL: Costal Convective Line ( Propagation < 170 km) SL1: Squall Line Type 1 ( 170 Km < Propagation < 400 km) SL2: Squall Line Type 2 ( Propagation > 400 km) SL2 – STM – Moved around Santarem = 56%
Locais do Experimento de Belém
21 km
24 km 5.5 km
8 km
Equipamentos dos sitos:
Sitio#1 – UFPA:
Radar X-POL, Field Mill (USP), GPS
Sítio#2 – UT-Outeiro (DTCEA-BE)
Radiômetro de microondas, Lidar, Micro Radar,
2 disdrômetros Joss e Parsivel, GPS, 2 pluviômetros,
estação de fluxo, field mil, sensor de umidade do solo.
Sítio#3 – UT-Benevides (DTCEA-BE)
Disdrômetros Parsivel, GPS (UEA), 2 pluviômetros, field Mill (USP), GPS.
Sítio#4 - DTCEA-BE – aeroporto:
Estação de Radiosondagem - Disdrômetros Parsivel, GPS (UEA),
2 pluviômetros, field Mill (USP) e Micro Radar (USP)
Sítio#5 – INMET - GPS (UEA), pluviômetro, field Mill (USP)/
GPS Meteorology in CHUVA Belem (L. Sapucci, D. Adams, R. Fernandes, L. Tanaka)
Our Principal Aims in
CHUVA Belem
Identify wv convergence
timescales and propagation of
convection/squall lines in GPS
PWV
Estimate wv convergence in a
limited region in conjunction
with sondes/radiometers, etc)
Test maximum temporal
resolution of the GPS PWV
technique (comparing GIPSY
with GAMIT)
Employ 3D/4D techniques for
estimating mesoscale wv fields.
Install 7 to 10 GPS within 70km of SIPAM Belem (See Map for Sample
Configuration of 8 probable sites). Ultimate configuration depends on siting of
radiosondes, etc.
Sítios em Belém
São Luiz do Paraitinga Campaign
Main Target Study: Warm Clouds, Cold Fronts, MCSs, SACZ and Local
Convection
From 31 October to 22 December 2011
Additional Data: S Band Radar and “Lightning Mapping Array” (LMA) – NOAA and NASA
– Steve Goodman
Posição do Radar e sitios.
39
Richard Blakeslee / NASA Marshall Space Fight Center
Larry Carey / University of Alabama in Huntsville
Jeff Bailey / University of Alabama in Huntsville
National Space Science and Technology Center (NSSTC)
Geostationary Lightning Mapper (GLM) Science Team Meeting, NSSTC, Huntsville, Alabama
2 December 2010
Lightning Mapping Array (LMA) Observations in CHUVA:
Overview of Plans
1Steven Goodman Program Senior Scientist
NOAA/NESDIS/ GOES-R Program Office http://www.goes-r.gov
2Richard Blakeslee, 2William Koshak, 2Walter Petersen, 3Larry Carey, 3Douglas Mach, 3Dennis Buechler, 4Monte Bateman,
4Eugene McCaul, 5Eric Bruning, 5Rachel Albrecht, 6Donald MacGorman
1GOES-R Program, NOAA/NESDIS, Greenbelt, MD2NASA Marshall Space Flight Center, Huntsville, AL,3UAHuntsville, Huntsville, AL,4Universities Space Research Association,5University of Maryland, College Park, MD,6NOAA/National Severe Storms Laboratory, Norman, OK
Fall AGU Meeting of the Committee on Atmospheric and Space Electricity 14 December 2010
GOES-R Geostationary Lightning Mapper (GLM): Pre-Launch Algorithm Validation-CHUVA Campaign Report
EUM/ Issue <No.> <Date>
Jochen Grandell, Hartmut Höller, Rolf Stuhlmann
EUMETSAT Contribution
to the CHUVA Campaign
Slid
e:
41
EUM/MTG/VWG/10/0567 AGU Fall meeting 2010
100 km 50 km
40 km radius 30 km
radius
LMA - Lightning Mapping Array
o The LMA system:
o locates the peak source of impulsive VHF radio
signals from lightning
o uses unused television channel by measuring the
time-of-arrival of the magnetic peak signals at
different receiving stations in successive 80 ms
intervals
o hundreds of sources per flash can be detected in
space and time (GPS), allowing a three-
dimensional (3-D) lightning map to be constructed
Foz do Iguaçu Campaign
Main Target Study: MCC and Cold Fronts
From 9 November to 13 January 2012
Additional Data: La Plata Basin Campaign
Goal: Measure MCCs to accomplish the GPM and La Plata Basin Regional Hydroclimate
Project (LPB) goals.
Foz do Iguaçu is located on the border of three countries: Brazil, Argentina and Paraguay, where MCSs
produce a large impact. More than the 80% of the precipitation is explained by those systems
Brazil
Argentina
Paraguay
Hailstorm climo derived from AMSR-E
Paraitinga
Foz do Iguacu
CHUVA - Foz do Iguacu (Nov
2012 - Jan 2013) is along edge
of the region with possibly the
world’s most frequent severe
thunderstorms
Rachel Albrecht
Foz do Iguaçu Campaign
Percentage of surface rain from 2A25 explained by MCSs over La Plata Basin
Partiticipation: Zipser, Houze, Ceci, Palio,......
This experiment will focus on these set of questions:
What are the main surface and boundary layer processes in the formation and maintenance of large and long live MCS?
How cloud microphysics and electrification processes evolves during the cloud life cycle?
What is the contribution of the aerosol in the process of formation of MCC precipitation?
How to improve both space and time precipitation estimation of rainfall over the continent for the GPM constellation over
the region?
How to improve quantitative precipitation forecast over MCS?
