Radiometer retrievals of LWP

1. Radiometer retrievals of LWP Nicolas GAUSSIAT

2. Statistical/physical retrieval Physical retrieval : kl, kv,d are estimated using GCM model vertical information, then with Statistical retrieval : a22, a28 and b are assumed to be constant and directly deduced from observations of Tb and LWP SOME BASICS: Radiometers measure Tb at 22.2 GHz end 28.8 GHz with

3. Model data /radiosondes 2 years of model data LWP 4 years of radiosondes VWP

4. Physical retrieval • (Kl22, kv22, d22),(Kl28, kv28, d28) are estimated using GCM model (ECMWF) • for each profiles, and a22, a28 and b are deduced. a22 Kl22, Kl28 Kv22, Kv28 a28 d22, d28 b

5. Statistical retrieval Use of a bi-linear regression to work out a22, a28 and b directly We assume that LWPi depends linearly on the optical depths 22i and 28i Ideally, we want to find a22, a28, b for all the N measurements : a2222i+ a2828i+ b =LWPi But the best we can do is to minimize the sum : R2=(a2222i+ a2828i+ b - LWPi)2 In matrices notations A=[…(22i28i1) ;…(22N28N1) ] X=[a22 ;a28 ; b] Y=[…LWPi ;… LWPN] X = (AtA)-1 AtY

6. Results can look good but … statistical physical clear sky • Lidar identify liquid-cloud-free regions (LWP should be 0)

7. when it comes to the details… • Fluctuations must be due to a calibration problem… minutes

8. Cunning technique… • In clear sky conditions LWP=0 so we have : • then (1) • A second constrain is found by minimizing the cost fct J, • then (2) • So, from (1) and (2), we work out C22 , C28 in the clear sky regions and interpolate values in between

9. …cunning results(1) • Chilbolton offset (lens ?) … solved

10. …cunning results(2) • Palaiseau calibration problem… not a problem.

11. Further improvement • Lidar measure cloud-base and using model temperature a better estimate of Kv is obtained.