SMOS STORM KO meeting 30/01/2012 ESRIN Ocean Surface Remote Sensing at High Winds with SMOS

Outline 1.The why of this study 2. Overview of the study 3. Detail on WP1100 Scientific Requirement consolidation 4. Web story 5. New developments on the use of SMOS for hurricane interactions with ocean

HURRICANE DANIELLE HURRICANE EARL Figure 6: Examples of other SMOS interceptions with North Atlantic Hurricanes in 2010.

SMOS TbGFDL model wind SMOS intercepts with IGOR (11-19 sep 2010) Hwind analysis Cat 4 “SMOS satellite L-band radiometer: a new capability for ocean surface remote sensing in Hurricanes”, N.Reul, J.Tenerelli, B.Chapron, D.Vandemark, Y.Quilfen and Y. Kerr, JGR Ocean, 2012 in press (shall be officially published this week).

Change of sensitivity at Hurricane wind Force (>33 m/s) Weak Incidence Angle dependence SMOS obs in IGOR are very consistent With PALS GMF for wind speed below 33 m/s

SMOS clearly outperform ASCAT in that case Maximum 10 mn sustained Wind speed estimates from SMOS very consistent SMOS estimates of radius at 34 knots & 50 knots SMOS overestimate 64 knots radii (spatial resolution ?) Radius of Wind speed larger than 34, 50 & 64 knots

Comparison SMOS wind versus SFMR rms~5 m/s

WP1000: Scientific Requirement Consolidation WP1100: Underlying physics of L-band Radio-Brightness contrasts at High Winds A review on Models and Observation of Thermal microwave emissions from sea foam: L-band peculiarities A review of Wind and Wave field Properties in Tropical Cyclones: potential fetch dependencies of the L-band radio-contrasts Atmospheric and Rain Effects SMOS observation capabilities in the context of storms event monitoring => Most of this worked has been published in WP1200: A review of existing ocean surface observation system in Hurricanes Visible and IR observations and the Dvorak Technique GPS DropwindSondes Airborne and Spaceborne Passive Spaceborne Active Use of the Microseismic Effects of Hurricane Coverage retrieval from passive microwave observations Ongoing activities and projects related to ocean remote sensing in High wind

WP1300:Survey of Datasets to be used for developement and validation The ensemble dasets to be used for developement and validation of the SMOS hurricane products will include: Microwave Brightness temperatures data: SMOS L1B, L1C data, AMSR-E,WindSat and SFMR C and X-band brightness temperatures, SSM/I 85 GHz Tbs. Aquarius L1 L-band Tbs and associated scatterometer data Storm track data: NHC BEST Tracks data, and, IBtracks data, Best track for the Pacific from the Joint Typhoon Warning Center (JTWC) Surface wind products including: HRD SFMR data sets, GPS dropwindsondes data and H*WInd analysis, GFDL hurricane wind model outputs, ECMWF wind products, WindSat and AMSR-E wind products, ASCAT and OceanSAT-II scatterometer produtcs, JASON 1,2 and Envisat/RA altimeter wind products. Sea Surface State parameters from numerical wave models (NAH, IFREMER wavewatch III), Envisat/ASAR and Radarsat-1 products, and, JASON 1,2 and Envisat/RA altimeter wave products. Rain Rates estimates from o TRMM, o HRD SFMR data sets, o WRF model outputs, o JASON 1,2 and Envisat/RA rain rate estimates.

WP1400: Description of the test sites and conditions Figure 11: Map showing the tracks of all Tropical cyclones which formed worldwide from 1985 to 2005 (NASA). In Red: area for which Radio Frequency Interference strongly contaminate SMOS data, in orange, zones for which potentially strong land contamination is expected. In green: potential test zones WP1500: Risk Analysis

Web Story

Legend: Sea Surface Wind Speed fields in meter per second retrieved from SMOS data over the Saffir–Simpson category 4 hurricane IGOR that developed in the North Atlantic ocean from 11 (a) to 19 (i) September The magenta curve is showing the Hurricane eye track (courtesy N.Reul (Ifremer) and J. Tenerelli (CLS)). The Soil Moisture and Ocean Salinity (SMOS) mission currently provides multi-angular L-band (1.4 GHz) brightness temperature images of the Earth. Because upwelling radiation at 1.4 GHz is significantly less affected by rain and atmospheric effects than at higher microwave frequencies, the new SMOS measurements offer unique opportunities to complement existing ocean satellite high wind observations that are often erroneous in these extreme conditions. This new capability was recently demonstrated by analyzing SMOS data over hurricane Igor, a tropical storm that developed to a Saffir–Simpson category 4 hurricane from September Thanks to its large spatial swath and frequent revisit time, SMOS observations intercepted the hurricane 9 times during this period. Surface wind speeds were estimated from SMOS brightness temperature images using an algorithm developed by scientists from IFREMER and CLS/brest. The evolution of the maximum surface wind speed and the radii of 34, 50 and 64 knots surface wind speeds retrieved from SMOS were shown to be consistent with hurricane model solutions and observation analyses. The SMOS sensor is thus closer to a true all-weather satellite ocean wind sensor with the capability to provide quantitative and complementary surface wind information of great interest for operational Hurricane intensity forecasts.

Potential Animation