How models do represents the evolution of the PBL and the microphysics of these complex convective systems?
The deployment of a dual frequency and
polarization radar like NASA's N-Pol would
contribute with other observations to better
understand the microphysics processes and
their evolution associated with MCS. Also
airplane measurements will be facilitate by
the geographical position.
Results from Paola Salio
Manaus Campaign
Main Target Study: Organized and Local Convection from Warm and Ice Clouds
From 6 January to 4 April 2014.
Additional Data: The ARM Climate Research Facility in the Amazon Basin (Scot Martin –
Havard University and several partners)
S Band Radar (SIPAM)
Manaus Campaign
Cloud-Aerosol-Precipitation Interactions
Aerosol effects on scattered cumulus clouds, especially the
aerosol radiative effect and with a special focus on the impact
of biomass burning aerosols;
Aerosol effects on deep convective clouds, precipitation, and
lightning under different aerosol and synoptic regimes,
including the roles of aerosols in changing regional climate and
atmospheric circulation; and
Improvement on parameterizations of aerosol-cloud
interactions in the climate models
The ARM Aerial Facility in Brazil
CHUVA – Basic Set of Equipments
Doppler X band dual polarization -
METEOR 50DX - Selex
Radiometrics MP 3000 - Brightness temperature
from 35 channels (22-30 and 51-59 Ghz)
X-POL Mobile Radar
CHUVA – Basic Set of Equipments
LIDAR – backscaterring coefficient.
Lidar Raman System 2 channels: 532nm and 607nm
GPS - A dual-frequency receiver - IWV
CHUVA – Basic Set of Equipments
3 Ott Inc. PARSIVEL Optical Laser Disdrometer.
1 Joss Waldvogel Acoustic Impact Disdrometer. (NASA)
5 Raingauge (NASA)
CHUVA – Basic Set of Equipments
Radiosonde RS92
Soil Mositure - EnviroSCAN Probe
Soil moisture profile (up to 0.5 m)
continous measurements
HFP01 – soil heat plates (2) for the soil heat flux measurement
STP01 – soil temperature profile (5 sensors 2,5,10,20,50 cm)
CHUVA – Basic Set of Equipments
Vertical pointing micro Doppler rain radar
Keplel – 24.1 Ghz
CS110 - Electric Field Sensor
Measuring the local electric field
CHUVA – Basic Set of Equipments
Values of air temperature, humidity, atmospheric
pressure, windspeed and direction, radiation
measurements
Surface Weather Measurements
EC150 open path gas analyser and the sonic
(CSAT3) coupled for the surface momentum,
energy, water vapour and CO2 fluxes
Radiation components: solar (shortwave) and
terrestrial (longwave) radiation upward and downward
fluxes
Classificação de Hidrometeoros:
mudança de fase diferencial Coeficiente de correlação transversal
Alan Calheiros
A physically-based identification of Vertical Profile of Reflectivity
Goal: use radar measurements to retrieve a physically-based representation of the Vertical Profile of Reflectrivity and characterize links between physical processes of rainfall at ground and aloft.
altitude
distance
Liquid phase
Melting phase
Solid zone
41/52 Pierre Emmanuel Kirstetter
sol
h
Distribution N(D,h) (gamma)
Zo
Zm
Dg
Phase & Composition ( « matrice-inclusion »
scheme)
Vertical profile of
Reflectivity
Diffusion model (Mie)
h h
Zo est fixé
Physically-based model
Nt Do
)(Z(h)h)Z,N(D,Z
Z
Z
DgZ
M
H
S
Z/Zo
Nts
Ntm
Dos
Dom
43/52 Pierre Emmanuel Kirstetter
High resolution - BRAMS 1 km.
BRAMS 1 km : NX, NY = 500, 500 300 processos –> 2 ½ h de processamento 24 horas de previsão.
BRAMS 1 km mm
Modelo – Radar – Satélite : Banco de Dados
Microfísicos
Modelo c/
microfísica
Satélite IR
Microondas Radar e a
técnica VPR
Modelo
radiativo
Radar
X-POL
Disdro
metros
Simulações com BRAMS e RTTOV
1. Simulação com BRAMS:
Entrada Processamento
Estudos de casos BRAMS
RTTOV Temp. Brilho
2. Simulação com RTTOVS:
Saída
3. Avaliação das Simulações:
Temp. de Brilho do RTTOV
Temp. de Brilho do Satélite
Profiles: Rain, Snow, Graupel,
Aggregates, Cloud-Water,
Cloud-Ice
INPUT DATA
Profiles: Rain, Snow, Graupel,
Aggregates, Cloud-Water,
Cloud-Ice
Simulações – Modelo de alta resolução e Modelo
radiativo – Base de Dados
Resultados do Renato Galante
3. Avaliação das Simulações: Sensor TMI/TRMM
Temperatura de Brilho Simulada
Temperatura de Brilho Observada
CHUVA WEB
Curso – Processos Físicos da Nuvens – 28/3 a 1/4
Segunda Terça Quarta Quinta Sexta
Micrometeorologi
a conceitos
básicos
(Gilberto)
Microfísica da
nuvens
(Morales)
Modelagem de
nuvens – interação
aerosol-nuvens
(Assunção)
Radar Princípios
básicos
(Frederico)
Estimativa de
precipitação
satélite e radar
(Frederico)
Modelagem em
alta resolução –
conceitos básicos
(Assunção)
Micrometeorologi
a e a formação de
nuvens
(Gilberto)
Satélites e
Modelagem
Radiativa
(Luiz)
Ferramentas para
Previsão imediata
(Luiz)
Eletrificação das
nuvens
(Morales)
6
Obrigado
Todos que desejarem participar do CHUVA
São Bem vindos.
