1. Precipitation and altimeter missions Jean Tournadre Laboratoire d’Océanographie Spatiale IFREMER Plouzane France

2. 1. Basic principles of satellite altimetry Interaction of the pulse of duration τ with a smooth sea surface. For an altimeter in a 1000-km orbit a pulse duration of about 3 ns would lead to a footprint of diameter 2.8 km.

3. In this way, the altimeter is able to average out the effect of the ocean waves. This parameter is called a Significant Wave Height (SWH), max power : sigma0 (wind), epoch (sea surface height) In practice sea surface is rough rather than flat. As a result, the first reflection of energy commences when the leading edge of the pulse reaches the topmost crests of the waves, earlier than for the flat surface, but the reflected energy does not achieve its maximum until the trailing edge reaches the lowest wave trough.

4. Problem of rain for altimeter: perturbations of the signal: attenuation and change of propagation speed. – Attenuation: modification of the waveforms – Speed change : conversion time/distance Since Topex: Radar altimeters operate at two frequencies: Ku and a C or S bands, mainly for correction of ionospheric effects Rain detection from dual-frequency backscatter coefficient   data well established (based of Ku vs C band attenuation) Used operationally for Jason and Envisat rain flagging Several studies showed that rain rate estimates are possible (McMillan et al 2002, Tournadre, 1998) Context

5. Two main problems for precipitations studies – Low time and space sampling of the ocean by one altimeter (nadir view only) – No estimation of the height of rain necessary (assimilated to the freezing level FL) to infer the surface rain rate from the attenuation over the atmospheric path New method to infer FL from radiometers (that are part of the altimetric missions) Merging of different altimeters data to improve the time and space sampling Rationale

6. Rain attenuation is frequency dependant : Attenuation by rain one/two order of magnitude larger at Ku band than that a C/S band Detection of occurrence where Ku   attenuated vs C/S   Use of rain free Ku/C band relation Overview of the Method Mean « rain free » KU/C(S) relation (f) RMS of the f relation L z :liquid water content from radiometer

7. Rain rate and Freezing level determination Rain rate from attenuation using Marshall-Palmer relation a and b frequency dependent coeff. H height of rain ~ freezing level Problem : determination of FL? Model of TB’s as a function of rain rate and FL Wilheit et al 1977 atmosphere model Rosencrantz 2002 Radiative transfer model FL estimated by inversion of TB for rain flagged samples Topex TMR microwave TB modelling

8. Radiometer Brightness Temperatures TB near 18 and 22 GHz selected for inversion for Topex and Jason (36.5 and 22 for Envisat). More sensitivity. Distribution of the TB for rain flagged samples. FL and R rad by inversion of TB 18 and TB 22 ~ 35% of TBs outside model because of difference of sensor resolution

9. Validation of Freezing level estimates About 50 % of FL for low rain rate ( 5 mm/hr Higher proportion for high latitude than in the Tropics. Proportion of valid FL estimates

10. Comparison with NCEP and ECMWF FL for 2003 Underestimation of high FL (>4 km) Overestimation for FL<3 km Overestimation at mid and high latitude Underestimation in the Tropics Similar results with SSM/I and TRMM Fl estimates using PR bright band Better than SSM/I and good overall agreement Validation of Freezing level estimates Topex Jason Envisat

11. Altimeter intercomparison Comparison of histograms of Rain rate and FL for Envisat, Jason and Topex : very good agreement Topex/jason Envisat underestimate low rain rate and overestimate high FL (histogram equalization) RAIN FL

12. Altimeter intercomparison (collocated samples) Comparison of Jason and Topex FL and rain rate for tandem mission: Very good agreement no calibration needed Comparison of Envisat and Jason/Topex : few collocated samples (less than 200)

13. Mean FL for winter 2003 JASONNCEPSSM/I F14

14. Log-normal distribution method (Berg and Chase (1992) The lognormal density : non linear function of two variables, μ and . where p is the probability of non zero rainfall value.  and  expressed by Ri : ensemble of instantaneous rainfall estimates Mean rain rate

15. Mean annual rain rate fields for 2003 Topex Jason Envisat Merged GPCP SSM/IF13 Very good agreement between Jason, Envisat and Topex expected for high northern latitude Good agreement with Global Precipitation Climatology Project More smaller scale details (coherent with TRMM climatology) Merged data set using histogram equalization for Envisat.

16. Mean annual rain rate fields for 2003 Mean latitudinal distribution

17. Improvement of mean rain rate by data set merging Correlation between Altimeter monthly rain rate and GPCP climatology RMS between Altimeter monthly rain rate and GPCP climatology

18. OTHER PARAMETER RAIN CELL LENGTH Very good along-track resolution by altimeter (~5-8 km) Length= number of consecutive rain samples Rain Cell Diameter Distribution (RCDD): exponential pdf Altimeter : Rain Cell Chord exponential pdf with l=2/  Mean rain cell diameter 1/ Topex param Can allow the study of rain event nature (stratiform, convective,..)

19. Online web server at IFREMER CERSAT All the data for the Topex,Jason and Envisat missions have been processed and are available at Ifrermer both on ftp and in a browser

20. MESCAL-ALTIKA Altika : altimeter in Ka band. Better performances but one major problem at Ka band (35.75 GHz) rain and cloud can strongly attenuate the signal and distort the echo waveform. At Ka band the attenuation by cloud droplet is about 1.1 dB/km par g/m 3 (10 time larger than Ku band), not negligible. Cloud at Ka = rain at Ku. Cloud more frequent than rain. Necessity to analyze in detail the effect of cloud on the signal Estimation of attenuation, off-nadir angle, leading edge slope at 1Hz and 20 Hz as a function of cloud parameters (IWC, height, diameter,..) Estimation of the impact of cloud on the geophysical parameters (ssh,s0, SWH) retrieval: waveform modeling and MLE4 (Stenou et al). Determination of data availibility Previous studies (Tournadre 1999). In presence of rain larger than 1-2 mm/hr the distortion of the waveform will inhibit the geophysical parameter retrieval.

21. Waveform distortion by rain and cloud Ka band : strong attenuation by rain and cloud But more important: strong distortions of the waveform shape : modification of leading edge and plateau slope 10 1 0.1 Altika WF over a 10 km 2.5 mm/hr rain cell Return powerAttenuation

22. Modeled waveforms using (10 km resolution 10 km) AIRS liquid water data from AIRS on AQUA attenuation Off-nadir angle variations

23. Ex of Altika pass over cloud or low rain

24. Waveforms in log scale Off- nadir sigma0 Variation of zeta Local attenuation ? Need of a 2nd frequency

25. Raw waveforms in log scale Change of slope

26. LWC WVC TB 23 & 37 GHz

27. Altimeter can be use to estimate oceanic precipitations. A 13 years database already exist (pb of time to complete for a 20 year one In the perspective of MESCAL the use of Ka band could allo to estimate the integrated precipitation for low rain rate. Conclusion