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Precipitation Observational Capabilities at the Brazilian Institute for Space Research Carlos Frederico Angelis* Luiz Augusto Toledo Machado* Carlos Augusto.

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Apresentação em tema: "Precipitation Observational Capabilities at the Brazilian Institute for Space Research Carlos Frederico Angelis* Luiz Augusto Toledo Machado* Carlos Augusto."— Transcrição da apresentação:

1 Precipitation Observational Capabilities at the Brazilian Institute for Space Research Carlos Frederico Angelis* Luiz Augusto Toledo Machado* Carlos Augusto Morales** * Brazilian Institute for Space Research – INPE/CPTEC ** University of Sao Paulo – USP/IAG Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

2 Instituto Nacional de Pesquisas Espaciais Brazilian Institute for Space Research INPE Centro de Previsão de Tempo e Estudos Climáticos Weather Forecast and Climate Studies Centre CPTEC Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

3 Centro de Previsão de Tempo e Estudos Climáticos Weather Forecast and Climate Studies Centre CPTEC Main facilities and data: NEC supercomputers SX-4 e SX-6; GOES, METEOSAT, NOAA, ACQUA,TERRA,TRMM database; 350 Data Collecting Plataforms (DCP); 16 Weather Radars Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

4 Satellite Precipitation Operational Monitoring of Rainfall Hydroestimator. An improved version of NESDIS Auto-estimator (Vicente et al. 1998/2001) Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

5 Satellite Precipitation Issues being addressed by CPTEC´s Satellite Meteorology team : 1.The Hydroestimator does not consider different rainfall regimes over South America; 2.The Hydroestimator uses only GOES images for precipitation estimation; 3.Although the Hydroestimator makes use of orography, wind and precipitable water data produced by ETA model, it still uses Brightness Temperature to access rain rates. Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

6 Satellite Precipitation 1.The Hydroestimator does not consider the different rainfall regimes over South America Location of all DCP´s whose data are transmitted to the Brazilian Data Collecting Sattelite (SCD) and downlinked to CPTEC Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

7 Rainfall regimes based on 1-yr hourly precipitation dataVariable 1 – Amount of rain 1 – Amount of rain 2 – Mean precipitation 2 – Mean precipitation 3 – Mean precipitation for rainy hours 3 – Mean precipitation for rainy hours 4 – Rainy hours and total of hours recorded ratio 4 – Rainy hours and total of hours recorded ratio 5 – Mean precipitation - January 5 – Mean precipitation - January 6 – Mean precipitation - February 6 – Mean precipitation - February 7 – Mean precipitation - March 7 – Mean precipitation - March 8 – Mean precipitation - April 8 – Mean precipitation - April 9 – Mean precipitation - May 9 – Mean precipitation - May 10 – Mean precipitation - June 11 – Mean precipitation - July 12 – Mean precipitation - August 13 – Mean precipitation - September 14 – Mean precipitation - October 15 – Mean precipitation - November 16 – Mean precipitation - December 17 – 1 st harmonic amplitude 18 – 1 st harmonic phase 19 – 2 nd harmonic amplitude 20 – 2 nd harmonic phase Satellite Precipitation 1.The Hydroestimator does not consider the different rainfall regimes over South America Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

8 Satellite Precipitation 2. The Hydroestimator uses only GOES images for precipitation estimation Due to the hurricane season over the Northern Hemisphere, CPTEC does not receive GOES images regularly. The Hydroestimator has produced only 8 daily accumullated rainfall estimations during September It causes impact on many users like agricultural companies which depend on daily precipitation to plan soybean, corn, bean and other crops. Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

9 Mean precipitation - October/2004 METEOSAT images have just been introduced to Hydroestimator when GOES images are not available Satellite Precipitation 2. The Hydroestimator uses only GOES images for precipitation estimation GOESMETEOSAT GOES - METEOSAT Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

10 Satellite Precipitation 3. The Hydroestimator uses Brightness Temperature to access rain rates Other parameters different from Brightness Temperature have been tested in order to develop a new algorithm which considers regional rainfall regimes and physical properties of convective systems. Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

11 Satellite Precipitation 3. The Hydroestimator uses Brightness Temperature to access rain rates According to Machado et al. (2004) the life span of a convective system is significantly related to its area expansion. Area expansion and associated Std Deviation as a function of the convective system lifetime Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

12 Satellite Precipitation 3. The Hydroestimator uses Brightness Temperature to access rain rates Forecasting and tracking of active convective cells cloud clusters Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

13 Weather Radars 16 weather radars are being integrated in two different networks Operational weather radars in South America Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

14 Weather Radars The radars networks are producing data which, in a near future, will be valuable to shed light on important topics like: 1. Which meteorological and climate processes are linked to the Amazonian and global climates? 2. How does the surface heterogeneity interfere in the vertical movements and also in the cloudiness? What are the effects of regional and long distance transportation of heat, humidity and aerosols? 3. What is the limit of current models in conceiving scenarios about land use and climate change impacts on global climate? 4. How does the South American Low Level Jets (SALLJ) vary as a function of synoptical conditions? What is the role of synoptical systems associated with the westerly flows in high altitudes? Does the Chaco Low play an important role on the SALLJ modulation? 5. What is SALLJ spatial structure and its temporal variability? What are the impacts of SALLJ on Mesoscale Convective Systems over the Prata Basin? 6.Do atmospheric simulation models reproduce satisfactorily SALLJ spatial and temporal structures in different spatial and temporal scales? Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

15 Weather Radars The Amazonian radar network will be fundamental to confirm the direction of rainfall propagation in Western Amazon showed by previous research. Difference between 1800 and 0600 LST (left) and 2100 and 0900 LST (right) SSM/I images averaged over the period Blue shades indicate morning maxima and red shades indicate afternoon maxima (Negri et al., 2000) Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos

16 Weather Radars TRMM-PR overlaid with gauge first harmonic phase (Angelis et al., 2004) Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos The Amazonian radar network will be fundamental to confirm the direction of rainfall propagation in Western Amazon showed by previous research.

17 CPTEC´s Satellite Meteorology team is the only group that works on research and development of meteorological and climatological operational products in Brazil. Instituto Nacional de Pesquisas Espaciais Centro de Previsão de Tempo e Estudos Climáticos


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