# Presentation: 107527

## Status of the mission and preliminary definition 
of rain retrieval algorithms

_**of rain retrieval algorithms**_

## MEGHA-TROPIQUES

**ISRO CNES mission aimed to study water cycle and energy exchanges in tropical zone**
** **
**Main objectives :**
_**Energy budget of the atmosphere**_** (radiation and latent heat) at scales from the whole intertropical zone the scale of convective systems**
_**Life cycle of tropical convective systems and associated water budgets**_
_**Relationships and feedbacks between convection, water vapour and radiation**_

## Principles of the mission Megha-Tropiques

**Measure simultaneously 3 parameters determining for the energy budgets of the atmosphere**
** ****radiative fluxes ****(ScaRaB),**
** ****water vapour distribution ****(Saphir)**
** ****precipitation ****(Madras)**
**Accounting for the variability of the phenomena and th large range of scales, repetitivity of measurement is privileged relative to the ground resolution ==> ****high orbit (870 km), low equatorial inclination (20°), resolution 10 to 40 km.**

## The Instruments

**ScaRaB ****: a wide band radiometer for radiative fluxes measurement ****	****(transversal scan, 40 km)**
**Saphir**** : a microwave water vapour sounder. 6 channels around 183.31 GHz. (transversal scan, 10 km)**
**Madras**** : a microwave imager**
**	****5 channels 18, 23, 37, 89 and 157 GHz**
**	****(conical scan, <10 km to 40 km)**
**	****	****	****Marfeq**** is the radiofrequency part of this instrument**

## Project status (in France)

**	**** **
**SCARAB**** ****: already flown instrument – Phase B1 ended Nov 2003**
**SAPHIR**** : New development – Phase B1 ended Nov 2003 **
**MARFEQ**** ****: Astrium company**
**New development - Phase B ended in october 2003**

## 2004 : new start thanks tonew sharing with ISRO

**ISRO accepts to shift from the PROTEUS platform to an Indian platform, and to take the corresponding responsibilities (system, ground control,...)**
**CNES is keeping the responsibility of the ScaRaB and SAPHIR instruments, and MARFEQ, the radiofrequency part of MADRAS**

## Preliminary new planning 

- New start june 2004
- Complementary phase B studies with ISRO (platform change)
- Minimal MARFEQ activity in 2004
- Start of complementary phase B studies for SAPHIR/SCARAB
- Start of phase C/D MARFEQ January 2005
- Delivery of MARFEQ end 2007
- Delivery SAPHIR/SCARAB end 2007
- launch 2009

## Status of rain retrieval algorithms 

- Status of rain retrieval algorithms
- (France)

- Two kind of studies
-  passive microwave algorithm (N. Viltard et al.)
- (BRAIN)
-  combined leo-geo algorithm (M. Desbois et al.)
- Re-scaling algorithm

## Algorithm General Principle

**Algorithm General Principle**

- Brightness Temperatures

- Atmos. Variables

- Co-located (TMI+PR) or

- Cloud Model Simulation+RTM

- DataBase

- Database Construction

- Retrieval Algorithm

- or Hybrid of  the two

- Measured brightness Temperatures

- Bayesian or
- Neuronal

- Algorithm

- Retrieved Variable

## BRAIN Algorithm Principle

- Derived from Gprof
- Bayesian approach
- Co-located data of TMI and PR
- Completion with model simulation
-  Test base for error estimation

## BRAIN Performances for TMI

## BRAIN for MADRAS Algorithm 

- PR profile used to find a matching cloud model simulation profile in a primary database
- Use a RTM to simulate T**B**s for MADRAS and TMI

- Use TMI channels simulated vs. observed to infer error (also for Madras)
- Build Madras database for BRAIN algorithm

## Combined GEO-IR + microwave (re-scaling algorithm)

- Combined GEO-IR + microwave (re-scaling algorithm)

- Tests over Africa : PR used as rainfall detector

## July 2000 tests and validation data

- Rainfall probability of occurencefrom Meteosat/PR

- Systems rainfall efficiency deduced from comparisons with Monthly GPCP

- Monthly results in terms of monthly rainfall

- Available validation data (collected by IRD)

## Statistical indicators show some improvements relative to a product as GPCP. This is still more valid at smaller time scales (10 days). 

- Statistical indicators show some improvements relative to a product as GPCP. This is still more valid at smaller time scales (10 days).

## Further developments

**use of new channels of MSG to improve the rain detection part of the re-scaling algorithm**
**Validation of BRAIN over Africa**
**Chaining between BRAIN and the re-scaling algorithm**
**Further validation studies over Africa during the AMMA experiment (African Monsoon Multiscale Experiment)**
**Hoping very much to have TRMM working during the most intensive phases of AMMA (2005-2007)**