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SOLab work description

Zabolotskikh E., Kudryavtsev V. SOLab work description. Rational.

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SOLab work description

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  1. Zabolotskikh E., Kudryavtsev V. SOLab work description

  2. Rational • Contribution to WP1100: L-band Signal Response over the Ocean in very high wind speed conditions (with the focus on model analysis on the potential effect of rain in TC & storms on the L-band microwave brightness over the ocean); • Contribution to WP1400: Merged Multi-mission Wind Speed product Algorithm (AMSR2 wind speed retrievals under rain in hurricanes) and WP2000: Generate & Validate SMOS High Wind Speed Product Databases;

  3. Rain impact on microwave brightness temperature • Rain increases the atmospheric attenuation, especially at higher frequencies. Therefore under rain the radiometer measurement is less sensitive to the surface wind speed; • It is very difficult to accurately model brightness temperatures in rain due high variability of rainy atmospheres (dependency on liquid drop form and size distribution, start of scattering); • The brightness temperature signals of rain and wind are very similar. Therefore the rain free wind speed algorithm tends to treat an increase in rain the same way as an increase in wind speed; • Intensive rain also changes the ocean surface and its properties and this effect is mostly hard to be studied (separated from atmospheric or wind influence);

  4. Study of potential effect of rain in TC & storms on the L-band microwave brightness • Select the RTM to be used in the analysis and code it (RTM without rain is established at SOLab, rain module should be incorporated; • Conduct RTM simulations and estimate the expected observational dependencies (in terms of incidence angle, polarization, radiometer footprint) of Tb on rain rate; TRMM Radar TRMM TMI RRmax=150 mm/h RRmax=15 mm/h 7 October 2013

  5. On 18 May 2012 Japan launched a new passive microwave instrument with the largest in the world diameter of antenna - Advanced Microwave Scanning Radiometer (AMSR2) onboard Global Change Observation Mission – Water satellite (GCOM-W1 “Shizuku”) Additional channel Better than AMSR-E Potential accuracy for SWS retrievals is 1 m/s Same as AMSR-E

  6. AMSR2 rain free wind speed retrieval algorithms • Are based on numerical experiment and physical modeling of AMSR2 brightness temperatures; • Use Neural Networks as an inversion function; • Are validated using Norwegian and North Sea oil platform high wind speed measurements; • Two SWS algorithms are developed – 1) using low frequency AMSR2 channels (LF algorithm - higher accuracy, lower resolution) and 2) using higher frequency AMSR2 channels (HF algorithm - lower accuracy under optically thick atmospheres, higher resolution); • Use newly developed atmospheric filtering based on the value of total atmospheric absorption 10.65 as a criterion for weather masking;

  7. AMSR2 SWS Surface wind speed (SWS) in the extratropical cyclone 29 January 2013 AMSR2 JAXA standard product AMSR2 new algorithm

  8. Development of AMSR2 all weather wind speed retrieval algorithms • Atmospheric parameter variations influencing TB in C- and X-bands are negligible for the area of equal distance from the cyclone center which does not relate rain (A section); • Though wind speed variations influencing TB in C- and X-bands cannot be priori considered negligible (wind field can be significantly asymmetric), wind dependency in C- and X-bands is very similar. So to some extension  TBV7,6 = TB7.3V-TB6.9V and  TBV10,7 = TB10.65V-TB7.3V do not depend on the sea state but rather the functions of rain rate;

  9. General idea over most rainy atmospheres rain radiation at 10.65, 7.3, and 6.9 GHz can be parameterized in terms of TBV7,6 and TBV10,7. and related to rain rate (RR). After subtraction of the rain part from the total TB rain-free SWS can be applied.

  10. Work plan: • Parameterize the rain part of the microwave radiation over TC & storms for AMSR2 channels (C and X-bands) as a function of TB7.3V-TB6.9V and TB10.65V-TB7.3V; • Develop an algorithm for Rain Rate retrieval from AMSR2; • Develop the methodology for RFI area detection for the channels used in the algorithms; • Validate RR algorithm using TMI RR (create a collocated data set); • Process AMSR2 data for TC events starting from August 2012 (generating AMSR2 SWS and RR products);

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