Satellite Wind Vectors from GOES Sounder Moisture Fields Iliana Genkova, Chris Velden, Steve Wanzong, Paul Menzel Motivation: (1) In support of the GOES-R Risk Reduction program, (2) Resolving uncertainties introduced by wind vector height assignment, (3) Provide wind fields at a number of constant pressure levels Previous talk presented an effort to solve the problem simulating the future HES data, this one will be dealing with existing data of similar nature

GOES I-M Sounder Moisture Fields SFOV Temperature and Moisture (RH, Td) Profiles 1h temporal and 10km SFOV nominal spatial resolution 40 pressure levels between 1000 and 0.1 hPa  30 between 1000 and 10 hPa Constant pressure images CIMSS satellite-derived wind algorithm (Velden at al., 2005) Different from the WV Imager and Sounder winds !!! GOES-East and GOES-West sounders provide real-time retrievals of temperature and moisture on an hourly basis. The single field-of-view product is generated every hour and has spatial resolution of 10 km. Vertical temperature profiles from sounder radiance measurements are produced at 40 pressure levels from 1000 to 0.1 mb using a physical retrieval algorithm that solves for surface skin temperature, atmospheric temperature, and atmospheric moisture simultaneously. Question: / What's the resolution of the GOES sounder? /*Answer:* The detectors themselves have a resolution of approximately 8.7 km (an Instantaneous Geometric Field Of View (IGFOV) of 242 micro-radians) on a side at the sub-satellite point (ie, 0 Latitude and 75 W Longitude for the eastern satellite). However, the IGFOV spacing (sampling) at the sub-satellite point is only every 10 km (280 micro-radians). This is why the sounder is said to have a "nominal resolution" of 10 km. Now, just as with the imager, the FOV resolution (area that is sensed) becomes more coarse as the sample is taken at higher local zenith angles (the local zenith angle is the same as the absolute value of the latitude for locations at the same longitude as the satellite). So, if the eastern sounder is taking samples over Wisconsin, the resolution is basically 11 km (East/West) by 16 km (North-South). Ma, X.L., Schmit, T. J., Smith, W. L.,1998: A Nonlinear Physical Retrieval Algorithm - Its Application to the GOES-8/9 Sounder, JAM, Vol.38, No5, pp.501–513

GOES Sounder constant pressure Td images 19 January 2006 , 10:46 UTC , 500mb We use McIDAS environment and MDDPI tool to create the “derived product constant pressure images” On the left – raw image, after cloud masking (clouds are black!) On the right – after median 3x3 filter, allow for eliminating “tracking” of single cloud y pixels as opposed to moisture features, we are reading 0-255 (inclusive) brightness. Individual Histogram stretch is applied to every image triplet to achieve maximum brightness contract in order to later on obtain more targets and wind vectors. Raw image Median 3x3 filter Constant pressure level Td images eliminate the AMV height assignment

GOES Sounder constant pressure Td images 19 January 2006 , 10:46 UTC , 500mb On the left – targets (clouds are black!) On the right – wind vectors at 500mb Before showing results, point out this is preliminary results! First attempt at deriving moisture tracked winds form the sounder. Wind code has not been significantly changed to accommodate the specific of the data set. Targets Wind Vectors Constant pressure level Td images eliminate the AMV height assignment

Simulated vs. Derived Moisture Retrieved Winds 19 January 2006 Pressure levels (mb) to be compared: 950 (931), 920 (878), 850 (827), 780 (777), 700 (729), 670 (683), 620 (596,639), 570 (555), 500 (515), 475 (477), 430 (441), 400 (374, 407), 350(343) As I mentioned, these are very preliminary examples. As a next step simulated data will be produces for over land, to compare wit the sounder winds. These 3 images show partial overlap for one of the cases S.W. showed earlier, and all the potential pressure levels at which (at this time) we could attempt comparisons. Simulated radiances are at Pressure levels mimicking the AIRS instrument spectral channels and weighting functions.

Example: 19 January 2006, Raw winds km NEWER profile retrieval code – same basic algorithm, but the initial profile guess is not the same for 3x3 FOV. This time we rather have individual interpolated GFS profiles to be worked on, hence better contrast in the images and more targets/winds. This hypothesis is to be validated with another example (new and old codes on the same case!!!) 12:00 UTC

Example: 19 January 2006, Raw winds km 12:00 UTC

Example: 19 January 2006, QI > 50 km 12:00 UTC

Example: Sounder vs. RAOBS Moisture Winds N Mean Bias (m/s) VRMS (m/s)_ All winds: 336 -2.90 14.72 Low winds: 114 -0.19 12.58 Mid winds: 143 -0.75 13.43 High winds: 79 -10.72 19.17 Search box size: 11x19 QI ≥ 50 All winds: 178 -0.48 14.83 Low winds: 42 2.51 13.78 Mid winds: 91 2.81 12.69 High winds: 45 -9.97 19.15 Search box size: 7x11 All winds: 468 -1.76 8.54 Low winds: 157 -1.47 8.48 Mid winds: 209 -0.54 8.00 High winds: 102 -4.72 9.66 Low : 1000 - 700mb; Mid : 699 - 400mb; High : 399 - 100mb

Example 2: Sounder vs. Operational WV Winds Better vertical coverage, consistent constant pressure levels. Now only 20 pressure levels between 1000 and 100mb, but as this is part pf the GOES R Risk Reduction program, a HES instrument being hyperspectral, will provide for denser vertical pressure level grid. Hopefully the HES will have 4km spatial resolution, and results will be better.

Future work Test varying search box size with altitude Implement the code in real time Test varying search box size with altitude Apply the wind retrieval to Mixing Ratio constant pressure images Further verification with Wind Profiling Radar data Produce long term statistics Perform model impact studies Initiate data assimilation collaboration VAD Wind Profile Radar - Velocity-Azimuth Display Wind Profile Radar

Thanks to Jim Nelson, Chris Schmidt, Gary Wade, Tim Schmit for their help with the GOES Snd data acquisition! Fin!