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Sergio Masuelli. System Engineer of SAC-D Geophysical Applications for MWR Professor of Gulich Institute (CONAE-UNC). sergio.masuelli@conae.gov.ar. November 2010 Fortaleza Brasil. Index. Activities of Gulich Institute Aearte Master Introduction to MWR L1 to L2 project plan
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Sergio Masuelli System Engineer of SAC-D Geophysical Applications for MWR Professor of Gulich Institute (CONAE-UNC) sergio.masuelli@conae.gov.ar November 2010 Fortaleza Brasil
Index Activities of Gulich Institute AearteMaster Introduction to MWR L1 to L2 project plan Surface retrievals Atmospheric Retrievals Sea Ice Concentration L2 Simulator
GULICHINSTITUTE CETT SAC-C MOC Instituto Gulich
GULICHINSTITUTE Instituto de Altos Estudios Espaciales Mario Gulich CONAE-UNC Activities began in 2001 Natural Emergencies: National Emergencies Services • Images supply • Users support Courses: • Non Qualified Users • National Courses (INTA, 2004) • International Charter (Regional PM, 2006) Health Applications: • Scientific Support to Health Authorities • Landscape study of vector dynamic. • Spatial Modelling of vector dynamic. • Regional Courses (Latinoamérica, 2006)
Modelado espacio-temporal de la densidad de Culicidos en escenarios heterogéneos derivados de información de sensores remotos. S. Masuelli, C. H. Rotela, M. Lamfri, C.M. Scavuzzo La Ecuación representa el modelo básico de difusión. El primer término representa la difusión, el segundo el transporte por el viento y el tercero la atracción por mamíferos (humanos). La ultima corresponde a los términos Fuente y Sumidero. ρ = Densidad de mosquitos DR = tensor de Difusión DW = Tensor de Rugosidad V = Velicidad Viento Superficie KH = Tensor de Atracción H = Campo de Atracción = Tasa de nacimientos β= Tasa de muertes Orán
AEARTE MASTER • Speciality branches: • Applications on Natural Disasters • Planning and Scheduling • Applications on Human, Animal and Vegetal Epidemiology.
AEARTE MASTER OBJECTIVES To specialize professionals for the interdisciplinary managing of Emergencies by doing effective use of space technologies, geoprocessing and AI P&S technologies. To promote research related to the factors originating natural Disasters including buds of agricultural, animal or human plagues. This would allow preparing strategies of Emergency prevention, monitoring, control and response . To make possible the application of the most modern technologies to the aims of gathering, summarize, analysis and diffusion of data.
Introduction to MWR • MWR swath width is ~380km, displaced 272km across-track (towards the right), wich overlaps the Aquarius instrument swath. • MWR IFOV ~40km
Conical Arc Conical Arc Introduction to MWR SUN
MWR beam overlapping along track 40 km 13 km Introduction to MWR 3 times
Introduction to MWR Objective: To obtain the Geophysical Variables WS: Wind Speed Surface: WD: Wind Direction IC: Ice Concentration WV: Water Vapor Atmosphere: LWC: Liquid Water Content RW: Rain Water
Radiative Transfer Model Microwave Antenna Up-welling Brightness Atmospheric Emission Atmospheric Absorption Reflected Atmospheric Brightness Down-welling Brightness Surface Emission Schematic Microwave Radiative Transfer Model [Thompson, 2004]. Introduction to MWR
The Retrieval Problem TBj= F (P)+ Dej Forward problem P= G(TB) Inverse problem ? Geophysical Variables P: WS, WD, IC, WV, LWC, RW Pi= Gi(TB*i) where TB*i=TB(P01,…,Pi ,…,P0N) Introduction to MWR We have 6 Ps but only 4 TBs
Simulators Depuration of Algorithms Application Prototype Calibration Prototype L1 to L2 project plan General Scheme of the Development Plan ATBD
A(WS,SST,f) TBH TBV F0(SST) (ATBV − TBH ) - F(SST) = C0(WS)+C1(WS)COS(χ)+C2(WS)COS(2χ) F(SST) = (ATBV − TBH) − [C0(WS)+C1(WS)COS(χ)+ C2(WS)COS(2χ)] Does C’S converge? No Yes END Surface retrievals Wind Retrieval. AVH Algorithm (ATBV − TBH ) - F(SST) - C0(WS) =C1(WS)COS(χ)+C2(WS)COS(2χ) Insensitive on atmospheric changes
Surface retrievals Wind Speed CFRSL Preliminary Results (AVH) EDR Wind Speed, m/s AVH Wind Speed, m/s
Surface retrievals Wind Direction CFRSL Preliminary Results (AVH) AVH Wind Direction, degree AVH Wind Direction, degree
Atmospheric retrievals The Cloud Problem
Atmospheric retrievals Precipitation and LWC signal (CFRSL)
Atmospheric retrievals Rain and Cloud Analysis Non PrecipitativeCloud Rainy Cell
Sea Ice Concentration Sea Ice Algorithms Bootstrap Algorithm Nasa Team Algorithm
Sea Ice Concentration First Year Ice Concentration using NT algorithm (CFRSL) WindSat: 19V & 37V GHz Latitude, (deg.) WindSat MWR 24V & 37V GHz Latitude, (deg.) MWR Simulated Longitude, (deg.)
Sea Ice Concentration CONAE Sea Ice Algorithm
Sea Ice Concentration Obtaining Parameters from a Scatter Plot
L2 Simulator GDAS Data Base L1B1 Data Base External Data Preparation Internal Data Preparation L2 Processor RTM IC/WS/WD WV/LWC/RW RTM No It converges? Yes END
Fin We have a lot of work to do…..