JOÃO CARLOS CARVALHOJOÃO CARLOS CARVALHO

Brasília - BrazilBrasília - Brazil

Academic BackgroundAcademic Background

Graduate: Physics - Federal University of São Carlos - UFScarGraduate: Physics - Federal University of São Carlos - UFScar

MSc and PhD in Meteorology - National Institute for Space Research – INPEMSc and PhD in Meteorology - National Institute for Space Research – INPE

Academic StudiesAcademic Studies

Retrieve of Temperature and Moisture Vertical Profile from Satellites Data Quantitative Analysis Techniques to Water Quality Monitoring

Fortaleza, Brazil – November 1-12, 2010.Fortaleza, Brazil – November 1-12, 2010.

This work consist in to obtain the vertical thermodynamic structure of atmosphere using algorithms based on the mathematical inversion of the RTE. In this work was used data from the satellites NOAA (Advanced TIROS Operational Vertical Sounder - ATOVS) – Visible, NIR, IR and Microwave spectral bands.

The results are compared with in-situ measurements (radiosonde profiles) and the numerical weather prediction data.

Different atmospheric conditions and surface types were considered, and the following parts of the cycles of sounding process were analyzed: treatment of the satellite’s received data; pre-processing (cloud detention, scattering identification, surface temperature and emissivity, etc.) data; the first guess selection and the inversion process (retrieval); the radiative transfer model (forward model); and the analysis of the impact of the retrieved profiles on a numeric forecast model.

Retrieve of Temperature and Moisture Retrieve of Temperature and Moisture Vertical Profile from Satellites DataVertical Profile from Satellites Data

)1(

2)(

2

3

Tkh

Bec

hTB

dpp

ppTBppIpI

p

pss

s

)()]([)()()(

0

0

pdpqpk

gp

p

p

)()(1

exp)(0

ResultsResults

0.0 0.5 1.0 1.5 2.0 2.5 3.0R M S error (g /kg)

100

1000

Pre

ssur

e (h

Pa)

G uess

R etrieva l

Sea

Impact of Assimilation of Retrieved Profiles in the CPTEC Numerical Weather Forecast Model.

RMS Error between Retrieved Profiles and Radiosondes Moisture Profiles

0.0 0.5 1.0 1.5 2.0 2.5 3.0R M S error (g /kg)

100

1000

Pre

ssur

e (h

Pa)

G uess

Retrieval

Land

Cloud and Scattering MaskCloud and Scattering Mask

Algorithm to determination of cloud and scattering pixels using AVHRR and ATOVS (NOAA Satellite) data.

Cloud mask based on Visible, NIR and IR bands - NOAA-15 - 02/03/2000Scattering mask based on microwave

band (AMSU-A and AMSU-B) - NOAA-15 - 02/03/2000

Quantitative Analysis Techniques to Monitor Water Quality of Curuai Lake, in the Amazon River, Brazil.

In this work are discuss the advantages and limitations of the Spectral Angle Mapper (SAM) and Continuum-Removal methods, to study the optically active water components. These techniques were applied at Lake Curuaí, located in the Amazonian floodplain, Brazil. The data are composed of limnological variables (TSS, chlorophyll, etc.), and in situ reflectance spectra from 400 to 900 nm and 1.59 nm of spectral resolution.The SAM algorithm succeeded in matching samples displaying similar spectral behavior allowing them to be classified as part of the same water type. Difficulties arise due to the large diversity of absorption and scattering patterns present in the water.

Spectral classification of the lake Curuaí data set using the SAM/KMeans classification method.

Correlogram of first-derivative of reflectance to variables Turbidity, TSS and Chorolophyll for the different spectral classes.

Spectral Classification of Water Body

Brazilian Water AgencyBrazilian Water Agency(Agência Nacional de Águas – ANA)

Superintendence of Hydrological Network Management - SGH

Coordinator of Telemetry Network

Water Resources Management (in the National Sphere)

Regulation of Water Resources (in the National Sphere)

Coordination of National Hydrologic Monitoring Network

ANA’s MissionANA’s Mission

Brazilian Water Agency - ANA is responsible for the management of the Brazilian Network Hydrologic Stations, whose goal is providing data for water resources management such as: water users permition, public water supply, monitoring of extreme events, electric power generation, navigation, irrigation and environmental aspects.

National Hydrologic Monitoring Network

Brazilian Hidrological Network

Operating Fluviometric Stations in Brazil (around 4.000)

Fonte: HIDRO.

Basically, the conventional hydrological network is composed of fluviometric, pluviometric, sedimentometric and water quality monitoring stations. Data are available on internet at the following website:

http://www.ana.gov.br/portalsnirh

Operating Pluviometric Stations in Brazil (around 8.400)

Fonte: HIDRO.

ANA’s Telemetry NetworkANA’s Telemetry Network

Hydrometeorological network is continually upgraded, and has increased demand for, online, water level, rainfall and water quality data.

Presently, around 300 Hydrologic Data Collection Platforms – DCPs whose transmission are based on SCD/ARGOS satellite system, using GOES/NOAA DCS satellite system, and cell phone technology (GPRS data transmission system).

The data acquired and transmitted by the DCPs are available in the following website: http://www.ana.gov.br/telemetria

Data Collection Platforms – DCPs

Data Transmission DCP - Satellite

Ground Reception Antennas - INPESCD/INPE and GOES/NOAA Satellites

Internet Availablewww.ana.gov.br/telemetria

Data Transmission Satellite – Base

Acquisition, Processing, Filtering and Quality Control

Telemetric Stations at ANASchematic Data Flow

Example of Telemetric Hydrologic Stations

SPATIAL HYDROLOGYRiver Level Estimation using

Satellite Radar (Jason, Pegasus, Envisat)

Reference:Seyler, F. et al. – SPIE - 2008.

Satellite-based monitoring of reservoir eutrophication

MOD09 Product - October/2008 MOD09 Product – May/2004

Reference: Martinez, J-M et al. - ICIPE-2010

Reservoir in the Brazilian Northwestern Region

Reservoir – Armando Ribeiro – RN, Brazil

Eutrophication Index

MODIS-derived index as a function of time compared with Armando Ribeiro reservoir water level over the period 2007-2010. During rainy season (February to May), the reservoir fills up and the index stays low. During the dry season, the water level decreases while the index increases.Satellite Index represents the difference between green and red spectral bands. Positive values reveal greenish water linked to the presence of green algae while negative values occur for brownish sediment-loaded originating from the run-off waters at rainy season.

Calibration of satellite data using in-situ chlorophyll-a data makes possible the definition of lakes trophic status.

Reference: Martinez, J-M et al. - ICIPE-2010

Thank You !!!