1 Susanne Crewell 1 & MICAM Team 2 1 Meteorologisches Institut Universität Bonn 2 Laurent Chardenal (CETP), Gunnar Elgered (Chalmers), Catherine Gaffard.

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Presentation transcript:

1 Susanne Crewell 1 & MICAM Team 2 1 Meteorologisches Institut Universität Bonn 2 Laurent Chardenal (CETP), Gunnar Elgered (Chalmers), Catherine Gaffard (Metoffice), Jürgen Güldner (DWD), Boris Kutuza (IRE Moskva), Lorenz Martin (IAP Bern) etc.. First Results of Microwave Radiometer Intercomparison Campaign (MICAM)

2 Setup  eight microwave radiometer with very different design  August 1-14, 2001 in Cabauw, The Netherlands  time series observation at different observation angles  34 radio soundings (Metoffice) Objectives  estimate accuracy of brightness temperature measurements  assess quality of CLIWA-NET CNN measurements  assess quality of derived liquid water path (LWP) and integrated water vapor (IWV) and influence of instrument specifications  set constraints on gas absorption at microwave frequencies  optimze low-cost microwave radiometer design Leipzig, May Setup and Objectives of MICAM

3 U. Bern, Switzerland Chalmers U., Sweden CETP Velizy, France UK Metoffice U. Bonn, Germany German Weather Service German Weather Service Inst. Radioeng., Russia Leipzig, May Overview of MICAM Frequencies

4 Leipzig, May Radiometer Specifications InstrumentIntegration Beam Elevation Time /sWidth /  Angle /  Conrad DRAKKAR fixed at 90 MARSS0.1110every 10 deg MICCY STPE6~10fixed at 40 THPR  1;  t= TROWARA WVRA Azimuth orientation: West

5 Impressions from MICAM MICCY Conrad MARSS WVR IRE TROWARA Drakkar 20 m

6 Observation Schedule Leipzig, May Zenith observation during day

7 MICAM WWW Site Leipzig, May  time series of brightness temperatures (T B ) in original resolution - similiar frequency channels are shown together - each observation period is shown separately  time series of T B averaged to 10 min mean values  differences between radiometers averaged over observation periods  calculated and measured T B for each radiosounding for all frequencies - temperature, humidity and calculated liquid water content  Six hourly plots of derived IWV and LWP from all radiometer

8 Rain Rate mm/h wet radiometer gives questionable measurements short integration time and high beam resolution give highest LWP values Time Series of Brightness Temperatures Leipzig, May

9 Comparison of 10 Minute Means Leipzig, May Comparison has to be limited to cloud free periods

10 Comparison of 10 Minute Means Leipzig, May

11 Direct comparison of Brightness Temperatures Leipzig, May  zenith observation  closest match in time (<36 s)  homogeneous atmosphere (  <1 K)  Bias = 1.1 K  RMS = 0.5 K  Correlation = 0.99

12 center of H 2 O line cloud sensitive frequency Leipzig, May Comparison with Radiative Transfer

13 all cloud free cases N=16 10 min means past launch partly cloudy Scences removed Comparison with Radiative Transfer Leipzig, May slope of regression line is significantly < 1 for many channels  description of water vapor line absorption and continuum might have opposite bias

14 Leipzig, May Conclusions and Implication on Retrieval Conclusions  relative accuraccy is much higher than absolute!  DRAKKAR needs recalibration (at 23.8 GHz)  calibration of Russian radiometer shouldn‘t be trusted  discrepancies between radiometer are as high as uncertainties in radiative transfer modelling  gas absorption (water vapor/continuum) needs clarification Implications on Retrieval  agreement between microwave profilers and radiative transfer is good along oxygen absorption complex (temperature profiling)  discrepancies at typical LWP/IWV frequencies are about 1-2 K (as assumed in the retrieval algorithm development)  bias in water vapor profiles due to uncertainty at line center

15 Leipzig, May Future work Implications on low-cost microwave radiometer  appropriate rain detection and protection neccesary  reference absolute calibration load Future work  investigate differences at 90 GHz (cloud sensitive)  analyse raw data and skydip calibration procedure  perform radiative transfer calculations with MONORTM  investigate spectral behaviour of T B differences  analyse influence of instrument specifications on time series characteristics

16 Retrieval Accuracy EGS, Nice, April 25, 2002  LWP is derived from perfect brightness temperature (TB) measurements  ill-determined problem  Retrievals rely on accuracy of radiative transfer; Uncertainties: - gas absorption (e.g. water vapor) - refractive index of water (e.g. <0  C [Westwater et al., 2001])  Error characteristics of TB are difficult to define absolute uncertainty (  1 K) is lower than relative (~0.2 K) Microwave Intercomparison Campaign (MICAM)  Influence of statistical assumptions in algorithm (e.g. LWC)

17 Conclusions / Outlook  uncertainty of gas absorption at microwave frequencies about as high as differences between different radiometers  LWP=20-40 gm -2  laboratory measurements needed for further improvement  evaluation of LWP in cloud free conditions (Ceilometer/IR)  synergetic algorithms (TBs, ceilometer, IR radiometer) to improve estimates of zero and low LWP cases  Brightness temperature simulations from atmospheric model output  low-cost microwave radiometer with improved precipitation detection/protection system and reference calibration EGS, Nice, April 25, 2002